Merge remote-tracking branch 'origin/dev' into fix/copilot-transcript-compaction

The `@@agptfile:` expansion system previously used content-sniffing
(trying
`json.loads` then `csv.Sniffer`) to decide whether to parse file content
as
structured data. This was fragile — a file containing just `"42"` would
be
parsed as an integer, and the heuristics could misfire on ambiguous
content.

This PR replaces content-sniffing with **extension/MIME-based format
detection**.
When the file has a well-known extension (`.json`, `.csv`, etc.) or MIME
type
fragment (`workspace://id#application/json`), the content is parsed
accordingly.
Unknown formats or parse failures always fall back to plain string — no
surprises.

> [!NOTE]
> This PR builds on the `@@agptfile:` file reference protocol introduced
in #12332 and the structured data auto-parsing added in #12390.
>
> **What is `@@agptfile:`?**
> It is a special URI prefix (e.g. `@@agptfile:workspace:///report.csv`)
that the CoPilot SDK expands inline before sending tool arguments to
blocks. This lets the AI reference workspace files by name, and the SDK
automatically reads and injects the file content. See #12332 for the
full design.

### Changes 🏗️

**New utility: `backend/util/file_content_parser.py`**
- `infer_format(uri)` — determines format from file extension or MIME
fragment
- `parse_file_content(content, fmt)` — parses content, never raises
- Supported text formats: JSON, JSONL/NDJSON, CSV, TSV, YAML, TOML
- Supported binary formats: Parquet (via pyarrow), Excel/XLSX (via
openpyxl)
- JSON scalars (strings, numbers, booleans, null) stay as strings — only
  containers (arrays, objects) are promoted
- CSV/TSV require ≥1 row and ≥2 columns to qualify as tabular data
- Added `openpyxl` dependency for Excel reading via pandas
- Case-insensitive MIME fragment matching per RFC 2045
- Shared `PARSE_EXCEPTIONS` constant to avoid duplication between
modules

**Updated `expand_file_refs_in_args` in `file_ref.py`**
- Bare refs now use `infer_format` + `parse_file_content` instead of the
  old `_try_parse_structured` content-sniffing function
- Binary formats (parquet, xlsx) read raw bytes via `read_file_bytes`
- Embedded refs (text around `@@agptfile:`) still produce plain strings
- **Size guards**: Workspace and sandbox file reads now enforce a 10 MB
limit
  (matching the existing local file limit) to prevent OOM on large files

**Updated `blocks/github/commits.py`**
- Consolidated `_create_blob` and `_create_binary_blob` into a single
function
  with an `encoding` parameter

**Updated copilot system prompt**
- Documents the extension-based structured data parsing and supported
formats

**66 new tests** in `file_content_parser_test.py` covering:
- Format inference (extension, MIME, case-insensitive, precedence)
- All 8 format parsers (happy path + edge cases + fallbacks)
- Binary format handling (string input fallback, invalid bytes fallback)
- Unknown format passthrough

### Checklist 📋

#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan:
  - [x] All 66 file_content_parser_test.py tests pass
  - [x] All 31 file_ref_test.py tests pass
  - [x] All 13 file_ref_integration_test.py tests pass
  - [x] `poetry run format` passes clean (including pyright)

autogpt_platform/backend/backend/api/features/admin/model.py

@@ -6,13 +6,11 @@ from typing import TYPE_CHECKING, Any, Literal, Optional
 import prisma.enums
 from pydantic import BaseModel, EmailStr
 
-from backend.copilot.session_types import ChatSessionStartType
 from backend.data.model import UserTransaction
 from backend.util.models import Pagination
 
 if TYPE_CHECKING:
     from backend.data.invited_user import BulkInvitedUsersResult, InvitedUserRecord
-    from backend.data.model import User
 
 
 class UserHistoryResponse(BaseModel):
@@ -92,51 +90,3 @@ class BulkInvitedUsersResponse(BaseModel):
                 for row in result.results
             ],
         )
-
-
-class AdminCopilotUserSummary(BaseModel):
-    id: str
-    email: str
-    name: Optional[str] = None
-    timezone: str
-    created_at: datetime
-    updated_at: datetime
-
-    @classmethod
-    def from_user(cls, user: "User") -> "AdminCopilotUserSummary":
-        return cls(
-            id=user.id,
-            email=user.email,
-            name=user.name,
-            timezone=user.timezone,
-            created_at=user.created_at,
-            updated_at=user.updated_at,
-        )
-
-
-class AdminCopilotUsersResponse(BaseModel):
-    users: list[AdminCopilotUserSummary]
-
-
-class TriggerCopilotSessionRequest(BaseModel):
-    user_id: str
-    start_type: ChatSessionStartType
-
-
-class TriggerCopilotSessionResponse(BaseModel):
-    session_id: str
-    start_type: ChatSessionStartType
-
-
-class SendCopilotEmailsRequest(BaseModel):
-    user_id: str
-
-
-class SendCopilotEmailsResponse(BaseModel):
-    candidate_count: int
-    processed_count: int
-    sent_count: int
-    skipped_count: int
-    repair_queued_count: int
-    running_count: int
-    failed_count: int

autogpt_platform/backend/backend/api/features/admin/user_admin_routes.py

@@ -2,12 +2,8 @@ import logging
 import math
 
 from autogpt_libs.auth import get_user_id, requires_admin_user
-from fastapi import APIRouter, File, HTTPException, Query, Security, UploadFile
+from fastapi import APIRouter, File, Query, Security, UploadFile
 
-from backend.copilot.autopilot import (
-    send_pending_copilot_emails_for_user,
-    trigger_autopilot_session_for_user,
-)
 from backend.data.invited_user import (
     bulk_create_invited_users_from_file,
     create_invited_user,
@@ -16,20 +12,13 @@ from backend.data.invited_user import (
     revoke_invited_user,
 )
 from backend.data.tally import mask_email
-from backend.data.user import search_users
 from backend.util.models import Pagination
 
 from .model import (
-    AdminCopilotUsersResponse,
-    AdminCopilotUserSummary,
     BulkInvitedUsersResponse,
     CreateInvitedUserRequest,
     InvitedUserResponse,
     InvitedUsersResponse,
-    SendCopilotEmailsRequest,
-    SendCopilotEmailsResponse,
-    TriggerCopilotSessionRequest,
-    TriggerCopilotSessionResponse,
 )
 
 logger = logging.getLogger(__name__)
@@ -146,95 +135,3 @@ async def retry_invited_user_tally_route(
         invited_user_id,
     )
     return InvitedUserResponse.from_record(invited_user)
-
-
-@router.get(
-    "/copilot/users",
-    response_model=AdminCopilotUsersResponse,
-    summary="Search Copilot Users",
-    operation_id="getV2SearchCopilotUsers",
-)
-async def search_copilot_users_route(
-    search: str = Query("", description="Search by email, name, or user ID"),
-    limit: int = Query(20, ge=1, le=50),
-    admin_user_id: str = Security(get_user_id),
-) -> AdminCopilotUsersResponse:
-    logger.info(
-        "Admin user %s searched Copilot users (query_length=%s, limit=%s)",
-        admin_user_id,
-        len(search.strip()),
-        limit,
-    )
-    users = await search_users(search, limit=limit)
-    return AdminCopilotUsersResponse(
-        users=[AdminCopilotUserSummary.from_user(user) for user in users]
-    )
-
-
-@router.post(
-    "/copilot/trigger",
-    response_model=TriggerCopilotSessionResponse,
-    summary="Trigger Copilot Session",
-    operation_id="postV2TriggerCopilotSession",
-)
-async def trigger_copilot_session_route(
-    request: TriggerCopilotSessionRequest,
-    admin_user_id: str = Security(get_user_id),
-) -> TriggerCopilotSessionResponse:
-    logger.info(
-        "Admin user %s manually triggered %s for user %s",
-        admin_user_id,
-        request.start_type,
-        request.user_id,
-    )
-    try:
-        session = await trigger_autopilot_session_for_user(
-            request.user_id,
-            start_type=request.start_type,
-        )
-    except LookupError as exc:
-        raise HTTPException(status_code=404, detail=str(exc)) from exc
-    except ValueError as exc:
-        raise HTTPException(status_code=400, detail=str(exc)) from exc
-
-    logger.info(
-        "Admin user %s created manual Copilot session %s for user %s",
-        admin_user_id,
-        session.session_id,
-        request.user_id,
-    )
-    return TriggerCopilotSessionResponse(
-        session_id=session.session_id,
-        start_type=request.start_type,
-    )
-
-
-@router.post(
-    "/copilot/send-emails",
-    response_model=SendCopilotEmailsResponse,
-    summary="Send Pending Copilot Emails",
-    operation_id="postV2SendPendingCopilotEmails",
-)
-async def send_pending_copilot_emails_route(
-    request: SendCopilotEmailsRequest,
-    admin_user_id: str = Security(get_user_id),
-) -> SendCopilotEmailsResponse:
-    logger.info(
-        "Admin user %s manually triggered pending Copilot emails for user %s",
-        admin_user_id,
-        request.user_id,
-    )
-    result = await send_pending_copilot_emails_for_user(request.user_id)
-    logger.info(
-        "Admin user %s completed pending Copilot email sweep for user %s "
-        "(candidates=%s, sent=%s, skipped=%s, repairs=%s, running=%s, failed=%s)",
-        admin_user_id,
-        request.user_id,
-        result.candidate_count,
-        result.sent_count,
-        result.skipped_count,
-        result.repair_queued_count,
-        result.running_count,
-        result.failed_count,
-    )
-    return SendCopilotEmailsResponse(**result.model_dump())

autogpt_platform/backend/backend/api/features/admin/user_admin_routes_test.py

@@ -8,15 +8,11 @@ import pytest
 import pytest_mock
 from autogpt_libs.auth.jwt_utils import get_jwt_payload
 
-from backend.copilot.autopilot_email import PendingCopilotEmailSweepResult
-from backend.copilot.model import ChatSession
-from backend.copilot.session_types import ChatSessionStartType
 from backend.data.invited_user import (
     BulkInvitedUserRowResult,
     BulkInvitedUsersResult,
     InvitedUserRecord,
 )
-from backend.data.model import User
 
 from .user_admin_routes import router as user_admin_router
 
@@ -76,20 +72,6 @@ def _sample_bulk_invited_users_result() -> BulkInvitedUsersResult:
     )
 
 
-def _sample_user() -> User:
-    now = datetime.now(timezone.utc)
-    return User(
-        id="user-1",
-        email="copilot@example.com",
-        name="Copilot User",
-        timezone="Europe/Madrid",
-        created_at=now,
-        updated_at=now,
-        stripe_customer_id=None,
-        top_up_config=None,
-    )
-
-
 def test_get_invited_users(
     mocker: pytest_mock.MockerFixture,
 ) -> None:
@@ -184,107 +166,3 @@ def test_retry_invited_user_tally(
 
     assert response.status_code == 200
     assert response.json()["tally_status"] == "RUNNING"
-
-
-def test_search_copilot_users(
-    mocker: pytest_mock.MockerFixture,
-) -> None:
-    mocker.patch(
-        "backend.api.features.admin.user_admin_routes.search_users",
-        AsyncMock(return_value=[_sample_user()]),
-    )
-
-    response = client.get("/admin/copilot/users", params={"search": "copilot"})
-
-    assert response.status_code == 200
-    data = response.json()
-    assert len(data["users"]) == 1
-    assert data["users"][0]["email"] == "copilot@example.com"
-    assert data["users"][0]["timezone"] == "Europe/Madrid"
-
-
-def test_trigger_copilot_session(
-    mocker: pytest_mock.MockerFixture,
-) -> None:
-    session = ChatSession.new(
-        "user-1",
-        start_type=ChatSessionStartType.AUTOPILOT_CALLBACK,
-    )
-    trigger = mocker.patch(
-        "backend.api.features.admin.user_admin_routes.trigger_autopilot_session_for_user",
-        AsyncMock(return_value=session),
-    )
-
-    response = client.post(
-        "/admin/copilot/trigger",
-        json={
-            "user_id": "user-1",
-            "start_type": ChatSessionStartType.AUTOPILOT_CALLBACK.value,
-        },
-    )
-
-    assert response.status_code == 200
-    assert response.json()["session_id"] == session.session_id
-    assert response.json()["start_type"] == "AUTOPILOT_CALLBACK"
-    assert trigger.await_args is not None
-    assert trigger.await_args.args[0] == "user-1"
-    assert (
-        trigger.await_args.kwargs["start_type"]
-        == ChatSessionStartType.AUTOPILOT_CALLBACK
-    )
-
-
-def test_trigger_copilot_session_returns_not_found(
-    mocker: pytest_mock.MockerFixture,
-) -> None:
-    mocker.patch(
-        "backend.api.features.admin.user_admin_routes.trigger_autopilot_session_for_user",
-        AsyncMock(side_effect=LookupError("User not found with ID: missing-user")),
-    )
-
-    response = client.post(
-        "/admin/copilot/trigger",
-        json={
-            "user_id": "missing-user",
-            "start_type": ChatSessionStartType.AUTOPILOT_NIGHTLY.value,
-        },
-    )
-
-    assert response.status_code == 404
-    assert response.json()["detail"] == "User not found with ID: missing-user"
-
-
-def test_send_pending_copilot_emails(
-    mocker: pytest_mock.MockerFixture,
-) -> None:
-    send_emails = mocker.patch(
-        "backend.api.features.admin.user_admin_routes.send_pending_copilot_emails_for_user",
-        AsyncMock(
-            return_value=PendingCopilotEmailSweepResult(
-                candidate_count=1,
-                processed_count=1,
-                sent_count=1,
-                skipped_count=0,
-                repair_queued_count=0,
-                running_count=0,
-                failed_count=0,
-            )
-        ),
-    )
-
-    response = client.post(
-        "/admin/copilot/send-emails",
-        json={"user_id": "user-1"},
-    )
-
-    assert response.status_code == 200
-    assert response.json() == {
-        "candidate_count": 1,
-        "processed_count": 1,
-        "sent_count": 1,
-        "skipped_count": 0,
-        "repair_queued_count": 0,
-        "running_count": 0,
-        "failed_count": 0,
-    }
-    send_emails.assert_awaited_once_with("user-1")

autogpt_platform/backend/backend/api/features/chat/routes.py

@@ -3,23 +3,18 @@
 import asyncio
 import logging
 import re
-import time
 from collections.abc import AsyncGenerator
-from typing import Annotated, Any, NoReturn
+from typing import Annotated
 from uuid import uuid4
 
 from autogpt_libs import auth
 from fastapi import APIRouter, Depends, HTTPException, Query, Response, Security
 from fastapi.responses import StreamingResponse
+from prisma.models import UserWorkspaceFile
 from pydantic import BaseModel, Field, field_validator
 
 from backend.copilot import service as chat_service
 from backend.copilot import stream_registry
-from backend.copilot.autopilot import (
-    consume_callback_token,
-    strip_internal_content,
-    unwrap_internal_content,
-)
 from backend.copilot.config import ChatConfig
 from backend.copilot.executor.utils import enqueue_cancel_task, enqueue_copilot_turn
 from backend.copilot.model import (
@@ -32,13 +27,7 @@ from backend.copilot.model import (
     get_user_sessions,
     update_session_title,
 )
-from backend.copilot.response_model import (
-    StreamBaseResponse,
-    StreamError,
-    StreamFinish,
-    StreamHeartbeat,
-)
-from backend.copilot.session_types import ChatSessionStartType
+from backend.copilot.response_model import StreamError, StreamFinish, StreamHeartbeat
 from backend.copilot.tools.e2b_sandbox import kill_sandbox
 from backend.copilot.tools.models import (
     AgentDetailsResponse,
@@ -64,7 +53,6 @@ from backend.copilot.tools.models import (
     UnderstandingUpdatedResponse,
 )
 from backend.copilot.tracking import track_user_message
-from backend.data.db_accessors import workspace_db
 from backend.data.redis_client import get_redis_async
 from backend.data.understanding import get_business_understanding
 from backend.data.workspace import get_or_create_workspace
@@ -77,187 +65,6 @@ _UUID_RE = re.compile(
 )
 
 logger = logging.getLogger(__name__)
-STREAM_QUEUE_GET_TIMEOUT_SECONDS = 10.0
-STREAMING_RESPONSE_HEADERS = {
-    "Cache-Control": "no-cache",
-    "Connection": "keep-alive",
-    "X-Accel-Buffering": "no",
-    "x-vercel-ai-ui-message-stream": "v1",
-}
-
-
-def _build_streaming_response(
-    generator: AsyncGenerator[str, None],
-) -> StreamingResponse:
-    return StreamingResponse(
-        generator,
-        media_type="text/event-stream",
-        headers=STREAMING_RESPONSE_HEADERS,
-    )
-
-
-async def _unsubscribe_stream_queue(
-    session_id: str,
-    subscriber_queue: asyncio.Queue[StreamBaseResponse] | None,
-) -> None:
-    if subscriber_queue is None:
-        return
-
-    try:
-        await stream_registry.unsubscribe_from_session(session_id, subscriber_queue)
-    except Exception as unsub_err:
-        logger.error(
-            f"Error unsubscribing from session {session_id}: {unsub_err}",
-            exc_info=True,
-        )
-
-
-async def _stream_subscriber_queue(
-    *,
-    session_id: str,
-    subscriber_queue: asyncio.Queue[StreamBaseResponse],
-    log_meta: dict[str, Any],
-    started_at: float,
-    label: str,
-    surface_errors: bool,
-) -> AsyncGenerator[str, None]:
-    chunk_count = 0
-    first_chunk_type: str | None = None
-
-    try:
-        while True:
-            try:
-                chunk = await asyncio.wait_for(
-                    subscriber_queue.get(),
-                    timeout=STREAM_QUEUE_GET_TIMEOUT_SECONDS,
-                )
-            except asyncio.TimeoutError:
-                yield StreamHeartbeat().to_sse()
-                continue
-
-            chunk_count += 1
-            if first_chunk_type is None:
-                first_chunk_type = type(chunk).__name__
-                elapsed = (time.perf_counter() - started_at) * 1000
-                logger.info(
-                    f"[TIMING] {label} first chunk at {elapsed:.1f}ms, type={first_chunk_type}",
-                    extra={
-                        "json_fields": {
-                            **log_meta,
-                            "chunk_type": first_chunk_type,
-                            "elapsed_ms": elapsed,
-                        }
-                    },
-                )
-
-            yield chunk.to_sse()
-
-            if isinstance(chunk, StreamFinish):
-                total_time = (time.perf_counter() - started_at) * 1000
-                logger.info(
-                    f"[TIMING] {label} received StreamFinish in {total_time:.1f}ms",
-                    extra={
-                        "json_fields": {
-                            **log_meta,
-                            "chunks_yielded": chunk_count,
-                            "total_time_ms": total_time,
-                        }
-                    },
-                )
-                break
-    except GeneratorExit:
-        logger.info(
-            f"[TIMING] {label} client disconnected after {chunk_count} chunks",
-            extra={
-                "json_fields": {
-                    **log_meta,
-                    "chunks_yielded": chunk_count,
-                    "reason": "client_disconnect",
-                }
-            },
-        )
-    except Exception as exc:
-        elapsed = (time.perf_counter() - started_at) * 1000
-        logger.error(
-            f"[TIMING] {label} error after {elapsed:.1f}ms: {exc}",
-            extra={
-                "json_fields": {**log_meta, "elapsed_ms": elapsed, "error": str(exc)}
-            },
-        )
-        if surface_errors:
-            yield StreamError(
-                errorText="An error occurred. Please try again.",
-                code="stream_error",
-            ).to_sse()
-            yield StreamFinish().to_sse()
-    finally:
-        total_time = (time.perf_counter() - started_at) * 1000
-        logger.info(
-            f"[TIMING] {label} finished in {total_time:.1f}ms",
-            extra={
-                "json_fields": {
-                    **log_meta,
-                    "total_time_ms": total_time,
-                    "chunks_yielded": chunk_count,
-                    "first_chunk_type": first_chunk_type,
-                }
-            },
-        )
-        yield "data: [DONE]\n\n"
-
-
-async def _stream_chat_events(
-    *,
-    session_id: str,
-    user_id: str | None,
-    subscribe_from_id: str,
-    turn_id: str,
-    log_meta: dict[str, Any],
-) -> AsyncGenerator[str, None]:
-    started_at = time.perf_counter()
-    subscriber_queue = await stream_registry.subscribe_to_session(
-        session_id=session_id,
-        user_id=user_id,
-        last_message_id=subscribe_from_id,
-    )
-
-    try:
-        if subscriber_queue is None:
-            yield StreamFinish().to_sse()
-            yield "data: [DONE]\n\n"
-            return
-
-        async for chunk in _stream_subscriber_queue(
-            session_id=session_id,
-            subscriber_queue=subscriber_queue,
-            log_meta=log_meta,
-            started_at=started_at,
-            label=f"stream_chat_post[{turn_id}]",
-            surface_errors=True,
-        ):
-            yield chunk
-    finally:
-        await _unsubscribe_stream_queue(session_id, subscriber_queue)
-
-
-async def _resume_stream_events(
-    *,
-    session_id: str,
-    subscriber_queue: asyncio.Queue[StreamBaseResponse],
-) -> AsyncGenerator[str, None]:
-    started_at = time.perf_counter()
-    try:
-        async for chunk in _stream_subscriber_queue(
-            session_id=session_id,
-            subscriber_queue=subscriber_queue,
-            log_meta={"session_id": session_id},
-            started_at=started_at,
-            label=f"resume_stream[{session_id}]",
-            surface_errors=False,
-        ):
-            yield chunk
-    finally:
-        await _unsubscribe_stream_queue(session_id, subscriber_queue)
 
 
 async def _validate_and_get_session(
@@ -311,8 +118,6 @@ class SessionDetailResponse(BaseModel):
     created_at: str
     updated_at: str
     user_id: str | None
-    start_type: ChatSessionStartType
-    execution_tag: str | None = None
     messages: list[dict]
     active_stream: ActiveStreamInfo | None = None  # Present if stream is still active
 
@@ -324,8 +129,6 @@ class SessionSummaryResponse(BaseModel):
     created_at: str
     updated_at: str
     title: str | None = None
-    start_type: ChatSessionStartType
-    execution_tag: str | None = None
     is_processing: bool
 
 
@@ -357,14 +160,6 @@ class UpdateSessionTitleRequest(BaseModel):
         return stripped
 
 
-class ConsumeCallbackTokenRequest(BaseModel):
-    token: str
-
-
-class ConsumeCallbackTokenResponse(BaseModel):
-    session_id: str
-
-
 # ========== Routes ==========
 
 
@@ -376,7 +171,6 @@ async def list_sessions(
     user_id: Annotated[str, Security(auth.get_user_id)],
     limit: int = Query(default=50, ge=1, le=100),
     offset: int = Query(default=0, ge=0),
-    with_auto: bool = Query(default=False),
 ) -> ListSessionsResponse:
     """
     List chat sessions for the authenticated user.
@@ -392,12 +186,7 @@ async def list_sessions(
     Returns:
         ListSessionsResponse: List of session summaries and total count.
     """
-    sessions, total_count = await get_user_sessions(
-        user_id,
-        limit,
-        offset,
-        with_auto=with_auto,
-    )
+    sessions, total_count = await get_user_sessions(user_id, limit, offset)
 
     # Batch-check Redis for active stream status on each session
     processing_set: set[str] = set()
@@ -428,8 +217,6 @@ async def list_sessions(
                 created_at=session.started_at.isoformat(),
                 updated_at=session.updated_at.isoformat(),
                 title=session.title,
-                start_type=session.start_type,
-                execution_tag=session.execution_tag,
                 is_processing=session.session_id in processing_set,
             )
             for session in sessions
@@ -581,26 +368,12 @@ async def get_session(
     if not session:
         raise NotFoundError(f"Session {session_id} not found.")
 
-    messages = []
-    for message in session.messages:
-        payload = message.model_dump()
-        if message.role == "user":
-            visible_content = strip_internal_content(message.content)
-            if (
-                visible_content is None
-                and session.start_type != ChatSessionStartType.MANUAL
-            ):
-                visible_content = unwrap_internal_content(message.content)
-            if visible_content is None:
-                continue
-            payload["content"] = visible_content
-        messages.append(payload)
+    messages = [message.model_dump() for message in session.messages]
 
     # Check if there's an active stream for this session
     active_stream_info = None
     active_session, last_message_id = await stream_registry.get_active_session(
-        session_id,
-        user_id,
+        session_id, user_id
     )
     logger.info(
         f"[GET_SESSION] session={session_id}, active_session={active_session is not None}, "
@@ -621,28 +394,11 @@ async def get_session(
         created_at=session.started_at.isoformat(),
         updated_at=session.updated_at.isoformat(),
         user_id=session.user_id or None,
-        start_type=session.start_type,
-        execution_tag=session.execution_tag,
         messages=messages,
         active_stream=active_stream_info,
     )
 
 
-@router.post(
-    "/sessions/callback-token/consume",
-    dependencies=[Security(auth.requires_user)],
-)
-async def consume_callback_token_route(
-    request: ConsumeCallbackTokenRequest,
-    user_id: Annotated[str, Security(auth.get_user_id)],
-) -> ConsumeCallbackTokenResponse:
-    try:
-        result = await consume_callback_token(request.token, user_id)
-    except ValueError as exc:
-        raise HTTPException(status_code=404, detail=str(exc)) from exc
-    return ConsumeCallbackTokenResponse(session_id=result.session_id)
-
-
 @router.post(
     "/sessions/{session_id}/cancel",
     status_code=200,
@@ -716,6 +472,9 @@ async def stream_chat_post(
         StreamingResponse: SSE-formatted response chunks.
 
     """
+    import asyncio
+    import time
+
     stream_start_time = time.perf_counter()
     log_meta = {"component": "ChatStream", "session_id": session_id}
     if user_id:
@@ -747,14 +506,18 @@ async def stream_chat_post(
 
         if valid_ids:
             workspace = await get_or_create_workspace(user_id)
-            files = await workspace_db().get_workspace_files_by_ids(
-                workspace_id=workspace.id,
-                file_ids=valid_ids,
+            # Batch query instead of N+1
+            files = await UserWorkspaceFile.prisma().find_many(
+                where={
+                    "id": {"in": valid_ids},
+                    "workspaceId": workspace.id,
+                    "isDeleted": False,
+                }
             )
             # Only keep IDs that actually exist in the user's workspace
             sanitized_file_ids = [wf.id for wf in files] or None
             file_lines: list[str] = [
-                f"- {wf.name} ({wf.mime_type}, {round(wf.size_bytes / 1024, 1)} KB), file_id={wf.id}"
+                f"- {wf.name} ({wf.mimeType}, {round(wf.sizeBytes / 1024, 1)} KB), file_id={wf.id}"
                 for wf in files
             ]
             if file_lines:
@@ -824,14 +587,141 @@ async def stream_chat_post(
         f"[TIMING] Task enqueued to RabbitMQ, setup={setup_time:.1f}ms",
         extra={"json_fields": {**log_meta, "setup_time_ms": setup_time}},
     )
-    return _build_streaming_response(
-        _stream_chat_events(
-            session_id=session_id,
-            user_id=user_id,
-            subscribe_from_id=subscribe_from_id,
-            turn_id=turn_id,
-            log_meta=log_meta,
+
+    # SSE endpoint that subscribes to the task's stream
+    async def event_generator() -> AsyncGenerator[str, None]:
+        import time as time_module
+
+        event_gen_start = time_module.perf_counter()
+        logger.info(
+            f"[TIMING] event_generator STARTED, turn={turn_id}, session={session_id}, "
+            f"user={user_id}",
+            extra={"json_fields": log_meta},
         )
+        subscriber_queue = None
+        first_chunk_yielded = False
+        chunks_yielded = 0
+        try:
+            # Subscribe from the position we captured before enqueuing
+            # This avoids replaying old messages while catching all new ones
+            subscriber_queue = await stream_registry.subscribe_to_session(
+                session_id=session_id,
+                user_id=user_id,
+                last_message_id=subscribe_from_id,
+            )
+
+            if subscriber_queue is None:
+                yield StreamFinish().to_sse()
+                yield "data: [DONE]\n\n"
+                return
+
+            # Read from the subscriber queue and yield to SSE
+            logger.info(
+                "[TIMING] Starting to read from subscriber_queue",
+                extra={"json_fields": log_meta},
+            )
+            while True:
+                try:
+                    chunk = await asyncio.wait_for(subscriber_queue.get(), timeout=10.0)
+                    chunks_yielded += 1
+
+                    if not first_chunk_yielded:
+                        first_chunk_yielded = True
+                        elapsed = time_module.perf_counter() - event_gen_start
+                        logger.info(
+                            f"[TIMING] FIRST CHUNK from queue at {elapsed:.2f}s, "
+                            f"type={type(chunk).__name__}",
+                            extra={
+                                "json_fields": {
+                                    **log_meta,
+                                    "chunk_type": type(chunk).__name__,
+                                    "elapsed_ms": elapsed * 1000,
+                                }
+                            },
+                        )
+
+                    yield chunk.to_sse()
+
+                    # Check for finish signal
+                    if isinstance(chunk, StreamFinish):
+                        total_time = time_module.perf_counter() - event_gen_start
+                        logger.info(
+                            f"[TIMING] StreamFinish received in {total_time:.2f}s; "
+                            f"n_chunks={chunks_yielded}",
+                            extra={
+                                "json_fields": {
+                                    **log_meta,
+                                    "chunks_yielded": chunks_yielded,
+                                    "total_time_ms": total_time * 1000,
+                                }
+                            },
+                        )
+                        break
+                except asyncio.TimeoutError:
+                    yield StreamHeartbeat().to_sse()
+
+        except GeneratorExit:
+            logger.info(
+                f"[TIMING] GeneratorExit (client disconnected), chunks={chunks_yielded}",
+                extra={
+                    "json_fields": {
+                        **log_meta,
+                        "chunks_yielded": chunks_yielded,
+                        "reason": "client_disconnect",
+                    }
+                },
+            )
+            pass  # Client disconnected - background task continues
+        except Exception as e:
+            elapsed = (time_module.perf_counter() - event_gen_start) * 1000
+            logger.error(
+                f"[TIMING] event_generator ERROR after {elapsed:.1f}ms: {e}",
+                extra={
+                    "json_fields": {**log_meta, "elapsed_ms": elapsed, "error": str(e)}
+                },
+            )
+            # Surface error to frontend so it doesn't appear stuck
+            yield StreamError(
+                errorText="An error occurred. Please try again.",
+                code="stream_error",
+            ).to_sse()
+            yield StreamFinish().to_sse()
+        finally:
+            # Unsubscribe when client disconnects or stream ends
+            if subscriber_queue is not None:
+                try:
+                    await stream_registry.unsubscribe_from_session(
+                        session_id, subscriber_queue
+                    )
+                except Exception as unsub_err:
+                    logger.error(
+                        f"Error unsubscribing from session {session_id}: {unsub_err}",
+                        exc_info=True,
+                    )
+            # AI SDK protocol termination - always yield even if unsubscribe fails
+            total_time = time_module.perf_counter() - event_gen_start
+            logger.info(
+                f"[TIMING] event_generator FINISHED in {total_time:.2f}s; "
+                f"turn={turn_id}, session={session_id}, n_chunks={chunks_yielded}",
+                extra={
+                    "json_fields": {
+                        **log_meta,
+                        "total_time_ms": total_time * 1000,
+                        "chunks_yielded": chunks_yielded,
+                    }
+                },
+            )
+            yield "data: [DONE]\n\n"
+
+    return StreamingResponse(
+        event_generator(),
+        media_type="text/event-stream",
+        headers={
+            "Cache-Control": "no-cache",
+            "Connection": "keep-alive",
+            "X-Accel-Buffering": "no",  # Disable nginx buffering
+            "x-vercel-ai-ui-message-stream": "v1",  # AI SDK protocol header
+        },
     )
 
 
@@ -857,7 +747,11 @@ async def resume_session_stream(
         StreamingResponse (SSE) when an active stream exists,
         or 204 No Content when there is nothing to resume.
     """
-    active_session, _ = await stream_registry.get_active_session(session_id, user_id)
+    import asyncio
+
+    active_session, last_message_id = await stream_registry.get_active_session(
+        session_id, user_id
+    )
 
     if not active_session:
         return Response(status_code=204)
@@ -874,11 +768,64 @@ async def resume_session_stream(
 
     if subscriber_queue is None:
         return Response(status_code=204)
-    return _build_streaming_response(
-        _resume_stream_events(
-            session_id=session_id,
-            subscriber_queue=subscriber_queue,
-        )
+
+    async def event_generator() -> AsyncGenerator[str, None]:
+        chunk_count = 0
+        first_chunk_type: str | None = None
+        try:
+            while True:
+                try:
+                    chunk = await asyncio.wait_for(subscriber_queue.get(), timeout=10.0)
+                    if chunk_count < 3:
+                        logger.info(
+                            "Resume stream chunk",
+                            extra={
+                                "session_id": session_id,
+                                "chunk_type": str(chunk.type),
+                            },
+                        )
+                    if not first_chunk_type:
+                        first_chunk_type = str(chunk.type)
+                    chunk_count += 1
+                    yield chunk.to_sse()
+
+                    if isinstance(chunk, StreamFinish):
+                        break
+                except asyncio.TimeoutError:
+                    yield StreamHeartbeat().to_sse()
+        except GeneratorExit:
+            pass
+        except Exception as e:
+            logger.error(f"Error in resume stream for session {session_id}: {e}")
+        finally:
+            try:
+                await stream_registry.unsubscribe_from_session(
+                    session_id, subscriber_queue
+                )
+            except Exception as unsub_err:
+                logger.error(
+                    f"Error unsubscribing from session {active_session.session_id}: {unsub_err}",
+                    exc_info=True,
+                )
+            logger.info(
+                "Resume stream completed",
+                extra={
+                    "session_id": session_id,
+                    "n_chunks": chunk_count,
+                    "first_chunk_type": first_chunk_type,
+                },
+            )
+            yield "data: [DONE]\n\n"
+
+    return StreamingResponse(
+        event_generator(),
+        media_type="text/event-stream",
+        headers={
+            "Cache-Control": "no-cache",
+            "Connection": "keep-alive",
+            "X-Accel-Buffering": "no",
+            "x-vercel-ai-ui-message-stream": "v1",
+        },
     )
 
 
@@ -1030,6 +977,6 @@ ToolResponseUnion = (
     description="This endpoint is not meant to be called. It exists solely to "
     "expose tool response models in the OpenAPI schema for frontend codegen.",
 )
-async def _tool_response_schema() -> NoReturn:
+async def _tool_response_schema() -> ToolResponseUnion:  # type: ignore[return]
     """Never called at runtime. Exists only so Orval generates TS types."""
     raise HTTPException(status_code=501, detail="Schema-only endpoint")

autogpt_platform/backend/backend/api/features/chat/routes_test.py

@@ -1,8 +1,5 @@
 """Tests for chat API routes: session title update, file attachment validation, and suggested prompts."""
 
-import asyncio
-from datetime import datetime, timezone
-from types import SimpleNamespace
 from unittest.mock import AsyncMock, MagicMock
 
 import fastapi
@@ -11,9 +8,6 @@ import pytest
 import pytest_mock
 
 from backend.api.features.chat import routes as chat_routes
-from backend.copilot.model import ChatMessage, ChatSession
-from backend.copilot.response_model import StreamFinish
-from backend.copilot.session_types import ChatSessionStartType
 
 app = fastapi.FastAPI()
 app.include_router(chat_routes.router)
@@ -121,238 +115,6 @@ def test_update_title_not_found(
     assert response.status_code == 404
 
 
-def test_list_sessions_defaults_to_manual_only(
-    mocker: pytest_mock.MockerFixture,
-    test_user_id: str,
-) -> None:
-    started_at = datetime.now(timezone.utc)
-    mock_get_user_sessions = mocker.patch(
-        "backend.api.features.chat.routes.get_user_sessions",
-        new_callable=AsyncMock,
-        return_value=(
-            [
-                SimpleNamespace(
-                    session_id="sess-1",
-                    started_at=started_at,
-                    updated_at=started_at,
-                    title="Nightly check-in",
-                    start_type=chat_routes.ChatSessionStartType.AUTOPILOT_NIGHTLY,
-                    execution_tag="autopilot-nightly:2026-03-13",
-                )
-            ],
-            1,
-        ),
-    )
-
-    pipe = MagicMock()
-    pipe.hget = MagicMock()
-    pipe.execute = AsyncMock(return_value=["running"])
-    redis = MagicMock()
-    redis.pipeline = MagicMock(return_value=pipe)
-    mocker.patch(
-        "backend.api.features.chat.routes.get_redis_async",
-        new_callable=AsyncMock,
-        return_value=redis,
-    )
-
-    response = client.get("/sessions")
-
-    assert response.status_code == 200
-    assert response.json() == {
-        "sessions": [
-            {
-                "id": "sess-1",
-                "created_at": started_at.isoformat(),
-                "updated_at": started_at.isoformat(),
-                "title": "Nightly check-in",
-                "start_type": "AUTOPILOT_NIGHTLY",
-                "execution_tag": "autopilot-nightly:2026-03-13",
-                "is_processing": True,
-            }
-        ],
-        "total": 1,
-    }
-    mock_get_user_sessions.assert_awaited_once_with(
-        test_user_id,
-        50,
-        0,
-        with_auto=False,
-    )
-
-
-def test_list_sessions_can_include_auto_sessions(
-    mocker: pytest_mock.MockerFixture,
-    test_user_id: str,
-) -> None:
-    mock_get_user_sessions = mocker.patch(
-        "backend.api.features.chat.routes.get_user_sessions",
-        new_callable=AsyncMock,
-        return_value=([], 0),
-    )
-
-    response = client.get("/sessions?with_auto=true")
-
-    assert response.status_code == 200
-    assert response.json() == {"sessions": [], "total": 0}
-    mock_get_user_sessions.assert_awaited_once_with(
-        test_user_id,
-        50,
-        0,
-        with_auto=True,
-    )
-
-
-def test_consume_callback_token_route_returns_session_id(
-    mocker: pytest_mock.MockerFixture,
-) -> None:
-    mock_consume = mocker.patch(
-        "backend.api.features.chat.routes.consume_callback_token",
-        new_callable=AsyncMock,
-        return_value=SimpleNamespace(session_id="sess-2"),
-    )
-
-    response = client.post(
-        "/sessions/callback-token/consume",
-        json={"token": "token-123"},
-    )
-
-    assert response.status_code == 200
-    assert response.json() == {"session_id": "sess-2"}
-    mock_consume.assert_awaited_once_with("token-123", TEST_USER_ID)
-
-
-def test_consume_callback_token_route_returns_404_on_invalid_token(
-    mocker: pytest_mock.MockerFixture,
-) -> None:
-    mocker.patch(
-        "backend.api.features.chat.routes.consume_callback_token",
-        new_callable=AsyncMock,
-        side_effect=ValueError("Callback token not found"),
-    )
-
-    response = client.post(
-        "/sessions/callback-token/consume",
-        json={"token": "token-123"},
-    )
-
-    assert response.status_code == 404
-    assert response.json() == {"detail": "Callback token not found"}
-
-
-def test_get_session_hides_internal_only_messages_for_manual_sessions(
-    mocker: pytest_mock.MockerFixture,
-) -> None:
-    session = ChatSession.new(
-        TEST_USER_ID,
-        start_type=ChatSessionStartType.MANUAL,
-    )
-    session.messages = [
-        ChatMessage(role="user", content="<internal>hidden</internal>"),
-        ChatMessage(
-            role="user",
-            content="Visible<internal>hidden</internal> text",
-        ),
-        ChatMessage(role="assistant", content="Public response"),
-    ]
-
-    mocker.patch(
-        "backend.api.features.chat.routes.get_chat_session",
-        new_callable=AsyncMock,
-        return_value=session,
-    )
-    mocker.patch(
-        "backend.api.features.chat.routes.stream_registry.get_active_session",
-        new_callable=AsyncMock,
-        return_value=(None, None),
-    )
-
-    response = client.get(f"/sessions/{session.session_id}")
-
-    assert response.status_code == 200
-    assert response.json()["messages"] == [
-        {
-            "role": "user",
-            "content": "Visible text",
-            "name": None,
-            "tool_call_id": None,
-            "refusal": None,
-            "tool_calls": None,
-            "function_call": None,
-        },
-        {
-            "role": "assistant",
-            "content": "Public response",
-            "name": None,
-            "tool_call_id": None,
-            "refusal": None,
-            "tool_calls": None,
-            "function_call": None,
-        },
-    ]
-
-
-def test_get_session_shows_cleaned_internal_kickoff_for_autopilot_sessions(
-    mocker: pytest_mock.MockerFixture,
-) -> None:
-    session = ChatSession.new(
-        TEST_USER_ID,
-        start_type=ChatSessionStartType.AUTOPILOT_NIGHTLY,
-        execution_tag="autopilot-nightly:2026-03-13",
-    )
-    session.messages = [
-        ChatMessage(role="user", content="<internal>hidden</internal>"),
-        ChatMessage(
-            role="user",
-            content="Visible<internal>hidden</internal> text",
-        ),
-        ChatMessage(role="assistant", content="Public response"),
-    ]
-
-    mocker.patch(
-        "backend.api.features.chat.routes.get_chat_session",
-        new_callable=AsyncMock,
-        return_value=session,
-    )
-    mocker.patch(
-        "backend.api.features.chat.routes.stream_registry.get_active_session",
-        new_callable=AsyncMock,
-        return_value=(None, None),
-    )
-
-    response = client.get(f"/sessions/{session.session_id}")
-
-    assert response.status_code == 200
-    assert response.json()["messages"] == [
-        {
-            "role": "user",
-            "content": "hidden",
-            "name": None,
-            "tool_call_id": None,
-            "refusal": None,
-            "tool_calls": None,
-            "function_call": None,
-        },
-        {
-            "role": "user",
-            "content": "Visible text",
-            "name": None,
-            "tool_call_id": None,
-            "refusal": None,
-            "tool_calls": None,
-            "function_call": None,
-        },
-        {
-            "role": "assistant",
-            "content": "Public response",
-            "name": None,
-            "tool_call_id": None,
-            "refusal": None,
-            "tool_calls": None,
-            "function_call": None,
-        },
-    ]
-
-
 # ─── file_ids Pydantic validation ─────────────────────────────────────
 
 
@@ -380,11 +142,7 @@ def _mock_stream_internals(mocker: pytest_mock.MockFixture):
         return_value=None,
     )
     mock_registry = mocker.MagicMock()
-    subscriber_queue = asyncio.Queue()
-    subscriber_queue.put_nowait(StreamFinish())
     mock_registry.create_session = mocker.AsyncMock(return_value=None)
-    mock_registry.subscribe_to_session = mocker.AsyncMock(return_value=subscriber_queue)
-    mock_registry.unsubscribe_from_session = mocker.AsyncMock(return_value=None)
     mocker.patch(
         "backend.api.features.chat.routes.stream_registry",
         mock_registry,
@@ -407,11 +165,11 @@ def test_stream_chat_accepts_20_file_ids(mocker: pytest_mock.MockFixture):
         "backend.api.features.chat.routes.get_or_create_workspace",
         return_value=type("W", (), {"id": "ws-1"})(),
     )
-    workspace_store = mocker.MagicMock()
-    workspace_store.get_workspace_files_by_ids = mocker.AsyncMock(return_value=[])
+    mock_prisma = mocker.MagicMock()
+    mock_prisma.find_many = mocker.AsyncMock(return_value=[])
     mocker.patch(
-        "backend.api.features.chat.routes.workspace_db",
-        return_value=workspace_store,
+        "prisma.models.UserWorkspaceFile.prisma",
+        return_value=mock_prisma,
     )
 
     response = client.post(
@@ -437,11 +195,11 @@ def test_file_ids_filters_invalid_uuids(mocker: pytest_mock.MockFixture):
         return_value=type("W", (), {"id": "ws-1"})(),
     )
 
-    workspace_store = mocker.MagicMock()
-    workspace_store.get_workspace_files_by_ids = mocker.AsyncMock(return_value=[])
+    mock_prisma = mocker.MagicMock()
+    mock_prisma.find_many = mocker.AsyncMock(return_value=[])
     mocker.patch(
-        "backend.api.features.chat.routes.workspace_db",
-        return_value=workspace_store,
+        "prisma.models.UserWorkspaceFile.prisma",
+        return_value=mock_prisma,
     )
 
     valid_id = "aaaaaaaa-bbbb-cccc-dddd-eeeeeeeeeeee"
@@ -459,10 +217,9 @@ def test_file_ids_filters_invalid_uuids(mocker: pytest_mock.MockFixture):
     )
 
     # The find_many call should only receive the one valid UUID
-    workspace_store.get_workspace_files_by_ids.assert_called_once_with(
-        workspace_id="ws-1",
-        file_ids=[valid_id],
-    )
+    mock_prisma.find_many.assert_called_once()
+    call_kwargs = mock_prisma.find_many.call_args[1]
+    assert call_kwargs["where"]["id"]["in"] == [valid_id]
 
 
 # ─── Cross-workspace file_ids ─────────────────────────────────────────
@@ -476,11 +233,11 @@ def test_file_ids_scoped_to_workspace(mocker: pytest_mock.MockFixture):
         return_value=type("W", (), {"id": "my-workspace-id"})(),
     )
 
-    workspace_store = mocker.MagicMock()
-    workspace_store.get_workspace_files_by_ids = mocker.AsyncMock(return_value=[])
+    mock_prisma = mocker.MagicMock()
+    mock_prisma.find_many = mocker.AsyncMock(return_value=[])
     mocker.patch(
-        "backend.api.features.chat.routes.workspace_db",
-        return_value=workspace_store,
+        "prisma.models.UserWorkspaceFile.prisma",
+        return_value=mock_prisma,
     )
 
     fid = "aaaaaaaa-bbbb-cccc-dddd-eeeeeeeeeeee"
@@ -489,10 +246,9 @@ def test_file_ids_scoped_to_workspace(mocker: pytest_mock.MockFixture):
         json={"message": "hi", "file_ids": [fid]},
     )
 
-    workspace_store.get_workspace_files_by_ids.assert_called_once_with(
-        workspace_id="my-workspace-id",
-        file_ids=[fid],
-    )
+    call_kwargs = mock_prisma.find_many.call_args[1]
+    assert call_kwargs["where"]["workspaceId"] == "my-workspace-id"
+    assert call_kwargs["where"]["isDeleted"] is False
 
 
 # ─── Suggested prompts endpoint ──────────────────────────────────────

autogpt_platform/backend/backend/blocks/github/commits.py

@@ -11,7 +11,10 @@ from backend.blocks._base import (
     BlockSchemaInput,
     BlockSchemaOutput,
 )
+from backend.data.execution import ExecutionContext
 from backend.data.model import SchemaField
+from backend.util.file import parse_data_uri, resolve_media_content
+from backend.util.type import MediaFileType
 
 from ._api import get_api
 from ._auth import (
@@ -178,7 +181,8 @@ class FileOperation(StrEnum):
 
 class FileOperationInput(TypedDict):
     path: str
-    content: str
+    # MediaFileType is a str NewType — no runtime breakage for existing callers.
+    content: MediaFileType
     operation: FileOperation
 
 
@@ -275,11 +279,11 @@ class GithubMultiFileCommitBlock(Block):
         base_tree_sha = commit_data["tree"]["sha"]
 
         # 3. Build tree entries for each file operation (blobs created concurrently)
-        async def _create_blob(content: str) -> str:
+        async def _create_blob(content: str, encoding: str = "utf-8") -> str:
             blob_url = repo_url + "/git/blobs"
             blob_response = await api.post(
                 blob_url,
-                json={"content": content, "encoding": "utf-8"},
+                json={"content": content, "encoding": encoding},
             )
             return blob_response.json()["sha"]
 
@@ -301,10 +305,19 @@ class GithubMultiFileCommitBlock(Block):
             else:
                 upsert_files.append((path, file_op.get("content", "")))
 
-        # Create all blobs concurrently
+        # Create all blobs concurrently. Data URIs (from store_media_file)
+        # are sent as base64 blobs to preserve binary content.
         if upsert_files:
+
+            async def _make_blob(content: str) -> str:
+                parsed = parse_data_uri(content)
+                if parsed is not None:
+                    _, b64_payload = parsed
+                    return await _create_blob(b64_payload, encoding="base64")
+                return await _create_blob(content)
+
             blob_shas = await asyncio.gather(
-                *[_create_blob(content) for _, content in upsert_files]
+                *[_make_blob(content) for _, content in upsert_files]
             )
             for (path, _), blob_sha in zip(upsert_files, blob_shas):
                 tree_entries.append(
@@ -358,15 +371,36 @@ class GithubMultiFileCommitBlock(Block):
         input_data: Input,
         *,
         credentials: GithubCredentials,
+        execution_context: ExecutionContext,
         **kwargs,
     ) -> BlockOutput:
         try:
+            # Resolve media references (workspace://, data:, URLs) to data
+            # URIs so _make_blob can send binary content correctly.
+            resolved_files: list[FileOperationInput] = []
+            for file_op in input_data.files:
+                content = file_op.get("content", "")
+                operation = FileOperation(file_op.get("operation", "upsert"))
+                if operation != FileOperation.DELETE:
+                    content = await resolve_media_content(
+                        MediaFileType(content),
+                        execution_context,
+                        return_format="for_external_api",
+                    )
+                resolved_files.append(
+                    FileOperationInput(
+                        path=file_op["path"],
+                        content=MediaFileType(content),
+                        operation=operation,
+                    )
+                )
+
             sha, url = await self.multi_file_commit(
                 credentials,
                 input_data.repo_url,
                 input_data.branch,
                 input_data.commit_message,
-                input_data.files,
+                resolved_files,
             )
             yield "sha", sha
             yield "url", url

autogpt_platform/backend/backend/blocks/github/test_github_blocks.py

@@ -8,6 +8,7 @@ from backend.blocks.github.pull_requests import (
     GithubMergePullRequestBlock,
     prepare_pr_api_url,
 )
+from backend.data.execution import ExecutionContext
 from backend.util.exceptions import BlockExecutionError
 
 # ── prepare_pr_api_url tests ──
@@ -97,7 +98,11 @@ async def test_multi_file_commit_error_path():
         "credentials": TEST_CREDENTIALS_INPUT,
     }
     with pytest.raises(BlockExecutionError, match="ref update failed"):
-        async for _ in block.execute(input_data, credentials=TEST_CREDENTIALS):
+        async for _ in block.execute(
+            input_data,
+            credentials=TEST_CREDENTIALS,
+            execution_context=ExecutionContext(),
+        ):
             pass
 
 

autogpt_platform/backend/backend/copilot/autopilot.py

@@ -1,135 +0,0 @@
-"""Autopilot public API — thin facade re-exporting from sub-modules.
-
-Implementation is split by responsibility:
-- autopilot_prompts: constants, prompt templates, context builders
-- autopilot_dispatch: timezone helpers, session creation, dispatch/scheduling
-- autopilot_completion: completion report extraction, repair, handler
-- autopilot_email: email sending, link building, notification sweep
-"""
-
-from __future__ import annotations
-
-import logging
-from datetime import UTC, datetime
-
-from pydantic import BaseModel
-
-from backend.copilot.autopilot_completion import (  # noqa: F401
-    CompletionReportToolCall,
-    CompletionReportToolCallFunction,
-    ToolOutputEnvelope,
-    _build_completion_report_repair_message,
-    _extract_completion_report_from_session,
-    _get_pending_approval_metadata,
-    _queue_completion_report_repair,
-    handle_non_manual_session_completion,
-)
-from backend.copilot.autopilot_dispatch import (  # noqa: F401
-    _bucket_end_for_now,
-    _create_autopilot_session,
-    _crosses_local_midnight,
-    _enqueue_session_turn,
-    _resolve_timezone_name,
-    _session_exists_for_execution_tag,
-    _try_create_callback_session,
-    _try_create_invite_cta_session,
-    _try_create_nightly_session,
-    _user_has_recent_manual_message,
-    _user_has_session_since,
-    dispatch_nightly_copilot,
-    get_callback_execution_tag,
-    get_graph_exec_id_for_session,
-    get_invite_cta_execution_tag,
-    get_nightly_execution_tag,
-    trigger_autopilot_session_for_user,
-)
-from backend.copilot.autopilot_email import (  # noqa: F401
-    PendingCopilotEmailSweepResult,
-    _build_session_link,
-    _get_completion_email_template_name,
-    _markdown_to_email_html,
-    _send_completion_email,
-    _send_nightly_copilot_emails,
-    send_nightly_copilot_emails,
-    send_pending_copilot_emails_for_user,
-)
-from backend.copilot.autopilot_prompts import (  # noqa: F401
-    AUTOPILOT_CALLBACK_EMAIL_TEMPLATE,
-    AUTOPILOT_CALLBACK_TAG,
-    AUTOPILOT_DISABLED_TOOLS,
-    AUTOPILOT_INVITE_CTA_EMAIL_TEMPLATE,
-    AUTOPILOT_INVITE_CTA_TAG,
-    AUTOPILOT_NIGHTLY_EMAIL_TEMPLATE,
-    AUTOPILOT_NIGHTLY_TAG_PREFIX,
-    DEFAULT_AUTOPILOT_CALLBACK_SYSTEM_PROMPT,
-    DEFAULT_AUTOPILOT_INVITE_CTA_SYSTEM_PROMPT,
-    DEFAULT_AUTOPILOT_NIGHTLY_SYSTEM_PROMPT,
-    INTERNAL_TAG_RE,
-    MAX_COMPLETION_REPORT_REPAIRS,
-    _build_autopilot_system_prompt,
-    _format_start_type_label,
-    _get_recent_manual_session_context,
-    _get_recent_sent_email_context,
-    _get_recent_session_summary_context,
-    strip_internal_content,
-    unwrap_internal_content,
-    wrap_internal_message,
-)
-from backend.copilot.model import ChatMessage, create_chat_session
-from backend.data.db_accessors import chat_db
-
-# -- re-exports from sub-modules (preserves existing import paths) ---------- #
-
-
-logger = logging.getLogger(__name__)
-
-
-class CallbackTokenConsumeResult(BaseModel):
-    session_id: str
-
-
-async def consume_callback_token(
-    token_id: str,
-    user_id: str,
-) -> CallbackTokenConsumeResult:
-    """Consume a callback token and return the resulting session.
-
-    Uses an atomic consume-and-update to prevent the TOCTOU race where two
-    concurrent requests could each see the token as unconsumed and create
-    duplicate sessions.
-    """
-    db = chat_db()
-    token = await db.get_chat_session_callback_token(token_id)
-    if token is None or token.user_id != user_id:
-        raise ValueError("Callback token not found")
-    if token.expires_at <= datetime.now(UTC):
-        raise ValueError("Callback token has expired")
-
-    if token.consumed_session_id:
-        return CallbackTokenConsumeResult(session_id=token.consumed_session_id)
-
-    session = await create_chat_session(
-        user_id,
-        initial_messages=[
-            ChatMessage(role="assistant", content=token.callback_session_message)
-        ],
-    )
-
-    # Atomically mark consumed — if another request already consumed the token
-    # concurrently, the DB will have a non-null consumed_session_id; we re-read
-    # and return the winner's session instead.
-    await db.mark_chat_session_callback_token_consumed(
-        token_id,
-        session.session_id,
-    )
-
-    # Re-read to see if we won the race
-    refreshed = await db.get_chat_session_callback_token(token_id)
-    if (
-        refreshed
-        and refreshed.consumed_session_id
-        and refreshed.consumed_session_id != session.session_id
-    ):
-        return CallbackTokenConsumeResult(session_id=refreshed.consumed_session_id)
-
-    return CallbackTokenConsumeResult(session_id=session.session_id)

autogpt_platform/backend/backend/copilot/autopilot_completion.py

@@ -1,198 +0,0 @@
-from __future__ import annotations
-
-import logging
-from datetime import UTC, datetime
-
-from pydantic import BaseModel, Field, ValidationError
-
-from backend.copilot.autopilot_dispatch import (
-    _enqueue_session_turn,
-    get_graph_exec_id_for_session,
-)
-from backend.copilot.autopilot_prompts import (
-    MAX_COMPLETION_REPORT_REPAIRS,
-    wrap_internal_message,
-)
-from backend.copilot.model import (
-    ChatMessage,
-    ChatSession,
-    get_chat_session,
-    upsert_chat_session,
-)
-from backend.copilot.session_types import CompletionReportInput, StoredCompletionReport
-from backend.data.db_accessors import review_db
-
-logger = logging.getLogger(__name__)
-
-
-# --------------- models --------------- #
-
-
-class CompletionReportToolCallFunction(BaseModel):
-    name: str | None = None
-    arguments: str | None = None
-
-
-class CompletionReportToolCall(BaseModel):
-    id: str
-    function: CompletionReportToolCallFunction = Field(
-        default_factory=CompletionReportToolCallFunction
-    )
-
-
-class ToolOutputEnvelope(BaseModel):
-    type: str | None = None
-
-
-# --------------- approval metadata --------------- #
-
-
-async def _get_pending_approval_metadata(
-    session: ChatSession,
-) -> tuple[int, str | None]:
-    graph_exec_id = get_graph_exec_id_for_session(session.session_id)
-    pending_count = await review_db().count_pending_reviews_for_graph_exec(
-        graph_exec_id,
-        session.user_id,
-    )
-    return pending_count, graph_exec_id if pending_count > 0 else None
-
-
-# --------------- extraction --------------- #
-
-
-def _extract_completion_report_from_session(
-    session: ChatSession,
-    *,
-    pending_approval_count: int,
-) -> CompletionReportInput | None:
-    tool_outputs = {
-        message.tool_call_id: message.content
-        for message in session.messages
-        if message.role == "tool" and message.tool_call_id
-    }
-
-    latest_report: CompletionReportInput | None = None
-    for message in session.messages:
-        if message.role != "assistant" or not message.tool_calls:
-            continue
-
-        for tool_call in message.tool_calls:
-            try:
-                parsed_tool_call = CompletionReportToolCall.model_validate(tool_call)
-            except ValidationError:
-                continue
-
-            if parsed_tool_call.function.name != "completion_report":
-                continue
-
-            output = tool_outputs.get(parsed_tool_call.id)
-            if not output:
-                continue
-
-            try:
-                output_payload = ToolOutputEnvelope.model_validate_json(output)
-            except ValidationError:
-                output_payload = None
-
-            if output_payload is not None and output_payload.type == "error":
-                continue
-
-            try:
-                raw_arguments = parsed_tool_call.function.arguments or "{}"
-                report = CompletionReportInput.model_validate_json(raw_arguments)
-            except ValidationError:
-                continue
-
-            if pending_approval_count > 0 and not report.approval_summary:
-                continue
-
-            latest_report = report
-
-    return latest_report
-
-
-# --------------- repair --------------- #
-
-
-def _build_completion_report_repair_message(
-    *,
-    attempt: int,
-    pending_approval_count: int,
-) -> str:
-    approval_instruction = ""
-    if pending_approval_count > 0:
-        approval_instruction = (
-            f" There are currently {pending_approval_count} pending approval item(s). "
-            "If they still exist, include approval_summary."
-        )
-
-    return wrap_internal_message(
-        "The session completed without a valid completion_report tool call. "
-        f"This is repair attempt {attempt}. Call completion_report now and do not do any additional user-facing work."
-        + approval_instruction
-    )
-
-
-async def _queue_completion_report_repair(
-    session: ChatSession,
-    *,
-    pending_approval_count: int,
-) -> None:
-    attempt = session.completion_report_repair_count + 1
-    repair_message = _build_completion_report_repair_message(
-        attempt=attempt,
-        pending_approval_count=pending_approval_count,
-    )
-    session.messages.append(ChatMessage(role="user", content=repair_message))
-    session.completion_report_repair_count = attempt
-    session.completion_report_repair_queued_at = datetime.now(UTC)
-    session.completed_at = None
-    session.completion_report = None
-    await upsert_chat_session(session)
-    await _enqueue_session_turn(
-        session,
-        message=repair_message,
-        tool_name="completion_report_repair",
-    )
-
-
-# --------------- handler --------------- #
-
-
-async def handle_non_manual_session_completion(session_id: str) -> None:
-    session = await get_chat_session(session_id)
-    if session is None or session.is_manual:
-        return
-
-    pending_approval_count, graph_exec_id = await _get_pending_approval_metadata(
-        session
-    )
-    report = _extract_completion_report_from_session(
-        session,
-        pending_approval_count=pending_approval_count,
-    )
-
-    if report is not None:
-        session.completion_report = StoredCompletionReport(
-            **report.model_dump(),
-            has_pending_approvals=pending_approval_count > 0,
-            pending_approval_count=pending_approval_count,
-            pending_approval_graph_exec_id=graph_exec_id,
-            saved_at=datetime.now(UTC),
-        )
-        session.completion_report_repair_queued_at = None
-        session.completed_at = datetime.now(UTC)
-        await upsert_chat_session(session)
-        return
-
-    if session.completion_report_repair_count >= MAX_COMPLETION_REPORT_REPAIRS:
-        session.completion_report_repair_queued_at = None
-        session.completed_at = datetime.now(UTC)
-        await upsert_chat_session(session)
-        return
-
-    await _queue_completion_report_repair(
-        session,
-        pending_approval_count=pending_approval_count,
-    )

autogpt_platform/backend/backend/copilot/autopilot_dispatch.py

@@ -1,386 +0,0 @@
-from __future__ import annotations
-
-import logging
-from datetime import UTC, date, datetime, time, timedelta
-from typing import TYPE_CHECKING
-from uuid import uuid4
-from zoneinfo import ZoneInfo
-
-import prisma.enums
-
-from backend.copilot import stream_registry
-from backend.copilot.autopilot_prompts import (
-    AUTOPILOT_CALLBACK_TAG,
-    AUTOPILOT_DISABLED_TOOLS,
-    AUTOPILOT_INVITE_CTA_TAG,
-    AUTOPILOT_NIGHTLY_TAG_PREFIX,
-    _build_autopilot_system_prompt,
-    _render_initial_message,
-)
-from backend.copilot.constants import COPILOT_SESSION_PREFIX
-from backend.copilot.executor.utils import enqueue_copilot_turn
-from backend.copilot.model import ChatMessage, ChatSession, create_chat_session
-from backend.copilot.session_types import ChatSessionConfig, ChatSessionStartType
-from backend.data.db_accessors import chat_db, invited_user_db, user_db
-from backend.data.model import User
-from backend.util.feature_flag import Flag, is_feature_enabled
-from backend.util.settings import Settings
-from backend.util.timezone_utils import get_user_timezone_or_utc
-
-if TYPE_CHECKING:
-    from backend.data.invited_user import InvitedUserRecord
-
-logger = logging.getLogger(__name__)
-settings = Settings()
-
-DISPATCH_BATCH_SIZE = 500
-
-
-# --------------- tag helpers --------------- #
-
-
-def get_graph_exec_id_for_session(session_id: str) -> str:
-    return f"{COPILOT_SESSION_PREFIX}{session_id}"
-
-
-def get_nightly_execution_tag(target_local_date: date) -> str:
-    return f"{AUTOPILOT_NIGHTLY_TAG_PREFIX}{target_local_date.isoformat()}"
-
-
-def get_callback_execution_tag() -> str:
-    return AUTOPILOT_CALLBACK_TAG
-
-
-def get_invite_cta_execution_tag() -> str:
-    return AUTOPILOT_INVITE_CTA_TAG
-
-
-def _get_manual_trigger_execution_tag(start_type: ChatSessionStartType) -> str:
-    timestamp = datetime.now(UTC).strftime("%Y%m%dT%H%M%S%fZ")
-    return f"admin-autopilot:{start_type.value}:{timestamp}:{uuid4()}"
-
-
-# --------------- timezone helpers --------------- #
-
-
-def _bucket_end_for_now(now_utc: datetime) -> datetime:
-    minute = 30 if now_utc.minute >= 30 else 0
-    return now_utc.replace(minute=minute, second=0, microsecond=0)
-
-
-def _resolve_timezone_name(raw_timezone: str | None) -> str:
-    return get_user_timezone_or_utc(raw_timezone)
-
-
-def _crosses_local_midnight(
-    bucket_start_utc: datetime,
-    bucket_end_utc: datetime,
-    timezone_name: str,
-) -> date | None:
-    """Return the new local date if *bucket_end_utc* falls on a different local
-    date than *bucket_start_utc*, taking DST transitions into account.
-
-    During a DST spring-forward the wall clock jumps forward (e.g. 01:59 →
-    03:00).  We use ``fold=0`` on the end instant so that ambiguous/missing
-    times are resolved consistently and a single 30-min UTC bucket can never
-    produce midnight on *two* consecutive calls.
-    """
-    tz = ZoneInfo(timezone_name)
-    start_local = bucket_start_utc.astimezone(tz)
-    end_local = bucket_end_utc.astimezone(tz)
-    # Resolve ambiguous wall-clock times consistently (spring-forward / fall-back)
-    end_local = end_local.replace(fold=0)
-    if start_local.date() == end_local.date():
-        return None
-    return end_local.date()
-
-
-# --------------- thin DB wrappers --------------- #
-
-
-async def _user_has_recent_manual_message(user_id: str, since: datetime) -> bool:
-    return await chat_db().has_recent_manual_message(user_id, since)
-
-
-async def _user_has_session_since(user_id: str, since: datetime) -> bool:
-    return await chat_db().has_session_since(user_id, since)
-
-
-async def _session_exists_for_execution_tag(user_id: str, execution_tag: str) -> bool:
-    return await chat_db().session_exists_for_execution_tag(user_id, execution_tag)
-
-
-# --------------- session creation --------------- #
-
-
-async def _enqueue_session_turn(
-    session: ChatSession,
-    *,
-    message: str,
-    tool_name: str,
-) -> None:
-    turn_id = str(uuid4())
-    await stream_registry.create_session(
-        session_id=session.session_id,
-        user_id=session.user_id,
-        tool_call_id=tool_name,
-        tool_name=tool_name,
-        turn_id=turn_id,
-        blocking=False,
-    )
-    await enqueue_copilot_turn(
-        session_id=session.session_id,
-        user_id=session.user_id,
-        message=message,
-        turn_id=turn_id,
-        is_user_message=True,
-    )
-
-
-async def _create_autopilot_session(
-    user: User,
-    *,
-    start_type: ChatSessionStartType,
-    execution_tag: str,
-    timezone_name: str,
-    target_local_date: date | None = None,
-    invited_user: InvitedUserRecord | None = None,
-) -> ChatSession | None:
-    if await _session_exists_for_execution_tag(user.id, execution_tag):
-        return None
-
-    system_prompt = await _build_autopilot_system_prompt(
-        user,
-        start_type=start_type,
-        timezone_name=timezone_name,
-        target_local_date=target_local_date,
-        invited_user=invited_user,
-    )
-    initial_message = _render_initial_message(
-        start_type,
-        user_name=user.name,
-        invited_user=invited_user,
-    )
-    session_config = ChatSessionConfig(
-        system_prompt_override=system_prompt,
-        initial_user_message=initial_message,
-        extra_tools=["completion_report"],
-        disabled_tools=AUTOPILOT_DISABLED_TOOLS,
-    )
-
-    session = await create_chat_session(
-        user.id,
-        start_type=start_type,
-        execution_tag=execution_tag,
-        session_config=session_config,
-        initial_messages=[ChatMessage(role="user", content=initial_message)],
-    )
-    await _enqueue_session_turn(
-        session,
-        message=initial_message,
-        tool_name="autopilot_dispatch",
-    )
-    return session
-
-
-# --------------- cohort helpers --------------- #
-
-
-async def _try_create_invite_cta_session(
-    user: User,
-    *,
-    invited_user: InvitedUserRecord | None,
-    now_utc: datetime,
-    timezone_name: str,
-    invite_cta_start: date,
-    invite_cta_delay: timedelta,
-) -> bool:
-    if invited_user is None:
-        return False
-    if invited_user.status != prisma.enums.InvitedUserStatus.INVITED:
-        return False
-    if invited_user.created_at.date() < invite_cta_start:
-        return False
-    if invited_user.created_at > now_utc - invite_cta_delay:
-        return False
-    if await _session_exists_for_execution_tag(user.id, get_invite_cta_execution_tag()):
-        return False
-
-    created = await _create_autopilot_session(
-        user,
-        start_type=ChatSessionStartType.AUTOPILOT_INVITE_CTA,
-        execution_tag=get_invite_cta_execution_tag(),
-        timezone_name=timezone_name,
-        invited_user=invited_user,
-    )
-    return created is not None
-
-
-async def _try_create_nightly_session(
-    user: User,
-    *,
-    now_utc: datetime,
-    timezone_name: str,
-    target_local_date: date,
-) -> bool:
-    if not await _user_has_recent_manual_message(
-        user.id,
-        now_utc - timedelta(hours=24),
-    ):
-        return False
-
-    created = await _create_autopilot_session(
-        user,
-        start_type=ChatSessionStartType.AUTOPILOT_NIGHTLY,
-        execution_tag=get_nightly_execution_tag(target_local_date),
-        timezone_name=timezone_name,
-        target_local_date=target_local_date,
-    )
-    return created is not None
-
-
-async def _try_create_callback_session(
-    user: User,
-    *,
-    callback_start: datetime,
-    timezone_name: str,
-) -> bool:
-    if not await _user_has_session_since(user.id, callback_start):
-        return False
-    if await _session_exists_for_execution_tag(user.id, get_callback_execution_tag()):
-        return False
-
-    created = await _create_autopilot_session(
-        user,
-        start_type=ChatSessionStartType.AUTOPILOT_CALLBACK,
-        execution_tag=get_callback_execution_tag(),
-        timezone_name=timezone_name,
-    )
-    return created is not None
-
-
-# --------------- dispatch --------------- #
-
-
-async def _dispatch_nightly_copilot() -> int:
-    now_utc = datetime.now(UTC)
-    bucket_end = _bucket_end_for_now(now_utc)
-    bucket_start = bucket_end - timedelta(minutes=30)
-    callback_start = datetime.combine(
-        settings.config.nightly_copilot_callback_start_date,
-        time.min,
-        tzinfo=UTC,
-    )
-    invite_cta_start = settings.config.nightly_copilot_invite_cta_start_date
-    invite_cta_delay = timedelta(
-        hours=settings.config.nightly_copilot_invite_cta_delay_hours
-    )
-
-    # Paginate user list to avoid loading the entire table into memory.
-    created_count = 0
-    cursor: str | None = None
-    while True:
-        batch = await user_db().list_users(
-            limit=DISPATCH_BATCH_SIZE,
-            cursor=cursor,
-        )
-        if not batch:
-            break
-
-        user_ids = [user.id for user in batch]
-        invites = await invited_user_db().list_invited_users_for_auth_users(user_ids)
-        invites_by_user_id = {
-            invite.auth_user_id: invite for invite in invites if invite.auth_user_id
-        }
-
-        for user in batch:
-            if not await is_feature_enabled(
-                Flag.NIGHTLY_COPILOT, user.id, default=False
-            ):
-                continue
-
-            timezone_name = _resolve_timezone_name(user.timezone)
-            target_local_date = _crosses_local_midnight(
-                bucket_start,
-                bucket_end,
-                timezone_name,
-            )
-            if target_local_date is None:
-                continue
-
-            invited_user = invites_by_user_id.get(user.id)
-            if await _try_create_invite_cta_session(
-                user,
-                invited_user=invited_user,
-                now_utc=now_utc,
-                timezone_name=timezone_name,
-                invite_cta_start=invite_cta_start,
-                invite_cta_delay=invite_cta_delay,
-            ):
-                created_count += 1
-                continue
-
-            if await _try_create_nightly_session(
-                user,
-                now_utc=now_utc,
-                timezone_name=timezone_name,
-                target_local_date=target_local_date,
-            ):
-                created_count += 1
-                continue
-
-            if await _try_create_callback_session(
-                user,
-                callback_start=callback_start,
-                timezone_name=timezone_name,
-            ):
-                created_count += 1
-
-        cursor = batch[-1].id if len(batch) == DISPATCH_BATCH_SIZE else None
-        if cursor is None:
-            break
-
-    return created_count
-
-
-async def dispatch_nightly_copilot() -> int:
-    return await _dispatch_nightly_copilot()
-
-
-async def trigger_autopilot_session_for_user(
-    user_id: str,
-    *,
-    start_type: ChatSessionStartType,
-) -> ChatSession:
-    allowed_start_types = {
-        ChatSessionStartType.AUTOPILOT_INVITE_CTA,
-        ChatSessionStartType.AUTOPILOT_NIGHTLY,
-        ChatSessionStartType.AUTOPILOT_CALLBACK,
-    }
-    if start_type not in allowed_start_types:
-        raise ValueError(f"Unsupported autopilot start type: {start_type}")
-
-    try:
-        user = await user_db().get_user_by_id(user_id)
-    except ValueError as exc:
-        raise LookupError(str(exc)) from exc
-
-    invites = await invited_user_db().list_invited_users_for_auth_users([user_id])
-    invited_user = invites[0] if invites else None
-    timezone_name = _resolve_timezone_name(user.timezone)
-    target_local_date = None
-    if start_type == ChatSessionStartType.AUTOPILOT_NIGHTLY:
-        target_local_date = datetime.now(UTC).astimezone(ZoneInfo(timezone_name)).date()
-
-    session = await _create_autopilot_session(
-        user,
-        start_type=start_type,
-        execution_tag=_get_manual_trigger_execution_tag(start_type),
-        timezone_name=timezone_name,
-        target_local_date=target_local_date,
-        invited_user=invited_user,
-    )
-    if session is None:
-        raise ValueError("Failed to create autopilot session")
-
-    return session

autogpt_platform/backend/backend/copilot/autopilot_email.py

@@ -1,297 +0,0 @@
-from __future__ import annotations
-
-import asyncio
-import logging
-from datetime import UTC, datetime
-
-from markdown_it import MarkdownIt
-from pydantic import BaseModel
-
-from backend.copilot import stream_registry
-from backend.copilot.autopilot_completion import (
-    _get_pending_approval_metadata,
-    _queue_completion_report_repair,
-)
-from backend.copilot.autopilot_prompts import (
-    AUTOPILOT_CALLBACK_EMAIL_TEMPLATE,
-    AUTOPILOT_INVITE_CTA_EMAIL_TEMPLATE,
-    AUTOPILOT_NIGHTLY_EMAIL_TEMPLATE,
-    MAX_COMPLETION_REPORT_REPAIRS,
-)
-from backend.copilot.model import (
-    ChatSession,
-    get_chat_session,
-    update_session_title,
-    upsert_chat_session,
-)
-from backend.copilot.service import _generate_session_title
-from backend.copilot.session_types import ChatSessionStartType
-from backend.data.db_accessors import chat_db, user_db
-from backend.notifications.email import EmailSender
-from backend.util.url import get_frontend_base_url
-
-logger = logging.getLogger(__name__)
-PENDING_NOTIFICATION_SWEEP_LIMIT = 200
-
-_md = MarkdownIt()
-
-_EMAIL_INLINE_STYLES: list[tuple[str, str]] = [
-    (
-        "<p>",
-        '<p style="font-size: 15px; line-height: 170%;'
-        " margin-top: 0; margin-bottom: 16px;"
-        ' color: #1F1F20;">',
-    ),
-    (
-        "<li>",
-        '<li style="font-size: 15px; line-height: 170%;'
-        " margin-top: 0; margin-bottom: 8px;"
-        ' color: #1F1F20;">',
-    ),
-    (
-        "<ul>",
-        '<ul style="padding: 0 0 0 24px;' ' margin-top: 0; margin-bottom: 16px;">',
-    ),
-    (
-        "<ol>",
-        '<ol style="padding: 0 0 0 24px;' ' margin-top: 0; margin-bottom: 16px;">',
-    ),
-    (
-        "<a ",
-        '<a style="color: #7733F5;'
-        " text-decoration: underline;"
-        ' font-weight: 500;" ',
-    ),
-    (
-        "<h2>",
-        '<h2 style="font-size: 20px; font-weight: 600;'
-        ' margin-top: 0; margin-bottom: 12px; color: #1F1F20;">',
-    ),
-    (
-        "<h3>",
-        '<h3 style="font-size: 18px; font-weight: 600;'
-        ' margin-top: 0; margin-bottom: 12px; color: #1F1F20;">',
-    ),
-]
-
-
-def _markdown_to_email_html(text: str | None) -> str:
-    """Convert markdown text to email-safe HTML with inline styles."""
-    if not text or not text.strip():
-        return ""
-    html = _md.render(text.strip())
-    for tag, styled_tag in _EMAIL_INLINE_STYLES:
-        html = html.replace(tag, styled_tag)
-    return html.strip()
-
-
-# --------------- link builders --------------- #
-
-
-def _build_session_link(session_id: str, *, show_autopilot: bool) -> str:
-    base_url = get_frontend_base_url()
-    suffix = "&showAutopilot=1" if show_autopilot else ""
-    return f"{base_url}/copilot?sessionId={session_id}{suffix}"
-
-
-def _get_completion_email_template_name(start_type: ChatSessionStartType) -> str:
-    if start_type == ChatSessionStartType.AUTOPILOT_NIGHTLY:
-        return AUTOPILOT_NIGHTLY_EMAIL_TEMPLATE
-    if start_type == ChatSessionStartType.AUTOPILOT_CALLBACK:
-        return AUTOPILOT_CALLBACK_EMAIL_TEMPLATE
-    if start_type == ChatSessionStartType.AUTOPILOT_INVITE_CTA:
-        return AUTOPILOT_INVITE_CTA_EMAIL_TEMPLATE
-    raise ValueError(f"Unsupported start type for completion email: {start_type}")
-
-
-class PendingCopilotEmailSweepResult(BaseModel):
-    candidate_count: int = 0
-    processed_count: int = 0
-    sent_count: int = 0
-    skipped_count: int = 0
-    repair_queued_count: int = 0
-    running_count: int = 0
-    failed_count: int = 0
-
-
-async def _ensure_session_title_for_completed_session(session: ChatSession) -> None:
-    if session.title or not session.user_id:
-        return
-
-    report = session.completion_report
-    if report is None:
-        return
-
-    title = report.email_title.strip() if report.email_title else ""
-    if not title:
-        title_seed = report.email_body or report.thoughts
-        if title_seed:
-            generated_title = await _generate_session_title(
-                title_seed,
-                user_id=session.user_id,
-                session_id=session.session_id,
-            )
-            title = generated_title.strip() if generated_title else ""
-
-    if not title:
-        return
-
-    updated = await update_session_title(
-        session.session_id,
-        session.user_id,
-        title,
-        only_if_empty=True,
-    )
-    if updated:
-        session.title = title
-
-
-# --------------- send email --------------- #
-
-
-async def _send_completion_email(session: ChatSession) -> None:
-    report = session.completion_report
-    if report is None:
-        raise ValueError("Missing completion report")
-    try:
-        user = await user_db().get_user_by_id(session.user_id)
-    except ValueError as exc:
-        raise ValueError(f"User {session.user_id} not found") from exc
-
-    if not user.email:
-        raise ValueError(f"User {session.user_id} not found")
-
-    approval_cta = report.has_pending_approvals
-    template_name = _get_completion_email_template_name(session.start_type)
-    if approval_cta:
-        cta_url = _build_session_link(session.session_id, show_autopilot=True)
-        cta_label = "Review in Copilot"
-    else:
-        cta_url = _build_session_link(session.session_id, show_autopilot=True)
-        cta_label = (
-            "Try Copilot"
-            if session.start_type == ChatSessionStartType.AUTOPILOT_INVITE_CTA
-            else "Open Copilot"
-        )
-
-    # EmailSender.send_template is synchronous (blocking HTTP call to Postmark).
-    # Run it in a thread to avoid blocking the async event loop.
-    sender = EmailSender()
-    await asyncio.to_thread(
-        sender.send_template,
-        user_email=user.email,
-        subject=report.email_title or "Autopilot update",
-        template_name=template_name,
-        data={
-            "email_body_html": _markdown_to_email_html(report.email_body),
-            "approval_summary_html": _markdown_to_email_html(report.approval_summary),
-            "cta_url": cta_url,
-            "cta_label": cta_label,
-        },
-    )
-
-
-# --------------- email sweep --------------- #
-
-
-async def _process_pending_copilot_email_candidates(
-    candidates: list,
-) -> PendingCopilotEmailSweepResult:
-    result = PendingCopilotEmailSweepResult(candidate_count=len(candidates))
-
-    for candidate in candidates:
-        session = await get_chat_session(candidate.session_id)
-        if session is None or session.is_manual:
-            continue
-
-        active = await stream_registry.get_session(session.session_id)
-        is_running = active is not None and active.status == "running"
-        if is_running:
-            result.running_count += 1
-            continue
-
-        pending_approval_count, graph_exec_id = await _get_pending_approval_metadata(
-            session
-        )
-
-        if session.completion_report is None:
-            if session.completion_report_repair_count < MAX_COMPLETION_REPORT_REPAIRS:
-                await _queue_completion_report_repair(
-                    session,
-                    pending_approval_count=pending_approval_count,
-                )
-                result.repair_queued_count += 1
-                continue
-
-            session.completed_at = session.completed_at or datetime.now(UTC)
-            session.completion_report_repair_queued_at = None
-            session.notification_email_skipped_at = datetime.now(UTC)
-            await upsert_chat_session(session)
-            result.skipped_count += 1
-            continue
-
-        session.completed_at = session.completed_at or datetime.now(UTC)
-        if (
-            session.completion_report.pending_approval_graph_exec_id is None
-            and graph_exec_id
-        ):
-            session.completion_report = session.completion_report.model_copy(
-                update={
-                    "has_pending_approvals": pending_approval_count > 0,
-                    "pending_approval_count": pending_approval_count,
-                    "pending_approval_graph_exec_id": graph_exec_id,
-                }
-            )
-
-        try:
-            await _ensure_session_title_for_completed_session(session)
-        except Exception:
-            logger.exception(
-                "Failed to ensure session title for session %s",
-                session.session_id,
-            )
-
-        if not session.completion_report.should_notify_user:
-            session.notification_email_skipped_at = datetime.now(UTC)
-            await upsert_chat_session(session)
-            result.skipped_count += 1
-            continue
-
-        try:
-            await _send_completion_email(session)
-        except Exception:
-            logger.exception(
-                "Failed to send nightly copilot email for session %s",
-                session.session_id,
-            )
-            result.failed_count += 1
-            continue
-
-        session.notification_email_sent_at = datetime.now(UTC)
-        await upsert_chat_session(session)
-        result.sent_count += 1
-
-    result.processed_count = result.sent_count + result.skipped_count
-    return result
-
-
-async def _send_nightly_copilot_emails() -> int:
-    candidates = await chat_db().get_pending_notification_chat_sessions(
-        limit=PENDING_NOTIFICATION_SWEEP_LIMIT
-    )
-    result = await _process_pending_copilot_email_candidates(candidates)
-    return result.processed_count
-
-
-async def send_nightly_copilot_emails() -> int:
-    return await _send_nightly_copilot_emails()
-
-
-async def send_pending_copilot_emails_for_user(
-    user_id: str,
-) -> PendingCopilotEmailSweepResult:
-    candidates = await chat_db().get_pending_notification_chat_sessions_for_user(
-        user_id,
-        limit=PENDING_NOTIFICATION_SWEEP_LIMIT,
-    )
-    return await _process_pending_copilot_email_candidates(candidates)

autogpt_platform/backend/backend/copilot/autopilot_prompts.py

@@ -1,409 +0,0 @@
-from __future__ import annotations
-
-import json
-import logging
-import re
-from datetime import date, datetime, time, timedelta
-from typing import TYPE_CHECKING, Any
-
-from backend.copilot.service import _get_system_prompt_template
-from backend.copilot.service import config as chat_config
-from backend.copilot.session_types import ChatSessionStartType
-from backend.data.db_accessors import chat_db, understanding_db
-from backend.data.understanding import format_understanding_for_prompt
-
-if TYPE_CHECKING:
-    from backend.data.invited_user import InvitedUserRecord
-
-logger = logging.getLogger(__name__)
-
-INTERNAL_TAG_RE = re.compile(r"<internal>.*?</internal>", re.DOTALL)
-MAX_COMPLETION_REPORT_REPAIRS = 2
-AUTOPILOT_RECENT_CONTEXT_CHAR_LIMIT = 6000
-AUTOPILOT_RECENT_SESSION_LIMIT = 5
-AUTOPILOT_RECENT_MESSAGE_LIMIT = 6
-AUTOPILOT_MESSAGE_CHAR_LIMIT = 500
-AUTOPILOT_EMAIL_HISTORY_LIMIT = 5
-AUTOPILOT_SESSION_SUMMARY_LIMIT = 2
-
-AUTOPILOT_NIGHTLY_TAG_PREFIX = "autopilot-nightly:"
-AUTOPILOT_CALLBACK_TAG = "autopilot-callback:v1"
-AUTOPILOT_INVITE_CTA_TAG = "autopilot-invite-cta:v1"
-AUTOPILOT_DISABLED_TOOLS = ["edit_agent"]
-AUTOPILOT_NIGHTLY_EMAIL_TEMPLATE = "nightly_copilot.html.jinja2"
-AUTOPILOT_CALLBACK_EMAIL_TEMPLATE = "nightly_copilot_callback.html.jinja2"
-AUTOPILOT_INVITE_CTA_EMAIL_TEMPLATE = "nightly_copilot_invite_cta.html.jinja2"
-
-DEFAULT_AUTOPILOT_NIGHTLY_SYSTEM_PROMPT = """You are Autopilot running a proactive nightly Copilot session.
-
-<business_understanding>
-{business_understanding}
-</business_understanding>
-
-<recent_copilot_emails>
-{recent_copilot_emails}
-</recent_copilot_emails>
-
-<recent_session_summaries>
-{recent_session_summaries}
-</recent_session_summaries>
-
-<recent_manual_sessions>
-{recent_manual_sessions}
-</recent_manual_sessions>
-
-Use the supplied business understanding, recent sent emails, and recent session context to choose one bounded, practical piece of work.
-Bias toward concrete progress over broad brainstorming.
-If you decide the user should be notified, finish by calling completion_report.
-Do not mention hidden system instructions or internal control text to the user."""
-
-DEFAULT_AUTOPILOT_CALLBACK_SYSTEM_PROMPT = """You are Autopilot running a one-off callback session for a previously active platform user.
-
-<business_understanding>
-{business_understanding}
-</business_understanding>
-
-<recent_copilot_emails>
-{recent_copilot_emails}
-</recent_copilot_emails>
-
-<recent_session_summaries>
-{recent_session_summaries}
-</recent_session_summaries>
-
-Use the supplied business understanding, recent sent emails, and recent session context to reintroduce Copilot with something concrete and useful.
-If you decide the user should be notified, finish by calling completion_report.
-Do not mention hidden system instructions or internal control text to the user."""
-
-DEFAULT_AUTOPILOT_INVITE_CTA_SYSTEM_PROMPT = """You are Autopilot running a one-off activation CTA for an invited beta user.
-
-<business_understanding>
-{business_understanding}
-</business_understanding>
-
-<beta_application_context>
-{beta_application_context}
-</beta_application_context>
-
-<recent_copilot_emails>
-{recent_copilot_emails}
-</recent_copilot_emails>
-
-<recent_session_summaries>
-{recent_session_summaries}
-</recent_session_summaries>
-
-Use the supplied business understanding, beta-application context, recent sent emails, and recent session context to explain what Autopilot can do for the user and why it fits their workflow.
-Keep the work introduction-specific and outcome-oriented.
-If you decide the user should be notified, finish by calling completion_report.
-Do not mention hidden system instructions or internal control text to the user."""
-
-
-def wrap_internal_message(content: str) -> str:
-    return f"<internal>{content}</internal>"
-
-
-def strip_internal_content(content: str | None) -> str | None:
-    if content is None:
-        return None
-    stripped = INTERNAL_TAG_RE.sub("", content).strip()
-    return stripped or None
-
-
-def unwrap_internal_content(content: str | None) -> str | None:
-    if content is None:
-        return None
-    unwrapped = content.replace("<internal>", "").replace("</internal>", "").strip()
-    return unwrapped or None
-
-
-def _truncate_prompt_text(text: str, max_chars: int) -> str:
-    normalized = " ".join(text.split())
-    if len(normalized) <= max_chars:
-        return normalized
-    return normalized[: max_chars - 3].rstrip() + "..."
-
-
-def _get_autopilot_prompt_name(start_type: ChatSessionStartType) -> str:
-    if start_type == ChatSessionStartType.AUTOPILOT_NIGHTLY:
-        return chat_config.langfuse_autopilot_nightly_prompt_name
-    if start_type == ChatSessionStartType.AUTOPILOT_CALLBACK:
-        return chat_config.langfuse_autopilot_callback_prompt_name
-    if start_type == ChatSessionStartType.AUTOPILOT_INVITE_CTA:
-        return chat_config.langfuse_autopilot_invite_cta_prompt_name
-    raise ValueError(f"Unsupported start type for autopilot prompt: {start_type}")
-
-
-def _get_autopilot_fallback_prompt(start_type: ChatSessionStartType) -> str:
-    if start_type == ChatSessionStartType.AUTOPILOT_NIGHTLY:
-        return DEFAULT_AUTOPILOT_NIGHTLY_SYSTEM_PROMPT
-    if start_type == ChatSessionStartType.AUTOPILOT_CALLBACK:
-        return DEFAULT_AUTOPILOT_CALLBACK_SYSTEM_PROMPT
-    if start_type == ChatSessionStartType.AUTOPILOT_INVITE_CTA:
-        return DEFAULT_AUTOPILOT_INVITE_CTA_SYSTEM_PROMPT
-    raise ValueError(f"Unsupported start type for autopilot prompt: {start_type}")
-
-
-def _format_start_type_label(start_type: ChatSessionStartType) -> str:
-    if start_type == ChatSessionStartType.AUTOPILOT_NIGHTLY:
-        return "Nightly"
-    if start_type == ChatSessionStartType.AUTOPILOT_CALLBACK:
-        return "Callback"
-    if start_type == ChatSessionStartType.AUTOPILOT_INVITE_CTA:
-        return "Beta Invite CTA"
-    return start_type.value
-
-
-def _get_invited_user_tally_understanding(
-    invited_user: InvitedUserRecord | None,
-) -> dict[str, Any] | None:
-    return invited_user.tally_understanding if invited_user is not None else None
-
-
-def _render_initial_message(
-    start_type: ChatSessionStartType,
-    *,
-    user_name: str | None,
-    invited_user: InvitedUserRecord | None = None,
-) -> str:
-    display_name = user_name or "the user"
-    if start_type == ChatSessionStartType.AUTOPILOT_NIGHTLY:
-        return wrap_internal_message(
-            "This is a nightly proactive Copilot session. Review recent manual activity, "
-            f"do one useful piece of work for {display_name}, and finish with completion_report."
-        )
-    if start_type == ChatSessionStartType.AUTOPILOT_CALLBACK:
-        return wrap_internal_message(
-            "This is a one-off callback session for a previously active user. "
-            f"Reintroduce Copilot with something concrete and useful for {display_name}, "
-            "then finish with completion_report."
-        )
-
-    invite_summary = ""
-    tally_understanding = _get_invited_user_tally_understanding(invited_user)
-    if tally_understanding is not None:
-        invite_summary = "\nKnown context from the beta application:\n" + json.dumps(
-            tally_understanding, ensure_ascii=False
-        )
-    return wrap_internal_message(
-        "This is a one-off invite CTA session for an invited beta user who has not yet activated. "
-        f"Create a tailored introduction for {display_name}, explain how Autopilot can help, "
-        f"and finish with completion_report.{invite_summary}"
-    )
-
-
-def _get_previous_local_midnight_utc(
-    target_local_date: date,
-    timezone_name: str,
-) -> datetime:
-    from datetime import UTC
-    from zoneinfo import ZoneInfo
-
-    tz = ZoneInfo(timezone_name)
-    previous_midnight_local = datetime.combine(
-        target_local_date - timedelta(days=1),
-        time.min,
-        tzinfo=tz,
-    )
-    return previous_midnight_local.astimezone(UTC)
-
-
-async def _get_recent_manual_session_context(
-    user_id: str,
-    *,
-    since_utc: datetime,
-) -> str:
-    sessions = await chat_db().get_manual_chat_sessions_since(
-        user_id,
-        since_utc,
-        AUTOPILOT_RECENT_SESSION_LIMIT,
-    )
-
-    if not sessions:
-        return "No recent manual sessions since the previous nightly run."
-
-    blocks: list[str] = []
-    used_chars = 0
-
-    for session in sessions:
-        messages = await chat_db().get_chat_messages_since(
-            session.session_id, since_utc
-        )
-
-        visible_messages: list[str] = []
-        for message in messages[-AUTOPILOT_RECENT_MESSAGE_LIMIT:]:
-            content = message.content or ""
-            if message.role == "user":
-                visible = strip_internal_content(content)
-            else:
-                visible = content.strip() or None
-            if not visible:
-                continue
-
-            role_label = {
-                "user": "User",
-                "assistant": "Assistant",
-                "tool": "Tool",
-            }.get(message.role, message.role.title())
-            visible_messages.append(
-                f"{role_label}: {_truncate_prompt_text(visible, AUTOPILOT_MESSAGE_CHAR_LIMIT)}"
-            )
-
-        if not visible_messages:
-            continue
-
-        title_suffix = f" ({session.title})" if session.title else ""
-        block = (
-            f"### Session updated {session.updated_at.isoformat()}{title_suffix}\n"
-            + "\n".join(visible_messages)
-        )
-        if used_chars + len(block) > AUTOPILOT_RECENT_CONTEXT_CHAR_LIMIT:
-            break
-
-        blocks.append(block)
-        used_chars += len(block)
-
-    return (
-        "\n\n".join(blocks)
-        if blocks
-        else "No recent manual sessions since the previous nightly run."
-    )
-
-
-async def _get_recent_sent_email_context(user_id: str) -> str:
-    sessions = await chat_db().get_recent_sent_email_chat_sessions(
-        user_id,
-        AUTOPILOT_EMAIL_HISTORY_LIMIT,
-    )
-    if not sessions:
-        return "No recent Copilot or Autopilot emails have been sent to this user."
-
-    blocks: list[str] = []
-    for session in sessions:
-        report = session.completion_report
-        sent_at = session.notification_email_sent_at
-        if report is None or sent_at is None:
-            continue
-
-        lines = [
-            f"### Sent {sent_at.isoformat()} ({_format_start_type_label(session.start_type)})",
-        ]
-        if report.email_title:
-            lines.append(
-                f"Subject: {_truncate_prompt_text(report.email_title, AUTOPILOT_MESSAGE_CHAR_LIMIT)}"
-            )
-        if report.email_body:
-            lines.append(
-                f"Body: {_truncate_prompt_text(report.email_body, AUTOPILOT_MESSAGE_CHAR_LIMIT)}"
-            )
-        if report.callback_session_message:
-            lines.append(
-                "CTA Message: "
-                + _truncate_prompt_text(
-                    report.callback_session_message,
-                    AUTOPILOT_MESSAGE_CHAR_LIMIT,
-                )
-            )
-        blocks.append("\n".join(lines))
-
-    return (
-        "\n\n".join(blocks)
-        if blocks
-        else "No recent Copilot or Autopilot emails have been sent to this user."
-    )
-
-
-async def _get_recent_session_summary_context(user_id: str) -> str:
-    sessions = await chat_db().get_recent_completion_report_chat_sessions(
-        user_id,
-        AUTOPILOT_SESSION_SUMMARY_LIMIT,
-    )
-    if not sessions:
-        return "No recent Copilot session summaries are available."
-
-    blocks: list[str] = []
-    for session in sessions:
-        report = session.completion_report
-        if report is None:
-            continue
-
-        title_suffix = f" ({session.title})" if session.title else ""
-        lines = [
-            f"### {_format_start_type_label(session.start_type)} session updated {session.updated_at.isoformat()}{title_suffix}",
-            f"Summary: {_truncate_prompt_text(report.thoughts, AUTOPILOT_MESSAGE_CHAR_LIMIT)}",
-        ]
-        if report.email_title:
-            lines.append(
-                "Email Title: "
-                + _truncate_prompt_text(
-                    report.email_title, AUTOPILOT_MESSAGE_CHAR_LIMIT
-                )
-            )
-        blocks.append("\n".join(lines))
-
-    return (
-        "\n\n".join(blocks)
-        if blocks
-        else "No recent Copilot session summaries are available."
-    )
-
-
-async def _build_autopilot_system_prompt(
-    user: Any,
-    *,
-    start_type: ChatSessionStartType,
-    timezone_name: str,
-    target_local_date: date | None = None,
-    invited_user: InvitedUserRecord | None = None,
-) -> str:
-    understanding = await understanding_db().get_business_understanding(user.id)
-    business_understanding = (
-        format_understanding_for_prompt(understanding)
-        if understanding
-        else "No saved business understanding yet."
-    )
-    recent_copilot_emails = await _get_recent_sent_email_context(user.id)
-    recent_session_summaries = await _get_recent_session_summary_context(user.id)
-    recent_manual_sessions = "Not applicable for this prompt type."
-    beta_application_context = "No beta application context available."
-
-    users_information_sections = [
-        "## Business Understanding\n" + business_understanding
-    ]
-    users_information_sections.append(
-        "## Recent Copilot Emails Sent To User\n" + recent_copilot_emails
-    )
-    users_information_sections.append(
-        "## Recent Copilot Session Summaries\n" + recent_session_summaries
-    )
-    users_information = "\n\n".join(users_information_sections)
-
-    if (
-        start_type == ChatSessionStartType.AUTOPILOT_NIGHTLY
-        and target_local_date is not None
-    ):
-        recent_manual_sessions = await _get_recent_manual_session_context(
-            user.id,
-            since_utc=_get_previous_local_midnight_utc(
-                target_local_date,
-                timezone_name,
-            ),
-        )
-
-    tally_understanding = _get_invited_user_tally_understanding(invited_user)
-    if tally_understanding is not None:
-        beta_application_context = json.dumps(tally_understanding, ensure_ascii=False)
-
-    return await _get_system_prompt_template(
-        users_information,
-        prompt_name=_get_autopilot_prompt_name(start_type),
-        fallback_prompt=_get_autopilot_fallback_prompt(start_type),
-        template_vars={
-            "users_information": users_information,
-            "business_understanding": business_understanding,
-            "recent_copilot_emails": recent_copilot_emails,
-            "recent_session_summaries": recent_session_summaries,
-            "recent_manual_sessions": recent_manual_sessions,
-            "beta_application_context": beta_application_context,
-        },
-    )

autogpt_platform/backend/backend/copilot/baseline/service.py

@@ -38,8 +38,8 @@ from backend.copilot.response_model import (
     StreamToolOutputAvailable,
 )
 from backend.copilot.service import (
+    _build_system_prompt,
     _generate_session_title,
-    _resolve_system_prompt,
     client,
     config,
 )
@@ -160,7 +160,7 @@ async def stream_chat_completion_baseline(
     session = await upsert_chat_session(session)
 
     # Generate title for new sessions
-    if is_user_message and session.is_manual and not session.title:
+    if is_user_message and not session.title:
         user_messages = [m for m in session.messages if m.role == "user"]
         if len(user_messages) == 1:
             first_message = user_messages[0].content or message or ""
@@ -177,20 +177,16 @@ async def stream_chat_completion_baseline(
     # changes from concurrent chats updating business understanding.
     is_first_turn = len(session.messages) <= 1
     if is_first_turn:
-        base_system_prompt, _ = await _resolve_system_prompt(
-            session,
-            user_id,
-            has_conversation_history=False,
+        base_system_prompt, _ = await _build_system_prompt(
+            user_id, has_conversation_history=False
         )
     else:
-        base_system_prompt, _ = await _resolve_system_prompt(
-            session,
-            user_id=None,
-            has_conversation_history=True,
+        base_system_prompt, _ = await _build_system_prompt(
+            user_id=None, has_conversation_history=True
         )
 
     # Append tool documentation and technical notes
-    system_prompt = base_system_prompt + get_baseline_supplement(session)
+    system_prompt = base_system_prompt + get_baseline_supplement()
 
     # Compress context if approaching the model's token limit
     messages_for_context = await _compress_session_messages(session.messages)
@@ -203,7 +199,7 @@ async def stream_chat_completion_baseline(
         if msg.role in ("user", "assistant") and msg.content:
             openai_messages.append({"role": msg.role, "content": msg.content})
 
-    tools = get_available_tools(session)
+    tools = get_available_tools()
 
     yield StreamStart(messageId=message_id, sessionId=session_id)
 

autogpt_platform/backend/backend/copilot/config.py

@@ -65,18 +65,6 @@ class ChatConfig(BaseSettings):
         default="CoPilot Prompt",
         description="Name of the prompt in Langfuse to fetch",
     )
-    langfuse_autopilot_nightly_prompt_name: str = Field(
-        default="CoPilot Nightly",
-        description="Langfuse prompt name for nightly Autopilot sessions",
-    )
-    langfuse_autopilot_callback_prompt_name: str = Field(
-        default="CoPilot Callback",
-        description="Langfuse prompt name for callback Autopilot sessions",
-    )
-    langfuse_autopilot_invite_cta_prompt_name: str = Field(
-        default="CoPilot Beta Invite CTA",
-        description="Langfuse prompt name for beta invite CTA Autopilot sessions",
-    )
     langfuse_prompt_cache_ttl: int = Field(
         default=300,
         description="Cache TTL in seconds for Langfuse prompt (0 to disable caching)",
@@ -127,7 +115,7 @@ class ChatConfig(BaseSettings):
         description="E2B sandbox template to use for copilot sessions.",
     )
     e2b_sandbox_timeout: int = Field(
-        default=300,  # 5 min safety net — explicit per-turn pause is the primary mechanism
+        default=420,  # 7 min safety net — allows headroom for compaction retries
         description="E2B sandbox running-time timeout (seconds). "
         "E2B timeout is wall-clock (not idle). Explicit per-turn pause is the primary "
         "mechanism; this is the safety net.",

autogpt_platform/backend/backend/copilot/context.py

@@ -11,6 +11,8 @@ from contextvars import ContextVar
 from typing import TYPE_CHECKING
 
 from backend.copilot.model import ChatSession
+from backend.data.db_accessors import workspace_db
+from backend.util.workspace import WorkspaceManager
 
 if TYPE_CHECKING:
     from e2b import AsyncSandbox
@@ -82,6 +84,17 @@ def resolve_sandbox_path(path: str) -> str:
     return normalized
 
 
+async def get_workspace_manager(user_id: str, session_id: str) -> WorkspaceManager:
+    """Create a session-scoped :class:`WorkspaceManager`.
+
+    Placed here (rather than in ``tools/workspace_files``) so that modules
+    like ``sdk/file_ref`` can import it without triggering the heavy
+    ``tools/__init__`` import chain.
+    """
+    workspace = await workspace_db().get_or_create_workspace(user_id)
+    return WorkspaceManager(user_id, workspace.id, session_id)
+
+
 def is_allowed_local_path(path: str, sdk_cwd: str | None = None) -> bool:
     """Return True if *path* is within an allowed host-filesystem location.
 

autogpt_platform/backend/backend/copilot/db.py

@@ -8,48 +8,19 @@ from typing import Any
 from prisma.errors import UniqueViolationError
 from prisma.models import ChatMessage as PrismaChatMessage
 from prisma.models import ChatSession as PrismaChatSession
-from prisma.models import ChatSessionCallbackToken as PrismaChatSessionCallbackToken
 from prisma.types import (
     ChatMessageCreateInput,
     ChatSessionCreateInput,
     ChatSessionUpdateInput,
     ChatSessionWhereInput,
 )
-from pydantic import BaseModel
 
 from backend.data import db
 from backend.util.json import SafeJson, sanitize_string
 
 from .model import ChatMessage, ChatSession, ChatSessionInfo
-from .session_types import ChatSessionStartType
 
 logger = logging.getLogger(__name__)
-_UNSET = object()
-
-
-class ChatSessionCallbackTokenInfo(BaseModel):
-    id: str
-    user_id: str
-    source_session_id: str | None = None
-    callback_session_message: str
-    expires_at: datetime
-    consumed_at: datetime | None = None
-    consumed_session_id: str | None = None
-
-    @classmethod
-    def from_db(
-        cls,
-        token: PrismaChatSessionCallbackToken,
-    ) -> "ChatSessionCallbackTokenInfo":
-        return cls(
-            id=token.id,
-            user_id=token.userId,
-            source_session_id=token.sourceSessionId,
-            callback_session_message=token.callbackSessionMessage,
-            expires_at=token.expiresAt,
-            consumed_at=token.consumedAt,
-            consumed_session_id=token.consumedSessionId,
-        )
 
 
 async def get_chat_session(session_id: str) -> ChatSession | None:
@@ -61,103 +32,9 @@ async def get_chat_session(session_id: str) -> ChatSession | None:
     return ChatSession.from_db(session) if session else None
 
 
-async def has_recent_manual_message(user_id: str, since: datetime) -> bool:
-    message = await PrismaChatMessage.prisma().find_first(
-        where={
-            "role": "user",
-            "createdAt": {"gte": since},
-            "Session": {
-                "is": {
-                    "userId": user_id,
-                    "startType": ChatSessionStartType.MANUAL.value,
-                }
-            },
-        }
-    )
-    return message is not None
-
-
-async def has_session_since(user_id: str, since: datetime) -> bool:
-    session = await PrismaChatSession.prisma().find_first(
-        where={"userId": user_id, "createdAt": {"gte": since}}
-    )
-    return session is not None
-
-
-async def session_exists_for_execution_tag(user_id: str, execution_tag: str) -> bool:
-    session = await PrismaChatSession.prisma().find_first(
-        where={"userId": user_id, "executionTag": execution_tag}
-    )
-    return session is not None
-
-
-async def get_manual_chat_sessions_since(
-    user_id: str,
-    since_utc: datetime,
-    limit: int,
-) -> list[ChatSessionInfo]:
-    sessions = await PrismaChatSession.prisma().find_many(
-        where={
-            "userId": user_id,
-            "startType": ChatSessionStartType.MANUAL.value,
-            "updatedAt": {"gte": since_utc},
-        },
-        order={"updatedAt": "desc"},
-        take=limit,
-    )
-    return [ChatSessionInfo.from_db(session) for session in sessions]
-
-
-async def get_chat_messages_since(
-    session_id: str,
-    since_utc: datetime,
-) -> list[ChatMessage]:
-    messages = await PrismaChatMessage.prisma().find_many(
-        where={
-            "sessionId": session_id,
-            "createdAt": {"gte": since_utc},
-        },
-        order={"sequence": "asc"},
-    )
-    return [ChatMessage.from_db(message) for message in messages]
-
-
-def _build_chat_message_create_input(
-    *,
-    session_id: str,
-    sequence: int,
-    now: datetime,
-    msg: dict[str, Any],
-) -> ChatMessageCreateInput:
-    data: ChatMessageCreateInput = {
-        "sessionId": session_id,
-        "role": msg["role"],
-        "sequence": sequence,
-        "createdAt": now,
-    }
-
-    if msg.get("content") is not None:
-        data["content"] = sanitize_string(msg["content"])
-    if msg.get("name") is not None:
-        data["name"] = msg["name"]
-    if msg.get("tool_call_id") is not None:
-        data["toolCallId"] = msg["tool_call_id"]
-    if msg.get("refusal") is not None:
-        data["refusal"] = sanitize_string(msg["refusal"])
-    if msg.get("tool_calls") is not None:
-        data["toolCalls"] = SafeJson(msg["tool_calls"])
-    if msg.get("function_call") is not None:
-        data["functionCall"] = SafeJson(msg["function_call"])
-
-    return data
-
-
 async def create_chat_session(
     session_id: str,
     user_id: str,
-    start_type: ChatSessionStartType = ChatSessionStartType.MANUAL,
-    execution_tag: str | None = None,
-    session_config: dict[str, Any] | None = None,
 ) -> ChatSessionInfo:
     """Create a new chat session in the database."""
     data = ChatSessionCreateInput(
@@ -166,9 +43,6 @@ async def create_chat_session(
         credentials=SafeJson({}),
         successfulAgentRuns=SafeJson({}),
         successfulAgentSchedules=SafeJson({}),
-        startType=start_type.value,
-        executionTag=execution_tag,
-        sessionConfig=SafeJson(session_config or {}),
     )
     prisma_session = await PrismaChatSession.prisma().create(data=data)
     return ChatSessionInfo.from_db(prisma_session)
@@ -182,19 +56,9 @@ async def update_chat_session(
     total_prompt_tokens: int | None = None,
     total_completion_tokens: int | None = None,
     title: str | None = None,
-    start_type: ChatSessionStartType | None = None,
-    execution_tag: str | None | object = _UNSET,
-    session_config: dict[str, Any] | None = None,
-    completion_report: dict[str, Any] | None | object = _UNSET,
-    completion_report_repair_count: int | None = None,
-    completion_report_repair_queued_at: datetime | None | object = _UNSET,
-    completed_at: datetime | None | object = _UNSET,
-    notification_email_sent_at: datetime | None | object = _UNSET,
-    notification_email_skipped_at: datetime | None | object = _UNSET,
 ) -> ChatSession | None:
     """Update a chat session's metadata."""
     data: ChatSessionUpdateInput = {"updatedAt": datetime.now(UTC)}
-    should_clear_completion_report = completion_report is None
 
     if credentials is not None:
         data["credentials"] = SafeJson(credentials)
@@ -208,41 +72,12 @@ async def update_chat_session(
         data["totalCompletionTokens"] = total_completion_tokens
     if title is not None:
         data["title"] = title
-    if start_type is not None:
-        data["startType"] = start_type.value
-    if execution_tag is not _UNSET:
-        data["executionTag"] = execution_tag
-    if session_config is not None:
-        data["sessionConfig"] = SafeJson(session_config)
-    if completion_report is not _UNSET and completion_report is not None:
-        data["completionReport"] = SafeJson(completion_report)
-    if completion_report_repair_count is not None:
-        data["completionReportRepairCount"] = completion_report_repair_count
-    if completion_report_repair_queued_at is not _UNSET:
-        data["completionReportRepairQueuedAt"] = completion_report_repair_queued_at
-    if completed_at is not _UNSET:
-        data["completedAt"] = completed_at
-    if notification_email_sent_at is not _UNSET:
-        data["notificationEmailSentAt"] = notification_email_sent_at
-    if notification_email_skipped_at is not _UNSET:
-        data["notificationEmailSkippedAt"] = notification_email_skipped_at
 
     session = await PrismaChatSession.prisma().update(
         where={"id": session_id},
         data=data,
         include={"Messages": {"order_by": {"sequence": "asc"}}},
     )
-
-    if should_clear_completion_report:
-        await db.execute_raw_with_schema(
-            'UPDATE {schema_prefix}"ChatSession" SET "completionReport" = NULL WHERE "id" = $1',
-            session_id,
-        )
-        session = await PrismaChatSession.prisma().find_unique(
-            where={"id": session_id},
-            include={"Messages": {"order_by": {"sequence": "asc"}}},
-        )
-
     return ChatSession.from_db(session) if session else None
 
 
@@ -352,15 +187,37 @@ async def add_chat_messages_batch(
             now = datetime.now(UTC)
 
             async with db.transaction() as tx:
-                messages_data = [
-                    _build_chat_message_create_input(
-                        session_id=session_id,
-                        sequence=start_sequence + i,
-                        now=now,
-                        msg=msg,
-                    )
-                    for i, msg in enumerate(messages)
-                ]
+                # Build all message data
+                messages_data = []
+                for i, msg in enumerate(messages):
+                    # Build ChatMessageCreateInput with only non-None values
+                    # (Prisma TypedDict rejects optional fields set to None)
+                    # Note: create_many doesn't support nested creates, use sessionId directly
+                    data: ChatMessageCreateInput = {
+                        "sessionId": session_id,
+                        "role": msg["role"],
+                        "sequence": start_sequence + i,
+                        "createdAt": now,
+                    }
+
+                    # Add optional string fields — sanitize to strip
+                    # PostgreSQL-incompatible control characters.
+                    if msg.get("content") is not None:
+                        data["content"] = sanitize_string(msg["content"])
+                    if msg.get("name") is not None:
+                        data["name"] = msg["name"]
+                    if msg.get("tool_call_id") is not None:
+                        data["toolCallId"] = msg["tool_call_id"]
+                    if msg.get("refusal") is not None:
+                        data["refusal"] = sanitize_string(msg["refusal"])
+
+                    # Add optional JSON fields only when they have values
+                    if msg.get("tool_calls") is not None:
+                        data["toolCalls"] = SafeJson(msg["tool_calls"])
+                    if msg.get("function_call") is not None:
+                        data["functionCall"] = SafeJson(msg["function_call"])
+
+                    messages_data.append(data)
 
                 # Run create_many and session update in parallel within transaction
                 # Both use the same timestamp for consistency
@@ -399,14 +256,10 @@ async def get_user_chat_sessions(
     user_id: str,
     limit: int = 50,
     offset: int = 0,
-    with_auto: bool = False,
 ) -> list[ChatSessionInfo]:
     """Get chat sessions for a user, ordered by most recent."""
     prisma_sessions = await PrismaChatSession.prisma().find_many(
-        where={
-            "userId": user_id,
-            **({} if with_auto else {"startType": ChatSessionStartType.MANUAL.value}),
-        },
+        where={"userId": user_id},
         order={"updatedAt": "desc"},
         take=limit,
         skip=offset,
@@ -414,88 +267,9 @@ async def get_user_chat_sessions(
     return [ChatSessionInfo.from_db(s) for s in prisma_sessions]
 
 
-async def get_pending_notification_chat_sessions(
-    limit: int = 200,
-) -> list[ChatSessionInfo]:
-    sessions = await PrismaChatSession.prisma().find_many(
-        where={
-            "startType": {"not": ChatSessionStartType.MANUAL.value},
-            "notificationEmailSentAt": None,
-            "notificationEmailSkippedAt": None,
-        },
-        order={"updatedAt": "asc"},
-        take=limit,
-    )
-    return [ChatSessionInfo.from_db(session) for session in sessions]
-
-
-async def get_pending_notification_chat_sessions_for_user(
-    user_id: str,
-    limit: int = 200,
-) -> list[ChatSessionInfo]:
-    sessions = await PrismaChatSession.prisma().find_many(
-        where={
-            "userId": user_id,
-            "startType": {"not": ChatSessionStartType.MANUAL.value},
-            "notificationEmailSentAt": None,
-            "notificationEmailSkippedAt": None,
-        },
-        order={"updatedAt": "asc"},
-        take=limit,
-    )
-    return [ChatSessionInfo.from_db(session) for session in sessions]
-
-
-async def get_recent_sent_email_chat_sessions(
-    user_id: str,
-    limit: int,
-) -> list[ChatSessionInfo]:
-    sessions = await PrismaChatSession.prisma().find_many(
-        where={
-            "userId": user_id,
-            "startType": {"not": ChatSessionStartType.MANUAL.value},
-            "notificationEmailSentAt": {"not": None},
-        },
-        order={"notificationEmailSentAt": "desc"},
-        take=max(limit * 3, limit),
-    )
-    return [
-        session_info
-        for session_info in (ChatSessionInfo.from_db(session) for session in sessions)
-        if session_info.notification_email_sent_at and session_info.completion_report
-    ][:limit]
-
-
-async def get_recent_completion_report_chat_sessions(
-    user_id: str,
-    limit: int,
-) -> list[ChatSessionInfo]:
-    sessions = await PrismaChatSession.prisma().find_many(
-        where={
-            "userId": user_id,
-            "startType": {"not": ChatSessionStartType.MANUAL.value},
-        },
-        order={"updatedAt": "desc"},
-        take=max(limit * 5, 10),
-    )
-    return [
-        session_info
-        for session_info in (ChatSessionInfo.from_db(session) for session in sessions)
-        if session_info.completion_report is not None
-    ][:limit]
-
-
-async def get_user_session_count(
-    user_id: str,
-    with_auto: bool = False,
-) -> int:
+async def get_user_session_count(user_id: str) -> int:
     """Get the total number of chat sessions for a user."""
-    return await PrismaChatSession.prisma().count(
-        where={
-            "userId": user_id,
-            **({} if with_auto else {"startType": ChatSessionStartType.MANUAL.value}),
-        }
-    )
+    return await PrismaChatSession.prisma().count(where={"userId": user_id})
 
 
 async def delete_chat_session(session_id: str, user_id: str | None = None) -> bool:
@@ -585,42 +359,3 @@ async def update_tool_message_content(
             f"tool_call_id {tool_call_id}: {e}"
         )
         return False
-
-
-async def create_chat_session_callback_token(
-    user_id: str,
-    source_session_id: str,
-    callback_session_message: str,
-    expires_at: datetime,
-) -> ChatSessionCallbackTokenInfo:
-    token = await PrismaChatSessionCallbackToken.prisma().create(
-        data={
-            "userId": user_id,
-            "sourceSessionId": source_session_id,
-            "callbackSessionMessage": callback_session_message,
-            "expiresAt": expires_at,
-        }
-    )
-    return ChatSessionCallbackTokenInfo.from_db(token)
-
-
-async def get_chat_session_callback_token(
-    token_id: str,
-) -> ChatSessionCallbackTokenInfo | None:
-    token = await PrismaChatSessionCallbackToken.prisma().find_unique(
-        where={"id": token_id}
-    )
-    return ChatSessionCallbackTokenInfo.from_db(token) if token else None
-
-
-async def mark_chat_session_callback_token_consumed(
-    token_id: str,
-    consumed_session_id: str,
-) -> None:
-    await PrismaChatSessionCallbackToken.prisma().update(
-        where={"id": token_id},
-        data={
-            "consumedAt": datetime.now(UTC),
-            "consumedSessionId": consumed_session_id,
-        },
-    )

autogpt_platform/backend/backend/copilot/model.py

@@ -21,7 +21,7 @@ from openai.types.chat.chat_completion_message_tool_call_param import (
 )
 from prisma.models import ChatMessage as PrismaChatMessage
 from prisma.models import ChatSession as PrismaChatSession
-from pydantic import BaseModel, Field
+from pydantic import BaseModel
 
 from backend.data.db_accessors import chat_db
 from backend.data.redis_client import get_redis_async
@@ -29,11 +29,6 @@ from backend.util import json
 from backend.util.exceptions import DatabaseError, RedisError
 
 from .config import ChatConfig
-from .session_types import (
-    ChatSessionConfig,
-    ChatSessionStartType,
-    StoredCompletionReport,
-)
 
 logger = logging.getLogger(__name__)
 config = ChatConfig()
@@ -85,20 +80,11 @@ class ChatSessionInfo(BaseModel):
     user_id: str
     title: str | None = None
     usage: list[Usage]
-    credentials: dict[str, dict] = Field(default_factory=dict)
+    credentials: dict[str, dict] = {}  # Map of provider -> credential metadata
     started_at: datetime
     updated_at: datetime
-    successful_agent_runs: dict[str, int] = Field(default_factory=dict)
-    successful_agent_schedules: dict[str, int] = Field(default_factory=dict)
-    start_type: ChatSessionStartType = ChatSessionStartType.MANUAL
-    execution_tag: str | None = None
-    session_config: ChatSessionConfig = Field(default_factory=ChatSessionConfig)
-    completion_report: StoredCompletionReport | None = None
-    completion_report_repair_count: int = 0
-    completion_report_repair_queued_at: datetime | None = None
-    completed_at: datetime | None = None
-    notification_email_sent_at: datetime | None = None
-    notification_email_skipped_at: datetime | None = None
+    successful_agent_runs: dict[str, int] = {}
+    successful_agent_schedules: dict[str, int] = {}
 
     @classmethod
     def from_db(cls, prisma_session: PrismaChatSession) -> Self:
@@ -111,8 +97,6 @@ class ChatSessionInfo(BaseModel):
         successful_agent_schedules = _parse_json_field(
             prisma_session.successfulAgentSchedules, default={}
         )
-        session_config = _parse_json_field(prisma_session.sessionConfig, default={})
-        completion_report = _parse_json_field(prisma_session.completionReport)
 
         # Calculate usage from token counts
         usage = []
@@ -126,20 +110,6 @@ class ChatSessionInfo(BaseModel):
                 )
             )
 
-        parsed_session_config = ChatSessionConfig.model_validate(session_config or {})
-        parsed_completion_report = None
-        if isinstance(completion_report, dict):
-            try:
-                parsed_completion_report = StoredCompletionReport.model_validate(
-                    completion_report
-                )
-            except Exception:
-                logger.warning(
-                    "Invalid completionReport payload on session %s",
-                    prisma_session.id,
-                    exc_info=True,
-                )
-
         return cls(
             session_id=prisma_session.id,
             user_id=prisma_session.userId,
@@ -150,15 +120,6 @@ class ChatSessionInfo(BaseModel):
             updated_at=prisma_session.updatedAt,
             successful_agent_runs=successful_agent_runs,
             successful_agent_schedules=successful_agent_schedules,
-            start_type=ChatSessionStartType(str(prisma_session.startType)),
-            execution_tag=prisma_session.executionTag,
-            session_config=parsed_session_config,
-            completion_report=parsed_completion_report,
-            completion_report_repair_count=prisma_session.completionReportRepairCount,
-            completion_report_repair_queued_at=prisma_session.completionReportRepairQueuedAt,
-            completed_at=prisma_session.completedAt,
-            notification_email_sent_at=prisma_session.notificationEmailSentAt,
-            notification_email_skipped_at=prisma_session.notificationEmailSkippedAt,
         )
 
 
@@ -166,13 +127,7 @@ class ChatSession(ChatSessionInfo):
     messages: list[ChatMessage]
 
     @classmethod
-    def new(
-        cls,
-        user_id: str,
-        start_type: ChatSessionStartType = ChatSessionStartType.MANUAL,
-        execution_tag: str | None = None,
-        session_config: ChatSessionConfig | None = None,
-    ) -> Self:
+    def new(cls, user_id: str) -> Self:
         return cls(
             session_id=str(uuid.uuid4()),
             user_id=user_id,
@@ -182,9 +137,6 @@ class ChatSession(ChatSessionInfo):
             credentials={},
             started_at=datetime.now(UTC),
             updated_at=datetime.now(UTC),
-            start_type=start_type,
-            execution_tag=execution_tag,
-            session_config=session_config or ChatSessionConfig(),
         )
 
     @classmethod
@@ -200,16 +152,6 @@ class ChatSession(ChatSessionInfo):
             messages=[ChatMessage.from_db(m) for m in prisma_session.Messages],
         )
 
-    @property
-    def is_manual(self) -> bool:
-        return self.start_type == ChatSessionStartType.MANUAL
-
-    def allows_tool(self, tool_name: str) -> bool:
-        return self.session_config.allows_tool(tool_name)
-
-    def disables_tool(self, tool_name: str) -> bool:
-        return self.session_config.disables_tool(tool_name)
-
     def add_tool_call_to_current_turn(self, tool_call: dict) -> None:
         """Attach a tool_call to the current turn's assistant message.
 
@@ -582,9 +524,6 @@ async def _save_session_to_db(
             await db.create_chat_session(
                 session_id=session.session_id,
                 user_id=session.user_id,
-                start_type=session.start_type,
-                execution_tag=session.execution_tag,
-                session_config=session.session_config.model_dump(mode="json"),
             )
             existing_message_count = 0
 
@@ -600,19 +539,6 @@ async def _save_session_to_db(
         successful_agent_schedules=session.successful_agent_schedules,
         total_prompt_tokens=total_prompt,
         total_completion_tokens=total_completion,
-        start_type=session.start_type,
-        execution_tag=session.execution_tag,
-        session_config=session.session_config.model_dump(mode="json"),
-        completion_report=(
-            session.completion_report.model_dump(mode="json")
-            if session.completion_report
-            else None
-        ),
-        completion_report_repair_count=session.completion_report_repair_count,
-        completion_report_repair_queued_at=session.completion_report_repair_queued_at,
-        completed_at=session.completed_at,
-        notification_email_sent_at=session.notification_email_sent_at,
-        notification_email_skipped_at=session.notification_email_skipped_at,
     )
 
     # Add new messages (only those after existing count)
@@ -675,13 +601,7 @@ async def append_and_save_message(session_id: str, message: ChatMessage) -> Chat
         return session
 
 
-async def create_chat_session(
-    user_id: str,
-    start_type: ChatSessionStartType = ChatSessionStartType.MANUAL,
-    execution_tag: str | None = None,
-    session_config: ChatSessionConfig | None = None,
-    initial_messages: list[ChatMessage] | None = None,
-) -> ChatSession:
+async def create_chat_session(user_id: str) -> ChatSession:
     """Create a new chat session and persist it.
 
     Raises:
@@ -689,30 +609,14 @@ async def create_chat_session(
             callers never receive a non-persisted session that only exists
             in cache (which would be lost when the cache expires).
     """
-    session = ChatSession.new(
-        user_id,
-        start_type=start_type,
-        execution_tag=execution_tag,
-        session_config=session_config,
-    )
-    if initial_messages:
-        session.messages.extend(initial_messages)
+    session = ChatSession.new(user_id)
 
     # Create in database first - fail fast if this fails
     try:
         await chat_db().create_chat_session(
             session_id=session.session_id,
             user_id=user_id,
-            start_type=session.start_type,
-            execution_tag=session.execution_tag,
-            session_config=session.session_config.model_dump(mode="json"),
         )
-        if session.messages:
-            await _save_session_to_db(
-                session,
-                0,
-                skip_existence_check=True,
-            )
     except Exception as e:
         logger.error(f"Failed to create session {session.session_id} in database: {e}")
         raise DatabaseError(
@@ -732,7 +636,6 @@ async def get_user_sessions(
     user_id: str,
     limit: int = 50,
     offset: int = 0,
-    with_auto: bool = False,
 ) -> tuple[list[ChatSessionInfo], int]:
     """Get chat sessions for a user from the database with total count.
 
@@ -741,16 +644,8 @@ async def get_user_sessions(
         number of sessions for the user (not just the current page).
     """
     db = chat_db()
-    sessions = await db.get_user_chat_sessions(
-        user_id,
-        limit,
-        offset,
-        with_auto=with_auto,
-    )
-    total_count = await db.get_user_session_count(
-        user_id,
-        with_auto=with_auto,
-    )
+    sessions = await db.get_user_chat_sessions(user_id, limit, offset)
+    total_count = await db.get_user_session_count(user_id)
 
     return sessions, total_count
 

autogpt_platform/backend/backend/copilot/model_test.py

@@ -19,7 +19,6 @@ from .model import (
     get_chat_session,
     upsert_chat_session,
 )
-from .session_types import ChatSessionConfig, ChatSessionStartType
 
 messages = [
     ChatMessage(content="Hello, how are you?", role="user"),
@@ -47,15 +46,7 @@ messages = [
 
 @pytest.mark.asyncio(loop_scope="session")
 async def test_chatsession_serialization_deserialization():
-    s = ChatSession.new(
-        user_id="abc123",
-        start_type=ChatSessionStartType.AUTOPILOT_NIGHTLY,
-        execution_tag="autopilot-nightly:2026-03-13",
-        session_config=ChatSessionConfig(
-            extra_tools=["completion_report"],
-            disabled_tools=["edit_agent"],
-        ),
-    )
+    s = ChatSession.new(user_id="abc123")
     s.messages = messages
     s.usage = [Usage(prompt_tokens=100, completion_tokens=200, total_tokens=300)]
     serialized = s.model_dump_json()

autogpt_platform/backend/backend/copilot/prompting.py

@@ -6,7 +6,7 @@ handling the distinction between:
 - Local mode vs E2B mode (storage/filesystem differences)
 """
 
-from backend.copilot.tools import iter_available_tools
+from backend.copilot.tools import TOOL_REGISTRY
 
 # Shared technical notes that apply to both SDK and baseline modes
 _SHARED_TOOL_NOTES = """\
@@ -52,11 +52,43 @@ Examples:
 You can embed a reference inside any string argument, or use it as the entire
 value.  Multiple references in one argument are all expanded.
 
-**Type coercion**: The platform automatically coerces expanded string values
-to match the block's expected input types.  For example, if a block expects
-`list[list[str]]` and you pass a string containing a JSON array (e.g. from
-an @@agptfile: expansion), the string will be parsed into the correct type.
+**Structured data**: When the **entire** argument value is a single file
+reference (no surrounding text), the platform automatically parses the file
+content based on its extension or MIME type.  Supported formats: JSON, JSONL,
+CSV, TSV, YAML, TOML, Parquet, and Excel (.xlsx — first sheet only).
+For example, pass `@@agptfile:workspace://<id>` where the file is a `.csv` and
+the rows will be parsed into `list[list[str]]` automatically.  If the format is
+unrecognised or parsing fails, the content is returned as a plain string.
+Legacy `.xls` files are **not** supported — only the modern `.xlsx` format.
 
+**Type coercion**: The platform also coerces expanded values to match the
+block's expected input types.  For example, if a block expects `list[list[str]]`
+and the expanded value is a JSON string, it will be parsed into the correct type.
+
+### Media file inputs (format: "file")
+Some block inputs accept media files — their schema shows `"format": "file"`.
+These fields accept:
+- **`workspace://<file_id>`** or **`workspace://<file_id>#<mime>`** — preferred
+  for large files (images, videos, PDFs). The platform passes the reference
+  directly to the block without reading the content into memory.
+- **`data:<mime>;base64,<payload>`** — inline base64 data URI, suitable for
+  small files only.
+
+When a block input has `format: "file"`, **pass the `workspace://` URI
+directly as the value** (do NOT wrap it in `@@agptfile:`). This avoids large
+payloads in tool arguments and preserves binary content (images, videos)
+that would be corrupted by text encoding.
+
+Example — committing an image file to GitHub:
+```json
+{
+  "files": [{
+    "path": "docs/hero.png",
+    "content": "workspace://abc123#image/png",
+    "operation": "upsert"
+  }]
+}
+```
 
 ### Sub-agent tasks
 - When using the Task tool, NEVER set `run_in_background` to true.
@@ -161,7 +193,7 @@ def _get_cloud_sandbox_supplement() -> str:
     )
 
 
-def _generate_tool_documentation(session=None) -> str:
+def _generate_tool_documentation() -> str:
     """Auto-generate tool documentation from TOOL_REGISTRY.
 
     NOTE: This is ONLY used in baseline mode (direct OpenAI API).
@@ -177,7 +209,11 @@ def _generate_tool_documentation(session=None) -> str:
     docs = "\n## AVAILABLE TOOLS\n\n"
 
     # Sort tools alphabetically for consistent output
-    for name, tool in sorted(iter_available_tools(session), key=lambda item: item[0]):
+    # Filter by is_available to match get_available_tools() behavior
+    for name in sorted(TOOL_REGISTRY.keys()):
+        tool = TOOL_REGISTRY[name]
+        if not tool.is_available:
+            continue
         schema = tool.as_openai_tool()
         desc = schema["function"].get("description", "No description available")
         # Format as bullet list with tool name in code style
@@ -205,7 +241,7 @@ def get_sdk_supplement(use_e2b: bool, cwd: str = "") -> str:
     return _get_local_storage_supplement(cwd)
 
 
-def get_baseline_supplement(session=None) -> str:
+def get_baseline_supplement() -> str:
     """Get the supplement for baseline mode (direct OpenAI API).
 
     Baseline mode INCLUDES auto-generated tool documentation because the
@@ -215,5 +251,5 @@ def get_baseline_supplement(session=None) -> str:
     Returns:
         The supplement string to append to the system prompt
     """
-    tool_docs = _generate_tool_documentation(session)
+    tool_docs = _generate_tool_documentation()
     return tool_docs + _SHARED_TOOL_NOTES

autogpt_platform/backend/backend/copilot/response_model.py

@@ -43,6 +43,7 @@ class ResponseType(str, Enum):
     ERROR = "error"
     USAGE = "usage"
     HEARTBEAT = "heartbeat"
+    STATUS = "status"
 
 
 class StreamBaseResponse(BaseModel):
@@ -232,3 +233,26 @@ class StreamHeartbeat(StreamBaseResponse):
     def to_sse(self) -> str:
         """Convert to SSE comment format to keep connection alive."""
         return ": heartbeat\n\n"
+
+
+class StreamStatus(StreamBaseResponse):
+    """Transient status notification shown to the user during long operations.
+
+    Used to provide feedback when the backend performs behind-the-scenes work
+    (e.g., compacting conversation context on a retry) that would otherwise
+    leave the user staring at an unexplained pause.
+    """
+
+    type: ResponseType = ResponseType.STATUS
+    message: str = Field(..., description="Human-readable status message")
+
+    def to_sse(self) -> str:
+        """Encode as an SSE comment so the AI SDK stream parser ignores it.
+
+        The frontend AI SDK validates every ``data:`` line against a strict
+        Zod union of known chunk types.  ``"status"`` is not in that union,
+        so sending it as ``data:`` would cause a schema-validation error that
+        breaks the entire stream.  Using an SSE comment (``:``) keeps the
+        connection alive and is silently discarded by ``EventSource`` parsers.
+        """
+        return f": status {self.message}\n\n"

autogpt_platform/backend/backend/copilot/sdk/__init__.py

@@ -3,12 +3,45 @@
 This module provides the integration layer between the Claude Agent SDK
 and the existing CoPilot tool system, enabling drop-in replacement of
 the current LLM orchestration with the battle-tested Claude Agent SDK.
+
+Submodule imports are deferred via PEP 562 ``__getattr__`` to break a
+circular import cycle::
+
+    sdk/__init__ → tool_adapter → copilot.tools (TOOL_REGISTRY)
+    copilot.tools → run_block → sdk.file_ref  (no cycle here, but…)
+    sdk/__init__ → service → copilot.prompting → copilot.tools  (cycle!)
+
+``tool_adapter`` uses ``TOOL_REGISTRY`` at **module level** to build the
+static ``COPILOT_TOOL_NAMES`` list, so the import cannot be deferred to
+function scope without a larger refactor (moving tool-name registration
+to a separate lightweight module).  The lazy-import pattern here is the
+least invasive way to break the cycle while keeping module-level constants
+intact.
 """
 
-from .service import stream_chat_completion_sdk
-from .tool_adapter import create_copilot_mcp_server
+from typing import Any
 
 __all__ = [
     "stream_chat_completion_sdk",
     "create_copilot_mcp_server",
 ]
+
+# Dispatch table for PEP 562 lazy imports.  Each entry is a (module, attr)
+# pair so new exports can be added without touching __getattr__ itself.
+_LAZY_IMPORTS: dict[str, tuple[str, str]] = {
+    "stream_chat_completion_sdk": (".service", "stream_chat_completion_sdk"),
+    "create_copilot_mcp_server": (".tool_adapter", "create_copilot_mcp_server"),
+}
+
+
+def __getattr__(name: str) -> Any:
+    entry = _LAZY_IMPORTS.get(name)
+    if entry is not None:
+        module_path, attr = entry
+        import importlib
+
+        module = importlib.import_module(module_path, package=__name__)
+        value = getattr(module, attr)
+        globals()[name] = value
+        return value
+    raise AttributeError(f"module {__name__!r} has no attribute {name!r}")

autogpt_platform/backend/backend/copilot/sdk/compaction.py

@@ -12,6 +12,7 @@ import asyncio
 import logging
 import uuid
 from dataclasses import dataclass, field
+from typing import Any
 
 from ..constants import COMPACTION_DONE_MSG, COMPACTION_TOOL_NAME
 from ..model import ChatMessage, ChatSession
@@ -119,14 +120,12 @@ def filter_compaction_messages(
     filtered: list[ChatMessage] = []
     for msg in messages:
         if msg.role == "assistant" and msg.tool_calls:
+            real_calls: list[dict[str, Any]] = []
             for tc in msg.tool_calls:
                 if tc.get("function", {}).get("name") == COMPACTION_TOOL_NAME:
                     compaction_ids.add(tc.get("id", ""))
-            real_calls = [
-                tc
-                for tc in msg.tool_calls
-                if tc.get("function", {}).get("name") != COMPACTION_TOOL_NAME
-            ]
+                else:
+                    real_calls.append(tc)
             if not real_calls and not msg.content:
                 continue
         if msg.role == "tool" and msg.tool_call_id in compaction_ids:
@@ -222,6 +221,7 @@ class CompactionTracker:
 
     def reset_for_query(self) -> None:
         """Reset per-query state before a new SDK query."""
+        self._compact_start.clear()
         self._done = False
         self._start_emitted = False
         self._tool_call_id = ""

autogpt_platform/backend/backend/copilot/sdk/conftest.py

@@ -0,0 +1,41 @@
+"""Shared test fixtures for copilot SDK tests."""
+
+from __future__ import annotations
+
+from uuid import uuid4
+
+from backend.util import json
+
+
+def build_test_transcript(pairs: list[tuple[str, str]]) -> str:
+    """Build a minimal valid JSONL transcript from (role, content) pairs.
+
+    Use this helper in any copilot SDK test that needs a well-formed
+    transcript without hitting the real storage layer.
+    """
+    lines: list[str] = []
+    last_uuid: str | None = None
+    for role, content in pairs:
+        uid = str(uuid4())
+        entry_type = "assistant" if role == "assistant" else "user"
+        msg: dict = {"role": role, "content": content}
+        if role == "assistant":
+            msg.update(
+                {
+                    "model": "",
+                    "id": f"msg_{uid[:8]}",
+                    "type": "message",
+                    "content": [{"type": "text", "text": content}],
+                    "stop_reason": "end_turn",
+                    "stop_sequence": None,
+                }
+            )
+        entry = {
+            "type": entry_type,
+            "uuid": uid,
+            "parentUuid": last_uuid,
+            "message": msg,
+        }
+        lines.append(json.dumps(entry, separators=(",", ":")))
+        last_uuid = uid
+    return "\n".join(lines) + "\n"

autogpt_platform/backend/backend/copilot/sdk/file_ref.py

@@ -41,12 +41,20 @@ from typing import Any
 from backend.copilot.context import (
     get_current_sandbox,
     get_sdk_cwd,
+    get_workspace_manager,
     is_allowed_local_path,
     resolve_sandbox_path,
 )
 from backend.copilot.model import ChatSession
-from backend.copilot.tools.workspace_files import get_manager
 from backend.util.file import parse_workspace_uri
+from backend.util.file_content_parser import (
+    BINARY_FORMATS,
+    MIME_TO_FORMAT,
+    PARSE_EXCEPTIONS,
+    infer_format_from_uri,
+    parse_file_content,
+)
+from backend.util.type import MediaFileType
 
 
 class FileRefExpansionError(Exception):
@@ -74,6 +82,8 @@ _FILE_REF_RE = re.compile(
 _MAX_EXPAND_CHARS = 200_000
 # Maximum total characters across all @@agptfile: expansions in one string.
 _MAX_TOTAL_EXPAND_CHARS = 1_000_000
+# Maximum raw byte size for bare ref structured parsing (10 MB).
+_MAX_BARE_REF_BYTES = 10_000_000
 
 
 @dataclass
@@ -83,6 +93,11 @@ class FileRef:
     end_line: int | None  # 1-indexed, inclusive
 
 
+# ---------------------------------------------------------------------------
+# Public API  (top-down: main functions first, helpers below)
+# ---------------------------------------------------------------------------
+
+
 def parse_file_ref(text: str) -> FileRef | None:
     """Return a :class:`FileRef` if *text* is a bare file reference token.
 
@@ -104,17 +119,6 @@ def parse_file_ref(text: str) -> FileRef | None:
     return FileRef(uri=m.group(1), start_line=start, end_line=end)
 
 
-def _apply_line_range(text: str, start: int | None, end: int | None) -> str:
-    """Slice *text* to the requested 1-indexed line range (inclusive)."""
-    if start is None and end is None:
-        return text
-    lines = text.splitlines(keepends=True)
-    s = (start - 1) if start is not None else 0
-    e = end if end is not None else len(lines)
-    selected = list(itertools.islice(lines, s, e))
-    return "".join(selected)
-
-
 async def read_file_bytes(
     uri: str,
     user_id: str | None,
@@ -130,27 +134,47 @@ async def read_file_bytes(
     if plain.startswith("workspace://"):
         if not user_id:
             raise ValueError("workspace:// file references require authentication")
-        manager = await get_manager(user_id, session.session_id)
+        manager = await get_workspace_manager(user_id, session.session_id)
         ws = parse_workspace_uri(plain)
         try:
-            return await (
+            data = await (
                 manager.read_file(ws.file_ref)
                 if ws.is_path
                 else manager.read_file_by_id(ws.file_ref)
             )
         except FileNotFoundError:
             raise ValueError(f"File not found: {plain}")
-        except Exception as exc:
+        except (PermissionError, OSError) as exc:
             raise ValueError(f"Failed to read {plain}: {exc}") from exc
+        except (AttributeError, TypeError, RuntimeError) as exc:
+            # AttributeError/TypeError: workspace manager returned an
+            # unexpected type or interface; RuntimeError: async runtime issues.
+            logger.warning("Unexpected error reading %s: %s", plain, exc)
+            raise ValueError(f"Failed to read {plain}: {exc}") from exc
+        # NOTE: Workspace API does not support pre-read size checks;
+        # the full file is loaded before the size guard below.
+        if len(data) > _MAX_BARE_REF_BYTES:
+            raise ValueError(
+                f"File too large ({len(data)} bytes, limit {_MAX_BARE_REF_BYTES})"
+            )
+        return data
 
     if is_allowed_local_path(plain, get_sdk_cwd()):
         resolved = os.path.realpath(os.path.expanduser(plain))
         try:
+            # Read with a one-byte overshoot to detect files that exceed the limit
+            # without a separate os.path.getsize call (avoids TOCTOU race).
             with open(resolved, "rb") as fh:
-                return fh.read()
+                data = fh.read(_MAX_BARE_REF_BYTES + 1)
+            if len(data) > _MAX_BARE_REF_BYTES:
+                raise ValueError(
+                    f"File too large (>{_MAX_BARE_REF_BYTES} bytes, "
+                    f"limit {_MAX_BARE_REF_BYTES})"
+                )
+            return data
         except FileNotFoundError:
             raise ValueError(f"File not found: {plain}")
-        except Exception as exc:
+        except OSError as exc:
             raise ValueError(f"Failed to read {plain}: {exc}") from exc
 
     sandbox = get_current_sandbox()
@@ -162,9 +186,33 @@ async def read_file_bytes(
                 f"Path is not allowed (not in workspace, sdk_cwd, or sandbox): {plain}"
             ) from exc
         try:
-            return bytes(await sandbox.files.read(remote, format="bytes"))
-        except Exception as exc:
+            data = bytes(await sandbox.files.read(remote, format="bytes"))
+        except (FileNotFoundError, OSError, UnicodeDecodeError) as exc:
             raise ValueError(f"Failed to read from sandbox: {plain}: {exc}") from exc
+        except Exception as exc:
+            # E2B SDK raises SandboxException subclasses (NotFoundException,
+            # TimeoutException, NotEnoughSpaceException, etc.) which don't
+            # inherit from standard exceptions.  Import lazily to avoid a
+            # hard dependency on e2b at module level.
+            try:
+                from e2b.exceptions import SandboxException  # noqa: PLC0415
+
+                if isinstance(exc, SandboxException):
+                    raise ValueError(
+                        f"Failed to read from sandbox: {plain}: {exc}"
+                    ) from exc
+            except ImportError:
+                pass
+            # Re-raise unexpected exceptions (TypeError, AttributeError, etc.)
+            # so they surface as real bugs rather than being silently masked.
+            raise
+        # NOTE: E2B sandbox API does not support pre-read size checks;
+        # the full file is loaded before the size guard below.
+        if len(data) > _MAX_BARE_REF_BYTES:
+            raise ValueError(
+                f"File too large ({len(data)} bytes, limit {_MAX_BARE_REF_BYTES})"
+            )
+        return data
 
     raise ValueError(
         f"Path is not allowed (not in workspace, sdk_cwd, or sandbox): {plain}"
@@ -178,15 +226,13 @@ async def resolve_file_ref(
 ) -> str:
     """Resolve a :class:`FileRef` to its text content."""
     raw = await read_file_bytes(ref.uri, user_id, session)
-    return _apply_line_range(
-        raw.decode("utf-8", errors="replace"), ref.start_line, ref.end_line
-    )
+    return _apply_line_range(_to_str(raw), ref.start_line, ref.end_line)
 
 
 async def expand_file_refs_in_string(
     text: str,
     user_id: str | None,
-    session: "ChatSession",
+    session: ChatSession,
     *,
     raise_on_error: bool = False,
 ) -> str:
@@ -232,6 +278,9 @@ async def expand_file_refs_in_string(
             if len(content) > _MAX_EXPAND_CHARS:
                 content = content[:_MAX_EXPAND_CHARS] + "\n... [truncated]"
             remaining = _MAX_TOTAL_EXPAND_CHARS - total_chars
+            # remaining == 0 means the budget was exactly exhausted by the
+            # previous ref.  The elif below (len > remaining) won't catch
+            # this since 0 > 0 is false, so we need the <= 0 check.
             if remaining <= 0:
                 content = "[file-ref budget exhausted: total expansion limit reached]"
             elif len(content) > remaining:
@@ -252,13 +301,31 @@ async def expand_file_refs_in_string(
 async def expand_file_refs_in_args(
     args: dict[str, Any],
     user_id: str | None,
-    session: "ChatSession",
+    session: ChatSession,
+    *,
+    input_schema: dict[str, Any] | None = None,
 ) -> dict[str, Any]:
     """Recursively expand ``@@agptfile:...`` references in tool call arguments.
 
     String values are expanded in-place.  Nested dicts and lists are
     traversed.  Non-string scalars are returned unchanged.
 
+    **Bare references** (the entire argument value is a single
+    ``@@agptfile:...`` token with no surrounding text) are resolved and then
+    parsed according to the file's extension or MIME type.  See
+    :mod:`backend.util.file_content_parser` for the full list of supported
+    formats (JSON, JSONL, CSV, TSV, YAML, TOML, Parquet, Excel).
+
+    When *input_schema* is provided and the target property has
+    ``"type": "string"``, structured parsing is skipped — the raw file content
+    is returned as a plain string so blocks receive the original text.
+
+    If the format is unrecognised or parsing fails, the content is returned as
+    a plain string (the fallback).
+
+    **Embedded references** (``@@agptfile:`` mixed with other text) always
+    produce a plain string — structured parsing only applies to bare refs.
+
     Raises :class:`FileRefExpansionError` if any reference fails to resolve,
     so the tool is *not* executed with an error string as its input.  The
     caller (the MCP tool wrapper) should convert this into an MCP error
@@ -267,15 +334,382 @@ async def expand_file_refs_in_args(
     if not args:
         return args
 
-    async def _expand(value: Any) -> Any:
+    properties = (input_schema or {}).get("properties", {})
+
+    async def _expand(
+        value: Any,
+        *,
+        prop_schema: dict[str, Any] | None = None,
+    ) -> Any:
+        """Recursively expand a single argument value.
+
+        Strings are checked for ``@@agptfile:`` references and expanded
+        (bare refs get structured parsing; embedded refs get inline
+        substitution).  Dicts and lists are traversed recursively,
+        threading the corresponding sub-schema from *prop_schema* so
+        that nested fields also receive correct type-aware expansion.
+        Non-string scalars pass through unchanged.
+        """
         if isinstance(value, str):
+            ref = parse_file_ref(value)
+            if ref is not None:
+                # MediaFileType fields: return the raw URI immediately —
+                # no file reading, no format inference, no content parsing.
+                if _is_media_file_field(prop_schema):
+                    return ref.uri
+
+                fmt = infer_format_from_uri(ref.uri)
+                # Workspace URIs by ID (workspace://abc123) have no extension.
+                # When the MIME fragment is also missing, fall back to the
+                # workspace file manager's metadata for format detection.
+                if fmt is None and ref.uri.startswith("workspace://"):
+                    fmt = await _infer_format_from_workspace(ref.uri, user_id, session)
+                return await _expand_bare_ref(ref, fmt, user_id, session, prop_schema)
+
+            # Not a bare ref — do normal inline expansion.
             return await expand_file_refs_in_string(
                 value, user_id, session, raise_on_error=True
             )
         if isinstance(value, dict):
-            return {k: await _expand(v) for k, v in value.items()}
+            # When the schema says this is an object but doesn't define
+            # inner properties, skip expansion — the caller (e.g.
+            # RunBlockTool) will expand with the actual nested schema.
+            if (
+                prop_schema is not None
+                and prop_schema.get("type") == "object"
+                and "properties" not in prop_schema
+            ):
+                return value
+            nested_props = (prop_schema or {}).get("properties", {})
+            return {
+                k: await _expand(v, prop_schema=nested_props.get(k))
+                for k, v in value.items()
+            }
         if isinstance(value, list):
-            return [await _expand(item) for item in value]
+            items_schema = (prop_schema or {}).get("items")
+            return [await _expand(item, prop_schema=items_schema) for item in value]
         return value
 
-    return {k: await _expand(v) for k, v in args.items()}
+    return {k: await _expand(v, prop_schema=properties.get(k)) for k, v in args.items()}
+
+
+# ---------------------------------------------------------------------------
+# Private helpers  (used by the public functions above)
+# ---------------------------------------------------------------------------
+
+
+def _apply_line_range(text: str, start: int | None, end: int | None) -> str:
+    """Slice *text* to the requested 1-indexed line range (inclusive).
+
+    When the requested range extends beyond the file, a note is appended
+    so the LLM knows it received the entire remaining content.
+    """
+    if start is None and end is None:
+        return text
+    lines = text.splitlines(keepends=True)
+    total = len(lines)
+    s = (start - 1) if start is not None else 0
+    e = end if end is not None else total
+    selected = list(itertools.islice(lines, s, e))
+    result = "".join(selected)
+    if end is not None and end > total:
+        result += f"\n[Note: file has only {total} lines]\n"
+    return result
+
+
+def _to_str(content: str | bytes) -> str:
+    """Decode *content* to a string if it is bytes, otherwise return as-is."""
+    if isinstance(content, str):
+        return content
+    return content.decode("utf-8", errors="replace")
+
+
+def _check_content_size(content: str | bytes) -> None:
+    """Raise :class:`ValueError` if *content* exceeds the byte limit.
+
+    Raises ``ValueError`` (not ``FileRefExpansionError``) so that the caller
+    (``_expand_bare_ref``) can unify all resolution errors into a single
+    ``except ValueError`` → ``FileRefExpansionError`` handler, keeping the
+    error-flow consistent with ``read_file_bytes`` and ``resolve_file_ref``.
+
+    For ``bytes``, the length is the byte count directly.  For ``str``,
+    we encode to UTF-8 first because multi-byte characters (e.g. emoji)
+    mean the byte size can be up to 4x the character count.
+    """
+    if isinstance(content, bytes):
+        size = len(content)
+    else:
+        char_len = len(content)
+        # Fast lower bound: UTF-8 byte count >= char count.
+        # If char count already exceeds the limit, reject immediately
+        # without allocating an encoded copy.
+        if char_len > _MAX_BARE_REF_BYTES:
+            size = char_len  # real byte size is even larger
+        # Fast upper bound: each char is at most 4 UTF-8 bytes.
+        # If worst-case is still under the limit, skip encoding entirely.
+        elif char_len * 4 <= _MAX_BARE_REF_BYTES:
+            return
+        else:
+            # Edge case: char count is under limit but multibyte chars
+            # might push byte count over. Encode to get exact size.
+            size = len(content.encode("utf-8"))
+    if size > _MAX_BARE_REF_BYTES:
+        raise ValueError(
+            f"File too large for structured parsing "
+            f"({size} bytes, limit {_MAX_BARE_REF_BYTES})"
+        )
+
+
+async def _infer_format_from_workspace(
+    uri: str,
+    user_id: str | None,
+    session: ChatSession,
+) -> str | None:
+    """Look up workspace file metadata to infer the format.
+
+    Workspace URIs by ID (``workspace://abc123``) have no file extension.
+    When the MIME fragment is also absent, we query the workspace file
+    manager for the file's stored MIME type and original filename.
+    """
+    if not user_id:
+        return None
+    try:
+        ws = parse_workspace_uri(uri)
+        manager = await get_workspace_manager(user_id, session.session_id)
+        info = await (
+            manager.get_file_info(ws.file_ref)
+            if not ws.is_path
+            else manager.get_file_info_by_path(ws.file_ref)
+        )
+        if info is None:
+            return None
+        # Try MIME type first, then filename extension.
+        mime = (info.mime_type or "").split(";", 1)[0].strip().lower()
+        return MIME_TO_FORMAT.get(mime) or infer_format_from_uri(info.name)
+    except (
+        ValueError,
+        FileNotFoundError,
+        OSError,
+        PermissionError,
+        AttributeError,
+        TypeError,
+    ):
+        # Expected failures: bad URI, missing file, permission denied, or
+        # workspace manager returning unexpected types.  Propagate anything
+        # else (e.g. programming errors) so they don't get silently swallowed.
+        logger.debug("workspace metadata lookup failed for %s", uri, exc_info=True)
+        return None
+
+
+def _is_media_file_field(prop_schema: dict[str, Any] | None) -> bool:
+    """Return True if *prop_schema* describes a MediaFileType field (format: file)."""
+    if prop_schema is None:
+        return False
+    return (
+        prop_schema.get("type") == "string"
+        and prop_schema.get("format") == MediaFileType.string_format
+    )
+
+
+async def _expand_bare_ref(
+    ref: FileRef,
+    fmt: str | None,
+    user_id: str | None,
+    session: ChatSession,
+    prop_schema: dict[str, Any] | None,
+) -> Any:
+    """Resolve and parse a bare ``@@agptfile:`` reference.
+
+    This is the structured-parsing path: the file is read, optionally parsed
+    according to *fmt*, and adapted to the target *prop_schema*.
+
+    Raises :class:`FileRefExpansionError` on resolution or parsing failure.
+
+    Note: MediaFileType fields (format: "file") are handled earlier in
+    ``_expand`` to avoid unnecessary format inference and file I/O.
+    """
+    try:
+        if fmt is not None and fmt in BINARY_FORMATS:
+            # Binary formats need raw bytes, not UTF-8 text.
+            # Line ranges are meaningless for binary formats (parquet/xlsx)
+            # — ignore them and parse full bytes.  Warn so the caller/model
+            # knows the range was silently dropped.
+            if ref.start_line is not None or ref.end_line is not None:
+                logger.warning(
+                    "Line range [%s-%s] ignored for binary format %s (%s); "
+                    "binary formats are always parsed in full.",
+                    ref.start_line,
+                    ref.end_line,
+                    fmt,
+                    ref.uri,
+                )
+            content: str | bytes = await read_file_bytes(ref.uri, user_id, session)
+        else:
+            content = await resolve_file_ref(ref, user_id, session)
+    except ValueError as exc:
+        raise FileRefExpansionError(str(exc)) from exc
+
+    # For known formats this rejects files >10 MB before parsing.
+    # For unknown formats _MAX_EXPAND_CHARS (200K chars) below is stricter,
+    # but this check still guards the parsing path which has no char limit.
+    # _check_content_size raises ValueError, which we unify here just like
+    # resolution errors above.
+    try:
+        _check_content_size(content)
+    except ValueError as exc:
+        raise FileRefExpansionError(str(exc)) from exc
+
+    # When the schema declares this parameter as "string",
+    # return raw file content — don't parse into a structured
+    # type that would need json.dumps() serialisation.
+    expect_string = (prop_schema or {}).get("type") == "string"
+    if expect_string:
+        if isinstance(content, bytes):
+            raise FileRefExpansionError(
+                f"Cannot use {fmt} file as text input: "
+                f"binary formats (parquet, xlsx) must be passed "
+                f"to a block that accepts structured data (list/object), "
+                f"not a string-typed parameter."
+            )
+        return content
+
+    if fmt is not None:
+        # Use strict mode for binary formats so we surface the
+        # actual error (e.g. missing pyarrow/openpyxl, corrupt
+        # file) instead of silently returning garbled bytes.
+        strict = fmt in BINARY_FORMATS
+        try:
+            parsed = parse_file_content(content, fmt, strict=strict)
+        except PARSE_EXCEPTIONS as exc:
+            raise FileRefExpansionError(f"Failed to parse {fmt} file: {exc}") from exc
+        # Normalize bytes fallback to str so tools never
+        # receive raw bytes when parsing fails.
+        if isinstance(parsed, bytes):
+            parsed = _to_str(parsed)
+        return _adapt_to_schema(parsed, prop_schema)
+
+    # Unknown format — return as plain string, but apply
+    # the same per-ref character limit used by inline refs
+    # to prevent injecting unexpectedly large content.
+    text = _to_str(content)
+    if len(text) > _MAX_EXPAND_CHARS:
+        text = text[:_MAX_EXPAND_CHARS] + "\n... [truncated]"
+    return text
+
+
+def _adapt_to_schema(parsed: Any, prop_schema: dict[str, Any] | None) -> Any:
+    """Adapt a parsed file value to better fit the target schema type.
+
+    When the parser returns a natural type (e.g. dict from YAML, list from CSV)
+    that doesn't match the block's expected type, this function converts it to
+    a more useful representation instead of relying on pydantic's generic
+    coercion (which can produce awkward results like flattened dicts → lists).
+
+    Returns *parsed* unchanged when no adaptation is needed.
+    """
+    if prop_schema is None:
+        return parsed
+
+    target_type = prop_schema.get("type")
+
+    # Dict → array: delegate to helper.
+    if isinstance(parsed, dict) and target_type == "array":
+        return _adapt_dict_to_array(parsed, prop_schema)
+
+    # List → object: delegate to helper (raises for non-tabular lists).
+    if isinstance(parsed, list) and target_type == "object":
+        return _adapt_list_to_object(parsed)
+
+    # Tabular list → Any (no type): convert to list of dicts.
+    # Blocks like FindInDictionaryBlock have `input: Any` which produces
+    # a schema with no "type" key.  Tabular [[header],[rows]] is unusable
+    # for key lookup, but [{col: val}, ...] works with FindInDict's
+    # list-of-dicts branch (line 195-199 in data_manipulation.py).
+    if isinstance(parsed, list) and target_type is None and _is_tabular(parsed):
+        return _tabular_to_list_of_dicts(parsed)
+
+    return parsed
+
+
+def _adapt_dict_to_array(parsed: dict, prop_schema: dict[str, Any]) -> Any:
+    """Adapt a parsed dict to an array-typed field.
+
+    Extracts list-valued entries when the target item type is ``array``,
+    passes through unchanged when item type is ``string`` (lets pydantic error),
+    or wraps in ``[parsed]`` as a fallback.
+    """
+    items_type = (prop_schema.get("items") or {}).get("type")
+    if items_type == "array":
+        # Target is List[List[Any]] — extract list-typed values from the
+        # dict as inner lists.  E.g. YAML {"fruits": [{...},...]}} with
+        # ConcatenateLists (List[List[Any]]) → [[{...},...]].
+        list_values = [v for v in parsed.values() if isinstance(v, list)]
+        if list_values:
+            return list_values
+    if items_type == "string":
+        # Target is List[str] — wrapping a dict would give [dict]
+        # which can't coerce to strings.  Return unchanged and let
+        # pydantic surface a clear validation error.
+        return parsed
+    # Fallback: wrap in a single-element list so the block gets [dict]
+    # instead of pydantic flattening keys/values into a flat list.
+    return [parsed]
+
+
+def _adapt_list_to_object(parsed: list) -> Any:
+    """Adapt a parsed list to an object-typed field.
+
+    Converts tabular lists to column-dicts; raises for non-tabular lists.
+    """
+    if _is_tabular(parsed):
+        return _tabular_to_column_dict(parsed)
+    # Non-tabular list (e.g. a plain Python list from a YAML file) cannot
+    # be meaningfully coerced to an object.  Raise explicitly so callers
+    # get a clear error rather than pydantic silently wrapping the list.
+    raise FileRefExpansionError(
+        "Cannot adapt a non-tabular list to an object-typed field. "
+        "Expected a tabular structure ([[header], [row1], ...]) or a dict."
+    )
+
+
+def _is_tabular(parsed: Any) -> bool:
+    """Check if parsed data is in tabular format: [[header], [row1], ...].
+
+    Uses isinstance checks because this is a structural type guard on
+    opaque parser output (Any), not duck typing.  A Protocol wouldn't
+    help here — we need to verify exact list-of-lists shape.
+    """
+    if not isinstance(parsed, list) or len(parsed) < 2:
+        return False
+    header = parsed[0]
+    if not isinstance(header, list) or not header:
+        return False
+    if not all(isinstance(h, str) for h in header):
+        return False
+    return all(isinstance(row, list) for row in parsed[1:])
+
+
+def _tabular_to_list_of_dicts(parsed: list) -> list[dict[str, Any]]:
+    """Convert [[header], [row1], ...] → [{header[0]: row[0], ...}, ...].
+
+    Ragged rows (fewer columns than the header) get None for missing values.
+    Extra values beyond the header length are silently dropped.
+    """
+    header = parsed[0]
+    return [
+        dict(itertools.zip_longest(header, row[: len(header)], fillvalue=None))
+        for row in parsed[1:]
+    ]
+
+
+def _tabular_to_column_dict(parsed: list) -> dict[str, list]:
+    """Convert [[header], [row1], ...] → {"col1": [val1, ...], ...}.
+
+    Ragged rows (fewer columns than the header) get None for missing values,
+    ensuring all columns have equal length.
+    """
+    header = parsed[0]
+    return {
+        col: [row[i] if i < len(row) else None for row in parsed[1:]]
+        for i, col in enumerate(header)
+    }

autogpt_platform/backend/backend/copilot/sdk/file_ref_integration_test.py

@@ -175,6 +175,199 @@ async def test_expand_args_replaces_file_ref_in_nested_dict():
         assert result["count"] == 42
 
 
+# ---------------------------------------------------------------------------
+# expand_file_refs_in_args — bare ref structured parsing
+# ---------------------------------------------------------------------------
+
+
+@pytest.mark.asyncio
+async def test_bare_ref_json_returns_parsed_dict():
+    """Bare ref to a .json file returns parsed dict, not raw string."""
+    with tempfile.TemporaryDirectory() as sdk_cwd:
+        json_file = os.path.join(sdk_cwd, "data.json")
+        with open(json_file, "w") as f:
+            f.write('{"key": "value", "count": 42}')
+
+        with patch("backend.copilot.context._current_sdk_cwd") as mock_cwd_var:
+            mock_cwd_var.get.return_value = sdk_cwd
+
+            result = await expand_file_refs_in_args(
+                {"data": f"@@agptfile:{json_file}"},
+                user_id="u1",
+                session=_make_session(),
+            )
+
+        assert result["data"] == {"key": "value", "count": 42}
+
+
+@pytest.mark.asyncio
+async def test_bare_ref_csv_returns_parsed_table():
+    """Bare ref to a .csv file returns list[list[str]] table."""
+    with tempfile.TemporaryDirectory() as sdk_cwd:
+        csv_file = os.path.join(sdk_cwd, "data.csv")
+        with open(csv_file, "w") as f:
+            f.write("Name,Score\nAlice,90\nBob,85")
+
+        with patch("backend.copilot.context._current_sdk_cwd") as mock_cwd_var:
+            mock_cwd_var.get.return_value = sdk_cwd
+
+            result = await expand_file_refs_in_args(
+                {"input": f"@@agptfile:{csv_file}"},
+                user_id="u1",
+                session=_make_session(),
+            )
+
+        assert result["input"] == [
+            ["Name", "Score"],
+            ["Alice", "90"],
+            ["Bob", "85"],
+        ]
+
+
+@pytest.mark.asyncio
+async def test_bare_ref_unknown_extension_returns_string():
+    """Bare ref to a file with unknown extension returns plain string."""
+    with tempfile.TemporaryDirectory() as sdk_cwd:
+        txt_file = os.path.join(sdk_cwd, "readme.txt")
+        with open(txt_file, "w") as f:
+            f.write("plain text content")
+
+        with patch("backend.copilot.context._current_sdk_cwd") as mock_cwd_var:
+            mock_cwd_var.get.return_value = sdk_cwd
+
+            result = await expand_file_refs_in_args(
+                {"data": f"@@agptfile:{txt_file}"},
+                user_id="u1",
+                session=_make_session(),
+            )
+
+        assert result["data"] == "plain text content"
+        assert isinstance(result["data"], str)
+
+
+@pytest.mark.asyncio
+async def test_bare_ref_invalid_json_falls_back_to_string():
+    """Bare ref to a .json file with invalid JSON falls back to string."""
+    with tempfile.TemporaryDirectory() as sdk_cwd:
+        json_file = os.path.join(sdk_cwd, "bad.json")
+        with open(json_file, "w") as f:
+            f.write("not valid json {{{")
+
+        with patch("backend.copilot.context._current_sdk_cwd") as mock_cwd_var:
+            mock_cwd_var.get.return_value = sdk_cwd
+
+            result = await expand_file_refs_in_args(
+                {"data": f"@@agptfile:{json_file}"},
+                user_id="u1",
+                session=_make_session(),
+            )
+
+        assert result["data"] == "not valid json {{{"
+        assert isinstance(result["data"], str)
+
+
+@pytest.mark.asyncio
+async def test_embedded_ref_always_returns_string_even_for_json():
+    """Embedded ref (text around it) returns plain string, not parsed JSON."""
+    with tempfile.TemporaryDirectory() as sdk_cwd:
+        json_file = os.path.join(sdk_cwd, "data.json")
+        with open(json_file, "w") as f:
+            f.write('{"key": "value"}')
+
+        with patch("backend.copilot.context._current_sdk_cwd") as mock_cwd_var:
+            mock_cwd_var.get.return_value = sdk_cwd
+
+            result = await expand_file_refs_in_args(
+                {"data": f"prefix @@agptfile:{json_file} suffix"},
+                user_id="u1",
+                session=_make_session(),
+            )
+
+        assert isinstance(result["data"], str)
+        assert result["data"].startswith("prefix ")
+        assert result["data"].endswith(" suffix")
+
+
+@pytest.mark.asyncio
+async def test_bare_ref_yaml_returns_parsed_dict():
+    """Bare ref to a .yaml file returns parsed dict."""
+    with tempfile.TemporaryDirectory() as sdk_cwd:
+        yaml_file = os.path.join(sdk_cwd, "config.yaml")
+        with open(yaml_file, "w") as f:
+            f.write("name: test\ncount: 42\n")
+
+        with patch("backend.copilot.context._current_sdk_cwd") as mock_cwd_var:
+            mock_cwd_var.get.return_value = sdk_cwd
+
+            result = await expand_file_refs_in_args(
+                {"config": f"@@agptfile:{yaml_file}"},
+                user_id="u1",
+                session=_make_session(),
+            )
+
+        assert result["config"] == {"name": "test", "count": 42}
+
+
+@pytest.mark.asyncio
+async def test_bare_ref_binary_with_line_range_ignores_range():
+    """Bare ref to a binary file (.parquet) with line range parses the full file.
+
+    Binary formats (parquet, xlsx) ignore line ranges — the full content is
+    parsed and the range is silently dropped with a log warning.
+    """
+    try:
+        import pandas as pd
+    except ImportError:
+        pytest.skip("pandas not installed")
+    try:
+        import pyarrow  # noqa: F401  # pyright: ignore[reportMissingImports]
+    except ImportError:
+        pytest.skip("pyarrow not installed")
+
+    with tempfile.TemporaryDirectory() as sdk_cwd:
+        parquet_file = os.path.join(sdk_cwd, "data.parquet")
+        import io as _io
+
+        df = pd.DataFrame({"A": [1, 2, 3], "B": [4, 5, 6]})
+        buf = _io.BytesIO()
+        df.to_parquet(buf, index=False)
+        with open(parquet_file, "wb") as f:
+            f.write(buf.getvalue())
+
+        with patch("backend.copilot.context._current_sdk_cwd") as mock_cwd_var:
+            mock_cwd_var.get.return_value = sdk_cwd
+
+            # Line range [1-2] should be silently ignored for binary formats.
+            result = await expand_file_refs_in_args(
+                {"data": f"@@agptfile:{parquet_file}[1-2]"},
+                user_id="u1",
+                session=_make_session(),
+            )
+
+        # Full file is returned despite the line range.
+        assert result["data"] == [["A", "B"], [1, 4], [2, 5], [3, 6]]
+
+
+@pytest.mark.asyncio
+async def test_bare_ref_toml_returns_parsed_dict():
+    """Bare ref to a .toml file returns parsed dict."""
+    with tempfile.TemporaryDirectory() as sdk_cwd:
+        toml_file = os.path.join(sdk_cwd, "config.toml")
+        with open(toml_file, "w") as f:
+            f.write('name = "test"\ncount = 42\n')
+
+        with patch("backend.copilot.context._current_sdk_cwd") as mock_cwd_var:
+            mock_cwd_var.get.return_value = sdk_cwd
+
+            result = await expand_file_refs_in_args(
+                {"config": f"@@agptfile:{toml_file}"},
+                user_id="u1",
+                session=_make_session(),
+            )
+
+        assert result["config"] == {"name": "test", "count": 42}
+
+
 # ---------------------------------------------------------------------------
 # _read_file_handler — extended to accept workspace:// and local paths
 # ---------------------------------------------------------------------------
@@ -219,7 +412,7 @@ async def test_read_file_handler_workspace_uri():
         "backend.copilot.sdk.tool_adapter.get_execution_context",
         return_value=("user-1", mock_session),
     ), patch(
-        "backend.copilot.sdk.file_ref.get_manager",
+        "backend.copilot.sdk.file_ref.get_workspace_manager",
         new=AsyncMock(return_value=mock_manager),
     ):
         result = await _read_file_handler(
@@ -276,7 +469,7 @@ async def test_read_file_bytes_workspace_virtual_path():
     mock_manager.read_file.return_value = b"virtual path content"
 
     with patch(
-        "backend.copilot.sdk.file_ref.get_manager",
+        "backend.copilot.sdk.file_ref.get_workspace_manager",
         new=AsyncMock(return_value=mock_manager),
     ):
         result = await read_file_bytes("workspace:///reports/q1.md", "user-1", session)

autogpt_platform/backend/backend/copilot/sdk/prompt_too_long_test.py

@@ -0,0 +1,552 @@
+"""Tests for retry logic and transcript compaction helpers."""
+
+from __future__ import annotations
+
+from unittest.mock import AsyncMock, patch
+from uuid import uuid4
+
+import pytest
+
+from backend.util import json
+
+from .conftest import build_test_transcript as _build_transcript
+from .service import _is_prompt_too_long
+from .transcript import (
+    _flatten_assistant_content,
+    _flatten_tool_result_content,
+    _messages_to_transcript,
+    _transcript_to_messages,
+    compact_transcript,
+    validate_transcript,
+)
+
+# ---------------------------------------------------------------------------
+# _flatten_assistant_content
+# ---------------------------------------------------------------------------
+
+
+class TestFlattenAssistantContent:
+    def test_text_blocks(self):
+        blocks = [
+            {"type": "text", "text": "Hello"},
+            {"type": "text", "text": "World"},
+        ]
+        assert _flatten_assistant_content(blocks) == "Hello\nWorld"
+
+    def test_tool_use_blocks(self):
+        blocks = [{"type": "tool_use", "name": "read_file", "input": {}}]
+        assert _flatten_assistant_content(blocks) == "[tool_use: read_file]"
+
+    def test_mixed_blocks(self):
+        blocks = [
+            {"type": "text", "text": "Let me read that."},
+            {"type": "tool_use", "name": "Read", "input": {"path": "/foo"}},
+        ]
+        result = _flatten_assistant_content(blocks)
+        assert "Let me read that." in result
+        assert "[tool_use: Read]" in result
+
+    def test_raw_strings(self):
+        assert _flatten_assistant_content(["hello", "world"]) == "hello\nworld"
+
+    def test_unknown_block_type_preserved_as_placeholder(self):
+        blocks = [
+            {"type": "text", "text": "See this image:"},
+            {"type": "image", "source": {"type": "base64", "data": "..."}},
+        ]
+        result = _flatten_assistant_content(blocks)
+        assert "See this image:" in result
+        assert "[__image__]" in result
+
+    def test_empty(self):
+        assert _flatten_assistant_content([]) == ""
+
+
+# ---------------------------------------------------------------------------
+# _flatten_tool_result_content
+# ---------------------------------------------------------------------------
+
+
+class TestFlattenToolResultContent:
+    def test_tool_result_with_text(self):
+        blocks = [
+            {
+                "type": "tool_result",
+                "tool_use_id": "123",
+                "content": [{"type": "text", "text": "file contents here"}],
+            }
+        ]
+        assert _flatten_tool_result_content(blocks) == "file contents here"
+
+    def test_tool_result_with_string_content(self):
+        blocks = [{"type": "tool_result", "tool_use_id": "123", "content": "ok"}]
+        assert _flatten_tool_result_content(blocks) == "ok"
+
+    def test_text_block(self):
+        blocks = [{"type": "text", "text": "plain text"}]
+        assert _flatten_tool_result_content(blocks) == "plain text"
+
+    def test_raw_string(self):
+        assert _flatten_tool_result_content(["raw"]) == "raw"
+
+    def test_tool_result_with_none_content(self):
+        """tool_result with content=None should produce empty string."""
+        blocks = [{"type": "tool_result", "tool_use_id": "x", "content": None}]
+        assert _flatten_tool_result_content(blocks) == ""
+
+    def test_tool_result_with_empty_list_content(self):
+        """tool_result with content=[] should produce empty string."""
+        blocks = [{"type": "tool_result", "tool_use_id": "x", "content": []}]
+        assert _flatten_tool_result_content(blocks) == ""
+
+    def test_empty(self):
+        assert _flatten_tool_result_content([]) == ""
+
+    def test_nested_dict_without_text(self):
+        """Dict blocks without text key use json.dumps fallback."""
+        blocks = [
+            {
+                "type": "tool_result",
+                "tool_use_id": "x",
+                "content": [{"type": "image", "source": "data:..."}],
+            }
+        ]
+        result = _flatten_tool_result_content(blocks)
+        assert "image" in result  # json.dumps fallback
+
+    def test_unknown_block_type_preserved_as_placeholder(self):
+        blocks = [{"type": "image", "source": {"type": "base64", "data": "..."}}]
+        result = _flatten_tool_result_content(blocks)
+        assert "[__image__]" in result
+
+
+# ---------------------------------------------------------------------------
+# _transcript_to_messages
+# ---------------------------------------------------------------------------
+
+
+def _make_entry(entry_type: str, role: str, content: str | list, **kwargs) -> str:
+    """Build a JSONL line for testing."""
+    uid = str(uuid4())
+    msg: dict = {"role": role, "content": content}
+    msg.update(kwargs)
+    entry = {
+        "type": entry_type,
+        "uuid": uid,
+        "parentUuid": None,
+        "message": msg,
+    }
+    return json.dumps(entry, separators=(",", ":"))
+
+
+class TestTranscriptToMessages:
+    def test_basic_roundtrip(self):
+        lines = [
+            _make_entry("user", "user", "Hello"),
+            _make_entry("assistant", "assistant", [{"type": "text", "text": "Hi"}]),
+        ]
+        content = "\n".join(lines) + "\n"
+        messages = _transcript_to_messages(content)
+        assert len(messages) == 2
+        assert messages[0] == {"role": "user", "content": "Hello"}
+        assert messages[1] == {"role": "assistant", "content": "Hi"}
+
+    def test_skips_strippable_types(self):
+        """Progress and metadata entries are excluded."""
+        lines = [
+            _make_entry("user", "user", "Hello"),
+            json.dumps(
+                {
+                    "type": "progress",
+                    "uuid": str(uuid4()),
+                    "parentUuid": None,
+                    "message": {"role": "assistant", "content": "..."},
+                }
+            ),
+            _make_entry("assistant", "assistant", [{"type": "text", "text": "Hi"}]),
+        ]
+        content = "\n".join(lines) + "\n"
+        messages = _transcript_to_messages(content)
+        assert len(messages) == 2
+
+    def test_empty_content(self):
+        assert _transcript_to_messages("") == []
+
+    def test_tool_result_content(self):
+        """User entries with tool_result content blocks are flattened."""
+        lines = [
+            _make_entry(
+                "user",
+                "user",
+                [
+                    {
+                        "type": "tool_result",
+                        "tool_use_id": "123",
+                        "content": "tool output",
+                    }
+                ],
+            ),
+        ]
+        content = "\n".join(lines) + "\n"
+        messages = _transcript_to_messages(content)
+        assert len(messages) == 1
+        assert messages[0]["content"] == "tool output"
+
+    def test_malformed_json_lines_skipped(self):
+        """Malformed JSON lines in transcript are silently skipped."""
+        lines = [
+            _make_entry("user", "user", "Hello"),
+            "this is not valid json",
+            _make_entry("assistant", "assistant", [{"type": "text", "text": "Hi"}]),
+        ]
+        content = "\n".join(lines) + "\n"
+        messages = _transcript_to_messages(content)
+        assert len(messages) == 2
+
+    def test_empty_lines_skipped(self):
+        """Empty lines and whitespace-only lines are skipped."""
+        lines = [
+            _make_entry("user", "user", "Hello"),
+            "",
+            "   ",
+            _make_entry("assistant", "assistant", [{"type": "text", "text": "Hi"}]),
+        ]
+        content = "\n".join(lines) + "\n"
+        messages = _transcript_to_messages(content)
+        assert len(messages) == 2
+
+    def test_unicode_content_preserved(self):
+        """Unicode characters survive transcript roundtrip."""
+        lines = [
+            _make_entry("user", "user", "Hello 你好 🌍"),
+            _make_entry(
+                "assistant",
+                "assistant",
+                [{"type": "text", "text": "Bonjour 日本語 émojis 🎉"}],
+            ),
+        ]
+        content = "\n".join(lines) + "\n"
+        messages = _transcript_to_messages(content)
+        assert messages[0]["content"] == "Hello 你好 🌍"
+        assert messages[1]["content"] == "Bonjour 日本語 émojis 🎉"
+
+    def test_entry_without_role_skipped(self):
+        """Entries with missing role in message are skipped."""
+        entry_no_role = json.dumps(
+            {
+                "type": "user",
+                "uuid": str(uuid4()),
+                "parentUuid": None,
+                "message": {"content": "no role here"},
+            }
+        )
+        lines = [
+            entry_no_role,
+            _make_entry("user", "user", "Hello"),
+        ]
+        content = "\n".join(lines) + "\n"
+        messages = _transcript_to_messages(content)
+        assert len(messages) == 1
+        assert messages[0]["content"] == "Hello"
+
+    def test_tool_use_and_result_pairs(self):
+        """Tool use + tool result pairs are properly flattened."""
+        lines = [
+            _make_entry(
+                "assistant",
+                "assistant",
+                [
+                    {"type": "text", "text": "Let me check."},
+                    {"type": "tool_use", "name": "read_file", "input": {"path": "/x"}},
+                ],
+            ),
+            _make_entry(
+                "user",
+                "user",
+                [
+                    {
+                        "type": "tool_result",
+                        "tool_use_id": "abc",
+                        "content": [{"type": "text", "text": "file contents"}],
+                    }
+                ],
+            ),
+        ]
+        content = "\n".join(lines) + "\n"
+        messages = _transcript_to_messages(content)
+        assert len(messages) == 2
+        assert "Let me check." in messages[0]["content"]
+        assert "[tool_use: read_file]" in messages[0]["content"]
+        assert messages[1]["content"] == "file contents"
+
+
+# ---------------------------------------------------------------------------
+# _messages_to_transcript
+# ---------------------------------------------------------------------------
+
+
+class TestMessagesToTranscript:
+    def test_produces_valid_jsonl(self):
+        messages = [
+            {"role": "user", "content": "Hello"},
+            {"role": "assistant", "content": "Hi there"},
+        ]
+        result = _messages_to_transcript(messages)
+        lines = result.strip().split("\n")
+        assert len(lines) == 2
+        for line in lines:
+            parsed = json.loads(line)
+            assert "type" in parsed
+            assert "uuid" in parsed
+            assert "message" in parsed
+
+    def test_assistant_has_proper_structure(self):
+        messages = [{"role": "assistant", "content": "Hello"}]
+        result = _messages_to_transcript(messages)
+        entry = json.loads(result.strip())
+        assert entry["type"] == "assistant"
+        msg = entry["message"]
+        assert msg["role"] == "assistant"
+        assert msg["type"] == "message"
+        assert msg["stop_reason"] == "end_turn"
+        assert isinstance(msg["content"], list)
+        assert msg["content"][0]["type"] == "text"
+
+    def test_user_has_plain_content(self):
+        messages = [{"role": "user", "content": "Hi"}]
+        result = _messages_to_transcript(messages)
+        entry = json.loads(result.strip())
+        assert entry["type"] == "user"
+        assert entry["message"]["content"] == "Hi"
+
+    def test_parent_uuid_chain(self):
+        messages = [
+            {"role": "user", "content": "A"},
+            {"role": "assistant", "content": "B"},
+            {"role": "user", "content": "C"},
+        ]
+        result = _messages_to_transcript(messages)
+        lines = result.strip().split("\n")
+        entries = [json.loads(line) for line in lines]
+        assert entries[0]["parentUuid"] == ""
+        assert entries[1]["parentUuid"] == entries[0]["uuid"]
+        assert entries[2]["parentUuid"] == entries[1]["uuid"]
+
+    def test_empty_messages(self):
+        assert _messages_to_transcript([]) == ""
+
+    def test_output_is_valid_transcript(self):
+        """Output should pass validate_transcript if it has assistant entries."""
+        messages = [
+            {"role": "user", "content": "Hello"},
+            {"role": "assistant", "content": "Hi"},
+        ]
+        result = _messages_to_transcript(messages)
+        assert validate_transcript(result)
+
+    def test_roundtrip_to_messages(self):
+        """Messages → transcript → messages preserves structure."""
+        original = [
+            {"role": "user", "content": "Hello"},
+            {"role": "assistant", "content": "Hi there"},
+            {"role": "user", "content": "How are you?"},
+        ]
+        transcript = _messages_to_transcript(original)
+        restored = _transcript_to_messages(transcript)
+        assert len(restored) == len(original)
+        for orig, rest in zip(original, restored):
+            assert orig["role"] == rest["role"]
+            assert orig["content"] == rest["content"]
+
+
+# ---------------------------------------------------------------------------
+# compact_transcript
+# ---------------------------------------------------------------------------
+
+
+class TestCompactTranscript:
+    @pytest.mark.asyncio
+    async def test_too_few_messages_returns_none(self):
+        """compact_transcript returns None when transcript has < 2 messages."""
+        transcript = _build_transcript([("user", "Hello")])
+        with patch(
+            "backend.copilot.config.ChatConfig",
+            return_value=type(
+                "Cfg", (), {"model": "m", "api_key": "k", "base_url": "u"}
+            )(),
+        ):
+            result = await compact_transcript(transcript, model="test-model")
+        assert result is None
+
+    @pytest.mark.asyncio
+    async def test_returns_none_when_not_compacted(self):
+        """When compress_context says no compaction needed, returns None.
+        The compressor couldn't reduce it, so retrying with the same
+        content would fail identically."""
+        transcript = _build_transcript(
+            [
+                ("user", "Hello"),
+                ("assistant", "Hi there"),
+            ]
+        )
+        mock_result = type(
+            "CompressResult",
+            (),
+            {
+                "was_compacted": False,
+                "messages": [],
+                "original_token_count": 100,
+                "token_count": 100,
+                "messages_summarized": 0,
+                "messages_dropped": 0,
+            },
+        )()
+        with (
+            patch(
+                "backend.copilot.config.ChatConfig",
+                return_value=type(
+                    "Cfg", (), {"model": "m", "api_key": "k", "base_url": "u"}
+                )(),
+            ),
+            patch(
+                "backend.copilot.sdk.transcript._run_compression",
+                new_callable=AsyncMock,
+                return_value=mock_result,
+            ),
+        ):
+            result = await compact_transcript(transcript, model="test-model")
+        assert result is None
+
+    @pytest.mark.asyncio
+    async def test_returns_compacted_transcript(self):
+        """When compaction succeeds, returns a valid compacted transcript."""
+        transcript = _build_transcript(
+            [
+                ("user", "Hello"),
+                ("assistant", "Hi"),
+                ("user", "More"),
+                ("assistant", "Details"),
+            ]
+        )
+        compacted_msgs = [
+            {"role": "user", "content": "[summary]"},
+            {"role": "assistant", "content": "Summarized response"},
+        ]
+        mock_result = type(
+            "CompressResult",
+            (),
+            {
+                "was_compacted": True,
+                "messages": compacted_msgs,
+                "original_token_count": 500,
+                "token_count": 100,
+                "messages_summarized": 2,
+                "messages_dropped": 0,
+            },
+        )()
+        with (
+            patch(
+                "backend.copilot.config.ChatConfig",
+                return_value=type(
+                    "Cfg", (), {"model": "m", "api_key": "k", "base_url": "u"}
+                )(),
+            ),
+            patch(
+                "backend.copilot.sdk.transcript._run_compression",
+                new_callable=AsyncMock,
+                return_value=mock_result,
+            ),
+        ):
+            result = await compact_transcript(transcript, model="test-model")
+        assert result is not None
+        assert validate_transcript(result)
+        msgs = _transcript_to_messages(result)
+        assert len(msgs) == 2
+        assert msgs[1]["content"] == "Summarized response"
+
+    @pytest.mark.asyncio
+    async def test_returns_none_on_compression_failure(self):
+        """When _run_compression raises, returns None."""
+        transcript = _build_transcript(
+            [
+                ("user", "Hello"),
+                ("assistant", "Hi"),
+            ]
+        )
+        with (
+            patch(
+                "backend.copilot.config.ChatConfig",
+                return_value=type(
+                    "Cfg", (), {"model": "m", "api_key": "k", "base_url": "u"}
+                )(),
+            ),
+            patch(
+                "backend.copilot.sdk.transcript._run_compression",
+                new_callable=AsyncMock,
+                side_effect=RuntimeError("LLM unavailable"),
+            ),
+        ):
+            result = await compact_transcript(transcript, model="test-model")
+        assert result is None
+
+
+# ---------------------------------------------------------------------------
+# _is_prompt_too_long
+# ---------------------------------------------------------------------------
+
+
+class TestIsPromptTooLong:
+    """Unit tests for _is_prompt_too_long pattern matching."""
+
+    def test_prompt_is_too_long(self):
+        err = RuntimeError("prompt is too long for model context")
+        assert _is_prompt_too_long(err) is True
+
+    def test_request_too_large(self):
+        err = Exception("request too large: 250000 tokens")
+        assert _is_prompt_too_long(err) is True
+
+    def test_maximum_context_length(self):
+        err = ValueError("maximum context length exceeded")
+        assert _is_prompt_too_long(err) is True
+
+    def test_context_length_exceeded(self):
+        err = Exception("context_length_exceeded")
+        assert _is_prompt_too_long(err) is True
+
+    def test_input_tokens_exceed(self):
+        err = Exception("input tokens exceed the max_tokens limit")
+        assert _is_prompt_too_long(err) is True
+
+    def test_input_is_too_long(self):
+        err = Exception("input is too long for the model")
+        assert _is_prompt_too_long(err) is True
+
+    def test_content_length_exceeds(self):
+        err = Exception("content length exceeds maximum")
+        assert _is_prompt_too_long(err) is True
+
+    def test_unrelated_error_returns_false(self):
+        err = RuntimeError("network timeout")
+        assert _is_prompt_too_long(err) is False
+
+    def test_auth_error_returns_false(self):
+        err = Exception("authentication failed: invalid API key")
+        assert _is_prompt_too_long(err) is False
+
+    def test_chained_exception_detected(self):
+        """Prompt-too-long error wrapped in another exception is detected."""
+        inner = RuntimeError("prompt is too long")
+        outer = Exception("SDK error")
+        outer.__cause__ = inner
+        assert _is_prompt_too_long(outer) is True
+
+    def test_case_insensitive(self):
+        err = Exception("PROMPT IS TOO LONG")
+        assert _is_prompt_too_long(err) is True
+
+    def test_old_max_tokens_exceeded_not_matched(self):
+        """The old broad 'max_tokens_exceeded' pattern was removed.
+        Only 'input tokens exceed' should match now."""
+        err = Exception("max_tokens_exceeded")
+        assert _is_prompt_too_long(err) is False

autogpt_platform/backend/backend/copilot/sdk/response_adapter.py

@@ -226,7 +226,7 @@ class SDKResponseAdapter:
                 responses.append(StreamFinish())
 
         else:
-            logger.debug(f"Unhandled SDK message type: {type(sdk_message).__name__}")
+            logger.debug("Unhandled SDK message type: %s", type(sdk_message).__name__)
 
         return responses
 

autogpt_platform/backend/backend/copilot/sdk/security_hooks.py

@@ -52,7 +52,7 @@ def _validate_workspace_path(
     if is_allowed_local_path(path, sdk_cwd):
         return {}
 
-    logger.warning(f"Blocked {tool_name} outside workspace: {path}")
+    logger.warning("Blocked %s outside workspace: %s", tool_name, path)
     workspace_hint = f" Allowed workspace: {sdk_cwd}" if sdk_cwd else ""
     return _deny(
         f"[SECURITY] Tool '{tool_name}' can only access files within the workspace "
@@ -71,7 +71,7 @@ def _validate_tool_access(
     """
     # Block forbidden tools
     if tool_name in BLOCKED_TOOLS:
-        logger.warning(f"Blocked tool access attempt: {tool_name}")
+        logger.warning("Blocked tool access attempt: %s", tool_name)
         return _deny(
             f"[SECURITY] Tool '{tool_name}' is blocked for security. "
             "This is enforced by the platform and cannot be bypassed. "
@@ -89,7 +89,9 @@ def _validate_tool_access(
     for pattern in DANGEROUS_PATTERNS:
         if re.search(pattern, input_str, re.IGNORECASE):
             logger.warning(
-                f"Blocked dangerous pattern in tool input: {pattern} in {tool_name}"
+                "Blocked dangerous pattern in tool input: %s in %s",
+                pattern,
+                tool_name,
             )
             return _deny(
                 "[SECURITY] Input contains a blocked pattern. "
@@ -111,7 +113,9 @@ def _validate_user_isolation(
         # the tool itself via _validate_ephemeral_path.
         path = tool_input.get("path", "") or tool_input.get("file_path", "")
         if path and ".." in path:
-            logger.warning(f"Blocked path traversal attempt: {path} by user {user_id}")
+            logger.warning(
+                "Blocked path traversal attempt: %s by user %s", path, user_id
+            )
             return {
                 "hookSpecificOutput": {
                     "hookEventName": "PreToolUse",
@@ -170,7 +174,7 @@ def create_security_hooks(
                 # Block background task execution first — denied calls
                 # should not consume a subtask slot.
                 if tool_input.get("run_in_background"):
-                    logger.info(f"[SDK] Blocked background Task, user={user_id}")
+                    logger.info("[SDK] Blocked background Task, user=%s", user_id)
                     return cast(
                         SyncHookJSONOutput,
                         _deny(
@@ -181,7 +185,9 @@ def create_security_hooks(
                     )
                 if len(task_tool_use_ids) >= max_subtasks:
                     logger.warning(
-                        f"[SDK] Task limit reached ({max_subtasks}), user={user_id}"
+                        "[SDK] Task limit reached (%d), user=%s",
+                        max_subtasks,
+                        user_id,
                     )
                     return cast(
                         SyncHookJSONOutput,
@@ -212,7 +218,7 @@ def create_security_hooks(
             if tool_name == "Task" and tool_use_id is not None:
                 task_tool_use_ids.add(tool_use_id)
 
-            logger.debug(f"[SDK] Tool start: {tool_name}, user={user_id}")
+            logger.debug("[SDK] Tool start: %s, user=%s", tool_name, user_id)
             return cast(SyncHookJSONOutput, {})
 
         def _release_task_slot(tool_name: str, tool_use_id: str | None) -> None:
@@ -282,8 +288,11 @@ def create_security_hooks(
             tool_name = cast(str, input_data.get("tool_name", ""))
             error = input_data.get("error", "Unknown error")
             logger.warning(
-                f"[SDK] Tool failed: {tool_name}, error={error}, "
-                f"user={user_id}, tool_use_id={tool_use_id}"
+                "[SDK] Tool failed: %s, error=%s, user=%s, tool_use_id=%s",
+                tool_name,
+                str(error).replace("\n", "").replace("\r", ""),
+                user_id,
+                tool_use_id,
             )
 
             _release_task_slot(tool_name, tool_use_id)
@@ -301,16 +310,19 @@ def create_security_hooks(
             This hook provides visibility into when compaction happens.
             """
             _ = context, tool_use_id
-            trigger = input_data.get("trigger", "auto")
             # Sanitize untrusted input before logging to prevent log injection
+            trigger = (
+                str(input_data.get("trigger", "auto"))
+                .replace("\n", "")
+                .replace("\r", "")
+            )
             transcript_path = (
                 str(input_data.get("transcript_path", ""))
                 .replace("\n", "")
                 .replace("\r", "")
             )
             logger.info(
-                "[SDK] Context compaction triggered: %s, user=%s, "
-                "transcript_path=%s",
+                "[SDK] Context compaction triggered: %s, user=%s, transcript_path=%s",
                 trigger,
                 user_id,
                 transcript_path,

autogpt_platform/backend/backend/copilot/sdk/service_helpers_test.py

@@ -0,0 +1,283 @@
+"""Unit tests for extracted service helpers.
+
+Covers ``_is_prompt_too_long``, ``_reduce_context``, ``_iter_sdk_messages``,
+and the ``ReducedContext`` named tuple.
+"""
+
+from __future__ import annotations
+
+import asyncio
+from collections.abc import AsyncGenerator
+from unittest.mock import AsyncMock, patch
+
+import pytest
+
+from .conftest import build_test_transcript as _build_transcript
+from .service import (
+    ReducedContext,
+    _is_prompt_too_long,
+    _iter_sdk_messages,
+    _reduce_context,
+)
+
+# ---------------------------------------------------------------------------
+# _is_prompt_too_long
+# ---------------------------------------------------------------------------
+
+
+class TestIsPromptTooLong:
+    def test_direct_match(self) -> None:
+        assert _is_prompt_too_long(Exception("prompt is too long")) is True
+
+    def test_case_insensitive(self) -> None:
+        assert _is_prompt_too_long(Exception("PROMPT IS TOO LONG")) is True
+
+    def test_no_match(self) -> None:
+        assert _is_prompt_too_long(Exception("network timeout")) is False
+
+    def test_request_too_large(self) -> None:
+        assert _is_prompt_too_long(Exception("request too large for model")) is True
+
+    def test_context_length_exceeded(self) -> None:
+        assert _is_prompt_too_long(Exception("context_length_exceeded")) is True
+
+    def test_max_tokens_exceeded_not_matched(self) -> None:
+        """'max_tokens_exceeded' is intentionally excluded (too broad)."""
+        assert _is_prompt_too_long(Exception("max_tokens_exceeded")) is False
+
+    def test_max_tokens_config_error_no_match(self) -> None:
+        """'max_tokens must be at least 1' should NOT match."""
+        assert _is_prompt_too_long(Exception("max_tokens must be at least 1")) is False
+
+    def test_chained_cause(self) -> None:
+        inner = Exception("prompt is too long")
+        outer = RuntimeError("SDK error")
+        outer.__cause__ = inner
+        assert _is_prompt_too_long(outer) is True
+
+    def test_chained_context(self) -> None:
+        inner = Exception("request too large")
+        outer = RuntimeError("wrapped")
+        outer.__context__ = inner
+        assert _is_prompt_too_long(outer) is True
+
+    def test_deep_chain(self) -> None:
+        bottom = Exception("maximum context length")
+        middle = RuntimeError("middle")
+        middle.__cause__ = bottom
+        top = ValueError("top")
+        top.__cause__ = middle
+        assert _is_prompt_too_long(top) is True
+
+    def test_chain_no_match(self) -> None:
+        inner = Exception("rate limit exceeded")
+        outer = RuntimeError("wrapped")
+        outer.__cause__ = inner
+        assert _is_prompt_too_long(outer) is False
+
+    def test_cycle_detection(self) -> None:
+        """Exception chain with a cycle should not infinite-loop."""
+        a = Exception("error a")
+        b = Exception("error b")
+        a.__cause__ = b
+        b.__cause__ = a  # cycle
+        assert _is_prompt_too_long(a) is False
+
+    def test_all_patterns(self) -> None:
+        patterns = [
+            "prompt is too long",
+            "request too large",
+            "maximum context length",
+            "context_length_exceeded",
+            "input tokens exceed",
+            "input is too long",
+            "content length exceeds",
+        ]
+        for pattern in patterns:
+            assert _is_prompt_too_long(Exception(pattern)) is True, pattern
+
+
+# ---------------------------------------------------------------------------
+# _reduce_context
+# ---------------------------------------------------------------------------
+
+
+class TestReduceContext:
+    @pytest.mark.asyncio
+    async def test_first_retry_compaction_success(self) -> None:
+        transcript = _build_transcript([("user", "hi"), ("assistant", "hello")])
+        compacted = _build_transcript([("user", "hi"), ("assistant", "[summary]")])
+
+        with (
+            patch(
+                "backend.copilot.sdk.service.compact_transcript",
+                new_callable=AsyncMock,
+                return_value=compacted,
+            ),
+            patch(
+                "backend.copilot.sdk.service.validate_transcript",
+                return_value=True,
+            ),
+            patch(
+                "backend.copilot.sdk.service.write_transcript_to_tempfile",
+                return_value="/tmp/resume.jsonl",
+            ),
+        ):
+            ctx = await _reduce_context(
+                transcript, False, "sess-123", "/tmp/cwd", "[test]"
+            )
+
+        assert isinstance(ctx, ReducedContext)
+        assert ctx.use_resume is True
+        assert ctx.resume_file == "/tmp/resume.jsonl"
+        assert ctx.transcript_lost is False
+        assert ctx.tried_compaction is True
+
+    @pytest.mark.asyncio
+    async def test_compaction_fails_drops_transcript(self) -> None:
+        transcript = _build_transcript([("user", "hi"), ("assistant", "hello")])
+
+        with patch(
+            "backend.copilot.sdk.service.compact_transcript",
+            new_callable=AsyncMock,
+            return_value=None,
+        ):
+            ctx = await _reduce_context(
+                transcript, False, "sess-123", "/tmp/cwd", "[test]"
+            )
+
+        assert ctx.use_resume is False
+        assert ctx.resume_file is None
+        assert ctx.transcript_lost is True
+        assert ctx.tried_compaction is True
+
+    @pytest.mark.asyncio
+    async def test_already_tried_compaction_skips(self) -> None:
+        transcript = _build_transcript([("user", "hi"), ("assistant", "hello")])
+
+        ctx = await _reduce_context(transcript, True, "sess-123", "/tmp/cwd", "[test]")
+
+        assert ctx.use_resume is False
+        assert ctx.transcript_lost is True
+        assert ctx.tried_compaction is True
+
+    @pytest.mark.asyncio
+    async def test_empty_transcript_drops(self) -> None:
+        ctx = await _reduce_context("", False, "sess-123", "/tmp/cwd", "[test]")
+
+        assert ctx.use_resume is False
+        assert ctx.transcript_lost is True
+
+    @pytest.mark.asyncio
+    async def test_compaction_returns_same_content_drops(self) -> None:
+        transcript = _build_transcript([("user", "hi"), ("assistant", "hello")])
+
+        with patch(
+            "backend.copilot.sdk.service.compact_transcript",
+            new_callable=AsyncMock,
+            return_value=transcript,  # same content
+        ):
+            ctx = await _reduce_context(
+                transcript, False, "sess-123", "/tmp/cwd", "[test]"
+            )
+
+        assert ctx.transcript_lost is True
+
+    @pytest.mark.asyncio
+    async def test_write_tempfile_fails_drops(self) -> None:
+        transcript = _build_transcript([("user", "hi"), ("assistant", "hello")])
+        compacted = _build_transcript([("user", "hi"), ("assistant", "[summary]")])
+
+        with (
+            patch(
+                "backend.copilot.sdk.service.compact_transcript",
+                new_callable=AsyncMock,
+                return_value=compacted,
+            ),
+            patch(
+                "backend.copilot.sdk.service.validate_transcript",
+                return_value=True,
+            ),
+            patch(
+                "backend.copilot.sdk.service.write_transcript_to_tempfile",
+                return_value=None,
+            ),
+        ):
+            ctx = await _reduce_context(
+                transcript, False, "sess-123", "/tmp/cwd", "[test]"
+            )
+
+        assert ctx.transcript_lost is True
+
+
+# ---------------------------------------------------------------------------
+# _iter_sdk_messages
+# ---------------------------------------------------------------------------
+
+
+class TestIterSdkMessages:
+    @pytest.mark.asyncio
+    async def test_yields_messages(self) -> None:
+        messages = ["msg1", "msg2", "msg3"]
+        client = AsyncMock()
+
+        async def _fake_receive() -> AsyncGenerator[str]:
+            for m in messages:
+                yield m
+
+        client.receive_response = _fake_receive
+        result = [msg async for msg in _iter_sdk_messages(client)]
+        assert result == messages
+
+    @pytest.mark.asyncio
+    async def test_heartbeat_on_timeout(self) -> None:
+        """Yields None when asyncio.wait times out."""
+        client = AsyncMock()
+        received: list = []
+
+        async def _slow_receive() -> AsyncGenerator[str]:
+            await asyncio.sleep(100)  # never completes
+            yield "never"  # pragma: no cover — unreachable, yield makes this an async generator
+
+        client.receive_response = _slow_receive
+
+        with patch("backend.copilot.sdk.service._HEARTBEAT_INTERVAL", 0.01):
+            count = 0
+            async for msg in _iter_sdk_messages(client):
+                received.append(msg)
+                count += 1
+                if count >= 3:
+                    break
+
+        assert all(m is None for m in received)
+
+    @pytest.mark.asyncio
+    async def test_exception_propagates(self) -> None:
+        client = AsyncMock()
+
+        async def _error_receive() -> AsyncGenerator[str]:
+            raise RuntimeError("SDK crash")
+            yield  # pragma: no cover — unreachable, yield makes this an async generator
+
+        client.receive_response = _error_receive
+
+        with pytest.raises(RuntimeError, match="SDK crash"):
+            async for _ in _iter_sdk_messages(client):
+                pass
+
+    @pytest.mark.asyncio
+    async def test_task_cleanup_on_break(self) -> None:
+        """Pending task is cancelled when generator is closed."""
+        client = AsyncMock()
+
+        async def _slow_receive() -> AsyncGenerator[str]:
+            yield "first"
+            await asyncio.sleep(100)
+            yield "second"
+
+        client.receive_response = _slow_receive
+
+        gen = _iter_sdk_messages(client)
+        first = await gen.__anext__()
+        assert first == "first"
+        await gen.aclose()  # should cancel pending task cleanly

autogpt_platform/backend/backend/copilot/sdk/service_test.py

@@ -20,7 +20,7 @@ class _FakeFileInfo:
     size_bytes: int
 
 
-_PATCH_TARGET = "backend.copilot.sdk.service.get_manager"
+_PATCH_TARGET = "backend.copilot.sdk.service.get_workspace_manager"
 
 
 class TestPrepareFileAttachments:
@@ -205,29 +205,6 @@ class TestPromptSupplement:
         ):
             assert "`browser_navigate`" in docs
 
-    def test_baseline_supplement_respects_session_disabled_tools(self):
-        """Session-specific docs should hide disabled tools and include added session tools."""
-        from backend.copilot.model import ChatSession
-        from backend.copilot.prompting import get_baseline_supplement
-        from backend.copilot.session_types import (
-            ChatSessionConfig,
-            ChatSessionStartType,
-        )
-
-        session = ChatSession.new(
-            "user-1",
-            start_type=ChatSessionStartType.AUTOPILOT_NIGHTLY,
-            session_config=ChatSessionConfig(
-                extra_tools=["completion_report"],
-                disabled_tools=["edit_agent"],
-            ),
-        )
-
-        docs = get_baseline_supplement(session)
-
-        assert "`completion_report`" in docs
-        assert "`edit_agent`" not in docs
-
     def test_baseline_supplement_includes_workflows(self):
         """Baseline supplement should include workflow guidance in tool descriptions."""
         from backend.copilot.prompting import get_baseline_supplement
@@ -242,13 +219,15 @@ class TestPromptSupplement:
     def test_baseline_supplement_completeness(self):
         """All available tools from TOOL_REGISTRY should appear in baseline supplement."""
         from backend.copilot.prompting import get_baseline_supplement
-        from backend.copilot.tools import iter_available_tools
+        from backend.copilot.tools import TOOL_REGISTRY
 
         docs = get_baseline_supplement()
 
         # Verify each available registered tool is documented
-        # (matches _generate_tool_documentation which filters with iter_available_tools)
-        for tool_name, _ in iter_available_tools():
+        # (matches _generate_tool_documentation which filters by is_available)
+        for tool_name, tool in TOOL_REGISTRY.items():
+            if not tool.is_available:
+                continue
             assert (
                 f"`{tool_name}`" in docs
             ), f"Tool '{tool_name}' missing from baseline supplement"
@@ -298,12 +277,14 @@ class TestPromptSupplement:
     def test_baseline_supplement_no_duplicate_tools(self):
         """No tool should appear multiple times in baseline supplement."""
         from backend.copilot.prompting import get_baseline_supplement
-        from backend.copilot.tools import iter_available_tools
+        from backend.copilot.tools import TOOL_REGISTRY
 
         docs = get_baseline_supplement()
 
         # Count occurrences of each available tool in the entire supplement
-        for tool_name, _ in iter_available_tools():
+        for tool_name, tool in TOOL_REGISTRY.items():
+            if not tool.is_available:
+                continue
             # Count how many times this tool appears as a bullet point
             count = docs.count(f"- **`{tool_name}`**")
             assert count == 1, f"Tool '{tool_name}' appears {count} times (should be 1)"

autogpt_platform/backend/backend/copilot/sdk/tool_adapter.py

@@ -32,7 +32,7 @@ from backend.copilot.sdk.file_ref import (
     expand_file_refs_in_args,
     read_file_bytes,
 )
-from backend.copilot.tools import iter_available_tools
+from backend.copilot.tools import TOOL_REGISTRY
 from backend.copilot.tools.base import BaseTool
 from backend.util.truncate import truncate
 
@@ -234,7 +234,9 @@ def create_tool_handler(base_tool: BaseTool):
         try:
             return await _execute_tool_sync(base_tool, user_id, session, args)
         except Exception as e:
-            logger.error(f"Error executing tool {base_tool.name}: {e}", exc_info=True)
+            logger.error(
+                "Error executing tool %s: %s", base_tool.name, e, exc_info=True
+            )
             return _mcp_error(f"Failed to execute {base_tool.name}: {e}")
 
     return tool_handler
@@ -338,11 +340,7 @@ def _text_from_mcp_result(result: dict[str, Any]) -> str:
     )
 
 
-def create_copilot_mcp_server(
-    session: ChatSession,
-    *,
-    use_e2b: bool = False,
-):
+def create_copilot_mcp_server(*, use_e2b: bool = False):
     """Create an in-process MCP server configuration for CoPilot tools.
 
     When *use_e2b* is True, five additional MCP file tools are registered
@@ -351,7 +349,7 @@ def create_copilot_mcp_server(
     :func:`get_sdk_disallowed_tools`.
     """
 
-    def _truncating(fn, tool_name: str):
+    def _truncating(fn, tool_name: str, input_schema: dict[str, Any] | None = None):
         """Wrap a tool handler so its response is truncated to stay under the
         SDK's 10 MB JSON buffer, and stash the (truncated) output for the
         response adapter before the SDK can apply its own head-truncation.
@@ -365,7 +363,9 @@ def create_copilot_mcp_server(
             user_id, session = get_execution_context()
             if session is not None:
                 try:
-                    args = await expand_file_refs_in_args(args, user_id, session)
+                    args = await expand_file_refs_in_args(
+                        args, user_id, session, input_schema=input_schema
+                    )
                 except FileRefExpansionError as exc:
                     return _mcp_error(
                         f"@@agptfile: reference could not be resolved: {exc}. "
@@ -391,13 +391,14 @@ def create_copilot_mcp_server(
 
     sdk_tools = []
 
-    for tool_name, base_tool in iter_available_tools(session):
+    for tool_name, base_tool in TOOL_REGISTRY.items():
         handler = create_tool_handler(base_tool)
+        schema = _build_input_schema(base_tool)
         decorated = tool(
             tool_name,
             base_tool.description,
-            _build_input_schema(base_tool),
-        )(_truncating(handler, tool_name))
+            schema,
+        )(_truncating(handler, tool_name, input_schema=schema))
         sdk_tools.append(decorated)
 
     # E2B file tools replace SDK built-in Read/Write/Edit/Glob/Grep.
@@ -479,30 +480,25 @@ DANGEROUS_PATTERNS = [
     r"subprocess",
 ]
 
+# Static tool name list for the non-E2B case (backward compatibility).
+COPILOT_TOOL_NAMES = [
+    *[f"{MCP_TOOL_PREFIX}{name}" for name in TOOL_REGISTRY.keys()],
+    f"{MCP_TOOL_PREFIX}{_READ_TOOL_NAME}",
+    *_SDK_BUILTIN_TOOLS,
+]
 
-def get_copilot_tool_names(
-    session: ChatSession,
-    *,
-    use_e2b: bool = False,
-) -> list[str]:
+
+def get_copilot_tool_names(*, use_e2b: bool = False) -> list[str]:
     """Build the ``allowed_tools`` list for :class:`ClaudeAgentOptions`.
 
     When *use_e2b* is True the SDK built-in file tools are replaced by MCP
     equivalents that route to the E2B sandbox.
     """
-    tool_names = [
-        f"{MCP_TOOL_PREFIX}{name}" for name, _ in iter_available_tools(session)
-    ]
-
     if not use_e2b:
-        return [
-            *tool_names,
-            f"{MCP_TOOL_PREFIX}{_READ_TOOL_NAME}",
-            *_SDK_BUILTIN_TOOLS,
-        ]
+        return list(COPILOT_TOOL_NAMES)
 
     return [
-        *tool_names,
+        *[f"{MCP_TOOL_PREFIX}{name}" for name in TOOL_REGISTRY.keys()],
         f"{MCP_TOOL_PREFIX}{_READ_TOOL_NAME}",
         *[f"{MCP_TOOL_PREFIX}{name}" for name in E2B_FILE_TOOL_NAMES],
         *_SDK_BUILTIN_ALWAYS,

autogpt_platform/backend/backend/copilot/sdk/tool_adapter_test.py

@@ -3,14 +3,11 @@
 import pytest
 
 from backend.copilot.context import get_sdk_cwd
-from backend.copilot.model import ChatSession
-from backend.copilot.session_types import ChatSessionConfig, ChatSessionStartType
 from backend.util.truncate import truncate
 
 from .tool_adapter import (
     _MCP_MAX_CHARS,
     _text_from_mcp_result,
-    get_copilot_tool_names,
     pop_pending_tool_output,
     set_execution_context,
     stash_pending_tool_output,
@@ -171,20 +168,3 @@ class TestTruncationAndStashIntegration:
         text = _text_from_mcp_result(truncated)
         assert len(text) < len(big_text)
         assert len(str(truncated)) <= _MCP_MAX_CHARS
-
-
-class TestSessionToolFiltering:
-    def test_disabled_tools_are_removed_from_sdk_allowed_tools(self):
-        session = ChatSession.new(
-            "user-1",
-            start_type=ChatSessionStartType.AUTOPILOT_NIGHTLY,
-            session_config=ChatSessionConfig(
-                extra_tools=["completion_report"],
-                disabled_tools=["edit_agent"],
-            ),
-        )
-
-        tool_names = get_copilot_tool_names(session)
-
-        assert "mcp__copilot__completion_report" in tool_names
-        assert "mcp__copilot__edit_agent" not in tool_names

autogpt_platform/backend/backend/copilot/sdk/transcript.py

@@ -10,6 +10,9 @@ Storage is handled via ``WorkspaceStorageBackend`` (GCS in prod, local
 filesystem for self-hosted) — no DB column needed.
 """
 
+from __future__ import annotations
+
+import asyncio
 import logging
 import os
 import re
@@ -17,8 +20,12 @@ import shutil
 import time
 from dataclasses import dataclass
 from pathlib import Path
+from uuid import uuid4
 
 from backend.util import json
+from backend.util.clients import get_openai_client
+from backend.util.prompt import CompressResult, compress_context
+from backend.util.workspace_storage import GCSWorkspaceStorage, get_workspace_storage
 
 logger = logging.getLogger(__name__)
 
@@ -99,7 +106,14 @@ def strip_progress_entries(content: str) -> str:
             continue
         parent = entry.get("parentUuid", "")
         original_parent = parent
-        while parent in stripped_uuids:
+        # seen_parents is local per-entry (not shared across iterations) so
+        # it can only detect cycles within a single ancestry walk, not across
+        # entries.  This is intentional: each entry's parent chain is
+        # independent, and reusing a global set would incorrectly short-circuit
+        # valid re-use of the same UUID as a parent in different subtrees.
+        seen_parents: set[str] = set()
+        while parent in stripped_uuids and parent not in seen_parents:
+            seen_parents.add(parent)
             parent = uuid_to_parent.get(parent, "")
         if parent != original_parent:
             entry["parentUuid"] = parent
@@ -327,7 +341,7 @@ def write_transcript_to_tempfile(
     # Validate cwd is under the expected sandbox prefix (CodeQL sanitizer).
     real_cwd = os.path.realpath(cwd)
     if not real_cwd.startswith(_SAFE_CWD_PREFIX):
-        logger.warning(f"[Transcript] cwd outside sandbox: {cwd}")
+        logger.warning("[Transcript] cwd outside sandbox: %s", cwd)
         return None
 
     try:
@@ -337,17 +351,17 @@ def write_transcript_to_tempfile(
             os.path.join(real_cwd, f"transcript-{safe_id}.jsonl")
         )
         if not jsonl_path.startswith(real_cwd):
-            logger.warning(f"[Transcript] Path escaped cwd: {jsonl_path}")
+            logger.warning("[Transcript] Path escaped cwd: %s", jsonl_path)
             return None
 
         with open(jsonl_path, "w") as f:
             f.write(transcript_content)
 
-        logger.info(f"[Transcript] Wrote resume file: {jsonl_path}")
+        logger.info("[Transcript] Wrote resume file: %s", jsonl_path)
         return jsonl_path
 
     except OSError as e:
-        logger.warning(f"[Transcript] Failed to write resume file: {e}")
+        logger.warning("[Transcript] Failed to write resume file: %s", e)
         return None
 
 
@@ -408,8 +422,6 @@ def _meta_storage_path_parts(user_id: str, session_id: str) -> tuple[str, str, s
 
 def _build_path_from_parts(parts: tuple[str, str, str], backend: object) -> str:
     """Build a full storage path from (workspace_id, file_id, filename) parts."""
-    from backend.util.workspace_storage import GCSWorkspaceStorage
-
     wid, fid, fname = parts
     if isinstance(backend, GCSWorkspaceStorage):
         blob = f"workspaces/{wid}/{fid}/{fname}"
@@ -448,17 +460,15 @@ async def upload_transcript(
         content: Complete JSONL transcript (from TranscriptBuilder).
         message_count: ``len(session.messages)`` at upload time.
     """
-    from backend.util.workspace_storage import get_workspace_storage
-
     # Strip metadata entries (progress, file-history-snapshot, etc.)
     # Note: SDK-built transcripts shouldn't have these, but strip for safety
     stripped = strip_progress_entries(content)
     if not validate_transcript(stripped):
         # Log entry types for debugging — helps identify why validation failed
-        entry_types: list[str] = []
-        for line in stripped.strip().split("\n"):
-            entry = json.loads(line, fallback={"type": "INVALID_JSON"})
-            entry_types.append(entry.get("type", "?"))
+        entry_types = [
+            json.loads(line, fallback={"type": "INVALID_JSON"}).get("type", "?")
+            for line in stripped.strip().split("\n")
+        ]
         logger.warning(
             "%s Skipping upload — stripped content not valid "
             "(types=%s, stripped_len=%d, raw_len=%d)",
@@ -494,11 +504,14 @@ async def upload_transcript(
             content=json.dumps(meta).encode("utf-8"),
         )
     except Exception as e:
-        logger.warning(f"{log_prefix} Failed to write metadata: {e}")
+        logger.warning("%s Failed to write metadata: %s", log_prefix, e)
 
     logger.info(
-        f"{log_prefix} Uploaded {len(encoded)}B "
-        f"(stripped from {len(content)}B, msg_count={message_count})"
+        "%s Uploaded %dB (stripped from %dB, msg_count=%d)",
+        log_prefix,
+        len(encoded),
+        len(content),
+        message_count,
     )
 
 
@@ -512,8 +525,6 @@ async def download_transcript(
     Returns a ``TranscriptDownload`` with the JSONL content and the
     ``message_count`` watermark from the upload, or ``None`` if not found.
     """
-    from backend.util.workspace_storage import get_workspace_storage
-
     storage = await get_workspace_storage()
     path = _build_storage_path(user_id, session_id, storage)
 
@@ -521,10 +532,10 @@ async def download_transcript(
         data = await storage.retrieve(path)
         content = data.decode("utf-8")
     except FileNotFoundError:
-        logger.debug(f"{log_prefix} No transcript in storage")
+        logger.debug("%s No transcript in storage", log_prefix)
         return None
     except Exception as e:
-        logger.warning(f"{log_prefix} Failed to download transcript: {e}")
+        logger.warning("%s Failed to download transcript: %s", log_prefix, e)
         return None
 
     # Try to load metadata (best-effort — old transcripts won't have it)
@@ -536,10 +547,14 @@ async def download_transcript(
         meta = json.loads(meta_data.decode("utf-8"), fallback={})
         message_count = meta.get("message_count", 0)
         uploaded_at = meta.get("uploaded_at", 0.0)
-    except (FileNotFoundError, Exception):
+    except FileNotFoundError:
         pass  # No metadata — treat as unknown (msg_count=0 → always fill gap)
+    except Exception as e:
+        logger.debug("%s Failed to load transcript metadata: %s", log_prefix, e)
 
-    logger.info(f"{log_prefix} Downloaded {len(content)}B (msg_count={message_count})")
+    logger.info(
+        "%s Downloaded %dB (msg_count=%d)", log_prefix, len(content), message_count
+    )
     return TranscriptDownload(
         content=content,
         message_count=message_count,
@@ -553,8 +568,6 @@ async def delete_transcript(user_id: str, session_id: str) -> None:
     Removes both the ``.jsonl`` transcript and the companion ``.meta.json``
     so stale ``message_count`` watermarks cannot corrupt gap-fill logic.
     """
-    from backend.util.workspace_storage import get_workspace_storage
-
     storage = await get_workspace_storage()
     path = _build_storage_path(user_id, session_id, storage)
 
@@ -571,3 +584,280 @@ async def delete_transcript(user_id: str, session_id: str) -> None:
         logger.info("[Transcript] Deleted metadata for session %s", session_id)
     except Exception as e:
         logger.warning("[Transcript] Failed to delete metadata: %s", e)
+
+
+# ---------------------------------------------------------------------------
+# Transcript compaction — LLM summarization for prompt-too-long recovery
+# ---------------------------------------------------------------------------
+
+# JSONL protocol values used in transcript serialization.
+STOP_REASON_END_TURN = "end_turn"
+COMPACT_MSG_ID_PREFIX = "msg_compact_"
+ENTRY_TYPE_MESSAGE = "message"
+
+
+def _flatten_assistant_content(blocks: list) -> str:
+    """Flatten assistant content blocks into a single plain-text string.
+
+    Structured ``tool_use`` blocks are converted to ``[tool_use: name]``
+    placeholders.  This is intentional: ``compress_context`` requires plain
+    text for token counting and LLM summarization.  The structural loss is
+    acceptable because compaction only runs when the original transcript was
+    already too large for the model — a summarized plain-text version is
+    better than no context at all.
+    """
+    parts: list[str] = []
+    for block in blocks:
+        if isinstance(block, dict):
+            btype = block.get("type", "")
+            if btype == "text":
+                parts.append(block.get("text", ""))
+            elif btype == "tool_use":
+                parts.append(f"[tool_use: {block.get('name', '?')}]")
+            else:
+                # Preserve non-text blocks (e.g. image) as placeholders.
+                # Use __prefix__ to distinguish from literal user text.
+                parts.append(f"[__{btype}__]")
+        elif isinstance(block, str):
+            parts.append(block)
+    return "\n".join(parts) if parts else ""
+
+
+def _flatten_tool_result_content(blocks: list) -> str:
+    """Flatten tool_result and other content blocks into plain text.
+
+    Handles nested tool_result structures, text blocks, and raw strings.
+    Uses ``json.dumps`` as fallback for dict blocks without a ``text`` key
+    or where ``text`` is ``None``.
+
+    Like ``_flatten_assistant_content``, structured blocks (images, nested
+    tool results) are reduced to text representations for compression.
+    """
+    str_parts: list[str] = []
+    for block in blocks:
+        if isinstance(block, dict) and block.get("type") == "tool_result":
+            inner = block.get("content") or ""
+            if isinstance(inner, list):
+                for sub in inner:
+                    if isinstance(sub, dict):
+                        sub_type = sub.get("type")
+                        if sub_type in ("image", "document"):
+                            # Avoid serializing base64 binary data into
+                            # the compaction input — use a placeholder.
+                            str_parts.append(f"[__{sub_type}__]")
+                        elif sub_type == "text" or sub.get("text") is not None:
+                            str_parts.append(str(sub.get("text", "")))
+                        else:
+                            str_parts.append(json.dumps(sub))
+                    else:
+                        str_parts.append(str(sub))
+            else:
+                str_parts.append(str(inner))
+        elif isinstance(block, dict) and block.get("type") == "text":
+            str_parts.append(str(block.get("text", "")))
+        elif isinstance(block, dict):
+            # Preserve non-text/non-tool_result blocks (e.g. image) as placeholders.
+            # Use __prefix__ to distinguish from literal user text.
+            btype = block.get("type", "unknown")
+            str_parts.append(f"[__{btype}__]")
+        elif isinstance(block, str):
+            str_parts.append(block)
+    return "\n".join(str_parts) if str_parts else ""
+
+
+def _transcript_to_messages(content: str) -> list[dict]:
+    """Convert JSONL transcript entries to plain message dicts for compression.
+
+    Parses each line of the JSONL *content*, skips strippable metadata entries
+    (progress, file-history-snapshot, etc.), and extracts the ``role`` and
+    flattened ``content`` from the ``message`` field of each remaining entry.
+
+    Structured content blocks (``tool_use``, ``tool_result``, images) are
+    flattened to plain text via ``_flatten_assistant_content`` and
+    ``_flatten_tool_result_content`` so that ``compress_context`` can
+    perform token counting and LLM summarization on uniform strings.
+
+    Returns:
+        A list of ``{"role": str, "content": str}`` dicts suitable for
+        ``compress_context``.
+    """
+    messages: list[dict] = []
+    for line in content.strip().split("\n"):
+        if not line.strip():
+            continue
+        entry = json.loads(line, fallback=None)
+        if not isinstance(entry, dict):
+            continue
+        if entry.get("type", "") in STRIPPABLE_TYPES and not entry.get(
+            "isCompactSummary"
+        ):
+            continue
+        msg = entry.get("message", {})
+        role = msg.get("role", "")
+        if not role:
+            continue
+        msg_dict: dict = {"role": role}
+        raw_content = msg.get("content")
+        if role == "assistant" and isinstance(raw_content, list):
+            msg_dict["content"] = _flatten_assistant_content(raw_content)
+        elif isinstance(raw_content, list):
+            msg_dict["content"] = _flatten_tool_result_content(raw_content)
+        else:
+            msg_dict["content"] = raw_content or ""
+        messages.append(msg_dict)
+    return messages
+
+
+def _messages_to_transcript(messages: list[dict]) -> str:
+    """Convert compressed message dicts back to JSONL transcript format.
+
+    Rebuilds a minimal JSONL transcript from the ``{"role", "content"}``
+    dicts returned by ``compress_context``.  Each message becomes one JSONL
+    line with a fresh ``uuid`` / ``parentUuid`` chain so the CLI's
+    ``--resume`` flag can reconstruct a valid conversation tree.
+
+    Assistant messages are wrapped in the full ``message`` envelope
+    (``id``, ``model``, ``stop_reason``, structured ``content`` blocks)
+    that the CLI expects.  User messages use the simpler ``{role, content}``
+    form.
+
+    Returns:
+        A newline-terminated JSONL string, or an empty string if *messages*
+        is empty.
+    """
+    lines: list[str] = []
+    last_uuid: str = ""  # root entry uses empty string, not null
+    for msg in messages:
+        role = msg.get("role", "user")
+        entry_type = "assistant" if role == "assistant" else "user"
+        uid = str(uuid4())
+        content = msg.get("content", "")
+        if role == "assistant":
+            message: dict = {
+                "role": "assistant",
+                "model": "",
+                "id": f"{COMPACT_MSG_ID_PREFIX}{uuid4().hex[:24]}",
+                "type": ENTRY_TYPE_MESSAGE,
+                "content": [{"type": "text", "text": content}] if content else [],
+                "stop_reason": STOP_REASON_END_TURN,
+                "stop_sequence": None,
+            }
+        else:
+            message = {"role": role, "content": content}
+        entry = {
+            "type": entry_type,
+            "uuid": uid,
+            "parentUuid": last_uuid,
+            "message": message,
+        }
+        lines.append(json.dumps(entry, separators=(",", ":")))
+        last_uuid = uid
+    return "\n".join(lines) + "\n" if lines else ""
+
+
+_COMPACTION_TIMEOUT_SECONDS = 60
+_TRUNCATION_TIMEOUT_SECONDS = 30
+
+
+async def _run_compression(
+    messages: list[dict],
+    model: str,
+    log_prefix: str,
+) -> CompressResult:
+    """Run LLM-based compression with truncation fallback.
+
+    Uses the shared OpenAI client from ``get_openai_client()``.
+    If no client is configured or the LLM call fails, falls back to
+    truncation-based compression which drops older messages without
+    summarization.
+
+    A 60-second timeout prevents a hung LLM call from blocking the
+    retry path indefinitely.  The truncation fallback also has a
+    30-second timeout to guard against slow tokenization on very large
+    transcripts.
+    """
+    client = get_openai_client()
+    if client is None:
+        logger.warning("%s No OpenAI client configured, using truncation", log_prefix)
+        return await asyncio.wait_for(
+            compress_context(messages=messages, model=model, client=None),
+            timeout=_TRUNCATION_TIMEOUT_SECONDS,
+        )
+    try:
+        return await asyncio.wait_for(
+            compress_context(messages=messages, model=model, client=client),
+            timeout=_COMPACTION_TIMEOUT_SECONDS,
+        )
+    except Exception as e:
+        logger.warning("%s LLM compaction failed, using truncation: %s", log_prefix, e)
+        return await asyncio.wait_for(
+            compress_context(messages=messages, model=model, client=None),
+            timeout=_TRUNCATION_TIMEOUT_SECONDS,
+        )
+
+
+async def compact_transcript(
+    content: str,
+    *,
+    model: str,
+    log_prefix: str = "[Transcript]",
+) -> str | None:
+    """Compact an oversized JSONL transcript using LLM summarization.
+
+    Converts transcript entries to plain messages, runs ``compress_context``
+    (the same compressor used for pre-query history), and rebuilds JSONL.
+
+    Structured content (``tool_use`` blocks, ``tool_result`` nesting, images)
+    is flattened to plain text for compression.  This matches the fidelity of
+    the Plan C (DB compression) fallback path, where
+    ``_format_conversation_context`` similarly renders tool calls as
+    ``You called tool: name(args)`` and results as ``Tool result: ...``.
+    Neither path preserves structured API content blocks — the compacted
+    context serves as text history for the LLM, which creates proper
+    structured tool calls going forward.
+
+    Images are per-turn attachments loaded from workspace storage by file ID
+    (via ``_prepare_file_attachments``), not part of the conversation history.
+    They are re-attached each turn and are unaffected by compaction.
+
+    Returns the compacted JSONL string, or ``None`` on failure.
+
+    See also:
+        ``_compress_messages`` in ``service.py`` — compresses ``ChatMessage``
+        lists for pre-query DB history.  Both share ``compress_context()``
+        but operate on different input formats (JSONL transcript entries
+        here vs. ChatMessage dicts there).
+    """
+    messages = _transcript_to_messages(content)
+    if len(messages) < 2:
+        logger.warning("%s Too few messages to compact (%d)", log_prefix, len(messages))
+        return None
+    try:
+        result = await _run_compression(messages, model, log_prefix)
+        if not result.was_compacted:
+            # Compressor says it's within budget, but the SDK rejected it.
+            # Return None so the caller falls through to DB fallback.
+            logger.warning(
+                "%s Compressor reports within budget but SDK rejected — "
+                "signalling failure",
+                log_prefix,
+            )
+            return None
+        logger.info(
+            "%s Compacted transcript: %d->%d tokens (%d summarized, %d dropped)",
+            log_prefix,
+            result.original_token_count,
+            result.token_count,
+            result.messages_summarized,
+            result.messages_dropped,
+        )
+        compacted = _messages_to_transcript(result.messages)
+        if not validate_transcript(compacted):
+            logger.warning("%s Compacted transcript failed validation", log_prefix)
+            return None
+        return compacted
+    except Exception as e:
+        logger.error(
+            "%s Transcript compaction failed: %s", log_prefix, e, exc_info=True
+        )
+        return None

autogpt_platform/backend/backend/copilot/sdk/transcript_builder.py

@@ -68,7 +68,7 @@ class TranscriptBuilder:
             type=entry_type,
             uuid=data.get("uuid") or str(uuid4()),
             parentUuid=data.get("parentUuid"),
-            isCompactSummary=data.get("isCompactSummary") or None,
+            isCompactSummary=data.get("isCompactSummary"),
             message=data.get("message", {}),
         )
 

autogpt_platform/backend/backend/copilot/sdk/transcript_test.py

@@ -1,7 +1,7 @@
 """Unit tests for JSONL transcript management utilities."""
 
 import os
-from unittest.mock import AsyncMock, patch
+from unittest.mock import AsyncMock, MagicMock, patch
 
 import pytest
 
@@ -382,7 +382,7 @@ class TestDeleteTranscript:
         mock_storage.delete = AsyncMock()
 
         with patch(
-            "backend.util.workspace_storage.get_workspace_storage",
+            "backend.copilot.sdk.transcript.get_workspace_storage",
             new_callable=AsyncMock,
             return_value=mock_storage,
         ):
@@ -402,7 +402,7 @@ class TestDeleteTranscript:
         )
 
         with patch(
-            "backend.util.workspace_storage.get_workspace_storage",
+            "backend.copilot.sdk.transcript.get_workspace_storage",
             new_callable=AsyncMock,
             return_value=mock_storage,
         ):
@@ -420,7 +420,7 @@ class TestDeleteTranscript:
         )
 
         with patch(
-            "backend.util.workspace_storage.get_workspace_storage",
+            "backend.copilot.sdk.transcript.get_workspace_storage",
             new_callable=AsyncMock,
             return_value=mock_storage,
         ):
@@ -897,3 +897,134 @@ class TestCompactionFlowIntegration:
         output2 = builder2.to_jsonl()
         lines2 = [json.loads(line) for line in output2.strip().split("\n")]
         assert lines2[-1]["parentUuid"] == "a2"
+
+
+# ---------------------------------------------------------------------------
+# _run_compression (direct tests for the 3 code paths)
+# ---------------------------------------------------------------------------
+
+
+class TestRunCompression:
+    """Direct tests for ``_run_compression`` covering all 3 code paths.
+
+    Paths:
+    (a) No OpenAI client configured → truncation fallback immediately.
+    (b) LLM success → returns LLM-compressed result.
+    (c) LLM call raises → truncation fallback.
+    """
+
+    def _make_compress_result(self, was_compacted: bool, msgs=None):
+        """Build a minimal CompressResult-like object."""
+        from types import SimpleNamespace
+
+        return SimpleNamespace(
+            was_compacted=was_compacted,
+            messages=msgs or [{"role": "user", "content": "summary"}],
+            original_token_count=500,
+            token_count=100 if was_compacted else 500,
+            messages_summarized=2 if was_compacted else 0,
+            messages_dropped=0,
+        )
+
+    @pytest.mark.asyncio
+    async def test_no_client_uses_truncation(self):
+        """Path (a): ``get_openai_client()`` returns None → truncation only."""
+        from .transcript import _run_compression
+
+        truncation_result = self._make_compress_result(
+            True, [{"role": "user", "content": "truncated"}]
+        )
+
+        with (
+            patch(
+                "backend.copilot.sdk.transcript.get_openai_client",
+                return_value=None,
+            ),
+            patch(
+                "backend.copilot.sdk.transcript.compress_context",
+                new_callable=AsyncMock,
+                return_value=truncation_result,
+            ) as mock_compress,
+        ):
+            result = await _run_compression(
+                [{"role": "user", "content": "hello"}],
+                model="test-model",
+                log_prefix="[test]",
+            )
+
+        # compress_context called with client=None (truncation mode)
+        call_kwargs = mock_compress.call_args
+        assert (
+            call_kwargs.kwargs.get("client") is None
+            or (call_kwargs.args and call_kwargs.args[2] is None)
+            or mock_compress.call_args[1].get("client") is None
+        )
+        assert result is truncation_result
+
+    @pytest.mark.asyncio
+    async def test_llm_success_returns_llm_result(self):
+        """Path (b): ``get_openai_client()`` returns a client → LLM compresses."""
+        from .transcript import _run_compression
+
+        llm_result = self._make_compress_result(
+            True, [{"role": "user", "content": "LLM summary"}]
+        )
+        mock_client = MagicMock()
+
+        with (
+            patch(
+                "backend.copilot.sdk.transcript.get_openai_client",
+                return_value=mock_client,
+            ),
+            patch(
+                "backend.copilot.sdk.transcript.compress_context",
+                new_callable=AsyncMock,
+                return_value=llm_result,
+            ) as mock_compress,
+        ):
+            result = await _run_compression(
+                [{"role": "user", "content": "long conversation"}],
+                model="test-model",
+                log_prefix="[test]",
+            )
+
+        # compress_context called with the real client
+        assert mock_compress.called
+        assert result is llm_result
+
+    @pytest.mark.asyncio
+    async def test_llm_failure_falls_back_to_truncation(self):
+        """Path (c): LLM call raises → truncation fallback used instead."""
+        from .transcript import _run_compression
+
+        truncation_result = self._make_compress_result(
+            True, [{"role": "user", "content": "truncated fallback"}]
+        )
+        mock_client = MagicMock()
+        call_count = [0]
+
+        async def _compress_side_effect(**kwargs):
+            call_count[0] += 1
+            if kwargs.get("client") is not None:
+                raise RuntimeError("LLM timeout")
+            return truncation_result
+
+        with (
+            patch(
+                "backend.copilot.sdk.transcript.get_openai_client",
+                return_value=mock_client,
+            ),
+            patch(
+                "backend.copilot.sdk.transcript.compress_context",
+                side_effect=_compress_side_effect,
+            ),
+        ):
+            result = await _run_compression(
+                [{"role": "user", "content": "long conversation"}],
+                model="test-model",
+                log_prefix="[test]",
+            )
+
+        # compress_context called twice: once for LLM (raises), once for truncation
+        assert call_count[0] == 2
+        assert result is truncation_result

autogpt_platform/backend/backend/copilot/service.py

@@ -22,7 +22,7 @@ from backend.util.exceptions import NotAuthorizedError, NotFoundError
 from backend.util.settings import AppEnvironment, Settings
 
 from .config import ChatConfig
-from .model import ChatSession, ChatSessionInfo, get_chat_session, upsert_chat_session
+from .model import ChatSessionInfo, get_chat_session, upsert_chat_session
 
 logger = logging.getLogger(__name__)
 
@@ -64,13 +64,7 @@ def _is_langfuse_configured() -> bool:
     )
 
 
-async def _get_system_prompt_template(
-    context: str,
-    *,
-    prompt_name: str | None = None,
-    fallback_prompt: str | None = None,
-    template_vars: dict[str, str] | None = None,
-) -> str:
+async def _get_system_prompt_template(context: str) -> str:
     """Get the system prompt, trying Langfuse first with fallback to default.
 
     Args:
@@ -79,11 +73,6 @@ async def _get_system_prompt_template(
     Returns:
         The compiled system prompt string.
     """
-    resolved_prompt_name = prompt_name or config.langfuse_prompt_name
-    resolved_template_vars = {
-        "users_information": context,
-        **(template_vars or {}),
-    }
     if _is_langfuse_configured():
         try:
             # Use asyncio.to_thread to avoid blocking the event loop
@@ -96,16 +85,16 @@ async def _get_system_prompt_template(
             )
             prompt = await asyncio.to_thread(
                 langfuse.get_prompt,
-                resolved_prompt_name,
+                config.langfuse_prompt_name,
                 label=label,
                 cache_ttl_seconds=config.langfuse_prompt_cache_ttl,
             )
-            return prompt.compile(**resolved_template_vars)
+            return prompt.compile(users_information=context)
         except Exception as e:
             logger.warning(f"Failed to fetch prompt from Langfuse, using default: {e}")
 
     # Fallback to default prompt
-    return (fallback_prompt or DEFAULT_SYSTEM_PROMPT).format(**resolved_template_vars)
+    return DEFAULT_SYSTEM_PROMPT.format(users_information=context)
 
 
 async def _build_system_prompt(
@@ -142,21 +131,6 @@ async def _build_system_prompt(
     return compiled, understanding
 
 
-async def _resolve_system_prompt(
-    session: ChatSession,
-    user_id: str | None,
-    *,
-    has_conversation_history: bool = False,
-) -> tuple[str, Any]:
-    override = session.session_config.system_prompt_override
-    if override:
-        return override, None
-    return await _build_system_prompt(
-        user_id,
-        has_conversation_history=has_conversation_history,
-    )
-
-
 async def _generate_session_title(
     message: str,
     user_id: str | None = None,

autogpt_platform/backend/backend/copilot/session_types.py

@@ -1,60 +0,0 @@
-from __future__ import annotations
-
-from datetime import datetime
-from enum import Enum
-
-from pydantic import BaseModel, Field, model_validator
-
-
-class ChatSessionStartType(str, Enum):
-    MANUAL = "MANUAL"
-    AUTOPILOT_NIGHTLY = "AUTOPILOT_NIGHTLY"
-    AUTOPILOT_CALLBACK = "AUTOPILOT_CALLBACK"
-    AUTOPILOT_INVITE_CTA = "AUTOPILOT_INVITE_CTA"
-
-
-class ChatSessionConfig(BaseModel):
-    system_prompt_override: str | None = None
-    initial_user_message: str | None = None
-    initial_assistant_message: str | None = None
-    extra_tools: list[str] = Field(default_factory=list)
-    disabled_tools: list[str] = Field(default_factory=list)
-
-    def allows_tool(self, tool_name: str) -> bool:
-        return tool_name in self.extra_tools
-
-    def disables_tool(self, tool_name: str) -> bool:
-        return tool_name in self.disabled_tools
-
-
-class CompletionReportInput(BaseModel):
-    thoughts: str
-    should_notify_user: bool
-    email_title: str | None = None
-    email_body: str | None = None
-    callback_session_message: str | None = None
-    approval_summary: str | None = None
-
-    @model_validator(mode="after")
-    def validate_notification_fields(self) -> "CompletionReportInput":
-        if self.should_notify_user:
-            required_fields = {
-                "email_title": self.email_title,
-                "email_body": self.email_body,
-                "callback_session_message": self.callback_session_message,
-            }
-            missing = [
-                field_name for field_name, value in required_fields.items() if not value
-            ]
-            if missing:
-                raise ValueError(
-                    "Missing required notification fields: " + ", ".join(missing)
-                )
-        return self
-
-
-class StoredCompletionReport(CompletionReportInput):
-    has_pending_approvals: bool
-    pending_approval_count: int
-    pending_approval_graph_exec_id: str | None = None
-    saved_at: datetime

autogpt_platform/backend/backend/copilot/stream_registry.py

@@ -17,12 +17,11 @@ Subscribers:
 import asyncio
 import logging
 import time
-from collections.abc import Awaitable
+from dataclasses import dataclass, field
 from datetime import datetime, timezone
-from typing import Any, Literal, cast
+from typing import Any, Literal
 
 import orjson
-from pydantic import BaseModel, ConfigDict, Field
 
 from backend.api.model import CopilotCompletionPayload
 from backend.data.notification_bus import (
@@ -56,12 +55,6 @@ _listener_sessions: dict[int, tuple[str, asyncio.Task]] = {}
 # Timeout for putting chunks into subscriber queues (seconds)
 # If the queue is full and doesn't drain within this time, send an overflow error
 QUEUE_PUT_TIMEOUT = 5.0
-SESSION_LOOKUP_RETRY_SECONDS = 0.05
-STREAM_REPLAY_COUNT = 1000
-STREAM_XREAD_BLOCK_MS = 5000
-STREAM_XREAD_COUNT = 100
-STALE_SESSION_BUFFER_SECONDS = 300
-UNSUBSCRIBE_TIMEOUT_SECONDS = 5.0
 
 # Lua script for atomic compare-and-swap status update (idempotent completion)
 # Returns 1 if status was updated, 0 if already completed/failed
@@ -75,24 +68,19 @@ return 0
 """
 
 
-SessionStatus = Literal["running", "completed", "failed"]
-RedisHash = dict[str, str]
-RedisStreamMessages = list[tuple[str, list[tuple[str, RedisHash]]]]
-
-
-class ActiveSession(BaseModel):
+@dataclass
+class ActiveSession:
     """Represents an active streaming session (metadata only, no in-memory queues)."""
 
-    model_config = ConfigDict(frozen=True)
-
     session_id: str
     user_id: str | None
     tool_call_id: str
     tool_name: str
     turn_id: str = ""
     blocking: bool = False  # If True, HTTP request is waiting for completion
-    status: SessionStatus = "running"
-    created_at: datetime = Field(default_factory=lambda: datetime.now(timezone.utc))
+    status: Literal["running", "completed", "failed"] = "running"
+    created_at: datetime = field(default_factory=lambda: datetime.now(timezone.utc))
+    asyncio_task: asyncio.Task | None = None
 
 
 def _get_session_meta_key(session_id: str) -> str:
@@ -105,54 +93,7 @@ def _get_turn_stream_key(turn_id: str) -> str:
     return f"{config.turn_stream_prefix}{turn_id}"
 
 
-async def _redis_hset_mapping(redis: Any, key: str, mapping: RedisHash) -> int:
-    return await cast(Awaitable[int], redis.hset(key, mapping=mapping))
-
-
-async def _redis_hgetall(redis: Any, key: str) -> RedisHash:
-    return cast(
-        RedisHash,
-        await cast(Awaitable[dict[str, str]], redis.hgetall(key)),
-    )
-
-
-async def _redis_hget(redis: Any, key: str, field: str) -> str | None:
-    return cast(
-        str | None,
-        await cast(Awaitable[str | None], redis.hget(key, field)),
-    )
-
-
-async def _redis_xread(
-    redis: Any,
-    streams: dict[str, str],
-    *,
-    count: int,
-    block: int | None,
-) -> RedisStreamMessages:
-    return cast(
-        RedisStreamMessages,
-        await cast(
-            Awaitable[RedisStreamMessages],
-            redis.xread(streams, count=count, block=block),
-        ),
-    )
-
-
-async def _redis_complete_session(
-    redis: Any,
-    meta_key: str,
-    status: SessionStatus,
-) -> int:
-    return int(
-        await cast(
-            Awaitable[int | str],
-            redis.eval(COMPLETE_SESSION_SCRIPT, 1, meta_key, status),
-        )
-    )
-
-
-def _parse_session_meta(meta: RedisHash, session_id: str = "") -> ActiveSession:
+def _parse_session_meta(meta: dict[Any, Any], session_id: str = "") -> ActiveSession:
     """Parse a raw Redis hash into a typed ActiveSession.
 
     Centralises the ``meta.get(...)`` boilerplate so callers don't repeat it.
@@ -166,7 +107,7 @@ def _parse_session_meta(meta: RedisHash, session_id: str = "") -> ActiveSession:
         tool_name=meta.get("tool_name", ""),
         turn_id=meta.get("turn_id", "") or session_id,
         blocking=meta.get("blocking") == "1",
-        status=cast(SessionStatus, meta.get("status", "running")),
+        status=meta.get("status", "running"),  # type: ignore[arg-type]
     )
 
 
@@ -229,8 +170,7 @@ async def create_session(
     # No need to delete old stream — each turn_id is a fresh UUID
 
     hset_start = time.perf_counter()
-    await _redis_hset_mapping(
-        redis,
+    await redis.hset(  # type: ignore[misc]
         meta_key,
         mapping={
             "session_id": session_id,
@@ -340,108 +280,6 @@ async def publish_chunk(
     return message_id
 
 
-def _decode_stream_chunk(msg_data: RedisHash) -> StreamBaseResponse | None:
-    raw_data = msg_data.get("data")
-    if raw_data is None:
-        return None
-
-    chunk_data = orjson.loads(raw_data)
-    return _reconstruct_chunk(chunk_data)
-
-
-async def _replay_messages(
-    messages: RedisStreamMessages,
-    subscriber_queue: asyncio.Queue[StreamBaseResponse],
-    *,
-    last_message_id: str,
-) -> tuple[int, str]:
-    replayed_count = 0
-    replay_last_id = last_message_id
-
-    for _stream_name, stream_messages in messages:
-        for msg_id, msg_data in stream_messages:
-            replay_last_id = msg_id
-            try:
-                chunk = _decode_stream_chunk(msg_data)
-                if chunk is None:
-                    continue
-                await subscriber_queue.put(chunk)
-                replayed_count += 1
-            except Exception as exc:
-                logger.warning("Failed to replay message: %s", exc)
-
-    return replayed_count, replay_last_id
-
-
-async def _deliver_message_to_queue(
-    session_id: str,
-    subscriber_queue: asyncio.Queue[StreamBaseResponse],
-    chunk: StreamBaseResponse,
-    *,
-    last_delivered_id: str,
-    log_meta: dict[str, Any],
-) -> bool:
-    try:
-        await asyncio.wait_for(
-            subscriber_queue.put(chunk),
-            timeout=QUEUE_PUT_TIMEOUT,
-        )
-        return True
-    except asyncio.TimeoutError:
-        logger.warning(
-            f"[TIMING] Subscriber queue full, delivery timed out after {QUEUE_PUT_TIMEOUT}s",
-            extra={
-                "json_fields": {
-                    **log_meta,
-                    "timeout_s": QUEUE_PUT_TIMEOUT,
-                    "reason": "queue_full",
-                }
-            },
-        )
-        try:
-            overflow_error = StreamError(
-                errorText="Message delivery timeout - some messages may have been missed",
-                code="QUEUE_OVERFLOW",
-                details={
-                    "last_delivered_id": last_delivered_id,
-                    "recovery_hint": f"Reconnect with last_message_id={last_delivered_id}",
-                },
-            )
-            subscriber_queue.put_nowait(overflow_error)
-        except asyncio.QueueFull:
-            logger.error(
-                f"Cannot deliver overflow error for session {session_id}, queue completely blocked"
-            )
-        return False
-
-
-async def _handle_xread_timeout(
-    redis: Any,
-    session_id: str,
-    subscriber_queue: asyncio.Queue[StreamBaseResponse],
-) -> bool:
-    meta_key = _get_session_meta_key(session_id)
-    status = await _redis_hget(redis, meta_key, "status")
-    if status != "running":
-        try:
-            await asyncio.wait_for(
-                subscriber_queue.put(StreamFinish()),
-                timeout=QUEUE_PUT_TIMEOUT,
-            )
-        except asyncio.TimeoutError:
-            logger.warning(f"Timeout delivering finish event for session {session_id}")
-        return False
-
-    try:
-        await asyncio.wait_for(
-            subscriber_queue.put(StreamHeartbeat()),
-            timeout=QUEUE_PUT_TIMEOUT,
-        )
-    except asyncio.TimeoutError:
-        logger.warning(f"Timeout delivering heartbeat for session {session_id}")
-    return True
-
-
 async def subscribe_to_session(
     session_id: str,
     user_id: str | None,
@@ -475,7 +313,7 @@ async def subscribe_to_session(
     redis_start = time.perf_counter()
     redis = await get_redis_async()
     meta_key = _get_session_meta_key(session_id)
-    meta = await _redis_hgetall(redis, meta_key)
+    meta: dict[Any, Any] = await redis.hgetall(meta_key)  # type: ignore[misc]
     hgetall_time = (time.perf_counter() - redis_start) * 1000
     logger.info(
         f"[TIMING] Redis hgetall took {hgetall_time:.1f}ms",
@@ -490,8 +328,8 @@ async def subscribe_to_session(
             "[TIMING] Session not found on first attempt, retrying after 50ms delay",
             extra={"json_fields": {**log_meta}},
         )
-        await asyncio.sleep(SESSION_LOOKUP_RETRY_SECONDS)
-        meta = await _redis_hgetall(redis, meta_key)
+        await asyncio.sleep(0.05)  # 50ms
+        meta = await redis.hgetall(meta_key)  # type: ignore[misc]
         if not meta:
             elapsed = (time.perf_counter() - start_time) * 1000
             logger.info(
@@ -536,12 +374,7 @@ async def subscribe_to_session(
 
     # Step 1: Replay messages from Redis Stream
     xread_start = time.perf_counter()
-    messages = await _redis_xread(
-        redis,
-        {stream_key: last_message_id},
-        block=None,
-        count=STREAM_REPLAY_COUNT,
-    )
+    messages = await redis.xread({stream_key: last_message_id}, block=None, count=1000)
     xread_time = (time.perf_counter() - xread_start) * 1000
     logger.info(
         f"[TIMING] Redis xread (replay) took {xread_time:.1f}ms, status={session_status}",
@@ -554,11 +387,22 @@ async def subscribe_to_session(
         },
     )
 
-    replayed_count, replay_last_id = await _replay_messages(
-        messages,
-        subscriber_queue,
-        last_message_id=last_message_id,
-    )
+    replayed_count = 0
+    replay_last_id = last_message_id
+    if messages:
+        for _stream_name, stream_messages in messages:
+            for msg_id, msg_data in stream_messages:
+                replay_last_id = msg_id if isinstance(msg_id, str) else msg_id.decode()
+                # Note: Redis client uses decode_responses=True, so keys are strings
+                if "data" in msg_data:
+                    try:
+                        chunk_data = orjson.loads(msg_data["data"])
+                        chunk = _reconstruct_chunk(chunk_data)
+                        if chunk:
+                            await subscriber_queue.put(chunk)
+                            replayed_count += 1
+                    except Exception as e:
+                        logger.warning(f"Failed to replay message: {e}")
 
     logger.info(
         f"[TIMING] Replayed {replayed_count} messages, last_id={replay_last_id}",
@@ -611,7 +455,7 @@ async def _stream_listener(
     session_id: str,
     subscriber_queue: asyncio.Queue[StreamBaseResponse],
     last_replayed_id: str,
-    log_meta: dict[str, Any] | None = None,
+    log_meta: dict | None = None,
     turn_id: str = "",
 ) -> None:
     """Listen to Redis Stream for new messages using blocking XREAD.
@@ -655,11 +499,8 @@ async def _stream_listener(
             # Short timeout prevents frontend timeout (12s) while waiting for heartbeats (15s)
             xread_start = time.perf_counter()
             xread_count += 1
-            messages = await _redis_xread(
-                redis,
-                {stream_key: current_id},
-                block=STREAM_XREAD_BLOCK_MS,
-                count=STREAM_XREAD_COUNT,
+            messages = await redis.xread(
+                {stream_key: current_id}, block=5000, count=100
             )
             xread_time = (time.perf_counter() - xread_start) * 1000
 
@@ -691,66 +532,114 @@ async def _stream_listener(
                 )
 
             if not messages:
-                if not await _handle_xread_timeout(
-                    redis,
-                    session_id,
-                    subscriber_queue,
-                ):
+                # Timeout - check if session is still running
+                meta_key = _get_session_meta_key(session_id)
+                status = await redis.hget(meta_key, "status")  # type: ignore[misc]
+                # Stop if session metadata is gone (TTL expired) or status is not "running"
+                if status != "running":
+                    try:
+                        await asyncio.wait_for(
+                            subscriber_queue.put(StreamFinish()),
+                            timeout=QUEUE_PUT_TIMEOUT,
+                        )
+                    except asyncio.TimeoutError:
+                        logger.warning(
+                            f"Timeout delivering finish event for session {session_id}"
+                        )
                     break
+                # Session still running - send heartbeat to keep connection alive
+                # This prevents frontend timeout (12s) during long-running operations
+                try:
+                    await asyncio.wait_for(
+                        subscriber_queue.put(StreamHeartbeat()),
+                        timeout=QUEUE_PUT_TIMEOUT,
+                    )
+                except asyncio.TimeoutError:
+                    logger.warning(
+                        f"Timeout delivering heartbeat for session {session_id}"
+                    )
                 continue
 
             for _stream_name, stream_messages in messages:
                 for msg_id, msg_data in stream_messages:
-                    current_id = msg_id
+                    current_id = msg_id if isinstance(msg_id, str) else msg_id.decode()
+
+                    if "data" not in msg_data:
+                        continue
+
                     try:
-                        chunk = _decode_stream_chunk(msg_data)
+                        chunk_data = orjson.loads(msg_data["data"])
+                        chunk = _reconstruct_chunk(chunk_data)
+                        if chunk:
+                            try:
+                                await asyncio.wait_for(
+                                    subscriber_queue.put(chunk),
+                                    timeout=QUEUE_PUT_TIMEOUT,
+                                )
+                                # Update last delivered ID on successful delivery
+                                last_delivered_id = current_id
+                                messages_delivered += 1
+                                if first_message_time is None:
+                                    first_message_time = time.perf_counter()
+                                    elapsed = (first_message_time - start_time) * 1000
+                                    logger.info(
+                                        f"[TIMING] FIRST live message at {elapsed:.1f}ms, type={type(chunk).__name__}",
+                                        extra={
+                                            "json_fields": {
+                                                **log_meta,
+                                                "elapsed_ms": elapsed,
+                                                "chunk_type": type(chunk).__name__,
+                                            }
+                                        },
+                                    )
+                            except asyncio.TimeoutError:
+                                logger.warning(
+                                    f"[TIMING] Subscriber queue full, delivery timed out after {QUEUE_PUT_TIMEOUT}s",
+                                    extra={
+                                        "json_fields": {
+                                            **log_meta,
+                                            "timeout_s": QUEUE_PUT_TIMEOUT,
+                                            "reason": "queue_full",
+                                        }
+                                    },
+                                )
+                                # Send overflow error with recovery info
+                                try:
+                                    overflow_error = StreamError(
+                                        errorText="Message delivery timeout - some messages may have been missed",
+                                        code="QUEUE_OVERFLOW",
+                                        details={
+                                            "last_delivered_id": last_delivered_id,
+                                            "recovery_hint": f"Reconnect with last_message_id={last_delivered_id}",
+                                        },
+                                    )
+                                    subscriber_queue.put_nowait(overflow_error)
+                                except asyncio.QueueFull:
+                                    # Queue is completely stuck, nothing more we can do
+                                    logger.error(
+                                        f"Cannot deliver overflow error for session {session_id}, "
+                                        "queue completely blocked"
+                                    )
+
+                            # Stop listening on finish
+                            if isinstance(chunk, StreamFinish):
+                                total_time = (time.perf_counter() - start_time) * 1000
+                                logger.info(
+                                    f"[TIMING] StreamFinish received in {total_time / 1000:.1f}s; delivered={messages_delivered}",
+                                    extra={
+                                        "json_fields": {
+                                            **log_meta,
+                                            "total_time_ms": total_time,
+                                            "messages_delivered": messages_delivered,
+                                        }
+                                    },
+                                )
+                                return
                     except Exception as e:
                         logger.warning(
                             f"Error processing stream message: {e}",
                             extra={"json_fields": {**log_meta, "error": str(e)}},
                         )
-                        continue
-
-                    if chunk is None:
-                        continue
-
-                    delivered = await _deliver_message_to_queue(
-                        session_id,
-                        subscriber_queue,
-                        chunk,
-                        last_delivered_id=last_delivered_id,
-                        log_meta=log_meta,
-                    )
-                    if delivered:
-                        last_delivered_id = current_id
-                        messages_delivered += 1
-                        if first_message_time is None:
-                            first_message_time = time.perf_counter()
-                            elapsed = (first_message_time - start_time) * 1000
-                            logger.info(
-                                f"[TIMING] FIRST live message at {elapsed:.1f}ms, type={type(chunk).__name__}",
-                                extra={
-                                    "json_fields": {
-                                        **log_meta,
-                                        "elapsed_ms": elapsed,
-                                        "chunk_type": type(chunk).__name__,
-                                    }
-                                },
-                            )
-
-                    if isinstance(chunk, StreamFinish):
-                        total_time = (time.perf_counter() - start_time) * 1000
-                        logger.info(
-                            f"[TIMING] StreamFinish received in {total_time / 1000:.1f}s; delivered={messages_delivered}",
-                            extra={
-                                "json_fields": {
-                                    **log_meta,
-                                    "total_time_ms": total_time,
-                                    "messages_delivered": messages_delivered,
-                                }
-                            },
-                        )
-                        return
 
     except asyncio.CancelledError:
         elapsed = (time.perf_counter() - start_time) * 1000
@@ -823,16 +712,16 @@ async def mark_session_completed(
     Returns:
         True if session was newly marked completed, False if already completed/failed
     """
-    status: SessionStatus = "failed" if error_message else "completed"
+    status: Literal["completed", "failed"] = "failed" if error_message else "completed"
     redis = await get_redis_async()
     meta_key = _get_session_meta_key(session_id)
 
     # Resolve turn_id for publishing to the correct stream
-    meta = await _redis_hgetall(redis, meta_key)
+    meta: dict[Any, Any] = await redis.hgetall(meta_key)  # type: ignore[misc]
     turn_id = _parse_session_meta(meta, session_id).turn_id if meta else session_id
 
     # Atomic compare-and-swap: only update if status is "running"
-    result = await _redis_complete_session(redis, meta_key, status)
+    result = await redis.eval(COMPLETE_SESSION_SCRIPT, 1, meta_key, status)  # type: ignore[misc]
 
     if result == 0:
         logger.debug(f"Session {session_id} already completed/failed, skipping")
@@ -885,18 +774,6 @@ async def mark_session_completed(
                     f"for session {session_id}: {e}"
                 )
 
-    try:
-        from backend.copilot.autopilot import handle_non_manual_session_completion
-
-        await handle_non_manual_session_completion(session_id)
-    except Exception as e:
-        logger.warning(
-            "Failed to process non-manual completion for session %s: %s",
-            session_id,
-            e,
-            exc_info=True,
-        )
-
     return True
 
 
@@ -911,7 +788,7 @@ async def get_session(session_id: str) -> ActiveSession | None:
     """
     redis = await get_redis_async()
     meta_key = _get_session_meta_key(session_id)
-    meta = await _redis_hgetall(redis, meta_key)
+    meta: dict[Any, Any] = await redis.hgetall(meta_key)  # type: ignore[misc]
 
     if not meta:
         return None
@@ -938,7 +815,7 @@ async def get_session_with_expiry_info(
     redis = await get_redis_async()
     meta_key = _get_session_meta_key(session_id)
 
-    meta = await _redis_hgetall(redis, meta_key)
+    meta: dict[Any, Any] = await redis.hgetall(meta_key)  # type: ignore[misc]
 
     if not meta:
         # Metadata expired — we can't resolve turn_id, so check using
@@ -970,7 +847,7 @@ async def get_active_session(
 
     redis = await get_redis_async()
     meta_key = _get_session_meta_key(session_id)
-    meta = await _redis_hgetall(redis, meta_key)
+    meta: dict[Any, Any] = await redis.hgetall(meta_key)  # type: ignore[misc]
 
     if not meta:
         return None, "0-0"
@@ -994,9 +871,7 @@ async def get_active_session(
         try:
             created_at = datetime.fromisoformat(created_at_str)
             age_seconds = (datetime.now(timezone.utc) - created_at).total_seconds()
-            stale_threshold = (
-                COPILOT_CONSUMER_TIMEOUT_SECONDS + STALE_SESSION_BUFFER_SECONDS
-            )
+            stale_threshold = COPILOT_CONSUMER_TIMEOUT_SECONDS + 300  # + 5min buffer
             if age_seconds > stale_threshold:
                 logger.warning(
                     f"[STALE_SESSION] Auto-completing stale session {session_id[:8]}... "
@@ -1071,11 +946,7 @@ def _reconstruct_chunk(chunk_data: dict) -> StreamBaseResponse | None:
     }
 
     chunk_type = chunk_data.get("type")
-    if not isinstance(chunk_type, str):
-        logger.warning(f"Unknown chunk type: {chunk_type}")
-        return None
-
-    chunk_class = type_to_class.get(chunk_type)
+    chunk_class = type_to_class.get(chunk_type)  # type: ignore[arg-type]
 
     if chunk_class is None:
         logger.warning(f"Unknown chunk type: {chunk_type}")
@@ -1140,7 +1011,7 @@ async def unsubscribe_from_session(
 
     try:
         # Wait for the task to be cancelled with a timeout
-        await asyncio.wait_for(listener_task, timeout=UNSUBSCRIBE_TIMEOUT_SECONDS)
+        await asyncio.wait_for(listener_task, timeout=5.0)
     except asyncio.CancelledError:
         # Expected - the task was successfully cancelled
         pass

autogpt_platform/backend/backend/copilot/tools/__init__.py

@@ -12,7 +12,6 @@ from .agent_browser import BrowserActTool, BrowserNavigateTool, BrowserScreensho
 from .agent_output import AgentOutputTool
 from .base import BaseTool
 from .bash_exec import BashExecTool
-from .completion_report import CompletionReportTool
 from .continue_run_block import ContinueRunBlockTool
 from .create_agent import CreateAgentTool
 from .customize_agent import CustomizeAgentTool
@@ -51,12 +50,10 @@ if TYPE_CHECKING:
     from backend.copilot.response_model import StreamToolOutputAvailable
 
 logger = logging.getLogger(__name__)
-SESSION_SCOPED_TOOL_NAMES = {"completion_report"}
 
 # Single source of truth for all tools
 TOOL_REGISTRY: dict[str, BaseTool] = {
     "add_understanding": AddUnderstandingTool(),
-    "completion_report": CompletionReportTool(),
     "create_agent": CreateAgentTool(),
     "customize_agent": CustomizeAgentTool(),
     "edit_agent": EditAgentTool(),
@@ -106,38 +103,16 @@ find_agent_tool = TOOL_REGISTRY["find_agent"]
 run_agent_tool = TOOL_REGISTRY["run_agent"]
 
 
-def is_tool_enabled(tool_name: str, session: "ChatSession | None" = None) -> bool:
-    if tool_name not in TOOL_REGISTRY:
-        return False
-    if session is not None and session.disables_tool(tool_name):
-        return False
-    if tool_name not in SESSION_SCOPED_TOOL_NAMES:
-        return True
-    if session is None:
-        return False
-    return session.allows_tool(tool_name)
-
-
-def iter_available_tools(
-    session: "ChatSession | None" = None,
-) -> list[tuple[str, BaseTool]]:
-    return [
-        (tool_name, tool)
-        for tool_name, tool in TOOL_REGISTRY.items()
-        if tool.is_available and is_tool_enabled(tool_name, session)
-    ]
-
-
-def get_available_tools(
-    session: "ChatSession | None" = None,
-) -> list[ChatCompletionToolParam]:
+def get_available_tools() -> list[ChatCompletionToolParam]:
     """Return OpenAI tool schemas for tools available in the current environment.
 
     Called per-request so that env-var or binary availability is evaluated
     fresh each time (e.g. browser_* tools are excluded when agent-browser
     CLI is not installed).
     """
-    return [tool.as_openai_tool() for _, tool in iter_available_tools(session)]
+    return [
+        tool.as_openai_tool() for tool in TOOL_REGISTRY.values() if tool.is_available
+    ]
 
 
 def get_tool(tool_name: str) -> BaseTool | None:
@@ -153,9 +128,6 @@ async def execute_tool(
     tool_call_id: str,
 ) -> "StreamToolOutputAvailable":
     """Execute a tool by name."""
-    if not is_tool_enabled(tool_name, session):
-        raise ValueError(f"Tool {tool_name} is not enabled for this session")
-
     tool = get_tool(tool_name)
     if not tool:
         raise ValueError(f"Tool {tool_name} not found")

autogpt_platform/backend/backend/copilot/tools/agent_browser.py

@@ -32,6 +32,7 @@ import shutil
 import tempfile
 from typing import Any
 
+from backend.copilot.context import get_workspace_manager
 from backend.copilot.model import ChatSession
 from backend.util.request import validate_url_host
 
@@ -43,7 +44,6 @@ from .models import (
     ErrorResponse,
     ToolResponseBase,
 )
-from .workspace_files import get_manager
 
 logger = logging.getLogger(__name__)
 
@@ -194,7 +194,7 @@ async def _save_browser_state(
             ),
         }
 
-        manager = await get_manager(user_id, session.session_id)
+        manager = await get_workspace_manager(user_id, session.session_id)
         await manager.write_file(
             content=json.dumps(state).encode("utf-8"),
             filename=_STATE_FILENAME,
@@ -218,7 +218,7 @@ async def _restore_browser_state(
     Returns True on success (or no state to restore), False on failure.
     """
     try:
-        manager = await get_manager(user_id, session.session_id)
+        manager = await get_workspace_manager(user_id, session.session_id)
 
         file_info = await manager.get_file_info_by_path(_STATE_FILENAME)
         if file_info is None:
@@ -360,7 +360,7 @@ async def close_browser_session(session_name: str, user_id: str | None = None) -
     # Delete persisted browser state (cookies, localStorage) from workspace.
     if user_id:
         try:
-            manager = await get_manager(user_id, session_name)
+            manager = await get_workspace_manager(user_id, session_name)
             file_info = await manager.get_file_info_by_path(_STATE_FILENAME)
             if file_info is not None:
                 await manager.delete_file(file_info.id)

autogpt_platform/backend/backend/copilot/tools/agent_browser_test.py

@@ -897,7 +897,7 @@ class TestHasLocalSession:
 # _save_browser_state
 # ---------------------------------------------------------------------------
 
-_GET_MANAGER = "backend.copilot.tools.agent_browser.get_manager"
+_GET_MANAGER = "backend.copilot.tools.agent_browser.get_workspace_manager"
 
 
 def _make_mock_manager():

autogpt_platform/backend/backend/copilot/tools/completion_report.py

@@ -1,83 +0,0 @@
-"""Tool for finalizing non-manual Copilot sessions."""
-
-from typing import Any
-
-from backend.copilot.constants import COPILOT_SESSION_PREFIX
-from backend.copilot.model import ChatSession
-from backend.copilot.session_types import CompletionReportInput
-from backend.data.db_accessors import review_db
-
-from .base import BaseTool
-from .models import CompletionReportSavedResponse, ErrorResponse, ToolResponseBase
-
-
-class CompletionReportTool(BaseTool):
-    @property
-    def name(self) -> str:
-        return "completion_report"
-
-    @property
-    def description(self) -> str:
-        return (
-            "Finalize a non-manual session after you have finished the work. "
-            "Use this exactly once at the end of the flow. "
-            "Summarize what you did, state whether the user should be notified, "
-            "and provide any email/callback content that should be used."
-        )
-
-    @property
-    def parameters(self) -> dict[str, Any]:
-        schema = CompletionReportInput.model_json_schema()
-        return {
-            "type": "object",
-            "properties": schema.get("properties", {}),
-            "required": [
-                "thoughts",
-                "should_notify_user",
-                "email_title",
-                "email_body",
-                "callback_session_message",
-                "approval_summary",
-            ],
-        }
-
-    async def _execute(
-        self,
-        user_id: str | None,
-        session: ChatSession,
-        **kwargs,
-    ) -> ToolResponseBase:
-        if session.is_manual:
-            return ErrorResponse(
-                message="completion_report is only available in non-manual sessions.",
-                session_id=session.session_id,
-            )
-
-        try:
-            report = CompletionReportInput.model_validate(kwargs)
-        except Exception as exc:
-            return ErrorResponse(
-                message="completion_report arguments are invalid.",
-                error=str(exc),
-                session_id=session.session_id,
-            )
-
-        pending_approval_count = await review_db().count_pending_reviews_for_graph_exec(
-            f"{COPILOT_SESSION_PREFIX}{session.session_id}",
-            session.user_id,
-        )
-
-        if pending_approval_count > 0 and not report.approval_summary:
-            return ErrorResponse(
-                message=(
-                    "approval_summary is required because this session has pending approvals."
-                ),
-                session_id=session.session_id,
-            )
-
-        return CompletionReportSavedResponse(
-            message="Completion report recorded successfully.",
-            session_id=session.session_id,
-            has_pending_approvals=pending_approval_count > 0,
-            pending_approval_count=pending_approval_count,
-        )

autogpt_platform/backend/backend/copilot/tools/completion_report_test.py

@@ -1,95 +0,0 @@
-from typing import cast
-from unittest.mock import AsyncMock, Mock
-
-import pytest
-
-from backend.copilot.model import ChatSession
-from backend.copilot.session_types import ChatSessionStartType
-from backend.copilot.tools.completion_report import CompletionReportTool
-from backend.copilot.tools.models import CompletionReportSavedResponse, ResponseType
-
-
-@pytest.mark.asyncio
-async def test_completion_report_rejects_manual_sessions() -> None:
-    tool = CompletionReportTool()
-    session = ChatSession.new("user-1")
-
-    response = await tool._execute(
-        user_id="user-1",
-        session=session,
-        thoughts="Wrapped up the session.",
-        should_notify_user=False,
-        email_title=None,
-        email_body=None,
-        callback_session_message=None,
-        approval_summary=None,
-    )
-
-    assert response.type == ResponseType.ERROR
-    assert "non-manual sessions" in response.message
-
-
-@pytest.mark.asyncio
-async def test_completion_report_requires_approval_summary_when_pending(
-    mocker,
-) -> None:
-    tool = CompletionReportTool()
-    session = ChatSession.new(
-        "user-1",
-        start_type=ChatSessionStartType.AUTOPILOT_NIGHTLY,
-    )
-
-    review_store = Mock()
-    review_store.count_pending_reviews_for_graph_exec = AsyncMock(return_value=2)
-    mocker.patch(
-        "backend.copilot.tools.completion_report.review_db",
-        return_value=review_store,
-    )
-
-    response = await tool._execute(
-        user_id="user-1",
-        session=session,
-        thoughts="Prepared a recommendation for the user.",
-        should_notify_user=True,
-        email_title="Your nightly update",
-        email_body="I found something worth reviewing.",
-        callback_session_message="Let's review the next step together.",
-        approval_summary=None,
-    )
-
-    assert response.type == ResponseType.ERROR
-    assert "approval_summary is required" in response.message
-
-
-@pytest.mark.asyncio
-async def test_completion_report_succeeds_without_pending_approvals(
-    mocker,
-) -> None:
-    tool = CompletionReportTool()
-    session = ChatSession.new(
-        "user-1",
-        start_type=ChatSessionStartType.AUTOPILOT_CALLBACK,
-    )
-
-    review_store = Mock()
-    review_store.count_pending_reviews_for_graph_exec = AsyncMock(return_value=0)
-    mocker.patch(
-        "backend.copilot.tools.completion_report.review_db",
-        return_value=review_store,
-    )
-
-    response = await tool._execute(
-        user_id="user-1",
-        session=session,
-        thoughts="Reviewed the account and prepared a useful follow-up.",
-        should_notify_user=True,
-        email_title="Autopilot found something useful",
-        email_body="I put together a recommendation for you.",
-        callback_session_message="Open this chat and I will walk you through it.",
-        approval_summary=None,
-    )
-
-    assert response.type == ResponseType.COMPLETION_REPORT_SAVED
-    response = cast(CompletionReportSavedResponse, response)
-    assert response.has_pending_approvals is False
-    assert response.pending_approval_count == 0

autogpt_platform/backend/backend/copilot/tools/e2b_sandbox.py

@@ -41,8 +41,7 @@ import contextlib
 import logging
 from typing import Any, Awaitable, Callable, Literal
 
-from e2b import AsyncSandbox
-from e2b.sandbox.sandbox_api import SandboxLifecycle
+from e2b import AsyncSandbox, SandboxLifecycle
 
 from backend.data.redis_client import get_redis_async
 

autogpt_platform/backend/backend/copilot/tools/models.py

@@ -16,7 +16,6 @@ class ResponseType(str, Enum):
     ERROR = "error"
     NO_RESULTS = "no_results"
     NEED_LOGIN = "need_login"
-    COMPLETION_REPORT_SAVED = "completion_report_saved"
 
     # Agent discovery & execution
     AGENTS_FOUND = "agents_found"
@@ -139,7 +138,7 @@ class NoResultsResponse(ToolResponseBase):
     """Response when no agents found."""
 
     type: ResponseType = ResponseType.NO_RESULTS
-    suggestions: list[str] = Field(default_factory=list)
+    suggestions: list[str] = []
     name: str = "no_results"
 
 
@@ -171,8 +170,8 @@ class AgentDetails(BaseModel):
     name: str
     description: str
     in_library: bool = False
-    inputs: dict[str, Any] = Field(default_factory=dict)
-    credentials: list[CredentialsMetaInput] = Field(default_factory=list)
+    inputs: dict[str, Any] = {}
+    credentials: list[CredentialsMetaInput] = []
     execution_options: ExecutionOptions = Field(default_factory=ExecutionOptions)
     trigger_info: dict[str, Any] | None = None
 
@@ -192,7 +191,7 @@ class UserReadiness(BaseModel):
     """User readiness status."""
 
     has_all_credentials: bool = False
-    missing_credentials: dict[str, Any] = Field(default_factory=dict)
+    missing_credentials: dict[str, Any] = {}
     ready_to_run: bool = False
 
 
@@ -249,14 +248,6 @@ class ErrorResponse(ToolResponseBase):
     details: dict[str, Any] | None = None
 
 
-class CompletionReportSavedResponse(ToolResponseBase):
-    """Response for completion_report."""
-
-    type: ResponseType = ResponseType.COMPLETION_REPORT_SAVED
-    has_pending_approvals: bool = False
-    pending_approval_count: int = 0
-
-
 class InputValidationErrorResponse(ToolResponseBase):
     """Response when run_agent receives unknown input fields."""
 
@@ -445,9 +436,9 @@ class BlockDetails(BaseModel):
     id: str
     name: str
     description: str
-    inputs: dict[str, Any] = Field(default_factory=dict)
-    outputs: dict[str, Any] = Field(default_factory=dict)
-    credentials: list[CredentialsMetaInput] = Field(default_factory=list)
+    inputs: dict[str, Any] = {}
+    outputs: dict[str, Any] = {}
+    credentials: list[CredentialsMetaInput] = []
 
 
 class BlockDetailsResponse(ToolResponseBase):
@@ -640,7 +631,7 @@ class FolderInfo(BaseModel):
 class FolderTreeInfo(FolderInfo):
     """Folder with nested children for tree display."""
 
-    children: list["FolderTreeInfo"] = Field(default_factory=list)
+    children: list["FolderTreeInfo"] = []
 
 
 class FolderCreatedResponse(ToolResponseBase):
@@ -687,6 +678,6 @@ class AgentsMovedToFolderResponse(ToolResponseBase):
 
     type: ResponseType = ResponseType.AGENTS_MOVED_TO_FOLDER
     agent_ids: list[str]
-    agent_names: list[str] = Field(default_factory=list)
+    agent_names: list[str] = []
     folder_id: str | None = None
     count: int = 0

autogpt_platform/backend/backend/copilot/tools/run_block.py

@@ -12,6 +12,7 @@ from backend.copilot.constants import (
     COPILOT_SESSION_PREFIX,
 )
 from backend.copilot.model import ChatSession
+from backend.copilot.sdk.file_ref import FileRefExpansionError, expand_file_refs_in_args
 from backend.data.db_accessors import review_db
 from backend.data.execution import ExecutionContext
 
@@ -197,6 +198,29 @@ class RunBlockTool(BaseTool):
                 session_id=session_id,
             )
 
+        # Expand @@agptfile: refs in input_data with the block's input
+        # schema.  The generic _truncating wrapper skips opaque object
+        # properties (input_data has no declared inner properties in the
+        # tool schema), so file ref tokens are still intact here.
+        # Using the block's schema lets us return raw text for string-typed
+        # fields and parsed structures for list/dict-typed fields.
+        if input_data:
+            try:
+                input_data = await expand_file_refs_in_args(
+                    input_data,
+                    user_id,
+                    session,
+                    input_schema=input_schema,
+                )
+            except FileRefExpansionError as exc:
+                return ErrorResponse(
+                    message=(
+                        f"Failed to resolve file reference: {exc}. "
+                        "Ensure the file exists before referencing it."
+                    ),
+                    session_id=session_id,
+                )
+
         if missing_credentials:
             # Return setup requirements response with missing credentials
             credentials_fields_info = block.input_schema.get_credentials_fields_info()

autogpt_platform/backend/backend/copilot/tools/workspace_files.py

@@ -10,11 +10,11 @@ from pydantic import BaseModel
 from backend.copilot.context import (
     E2B_WORKDIR,
     get_current_sandbox,
+    get_workspace_manager,
     resolve_sandbox_path,
 )
 from backend.copilot.model import ChatSession
 from backend.copilot.tools.sandbox import make_session_path
-from backend.data.db_accessors import workspace_db
 from backend.util.settings import Config
 from backend.util.virus_scanner import scan_content_safe
 from backend.util.workspace import WorkspaceManager
@@ -218,12 +218,6 @@ def _is_text_mime(mime_type: str) -> bool:
     return any(mime_type.startswith(t) for t in _TEXT_MIME_PREFIXES)
 
 
-async def get_manager(user_id: str, session_id: str) -> WorkspaceManager:
-    """Create a session-scoped WorkspaceManager."""
-    workspace = await workspace_db().get_or_create_workspace(user_id)
-    return WorkspaceManager(user_id, workspace.id, session_id)
-
-
 async def _resolve_file(
     manager: WorkspaceManager,
     file_id: str | None,
@@ -386,7 +380,7 @@ class ListWorkspaceFilesTool(BaseTool):
         include_all_sessions: bool = kwargs.get("include_all_sessions", False)
 
         try:
-            manager = await get_manager(user_id, session_id)
+            manager = await get_workspace_manager(user_id, session_id)
             files = await manager.list_files(
                 path=path_prefix, limit=limit, include_all_sessions=include_all_sessions
             )
@@ -536,7 +530,7 @@ class ReadWorkspaceFileTool(BaseTool):
             )
 
         try:
-            manager = await get_manager(user_id, session_id)
+            manager = await get_workspace_manager(user_id, session_id)
             resolved = await _resolve_file(manager, file_id, path, session_id)
             if isinstance(resolved, ErrorResponse):
                 return resolved
@@ -772,7 +766,7 @@ class WriteWorkspaceFileTool(BaseTool):
 
         try:
             await scan_content_safe(content, filename=filename)
-            manager = await get_manager(user_id, session_id)
+            manager = await get_workspace_manager(user_id, session_id)
             rec = await manager.write_file(
                 content=content,
                 filename=filename,
@@ -899,7 +893,7 @@ class DeleteWorkspaceFileTool(BaseTool):
             )
 
         try:
-            manager = await get_manager(user_id, session_id)
+            manager = await get_workspace_manager(user_id, session_id)
             resolved = await _resolve_file(manager, file_id, path, session_id)
             if isinstance(resolved, ErrorResponse):
                 return resolved

autogpt_platform/backend/backend/data/db_accessors.py

@@ -92,19 +92,6 @@ def user_db():
     return user_db
 
 
-def invited_user_db():
-    if db.is_connected():
-        from backend.data import invited_user as _invited_user_db
-
-        invited_user_db = _invited_user_db
-    else:
-        from backend.util.clients import get_database_manager_async_client
-
-        invited_user_db = get_database_manager_async_client()
-
-    return invited_user_db
-
-
 def understanding_db():
     if db.is_connected():
         from backend.data import understanding as _understanding_db

autogpt_platform/backend/backend/data/db_manager.py

@@ -79,7 +79,6 @@ from backend.data.graph import (
 from backend.data.human_review import (
     cancel_pending_reviews_for_execution,
     check_approval,
-    count_pending_reviews_for_graph_exec,
     delete_review_by_node_exec_id,
     get_or_create_human_review,
     get_pending_reviews_for_execution,
@@ -87,7 +86,6 @@ from backend.data.human_review import (
     has_pending_reviews_for_graph_exec,
     update_review_processed_status,
 )
-from backend.data.invited_user import list_invited_users_for_auth_users
 from backend.data.notifications import (
     clear_all_user_notification_batches,
     create_or_add_to_user_notification_batch,
@@ -109,7 +107,6 @@ from backend.data.user import (
     get_user_email_verification,
     get_user_integrations,
     get_user_notification_preference,
-    list_users,
     update_user_integrations,
 )
 from backend.data.workspace import (
@@ -118,7 +115,6 @@ from backend.data.workspace import (
     get_or_create_workspace,
     get_workspace_file,
     get_workspace_file_by_path,
-    get_workspace_files_by_ids,
     list_workspace_files,
     soft_delete_workspace_file,
 )
@@ -241,7 +237,6 @@ class DatabaseManager(AppService):
 
     # ============ User + Integrations ============ #
     get_user_by_id = _(get_user_by_id)
-    list_users = _(list_users)
     get_user_integrations = _(get_user_integrations)
     update_user_integrations = _(update_user_integrations)
 
@@ -254,7 +249,6 @@ class DatabaseManager(AppService):
     # ============ Human In The Loop ============ #
     cancel_pending_reviews_for_execution = _(cancel_pending_reviews_for_execution)
     check_approval = _(check_approval)
-    count_pending_reviews_for_graph_exec = _(count_pending_reviews_for_graph_exec)
     delete_review_by_node_exec_id = _(delete_review_by_node_exec_id)
     get_or_create_human_review = _(get_or_create_human_review)
     get_pending_reviews_for_execution = _(get_pending_reviews_for_execution)
@@ -319,16 +313,12 @@ class DatabaseManager(AppService):
     # ============ Workspace ============ #
     count_workspace_files = _(count_workspace_files)
     create_workspace_file = _(create_workspace_file)
-    get_workspace_files_by_ids = _(get_workspace_files_by_ids)
     get_or_create_workspace = _(get_or_create_workspace)
     get_workspace_file = _(get_workspace_file)
     get_workspace_file_by_path = _(get_workspace_file_by_path)
     list_workspace_files = _(list_workspace_files)
     soft_delete_workspace_file = _(soft_delete_workspace_file)
 
-    # ============ Invited Users ============ #
-    list_invited_users_for_auth_users = _(list_invited_users_for_auth_users)
-
     # ============ Understanding ============ #
     get_business_understanding = _(get_business_understanding)
     upsert_business_understanding = _(upsert_business_understanding)
@@ -338,28 +328,8 @@ class DatabaseManager(AppService):
     update_block_optimized_description = _(update_block_optimized_description)
 
     # ============ CoPilot Chat Sessions ============ #
-    get_chat_messages_since = _(chat_db.get_chat_messages_since)
-    get_chat_session_callback_token = _(chat_db.get_chat_session_callback_token)
     get_chat_session = _(chat_db.get_chat_session)
-    create_chat_session_callback_token = _(chat_db.create_chat_session_callback_token)
     create_chat_session = _(chat_db.create_chat_session)
-    get_manual_chat_sessions_since = _(chat_db.get_manual_chat_sessions_since)
-    get_pending_notification_chat_sessions = _(
-        chat_db.get_pending_notification_chat_sessions
-    )
-    get_pending_notification_chat_sessions_for_user = _(
-        chat_db.get_pending_notification_chat_sessions_for_user
-    )
-    get_recent_completion_report_chat_sessions = _(
-        chat_db.get_recent_completion_report_chat_sessions
-    )
-    get_recent_sent_email_chat_sessions = _(chat_db.get_recent_sent_email_chat_sessions)
-    has_recent_manual_message = _(chat_db.has_recent_manual_message)
-    has_session_since = _(chat_db.has_session_since)
-    mark_chat_session_callback_token_consumed = _(
-        chat_db.mark_chat_session_callback_token_consumed
-    )
-    session_exists_for_execution_tag = _(chat_db.session_exists_for_execution_tag)
     update_chat_session = _(chat_db.update_chat_session)
     add_chat_message = _(chat_db.add_chat_message)
     add_chat_messages_batch = _(chat_db.add_chat_messages_batch)
@@ -404,18 +374,10 @@ class DatabaseManagerClient(AppServiceClient):
     get_marketplace_graphs_for_monitoring = _(d.get_marketplace_graphs_for_monitoring)
 
     # Human In The Loop
-    count_pending_reviews_for_graph_exec = _(d.count_pending_reviews_for_graph_exec)
     has_pending_reviews_for_graph_exec = _(d.has_pending_reviews_for_graph_exec)
 
     # User Emails
     get_user_email_by_id = _(d.get_user_email_by_id)
-    list_users = _(d.list_users)
-
-    # CoPilot Chat Sessions
-    get_recent_completion_report_chat_sessions = _(
-        d.get_recent_completion_report_chat_sessions
-    )
-    get_recent_sent_email_chat_sessions = _(d.get_recent_sent_email_chat_sessions)
 
     # Library
     list_library_agents = _(d.list_library_agents)
@@ -471,14 +433,12 @@ class DatabaseManagerAsyncClient(AppServiceClient):
 
     # ============ User + Integrations ============ #
     get_user_by_id = d.get_user_by_id
-    list_users = d.list_users
     get_user_integrations = d.get_user_integrations
     update_user_integrations = d.update_user_integrations
 
     # ============ Human In The Loop ============ #
     cancel_pending_reviews_for_execution = d.cancel_pending_reviews_for_execution
     check_approval = d.check_approval
-    count_pending_reviews_for_graph_exec = d.count_pending_reviews_for_graph_exec
     delete_review_by_node_exec_id = d.delete_review_by_node_exec_id
     get_or_create_human_review = d.get_or_create_human_review
     get_pending_reviews_for_execution = d.get_pending_reviews_for_execution
@@ -546,16 +506,12 @@ class DatabaseManagerAsyncClient(AppServiceClient):
     # ============ Workspace ============ #
     count_workspace_files = d.count_workspace_files
     create_workspace_file = d.create_workspace_file
-    get_workspace_files_by_ids = d.get_workspace_files_by_ids
     get_or_create_workspace = d.get_or_create_workspace
     get_workspace_file = d.get_workspace_file
     get_workspace_file_by_path = d.get_workspace_file_by_path
     list_workspace_files = d.list_workspace_files
     soft_delete_workspace_file = d.soft_delete_workspace_file
 
-    # ============ Invited Users ============ #
-    list_invited_users_for_auth_users = d.list_invited_users_for_auth_users
-
     # ============ Understanding ============ #
     get_business_understanding = d.get_business_understanding
     upsert_business_understanding = d.upsert_business_understanding
@@ -564,26 +520,8 @@ class DatabaseManagerAsyncClient(AppServiceClient):
     get_blocks_needing_optimization = d.get_blocks_needing_optimization
 
     # ============ CoPilot Chat Sessions ============ #
-    get_chat_messages_since = d.get_chat_messages_since
-    get_chat_session_callback_token = d.get_chat_session_callback_token
     get_chat_session = d.get_chat_session
-    create_chat_session_callback_token = d.create_chat_session_callback_token
     create_chat_session = d.create_chat_session
-    get_manual_chat_sessions_since = d.get_manual_chat_sessions_since
-    get_pending_notification_chat_sessions = d.get_pending_notification_chat_sessions
-    get_pending_notification_chat_sessions_for_user = (
-        d.get_pending_notification_chat_sessions_for_user
-    )
-    get_recent_completion_report_chat_sessions = (
-        d.get_recent_completion_report_chat_sessions
-    )
-    get_recent_sent_email_chat_sessions = d.get_recent_sent_email_chat_sessions
-    has_recent_manual_message = d.has_recent_manual_message
-    has_session_since = d.has_session_since
-    mark_chat_session_callback_token_consumed = (
-        d.mark_chat_session_callback_token_consumed
-    )
-    session_exists_for_execution_tag = d.session_exists_for_execution_tag
     update_chat_session = d.update_chat_session
     add_chat_message = d.add_chat_message
     add_chat_messages_batch = d.add_chat_messages_batch

autogpt_platform/backend/backend/data/human_review.py

@@ -342,19 +342,6 @@ async def has_pending_reviews_for_graph_exec(graph_exec_id: str) -> bool:
     return count > 0
 
 
-async def count_pending_reviews_for_graph_exec(
-    graph_exec_id: str,
-    user_id: str,
-) -> int:
-    return await PendingHumanReview.prisma().count(
-        where={
-            "userId": user_id,
-            "graphExecId": graph_exec_id,
-            "status": ReviewStatus.WAITING,
-        }
-    )
-
-
 async def _resolve_node_id(node_exec_id: str, get_node_execution) -> str:
     """Resolve node_id from a node_exec_id.
 

autogpt_platform/backend/backend/data/invited_user.py

@@ -21,8 +21,8 @@ from backend.data.model import User
 from backend.data.redis_client import get_redis_async
 from backend.data.tally import get_business_understanding_input_from_tally, mask_email
 from backend.data.understanding import (
+    BusinessUnderstandingInput,
     merge_business_understanding_data,
-    parse_business_understanding_input,
 )
 from backend.data.user import get_user_by_email, get_user_by_id
 from backend.executor.cluster_lock import AsyncClusterLock
@@ -63,16 +63,18 @@ class InvitedUserRecord(BaseModel):
 
     @classmethod
     def from_db(cls, invited_user: "prisma.models.InvitedUser") -> "InvitedUserRecord":
-        payload = parse_business_understanding_input(invited_user.tallyUnderstanding)
+        payload = (
+            invited_user.tallyUnderstanding
+            if isinstance(invited_user.tallyUnderstanding, dict)
+            else None
+        )
         return cls(
             id=invited_user.id,
             email=invited_user.email,
             status=invited_user.status,
             auth_user_id=invited_user.authUserId,
             name=invited_user.name,
-            tally_understanding=(
-                payload.model_dump(mode="json") if payload is not None else None
-            ),
+            tally_understanding=payload,
             tally_status=invited_user.tallyStatus,
             tally_computed_at=invited_user.tallyComputedAt,
             tally_error=invited_user.tallyError,
@@ -183,13 +185,19 @@ async def _apply_tally_understanding(
     invited_user: "prisma.models.InvitedUser",
     tx,
 ) -> None:
-    input_data = parse_business_understanding_input(invited_user.tallyUnderstanding)
-    if input_data is None:
-        if invited_user.tallyUnderstanding is not None:
-            logger.warning(
-                "Malformed tallyUnderstanding for invited user %s; skipping",
-                invited_user.id,
-            )
+    if not isinstance(invited_user.tallyUnderstanding, dict):
+        return
+
+    try:
+        input_data = BusinessUnderstandingInput.model_validate(
+            invited_user.tallyUnderstanding
+        )
+    except Exception:
+        logger.warning(
+            "Malformed tallyUnderstanding for invited user %s; skipping",
+            invited_user.id,
+            exc_info=True,
+        )
         return
 
     payload = merge_business_understanding_data({}, input_data)
@@ -215,18 +223,6 @@ async def list_invited_users(
     return [InvitedUserRecord.from_db(iu) for iu in invited_users], total
 
 
-async def list_invited_users_for_auth_users(
-    auth_user_ids: list[str],
-) -> list[InvitedUserRecord]:
-    if not auth_user_ids:
-        return []
-
-    invited_users = await prisma.models.InvitedUser.prisma().find_many(
-        where={"authUserId": {"in": auth_user_ids}}
-    )
-    return [InvitedUserRecord.from_db(invited_user) for invited_user in invited_users]
-
-
 async def create_invited_user(
     email: str, name: Optional[str] = None
 ) -> InvitedUserRecord:

autogpt_platform/backend/backend/data/understanding.py

@@ -31,18 +31,6 @@ def _json_to_list(value: Any) -> list[str]:
     return []
 
 
-def parse_business_understanding_input(
-    payload: Any,
-) -> "BusinessUnderstandingInput | None":
-    if payload is None:
-        return None
-
-    try:
-        return BusinessUnderstandingInput.model_validate(payload)
-    except pydantic.ValidationError:
-        return None
-
-
 class BusinessUnderstandingInput(pydantic.BaseModel):
     """Input model for updating business understanding - all fields optional for incremental updates."""
 

autogpt_platform/backend/backend/data/user.py

@@ -62,61 +62,6 @@ async def get_user_by_id(user_id: str) -> User:
     return User.from_db(user)
 
 
-async def list_users(
-    limit: int = 500,
-    cursor: str | None = None,
-) -> list[User]:
-    try:
-        kwargs: dict = {
-            "take": limit,
-            "order": {"id": "asc"},
-        }
-        if cursor is not None:
-            kwargs["cursor"] = {"id": cursor}
-            kwargs["skip"] = 1
-        users = await PrismaUser.prisma().find_many(**kwargs)
-        return [User.from_db(user) for user in users]
-    except Exception as e:
-        raise DatabaseError(f"Failed to list users: {e}") from e
-
-
-async def search_users(query: str, limit: int = 20) -> list[User]:
-    normalized_query = query.strip()
-    if not normalized_query:
-        return []
-
-    try:
-        users = await PrismaUser.prisma().find_many(
-            where={
-                "OR": [
-                    {
-                        "email": {
-                            "contains": normalized_query,
-                            "mode": "insensitive",
-                        }
-                    },
-                    {
-                        "name": {
-                            "contains": normalized_query,
-                            "mode": "insensitive",
-                        }
-                    },
-                    {
-                        "id": {
-                            "contains": normalized_query,
-                            "mode": "insensitive",
-                        }
-                    },
-                ]
-            },
-            order={"updatedAt": "desc"},
-            take=limit,
-        )
-        return [User.from_db(user) for user in users]
-    except Exception as e:
-        raise DatabaseError(f"Failed to search users for query {query!r}: {e}") from e
-
-
 async def get_user_email_by_id(user_id: str) -> Optional[str]:
     try:
         user = await prisma.user.find_unique(where={"id": user_id})

autogpt_platform/backend/backend/data/workspace.py

@@ -254,23 +254,6 @@ async def list_workspace_files(
     return [WorkspaceFile.from_db(f) for f in files]
 
 
-async def get_workspace_files_by_ids(
-    workspace_id: str,
-    file_ids: list[str],
-) -> list[WorkspaceFile]:
-    if not file_ids:
-        return []
-
-    files = await UserWorkspaceFile.prisma().find_many(
-        where={
-            "id": {"in": file_ids},
-            "workspaceId": workspace_id,
-            "isDeleted": False,
-        }
-    )
-    return [WorkspaceFile.from_db(file) for file in files]
-
-
 async def count_workspace_files(
     workspace_id: str,
     path_prefix: Optional[str] = None,

autogpt_platform/backend/backend/executor/scheduler.py

@@ -24,12 +24,6 @@ from dotenv import load_dotenv
 from pydantic import BaseModel, Field, ValidationError
 from sqlalchemy import MetaData, create_engine
 
-from backend.copilot.autopilot import (
-    dispatch_nightly_copilot as dispatch_nightly_copilot_async,
-)
-from backend.copilot.autopilot import (
-    send_nightly_copilot_emails as send_nightly_copilot_emails_async,
-)
 from backend.copilot.optimize_blocks import optimize_block_descriptions
 from backend.data.execution import GraphExecutionWithNodes
 from backend.data.model import CredentialsMetaInput, GraphInput
@@ -265,16 +259,6 @@ def cleanup_oauth_tokens():
     run_async(_cleanup())
 
 
-def dispatch_nightly_copilot():
-    """Dispatch proactive nightly copilot sessions."""
-    return run_async(dispatch_nightly_copilot_async())
-
-
-def send_nightly_copilot_emails():
-    """Send emails for completed non-manual copilot sessions."""
-    return run_async(send_nightly_copilot_emails_async())
-
-
 def execution_accuracy_alerts():
     """Check execution accuracy and send alerts if drops are detected."""
     return report_execution_accuracy_alerts()
@@ -420,7 +404,7 @@ class GraphExecutionJobInfo(GraphExecutionJobArgs):
     ) -> "GraphExecutionJobInfo":
         # Extract timezone from the trigger if it's a CronTrigger
         timezone_str = "UTC"
-        if isinstance(job_obj.trigger, CronTrigger):
+        if hasattr(job_obj.trigger, "timezone"):
             timezone_str = str(job_obj.trigger.timezone)
 
         return GraphExecutionJobInfo(
@@ -635,24 +619,6 @@ class Scheduler(AppService):
                 jobstore=Jobstores.EXECUTION.value,
             )
 
-            self.scheduler.add_job(
-                dispatch_nightly_copilot,
-                id="dispatch_nightly_copilot",
-                trigger=CronTrigger(minute="0,30", timezone=ZoneInfo("UTC")),
-                replace_existing=True,
-                max_instances=1,
-                jobstore=Jobstores.EXECUTION.value,
-            )
-
-            self.scheduler.add_job(
-                send_nightly_copilot_emails,
-                id="send_nightly_copilot_emails",
-                trigger=CronTrigger(minute="15,45", timezone=ZoneInfo("UTC")),
-                replace_existing=True,
-                max_instances=1,
-                jobstore=Jobstores.EXECUTION.value,
-            )
-
         self.scheduler.add_listener(job_listener, EVENT_JOB_EXECUTED | EVENT_JOB_ERROR)
         self.scheduler.add_listener(job_missed_listener, EVENT_JOB_MISSED)
         self.scheduler.add_listener(job_max_instances_listener, EVENT_JOB_MAX_INSTANCES)
@@ -827,14 +793,6 @@ class Scheduler(AppService):
         """Manually trigger embedding backfill for approved store agents."""
         return ensure_embeddings_coverage()
 
-    @expose
-    def execute_dispatch_nightly_copilot(self):
-        return dispatch_nightly_copilot()
-
-    @expose
-    def execute_send_nightly_copilot_emails(self):
-        return send_nightly_copilot_emails()
-
 
 class SchedulerClient(AppServiceClient):
     @classmethod

autogpt_platform/backend/backend/notifications/email.py

@@ -1,6 +1,5 @@
 import logging
 import pathlib
-from typing import Any
 
 from postmarker.core import PostmarkClient
 from postmarker.models.emails import EmailManager
@@ -8,14 +7,12 @@ from prisma.enums import NotificationType
 from pydantic import BaseModel
 
 from backend.data.notifications import (
-    AgentRunData,
     NotificationDataType_co,
     NotificationEventModel,
     NotificationTypeOverride,
 )
 from backend.util.settings import Settings
 from backend.util.text import TextFormatter
-from backend.util.url import get_frontend_base_url
 
 logger = logging.getLogger(__name__)
 settings = Settings()
@@ -49,102 +46,6 @@ class EmailSender:
 
     MAX_EMAIL_CHARS = 5_000_000  # ~5MB buffer
 
-    def _get_unsubscribe_link(self, user_unsubscribe_link: str | None) -> str:
-        return user_unsubscribe_link or f"{get_frontend_base_url()}/profile/settings"
-
-    def _format_template_email(
-        self,
-        *,
-        subject_template: str,
-        content_template: str,
-        data: Any,
-        unsubscribe_link: str,
-    ) -> tuple[str, str]:
-        return self.formatter.format_email(
-            base_template=self._read_template("templates/base.html.jinja2"),
-            subject_template=subject_template,
-            content_template=content_template,
-            data=data,
-            unsubscribe_link=unsubscribe_link,
-        )
-
-    def _build_large_output_summary(
-        self,
-        data: (
-            NotificationEventModel[NotificationDataType_co]
-            | list[NotificationEventModel[NotificationDataType_co]]
-        ),
-        *,
-        email_size: int,
-        base_url: str,
-    ) -> str:
-        if isinstance(data, list):
-            if not data:
-                return (
-                    "⚠️ A notification generated a very large output "
-                    f"({email_size / 1_000_000:.2f} MB)."
-                )
-            event = data[0]
-        else:
-            event = data
-        execution_url = (
-            f"{base_url}/executions/{event.id}" if event.id is not None else None
-        )
-
-        if isinstance(event.data, AgentRunData):
-            lines = [
-                f"⚠️ Your agent '{event.data.agent_name}' generated a very large output ({email_size / 1_000_000:.2f} MB).",
-                "",
-                f"Execution time: {event.data.execution_time}",
-                f"Credits used: {event.data.credits_used}",
-            ]
-            if execution_url is not None:
-                lines.append(f"View full results: {execution_url}")
-            return "\n".join(lines)
-
-        lines = [
-            f"⚠️ A notification generated a very large output ({email_size / 1_000_000:.2f} MB).",
-        ]
-        if execution_url is not None:
-            lines.extend(["", f"View full results: {execution_url}"])
-        return "\n".join(lines)
-
-    def send_template(
-        self,
-        *,
-        user_email: str,
-        subject: str,
-        template_name: str,
-        data: dict[str, Any] | None = None,
-        user_unsubscribe_link: str | None = None,
-    ) -> None:
-        """Send an email using a named Jinja2 template file.
-
-        Unlike ``send_templated`` (which resolves templates via
-        ``NotificationType``), this method accepts a template filename
-        directly.  Both delegate to the shared ``_format_template_email``
-        + ``_send_email`` pipeline.
-        """
-        if not self.postmark:
-            logger.warning("Postmark client not initialized, email not sent")
-            return
-
-        unsubscribe_link = self._get_unsubscribe_link(user_unsubscribe_link)
-
-        _, full_message = self._format_template_email(
-            subject_template="{{ subject }}",
-            content_template=self._read_template(f"templates/{template_name}"),
-            data={"subject": subject, **(data or {})},
-            unsubscribe_link=unsubscribe_link,
-        )
-
-        self._send_email(
-            user_email=user_email,
-            subject=subject,
-            body=full_message,
-            user_unsubscribe_link=unsubscribe_link,
-        )
-
     def send_templated(
         self,
         notification: NotificationType,
@@ -161,18 +62,21 @@ class EmailSender:
             return
 
         template = self._get_template(notification)
-        base_url = get_frontend_base_url()
-        unsubscribe_link = self._get_unsubscribe_link(user_unsub_link)
+
+        base_url = (
+            settings.config.frontend_base_url or settings.config.platform_base_url
+        )
 
         # Normalize data
         template_data = {"notifications": data} if isinstance(data, list) else data
 
         try:
-            subject, full_message = self._format_template_email(
+            subject, full_message = self.formatter.format_email(
+                base_template=template.base_template,
                 subject_template=template.subject_template,
                 content_template=template.body_template,
                 data=template_data,
-                unsubscribe_link=unsubscribe_link,
+                unsubscribe_link=f"{base_url}/profile/settings",
             )
         except Exception as e:
             logger.error(f"Error formatting full message: {e}")
@@ -186,17 +90,20 @@ class EmailSender:
                 "Sending summary email instead."
             )
 
-            summary_message = self._build_large_output_summary(
-                data,
-                email_size=email_size,
-                base_url=base_url,
+            # Create lightweight summary
+            summary_message = (
+                f"⚠️ Your agent '{getattr(data, 'agent_name', 'Unknown')}' "
+                f"generated a very large output ({email_size / 1_000_000:.2f} MB).\n\n"
+                f"Execution time: {getattr(data, 'execution_time', 'N/A')}\n"
+                f"Credits used: {getattr(data, 'credits_used', 'N/A')}\n"
+                f"View full results: {base_url}/executions/{getattr(data, 'id', 'N/A')}"
             )
 
             self._send_email(
                 user_email=user_email,
                 subject=f"{subject} (Output Too Large)",
                 body=summary_message,
-                user_unsubscribe_link=unsubscribe_link,
+                user_unsubscribe_link=user_unsub_link,
             )
             return  # Skip sending full email
 
@@ -205,7 +112,7 @@ class EmailSender:
             user_email=user_email,
             subject=subject,
             body=full_message,
-            user_unsubscribe_link=unsubscribe_link,
+            user_unsubscribe_link=user_unsub_link,
         )
 
     def _get_template(self, notification: NotificationType):
@@ -216,18 +123,17 @@ class EmailSender:
         logger.debug(
             f"Template full path: {pathlib.Path(__file__).parent / template_path}"
         )
-        base_template = self._read_template("templates/base.html.jinja2")
-        template = self._read_template(template_path)
+        base_template_path = "templates/base.html.jinja2"
+        with open(pathlib.Path(__file__).parent / base_template_path, "r") as file:
+            base_template = file.read()
+        with open(pathlib.Path(__file__).parent / template_path, "r") as file:
+            template = file.read()
         return Template(
             subject_template=notification_type_override.subject,
             body_template=template,
             base_template=base_template,
         )
 
-    def _read_template(self, template_path: str) -> str:
-        with open(pathlib.Path(__file__).parent / template_path, "r") as file:
-            return file.read()
-
     def _send_email(
         self,
         user_email: str,
@@ -238,33 +144,18 @@ class EmailSender:
         if not self.postmark:
             logger.warning("Email tried to send without postmark configured")
             return
-        sender_email = settings.config.postmark_sender_email
-        if not sender_email:
-            logger.warning("postmark_sender_email not configured, email not sent")
-            return
-        unsubscribe_link = self._get_unsubscribe_link(user_unsubscribe_link)
         logger.debug(f"Sending email to {user_email} with subject {subject}")
         self.postmark.emails.send(
-            From=sender_email,
+            From=settings.config.postmark_sender_email,
             To=user_email,
             Subject=subject,
             HtmlBody=body,
-            Headers={
-                "List-Unsubscribe-Post": "List-Unsubscribe=One-Click",
-                "List-Unsubscribe": f"<{unsubscribe_link}>",
-            },
-        )
-
-    def send_html(
-        self,
-        user_email: str,
-        subject: str,
-        body: str,
-        user_unsubscribe_link: str | None = None,
-    ) -> None:
-        self._send_email(
-            user_email=user_email,
-            subject=subject,
-            body=body,
-            user_unsubscribe_link=user_unsubscribe_link,
+            Headers=(
+                {
+                    "List-Unsubscribe-Post": "List-Unsubscribe=One-Click",
+                    "List-Unsubscribe": f"<{user_unsubscribe_link}>",
+                }
+                if user_unsubscribe_link
+                else None
+            ),
         )

autogpt_platform/backend/backend/notifications/email_test.py

@@ -1,241 +0,0 @@
-from types import SimpleNamespace
-from typing import Any, cast
-
-from backend.api.test_helpers import override_config
-from backend.copilot.autopilot_email import _markdown_to_email_html
-from backend.notifications.email import EmailSender, settings
-from backend.util.settings import AppEnvironment
-
-
-def test_markdown_to_email_html_renders_bold_and_italic() -> None:
-    html = _markdown_to_email_html("**bold** and *italic*")
-    assert "<strong>bold</strong>" in html
-    assert "<em>italic</em>" in html
-    assert 'style="' in html
-
-
-def test_markdown_to_email_html_renders_links() -> None:
-    html = _markdown_to_email_html("[click here](https://example.com)")
-    assert 'href="https://example.com"' in html
-    assert "click here" in html
-    assert "color: #7733F5" in html
-
-
-def test_markdown_to_email_html_renders_bullet_list() -> None:
-    html = _markdown_to_email_html("- item one\n- item two")
-    assert "<ul" in html
-    assert "<li" in html
-    assert "item one" in html
-    assert "item two" in html
-
-
-def test_markdown_to_email_html_handles_empty_input() -> None:
-    assert _markdown_to_email_html(None) == ""
-    assert _markdown_to_email_html("") == ""
-    assert _markdown_to_email_html("   ") == ""
-
-
-def test_send_template_renders_nightly_copilot_email(mocker) -> None:
-    sender = EmailSender()
-    sender.postmark = cast(Any, object())
-    send_email = mocker.patch.object(sender, "_send_email")
-
-    sender.send_template(
-        user_email="user@example.com",
-        subject="Autopilot update",
-        template_name="nightly_copilot.html.jinja2",
-        data={
-            "email_body_html": _markdown_to_email_html(
-                "I found something useful for you.\n\n"
-                "Open Copilot and I will walk you through it."
-            ),
-            "cta_url": "https://example.com/copilot?callbackToken=token-1",
-            "cta_label": "Open Copilot",
-        },
-    )
-
-    body = send_email.call_args.kwargs["body"]
-
-    assert "I found something useful for you." in body
-    assert "Open Copilot" in body
-    assert "Approval needed" not in body
-    assert send_email.call_args.kwargs["user_unsubscribe_link"].endswith(
-        "/profile/settings"
-    )
-
-
-def test_send_template_renders_nightly_copilot_approval_block(mocker) -> None:
-    sender = EmailSender()
-    sender.postmark = cast(Any, object())
-    send_email = mocker.patch.object(sender, "_send_email")
-
-    sender.send_template(
-        user_email="user@example.com",
-        subject="Autopilot update",
-        template_name="nightly_copilot.html.jinja2",
-        data={
-            "email_body_html": _markdown_to_email_html(
-                "I prepared a change worth reviewing."
-            ),
-            "approval_summary_html": _markdown_to_email_html(
-                "I drafted a follow-up because it matches your recent activity."
-            ),
-            "cta_url": "https://example.com/copilot?sessionId=session-1&showAutopilot=1",
-            "cta_label": "Review in Copilot",
-        },
-    )
-
-    body = send_email.call_args.kwargs["body"]
-
-    assert "Approval needed" in body
-    assert "If you want it to happen, please hit approve." in body
-    assert "Review in Copilot" in body
-
-
-def test_send_template_renders_nightly_copilot_callback_email(mocker) -> None:
-    sender = EmailSender()
-    sender.postmark = cast(Any, object())
-    send_email = mocker.patch.object(sender, "_send_email")
-
-    sender.send_template(
-        user_email="user@example.com",
-        subject="Autopilot update",
-        template_name="nightly_copilot_callback.html.jinja2",
-        data={
-            "email_body_html": _markdown_to_email_html(
-                "I prepared a follow-up based on your recent work."
-            ),
-            "cta_url": "https://example.com/copilot?callbackToken=token-1",
-            "cta_label": "Open Copilot",
-        },
-    )
-
-    body = send_email.call_args.kwargs["body"]
-
-    assert "Autopilot picked up where you left off" in body
-    assert "I prepared a follow-up based on your recent work." in body
-
-
-def test_send_template_renders_nightly_copilot_callback_approval_block(mocker) -> None:
-    sender = EmailSender()
-    sender.postmark = cast(Any, object())
-    send_email = mocker.patch.object(sender, "_send_email")
-
-    sender.send_template(
-        user_email="user@example.com",
-        subject="Autopilot update",
-        template_name="nightly_copilot_callback.html.jinja2",
-        data={
-            "email_body_html": _markdown_to_email_html(
-                "I prepared a follow-up based on your recent work."
-            ),
-            "approval_summary_html": _markdown_to_email_html(
-                "I want your approval before I apply the next step."
-            ),
-            "cta_url": "https://example.com/copilot?sessionId=session-1&showAutopilot=1",
-            "cta_label": "Review in Copilot",
-        },
-    )
-
-    body = send_email.call_args.kwargs["body"]
-
-    assert "Approval needed" in body
-    assert "I want your approval before I apply the next step." in body
-
-
-def test_send_template_renders_nightly_copilot_invite_cta_email(mocker) -> None:
-    sender = EmailSender()
-    sender.postmark = cast(Any, object())
-    send_email = mocker.patch.object(sender, "_send_email")
-
-    sender.send_template(
-        user_email="user@example.com",
-        subject="Autopilot update",
-        template_name="nightly_copilot_invite_cta.html.jinja2",
-        data={
-            "email_body_html": _markdown_to_email_html(
-                "I put together an example of how Autopilot could help you."
-            ),
-            "cta_url": "https://example.com/copilot?callbackToken=token-1",
-            "cta_label": "Try Copilot",
-        },
-    )
-
-    body = send_email.call_args.kwargs["body"]
-
-    assert "Your Autopilot beta access is waiting" in body
-    assert "I put together an example of how Autopilot could help you." in body
-    assert "Try Copilot" in body
-
-
-def test_send_template_renders_nightly_copilot_invite_cta_approval_block(
-    mocker,
-) -> None:
-    sender = EmailSender()
-    sender.postmark = cast(Any, object())
-    send_email = mocker.patch.object(sender, "_send_email")
-
-    sender.send_template(
-        user_email="user@example.com",
-        subject="Autopilot update",
-        template_name="nightly_copilot_invite_cta.html.jinja2",
-        data={
-            "email_body_html": _markdown_to_email_html(
-                "I put together an example of how Autopilot could help you."
-            ),
-            "approval_summary_html": _markdown_to_email_html(
-                "If this looks useful, approve the next step to try it."
-            ),
-            "cta_url": "https://example.com/copilot?sessionId=session-1&showAutopilot=1",
-            "cta_label": "Review in Copilot",
-        },
-    )
-
-    body = send_email.call_args.kwargs["body"]
-
-    assert "Approval needed" in body
-    assert "If this looks useful, approve the next step to try it." in body
-
-
-def test_send_template_still_sends_in_production(mocker) -> None:
-    sender = EmailSender()
-    sender.postmark = cast(Any, object())
-    send_email = mocker.patch.object(sender, "_send_email")
-
-    with override_config(settings, "app_env", AppEnvironment.PRODUCTION):
-        sender.send_template(
-            user_email="user@example.com",
-            subject="Autopilot update",
-            template_name="nightly_copilot.html.jinja2",
-            data={
-                "email_body_html": _markdown_to_email_html(
-                    "I found something useful for you."
-                ),
-                "cta_url": "https://example.com/copilot?callbackToken=token-1",
-                "cta_label": "Open Copilot",
-            },
-        )
-
-    send_email.assert_called_once()
-
-
-def test_send_html_uses_default_unsubscribe_link(mocker) -> None:
-    sender = EmailSender()
-    send = mocker.Mock()
-    sender.postmark = cast(Any, SimpleNamespace(emails=SimpleNamespace(send=send)))
-
-    mocker.patch(
-        "backend.notifications.email.get_frontend_base_url",
-        return_value="https://example.com",
-    )
-    with override_config(settings, "postmark_sender_email", "test@example.com"):
-        sender.send_html(
-            user_email="user@example.com",
-            subject="Autopilot update",
-            body="<p>Hello</p>",
-        )
-
-    headers = send.call_args.kwargs["Headers"]
-
-    assert headers["List-Unsubscribe-Post"] == "List-Unsubscribe=One-Click"
-    assert headers["List-Unsubscribe"] == "<https://example.com/profile/settings>"

autogpt_platform/backend/backend/notifications/templates/base.html.jinja2

@@ -29,6 +29,7 @@
     </noscript>
     <![endif]-->
   <style type="text/css">
+    /* RESET STYLES */
     html,
     body {
       margin: 0 !important;
@@ -84,6 +85,7 @@
       word-break: break-word;
     }
 
+    /* iOS BLUE LINKS */
     a[x-apple-data-detectors] {
       color: inherit !important;
       text-decoration: none !important;
@@ -93,11 +95,13 @@
       line-height: inherit !important;
     }
 
+    /* ANDROID CENTER FIX */
     div[style*="margin: 16px 0;"] {
       margin: 0 !important;
     }
 
-    @media all and (max-width: 639px) {
+    /* MEDIA QUERIES */
+    @media all and (max-width:639px) {
       .wrapper {
         width: 100% !important;
       }
@@ -109,8 +113,8 @@
       }
 
       .row {
-        padding-left: 24px !important;
-        padding-right: 24px !important;
+        padding-left: 20px !important;
+        padding-right: 20px !important;
       }
 
       .col-mobile {
@@ -132,6 +136,11 @@
         float: none !important;
       }
 
+      .mobile-left {
+        text-align: center !important;
+        float: left !important;
+      }
+
       .mobile-hide {
         display: none !important;
       }
@@ -146,9 +155,9 @@
         max-width: 100% !important;
       }
 
-      .card-inner {
-        padding-left: 24px !important;
-        padding-right: 24px !important;
+      .ml-btn-container {
+        width: 100% !important;
+        max-width: 100% !important;
       }
     }
   </style>
@@ -165,139 +174,170 @@
   <title>{{data.title}}</title>
 </head>
 
-<body style="margin: 0 !important; padding: 0 !important; background-color: #070629;">
+<body style="margin: 0 !important; padding: 0 !important; background-color:#070629;">
   <div class="document" role="article" aria-roledescription="email" aria-label lang dir="ltr"
-    style="background-color: #070629; line-height: 100%; font-size: medium; font-size: max(16px, 1rem);">
-
+    style="background-color:#070629; line-height: 100%; font-size:medium; font-size:max(16px, 1rem);">
+    <!-- Main Content -->
     <table width="100%" align="center" cellspacing="0" cellpadding="0" border="0">
       <tr>
-        <td align="center" valign="top" style="padding: 48px 16px 40px;">
-
-          <!-- ============ CARD ============ -->
-          <table class="container" align="center" width="640" cellpadding="0" cellspacing="0" border="0"
-            style="max-width: 640px;">
-
-            <!-- Gradient Accent Strip -->
-            <tr>
-              <td bgcolor="#7733F5"
-                style="background: linear-gradient(90deg, #7733F5 0%, #60A5FA 35%, #EC4899 65%, #7733F5 100%); height: 6px; border-radius: 16px 16px 0 0; font-size: 0; line-height: 0;">
-                &nbsp;</td>
-            </tr>
-
-            <!-- Logo -->
-            <tr>
-              <td bgcolor="#FFFFFF" align="center" class="card-inner" style="padding: 32px 48px 24px;">
-                <img
-                  src="https://storage.mlcdn.com/account_image/597379/8QJ8kOjXakVvfe1kJLY2wWCObU1mp5EiDLfBlbQa.png"
-                  border="0" alt="AutoGPT" width="120"
-                  style="max-width: 120px; display: inline-block;">
-              </td>
-            </tr>
-
-            <!-- Divider -->
-            <tr>
-              <td bgcolor="#FFFFFF" class="card-inner" style="padding: 0 48px;">
-                <table width="100%" cellpadding="0" cellspacing="0" border="0">
-                  <tr>
-                    <td style="border-top: 1px solid #E8E5F0; font-size: 0; line-height: 0; height: 1px;">&nbsp;</td>
-                  </tr>
-                </table>
-              </td>
-            </tr>
-
-            <!-- Content -->
-            <tr>
-              <td class="card-inner" bgcolor="#FFFFFF"
-                style="padding: 36px 48px 44px; color: #1F1F20; font-family: 'Poppins', sans-serif; border-radius: 0 0 16px 16px;">
-                {{data.message|safe}}
-              </td>
-            </tr>
-
-          </table>
-          <!-- ============ END CARD ============ -->
-
-          <!-- Spacer -->
-          <table width="640" class="container" align="center" cellpadding="0" cellspacing="0" border="0"
-            style="max-width: 640px;">
-            <tr>
-              <td style="height: 40px; font-size: 0; line-height: 0;">&nbsp;</td>
-            </tr>
-          </table>
-
-          <!-- ============ FOOTER ============ -->
+        <td class="background" bgcolor="#070629" align="center" valign="top" style="padding: 0 8px;">
+          <!-- Email Content -->
           <table class="container" align="center" width="640" cellpadding="0" cellspacing="0" border="0"
             style="max-width: 640px;">
             <tr>
-              <td align="center" style="padding: 0 48px;">
-
-                <!-- Logo Text -->
-                <p
-                  style="font-family: 'Poppins', sans-serif; font-size: 22px; font-weight: 700; color: #FFFFFF; margin: 0 0 16px; letter-spacing: -0.5px;">
-                  AutoGPT</p>
-
-                <!-- Social Icons -->
-                <table role="presentation" cellpadding="0" cellspacing="0" border="0" align="center">
+              <td align="center">
+                <!-- Logo Section -->
+                <table class="container ml-4 ml-default-border" width="640" bgcolor="#E2ECFD" align="center" border="0"
+                  cellspacing="0" cellpadding="0" style="width: 640px; min-width: 640px;">
                   <tr>
-                    <td align="center" valign="middle" style="padding: 0 8px;">
-                      <a href="https://x.com/auto_gpt" target="_blank" style="text-decoration: none;">
-                        <img
-                          src="https://assets.mlcdn.com/ml/images/icons/default/rounded_corners/white/x.png"
-                          width="22" alt="X" style="display: block; opacity: 0.6;">
-                      </a>
+                    <td class="ml-default-border container" height="40" style="line-height: 40px; min-width: 640px;">
                     </td>
-                    <td align="center" valign="middle" style="padding: 0 8px;">
-                      <a href="https://discord.gg/autogpt" target="_blank" style="text-decoration: none;">
-                        <img
-                          src="https://assets.mlcdn.com/ml/images/icons/default/rounded_corners/white/discord.png"
-                          width="22" alt="Discord" style="display: block; opacity: 0.6;">
-                      </a>
-                    </td>
-                    <td align="center" valign="middle" style="padding: 0 8px;">
-                      <a href="https://agpt.co/" target="_blank" style="text-decoration: none;">
-                        <img
-                          src="https://assets.mlcdn.com/ml/images/icons/default/rounded_corners/white/website.png"
-                          width="22" alt="Website" style="display: block; opacity: 0.6;">
-                      </a>
+                  </tr>
+                  <tr>
+                    <td>
+                      <table align="center" width="100%" border="0" cellspacing="0" cellpadding="0">
+                        <tr>
+                          <td class="row" align="center" style="padding: 0 50px;">
+                            <img
+                              src="https://storage.mlcdn.com/account_image/597379/8QJ8kOjXakVvfe1kJLY2wWCObU1mp5EiDLfBlbQa.png"
+                              border="0" alt="" width="120" class="logo"
+                              style="max-width: 120px; display: inline-block;">
+                          </td>
+                        </tr>
+                      </table>
                     </td>
                   </tr>
                 </table>
 
-                <!-- Spacer -->
-                <table width="100%" cellpadding="0" cellspacing="0" border="0">
+                <!-- Main Content Section -->
+                <table class="container ml-6 ml-default-border" width="640" bgcolor="#E2ECFD" align="center" border="0"
+                  cellspacing="0" cellpadding="0" style="color: #070629; width: 640px; min-width: 640px;">
                   <tr>
-                    <td style="height: 20px; font-size: 0; line-height: 0;">&nbsp;</td>
+                    <td class="row" style="padding: 0 50px;">
+                      {{data.message|safe}}
+                    </td>
                   </tr>
                 </table>
 
-                <!-- Divider -->
-                <table width="100%" cellpadding="0" cellspacing="0" border="0">
+                <!-- Signature Section -->
+                <table class="container ml-8 ml-default-border" width="640" bgcolor="#E2ECFD" align="center" border="0"
+                  cellspacing="0" cellpadding="0" style="color: #070629; width: 640px; min-width: 640px;">
                   <tr>
-                    <td
-                      style="border-top: 1px solid rgba(255,255,255,0.08); font-size: 0; line-height: 0; height: 1px;">
-                      &nbsp;</td>
+                    <td class="row mobile-center" align="left" style="padding: 0 50px;">
+                      <table class="ml-8 wrapper" border="0" cellspacing="0" cellpadding="0"
+                        style="color: #070629; text-align: left;">
+                        <tr>
+                          <td class="col center mobile-center" align>
+                            <p
+                              style="font-family: 'Poppins', sans-serif; color: #070629; font-size: 16px; line-height: 165%; margin-top: 0; margin-bottom: 0;">
+                              Thank you for being a part of the AutoGPT community! Join the conversation on our Discord <a href="https://discord.gg/autogpt" style="color: #4285F4; text-decoration: underline;">here</a> and share your thoughts with us anytime.
+                            </p>
+                          </td>
+                        </tr>
+                      </table>
+                    </td>
                   </tr>
                 </table>
 
-                <!-- Footer Text -->
-                <p
-                  style="font-family: 'Poppins', sans-serif; color: rgba(255,255,255,0.3); font-size: 12px; line-height: 165%; margin: 16px 0 0; text-align: center;">
-                  AutoGPT &middot; 3rd Floor 1 Ashley Road, Altrincham, WA14 2DT, United Kingdom
-                </p>
-                <p
-                  style="font-family: 'Poppins', sans-serif; color: rgba(255,255,255,0.3); font-size: 12px; line-height: 165%; margin: 4px 0 0; text-align: center;">
-                  You received this email because you signed up on our website.
-                  <a href="{{data.unsubscribe_link}}"
-                    style="color: rgba(255,255,255,0.45); text-decoration: underline;">Unsubscribe</a>
-                </p>
-
+                <!-- Footer Section -->
+                <table class="container ml-10 ml-default-border" width="640" bgcolor="#ffffff" align="center" border="0"
+                  cellspacing="0" cellpadding="0" style="width: 640px; min-width: 640px;">
+                  <tr>
+                    <td class="row" style="padding: 0 50px;">
+                      <table align="center" width="100%" border="0" cellspacing="0" cellpadding="0">
+                        <tr>
+                          <td>
+                            <!-- Footer Content -->
+                            <table align="center" width="100%" border="0" cellspacing="0" cellpadding="0">
+                              <tr>
+                                <td class="col" align="left" valign="middle" width="120">
+                                  <img
+                                    src="https://storage.mlcdn.com/account_image/597379/8QJ8kOjXakVvfe1kJLY2wWCObU1mp5EiDLfBlbQa.png"
+                                    border="0" alt="" width="120" class="logo"
+                                    style="max-width: 120px; display: inline-block;">
+                                </td>
+                                <td class="col" width="40" height="30" style="line-height: 30px;"></td>
+                                <td class="col mobile-left" align="right" valign="middle" width="250">
+                                  <table role="presentation" cellpadding="0" cellspacing="0" border="0">
+                                    <tr>
+                                      <td align="center" valign="middle" width="18" style="padding: 0 5px 0 0;">
+                                        <a href="https://x.com/auto_gpt" target="blank" style="text-decoration: none;">
+                                          <img
+                                            src="https://assets.mlcdn.com/ml/images/icons/default/rounded_corners/black/x.png"
+                                            width="18" alt="x">
+                                        </a>
+                                      </td>
+                                      <td align="center" valign="middle" width="18" style="padding: 0 5px;">
+                                        <a href="https://discord.gg/autogpt" target="blank"
+                                          style="text-decoration: none;">
+                                          <img
+                                            src="https://assets.mlcdn.com/ml/images/icons/default/rounded_corners/black/discord.png"
+                                            width="18" alt="discord">
+                                        </a>
+                                      </td>
+                                      <td align="center" valign="middle" width="18" style="padding: 0 0 0 5px;">
+                                        <a href="https://agpt.co/" target="blank" style="text-decoration: none;">
+                                          <img
+                                            src="https://assets.mlcdn.com/ml/images/icons/default/rounded_corners/black/website.png"
+                                            width="18" alt="website">
+                                        </a>
+                                      </td>
+                                    </tr>
+                                  </table>
+                                </td>
+                              </tr>
+                            </table>
+                          </td>
+                        </tr>
+                        <tr>
+                          <td align="center" style="text-align: left!important;">
+                            <h5
+                              style="font-family: 'Poppins', sans-serif; color: #070629; font-size: 15px; line-height: 125%; font-weight: bold; font-style: normal; text-decoration: none; margin-bottom: 6px;">
+                              AutoGPT
+                            </h5>
+                          </td>
+                        </tr>
+                        <tr>
+                          <td align="center" style="text-align: left!important;">
+                            <p
+                              style="font-family: 'Poppins', sans-serif; color: #070629; font-size: 14px; line-height: 150%; display: inline-block; margin-bottom: 0;">
+                              3rd Floor 1 Ashley Road, Cheshire, United Kingdom, WA14 2DT, Altrincham<br>United Kingdom
+                            </p>
+                          </td>
+                        </tr>
+                        <tr>
+                          <td height="8" style="line-height: 8px;"></td>
+                        </tr>
+                        <tr>
+                          <td align="left" style="text-align: left!important;">
+                            <p
+                              style="font-family: 'Poppins', sans-serif; color: #070629; font-size: 14px; line-height: 150%; display: inline-block; margin-bottom: 0;">
+                              You received this email because you signed up on our website.</p>
+                          </td>
+                        </tr>
+                        <tr>
+                          <td height="1" style="line-height: 12px;"></td>
+                        </tr>
+                        <tr>
+                          <td align="left">
+                            <p
+                              style="font-family: 'Poppins', sans-serif; color: #070629; font-size: 14px; line-height: 150%; display: inline-block; margin-bottom: 0;">
+                              <a href="{{data.unsubscribe_link}}"
+                                style="color: #4285F4; font-weight: normal; font-style: normal; text-decoration: underline;">Unsubscribe</a>
+                            </p>
+                          </td>
+                        </tr>
+                      </table>
+                    </td>
+                  </tr>
+                </table>
               </td>
             </tr>
           </table>
-
         </td>
       </tr>
     </table>
   </div>
 </body>
 
-</html>
+</html>

autogpt_platform/backend/backend/notifications/templates/nightly_copilot.html.jinja2

@@ -1,41 +0,0 @@
-<div style="font-family: 'Poppins', sans-serif; color: #1F1F20;">
-  {{ email_body_html|safe }}
-
-  {% if approval_summary_html %}
-  <!-- Approval Callout -->
-  <table width="100%" cellpadding="0" cellspacing="0" border="0" style="margin-top: 28px; margin-bottom: 8px;">
-    <tr>
-      <td bgcolor="#FFF3E6"
-        style="background-color: #FFF3E6; border-left: 4px solid #FE8700; border-radius: 12px; padding: 20px 24px;">
-        <table width="100%" cellpadding="0" cellspacing="0" border="0">
-          <tr>
-            <td style="padding: 0 0 12px 0;">
-              <span
-                style="display: inline-block; background-color: #FE8700; color: #FFFFFF; font-size: 11px; font-weight: 600; letter-spacing: 0.05em; text-transform: uppercase; padding: 4px 10px; border-radius: 999px;">
-                Approval needed
-              </span>
-            </td>
-          </tr>
-        </table>
-        {{ approval_summary_html|safe }}
-        <p style="font-size: 14px; line-height: 165%; margin-top: 8px; margin-bottom: 0; color: #505057;">
-          I thought this was a good idea. If you want it to happen, please hit approve.
-        </p>
-      </td>
-    </tr>
-  </table>
-  {% endif %}
-
-  <!-- CTA Button -->
-  <table cellpadding="0" cellspacing="0" border="0" style="margin-top: 32px;">
-    <tr>
-      <td align="center" bgcolor="#7733F5"
-        style="background-color: #7733F5; border-radius: 12px;">
-        <a href="{{ cta_url }}"
-          style="display: inline-block; padding: 16px 36px; background-color: #7733F5; color: #FFFFFF; text-decoration: none; font-family: 'Poppins', sans-serif; font-weight: 600; font-size: 16px; border-radius: 12px; line-height: 1;">
-          {{ cta_label }}
-        </a>
-      </td>
-    </tr>
-  </table>
-</div>

autogpt_platform/backend/backend/notifications/templates/nightly_copilot_callback.html.jinja2

@@ -1,58 +0,0 @@
-<div style="font-family: 'Poppins', sans-serif; color: #1F1F20;">
-  <!-- Header -->
-  <h2
-    style="font-size: 24px; line-height: 130%; font-weight: 700; margin-top: 0; margin-bottom: 8px; color: #1F1F20; letter-spacing: -0.5px;">
-    Autopilot picked up where you left off
-  </h2>
-  <p style="font-size: 14px; line-height: 165%; margin-top: 0; margin-bottom: 28px; color: #505057;">
-    We used your recent Copilot activity to prepare a concrete follow-up for you.
-  </p>
-
-  <!-- Divider -->
-  <table width="100%" cellpadding="0" cellspacing="0" border="0" style="margin-bottom: 28px;">
-    <tr>
-      <td style="border-top: 1px solid #E8E5F0; font-size: 0; line-height: 0; height: 1px;">&nbsp;</td>
-    </tr>
-  </table>
-
-  <!-- Body -->
-  {{ email_body_html|safe }}
-
-  {% if approval_summary_html %}
-  <!-- Approval Callout -->
-  <table width="100%" cellpadding="0" cellspacing="0" border="0" style="margin-top: 28px; margin-bottom: 8px;">
-    <tr>
-      <td bgcolor="#FFF3E6"
-        style="background-color: #FFF3E6; border-left: 4px solid #FE8700; border-radius: 12px; padding: 20px 24px;">
-        <table width="100%" cellpadding="0" cellspacing="0" border="0">
-          <tr>
-            <td style="padding: 0 0 12px 0;">
-              <span
-                style="display: inline-block; background-color: #FE8700; color: #FFFFFF; font-size: 11px; font-weight: 600; letter-spacing: 0.05em; text-transform: uppercase; padding: 4px 10px; border-radius: 999px;">
-                Approval needed
-              </span>
-            </td>
-          </tr>
-        </table>
-        {{ approval_summary_html|safe }}
-        <p style="font-size: 14px; line-height: 165%; margin-top: 8px; margin-bottom: 0; color: #505057;">
-          I thought this was a good idea. If you want it to happen, please hit approve.
-        </p>
-      </td>
-    </tr>
-  </table>
-  {% endif %}
-
-  <!-- CTA Button -->
-  <table cellpadding="0" cellspacing="0" border="0" style="margin-top: 32px;">
-    <tr>
-      <td align="center" bgcolor="#7733F5"
-        style="background-color: #7733F5; border-radius: 12px;">
-        <a href="{{ cta_url }}"
-          style="display: inline-block; padding: 16px 36px; background-color: #7733F5; color: #FFFFFF; text-decoration: none; font-family: 'Poppins', sans-serif; font-weight: 600; font-size: 16px; border-radius: 12px; line-height: 1;">
-          {{ cta_label }}
-        </a>
-      </td>
-    </tr>
-  </table>
-</div>

autogpt_platform/backend/backend/notifications/templates/nightly_copilot_invite_cta.html.jinja2

@@ -1,64 +0,0 @@
-<div style="font-family: 'Poppins', sans-serif; color: #1F1F20;">
-  <!-- Header -->
-  <h2
-    style="font-size: 24px; line-height: 130%; font-weight: 700; margin-top: 0; margin-bottom: 8px; color: #1F1F20; letter-spacing: -0.5px;">
-    Your Autopilot beta access is waiting
-  </h2>
-  <p style="font-size: 14px; line-height: 165%; margin-top: 0; margin-bottom: 28px; color: #505057;">
-    You applied to try Autopilot. Here is a tailored example of how it can help once you jump back in.
-  </p>
-
-  <!-- Highlight Card -->
-  <table width="100%" cellpadding="0" cellspacing="0" border="0" style="margin-bottom: 28px;">
-    <tr>
-      <td bgcolor="#5424AE"
-        style="background-color: #5424AE; border-radius: 12px; padding: 20px 24px;">
-        <p
-          style="font-size: 14px; line-height: 165%; margin-top: 0; margin-bottom: 0; color: #FFFFFF; font-weight: 500;">
-          Autopilot works in the background to handle tasks, surface insights, and take action on your behalf.
-        </p>
-      </td>
-    </tr>
-  </table>
-
-  <!-- Body -->
-  {{ email_body_html|safe }}
-
-  {% if approval_summary_html %}
-  <!-- Approval Callout -->
-  <table width="100%" cellpadding="0" cellspacing="0" border="0" style="margin-top: 28px; margin-bottom: 8px;">
-    <tr>
-      <td bgcolor="#FFF3E6"
-        style="background-color: #FFF3E6; border-left: 4px solid #FE8700; border-radius: 12px; padding: 20px 24px;">
-        <table width="100%" cellpadding="0" cellspacing="0" border="0">
-          <tr>
-            <td style="padding: 0 0 12px 0;">
-              <span
-                style="display: inline-block; background-color: #FE8700; color: #FFFFFF; font-size: 11px; font-weight: 600; letter-spacing: 0.05em; text-transform: uppercase; padding: 4px 10px; border-radius: 999px;">
-                Approval needed
-              </span>
-            </td>
-          </tr>
-        </table>
-        {{ approval_summary_html|safe }}
-        <p style="font-size: 14px; line-height: 165%; margin-top: 8px; margin-bottom: 0; color: #505057;">
-          I thought this was a good idea. If you want it to happen, please hit approve.
-        </p>
-      </td>
-    </tr>
-  </table>
-  {% endif %}
-
-  <!-- CTA Button -->
-  <table cellpadding="0" cellspacing="0" border="0" style="margin-top: 32px;">
-    <tr>
-      <td align="center" bgcolor="#7733F5"
-        style="background-color: #7733F5; border-radius: 12px;">
-        <a href="{{ cta_url }}"
-          style="display: inline-block; padding: 16px 36px; background-color: #7733F5; color: #FFFFFF; text-decoration: none; font-family: 'Poppins', sans-serif; font-weight: 600; font-size: 16px; border-radius: 12px; line-height: 1;">
-          {{ cta_label }}
-        </a>
-      </td>
-    </tr>
-  </table>
-</div>

autogpt_platform/backend/backend/util/feature_flag.py

@@ -39,7 +39,6 @@ class Flag(str, Enum):
     ENABLE_PLATFORM_PAYMENT = "enable-platform-payment"
     CHAT = "chat"
     COPILOT_SDK = "copilot-sdk"
-    NIGHTLY_COPILOT = "nightly-copilot"
 
 
 def is_configured() -> bool:

autogpt_platform/backend/backend/util/file.py

@@ -275,13 +275,12 @@ async def store_media_file(
     # Process file
     elif file.startswith("data:"):
         # Data URI
-        match = re.match(r"^data:([^;]+);base64,(.*)$", file, re.DOTALL)
-        if not match:
+        parsed_uri = parse_data_uri(file)
+        if parsed_uri is None:
             raise ValueError(
                 "Invalid data URI format. Expected data:<mime>;base64,<data>"
             )
-        mime_type = match.group(1).strip().lower()
-        b64_content = match.group(2).strip()
+        mime_type, b64_content = parsed_uri
 
         # Generate filename and decode
         extension = _extension_from_mime(mime_type)
@@ -415,13 +414,70 @@ def get_dir_size(path: Path) -> int:
     return total
 
 
+async def resolve_media_content(
+    content: MediaFileType,
+    execution_context: "ExecutionContext",
+    *,
+    return_format: MediaReturnFormat,
+) -> MediaFileType:
+    """Resolve a ``MediaFileType`` value if it is a media reference, pass through otherwise.
+
+    Convenience wrapper around :func:`is_media_file_ref` + :func:`store_media_file`.
+    Plain text content (source code, filenames) is returned unchanged.  Media
+    references (``data:``, ``workspace://``, ``http(s)://``) are resolved via
+    :func:`store_media_file` using *return_format*.
+
+    Use this when a block field is typed as ``MediaFileType`` but may contain
+    either literal text or a media reference.
+    """
+    if not content or not is_media_file_ref(content):
+        return content
+    return await store_media_file(
+        content, execution_context, return_format=return_format
+    )
+
+
+def is_media_file_ref(value: str) -> bool:
+    """Return True if *value* looks like a ``MediaFileType`` reference.
+
+    Detects data URIs, workspace:// references, and HTTP(S) URLs — the
+    formats accepted by :func:`store_media_file`.  Plain text content
+    (e.g. source code, filenames) returns False.
+
+    Known limitation: HTTP(S) URL detection is heuristic.  Any string that
+    starts with ``http://`` or ``https://`` is treated as a media URL, even
+    if it appears as a URL inside source-code comments or documentation.
+    Blocks that produce source code or Markdown as output may therefore
+    trigger false positives.  Callers that need higher precision should
+    inspect the string further (e.g. verify the URL is reachable or has a
+    media-friendly extension).
+
+    Note: this does *not* match local file paths, which are ambiguous
+    (could be filenames or actual paths).  Blocks that need to resolve
+    local paths should check for them separately.
+    """
+    return value.startswith(("data:", "workspace://", "http://", "https://"))
+
+
+def parse_data_uri(value: str) -> tuple[str, str] | None:
+    """Parse a ``data:<mime>;base64,<payload>`` URI.
+
+    Returns ``(mime_type, base64_payload)`` if *value* is a valid data URI,
+    or ``None`` if it is not.
+    """
+    match = re.match(r"^data:([^;]+);base64,(.*)$", value, re.DOTALL)
+    if not match:
+        return None
+    return match.group(1).strip().lower(), match.group(2).strip()
+
+
 def get_mime_type(file: str) -> str:
     """
     Get the MIME type of a file, whether it's a data URI, URL, or local path.
     """
     if file.startswith("data:"):
-        match = re.match(r"^data:([^;]+);base64,", file)
-        return match.group(1) if match else "application/octet-stream"
+        parsed_uri = parse_data_uri(file)
+        return parsed_uri[0] if parsed_uri else "application/octet-stream"
 
     elif file.startswith(("http://", "https://")):
         parsed_url = urlparse(file)

autogpt_platform/backend/backend/util/file_content_parser.py

@@ -0,0 +1,375 @@
+"""Parse file content into structured Python objects based on file format.
+
+Used by the ``@@agptfile:`` expansion system to eagerly parse well-known file
+formats into native Python types *before* schema-driven coercion runs.  This
+lets blocks with ``Any``-typed inputs receive structured data rather than raw
+strings, while blocks expecting strings get the value coerced back via
+``convert()``.
+
+Supported formats:
+
+- **JSON** (``.json``) — arrays and objects are promoted; scalars stay as strings
+- **JSON Lines** (``.jsonl``, ``.ndjson``) — each non-empty line parsed as JSON;
+  when all lines are dicts with the same keys (tabular data), output is
+  ``list[list[Any]]`` with a header row, consistent with CSV/Parquet/Excel;
+  otherwise returns a plain ``list`` of parsed values
+- **CSV** (``.csv``) — ``csv.reader`` → ``list[list[str]]``
+- **TSV** (``.tsv``) — tab-delimited → ``list[list[str]]``
+- **YAML** (``.yaml``, ``.yml``) — parsed via PyYAML; containers only
+- **TOML** (``.toml``) — parsed via stdlib ``tomllib``
+- **Parquet** (``.parquet``) — via pandas/pyarrow → ``list[list[Any]]`` with header row
+- **Excel** (``.xlsx``) — via pandas/openpyxl → ``list[list[Any]]`` with header row
+  (legacy ``.xls`` is **not** supported — only the modern OOXML format)
+
+The **fallback contract** is enforced by :func:`parse_file_content`, not by
+individual parser functions.  If any parser raises, ``parse_file_content``
+catches the exception and returns the original content unchanged (string for
+text formats, bytes for binary formats).  Callers should never see an
+exception from the public API when ``strict=False``.
+"""
+
+import csv
+import io
+import json
+import logging
+import tomllib
+import zipfile
+from collections.abc import Callable
+
+# posixpath.splitext handles forward-slash URI paths correctly on all platforms,
+# unlike os.path.splitext which uses platform-native separators.
+from posixpath import splitext
+from typing import Any
+
+import yaml
+
+logger = logging.getLogger(__name__)
+
+# ---------------------------------------------------------------------------
+# Extension / MIME → format label mapping
+# ---------------------------------------------------------------------------
+
+_EXT_TO_FORMAT: dict[str, str] = {
+    ".json": "json",
+    ".jsonl": "jsonl",
+    ".ndjson": "jsonl",
+    ".csv": "csv",
+    ".tsv": "tsv",
+    ".yaml": "yaml",
+    ".yml": "yaml",
+    ".toml": "toml",
+    ".parquet": "parquet",
+    ".xlsx": "xlsx",
+}
+
+MIME_TO_FORMAT: dict[str, str] = {
+    "application/json": "json",
+    "application/x-ndjson": "jsonl",
+    "application/jsonl": "jsonl",
+    "text/csv": "csv",
+    "text/tab-separated-values": "tsv",
+    "application/x-yaml": "yaml",
+    "application/yaml": "yaml",
+    "text/yaml": "yaml",
+    "application/toml": "toml",
+    "application/vnd.apache.parquet": "parquet",
+    "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet": "xlsx",
+}
+
+# Formats that require raw bytes rather than decoded text.
+BINARY_FORMATS: frozenset[str] = frozenset({"parquet", "xlsx"})
+
+
+# ---------------------------------------------------------------------------
+# Public API  (top-down: main functions first, helpers below)
+# ---------------------------------------------------------------------------
+
+
+def infer_format_from_uri(uri: str) -> str | None:
+    """Return a format label based on URI extension or MIME fragment.
+
+    Returns ``None`` when the format cannot be determined — the caller should
+    fall back to returning the content as a plain string.
+    """
+    # 1. Check MIME fragment  (workspace://abc123#application/json)
+    if "#" in uri:
+        _, fragment = uri.rsplit("#", 1)
+        fmt = MIME_TO_FORMAT.get(fragment.lower())
+        if fmt:
+            return fmt
+
+    # 2. Check file extension from the path portion.
+    #    Strip the fragment first so ".json#mime" doesn't confuse splitext.
+    path = uri.split("#")[0].split("?")[0]
+    _, ext = splitext(path)
+    fmt = _EXT_TO_FORMAT.get(ext.lower())
+    if fmt is not None:
+        return fmt
+
+    # Legacy .xls is not supported — map it so callers can produce a
+    # user-friendly error instead of returning garbled binary.
+    if ext.lower() == ".xls":
+        return "xls"
+
+    return None
+
+
+def parse_file_content(content: str | bytes, fmt: str, *, strict: bool = False) -> Any:
+    """Parse *content* according to *fmt* and return a native Python value.
+
+    When *strict* is ``False`` (default), returns the original *content*
+    unchanged if *fmt* is not recognised or parsing fails for any reason.
+    This mode **never raises**.
+
+    When *strict* is ``True``, parsing errors are propagated to the caller.
+    Unrecognised formats or type mismatches (e.g. text for a binary format)
+    still return *content* unchanged without raising.
+    """
+    if fmt == "xls":
+        return (
+            "[Unsupported format] Legacy .xls files are not supported. "
+            "Please re-save the file as .xlsx (Excel 2007+) and upload again."
+        )
+
+    try:
+        if fmt in BINARY_FORMATS:
+            parser = _BINARY_PARSERS.get(fmt)
+            if parser is None:
+                return content
+            if isinstance(content, str):
+                # Caller gave us text for a binary format — can't parse.
+                return content
+            return parser(content)
+
+        parser = _TEXT_PARSERS.get(fmt)
+        if parser is None:
+            return content
+        if isinstance(content, bytes):
+            content = content.decode("utf-8", errors="replace")
+        return parser(content)
+
+    except PARSE_EXCEPTIONS:
+        if strict:
+            raise
+        logger.debug("Structured parsing failed for format=%s, falling back", fmt)
+        return content
+
+
+# ---------------------------------------------------------------------------
+# Exception loading helpers
+# ---------------------------------------------------------------------------
+
+
+def _load_openpyxl_exception() -> type[Exception]:
+    """Return openpyxl's InvalidFileException, raising ImportError if absent."""
+    from openpyxl.utils.exceptions import InvalidFileException  # noqa: PLC0415
+
+    return InvalidFileException
+
+
+def _load_arrow_exception() -> type[Exception]:
+    """Return pyarrow's ArrowException, raising ImportError if absent."""
+    from pyarrow import ArrowException  # noqa: PLC0415
+
+    return ArrowException
+
+
+def _optional_exc(loader: "Callable[[], type[Exception]]") -> "type[Exception] | None":
+    """Return the exception class from *loader*, or ``None`` if the dep is absent."""
+    try:
+        return loader()
+    except ImportError:
+        return None
+
+
+# Exception types that can be raised during file content parsing.
+# Shared between ``parse_file_content`` (which catches them in non-strict mode)
+# and ``file_ref._expand_bare_ref`` (which re-raises them as FileRefExpansionError).
+#
+# Optional-dependency exception types are loaded via a helper that raises
+# ``ImportError`` at *parse time* rather than silently becoming ``None`` here.
+# This ensures mypy sees clean types and missing deps surface as real errors.
+PARSE_EXCEPTIONS: tuple[type[BaseException], ...] = tuple(
+    exc
+    for exc in (
+        json.JSONDecodeError,
+        csv.Error,
+        yaml.YAMLError,
+        tomllib.TOMLDecodeError,
+        ValueError,
+        UnicodeDecodeError,
+        ImportError,
+        OSError,
+        KeyError,
+        TypeError,
+        zipfile.BadZipFile,
+        _optional_exc(_load_openpyxl_exception),
+        # ArrowException covers ArrowIOError and ArrowCapacityError which
+        # do not inherit from standard exceptions; ArrowInvalid/ArrowTypeError
+        # already map to ValueError/TypeError but this catches the rest.
+        _optional_exc(_load_arrow_exception),
+    )
+    if exc is not None
+)
+
+
+# ---------------------------------------------------------------------------
+# Text-based parsers  (content: str → Any)
+# ---------------------------------------------------------------------------
+
+
+def _parse_container(parser: Callable[[str], Any], content: str) -> list | dict | str:
+    """Parse *content* and return the result only if it is a container (list/dict).
+
+    Scalar values (strings, numbers, booleans, None) are discarded and the
+    original *content* string is returned instead.  This prevents e.g. a JSON
+    file containing just ``"42"`` from silently becoming an int.
+    """
+    parsed = parser(content)
+    if isinstance(parsed, (list, dict)):
+        return parsed
+    return content
+
+
+def _parse_json(content: str) -> list | dict | str:
+    return _parse_container(json.loads, content)
+
+
+def _parse_jsonl(content: str) -> Any:
+    lines = [json.loads(line) for line in content.splitlines() if line.strip()]
+    if not lines:
+        return content
+
+    # When every line is a dict with the same keys, convert to table format
+    # (header row + data rows) — consistent with CSV/TSV/Parquet/Excel output.
+    # Require ≥2 dicts so a single-line JSONL stays as [dict] (not a table).
+    if len(lines) >= 2 and all(isinstance(obj, dict) for obj in lines):
+        keys = list(lines[0].keys())
+        # Cache as tuple to avoid O(n×k) list allocations in the all() call.
+        keys_tuple = tuple(keys)
+        if keys and all(tuple(obj.keys()) == keys_tuple for obj in lines[1:]):
+            return [keys] + [[obj[k] for k in keys] for obj in lines]
+
+    return lines
+
+
+def _parse_csv(content: str) -> Any:
+    return _parse_delimited(content, delimiter=",")
+
+
+def _parse_tsv(content: str) -> Any:
+    return _parse_delimited(content, delimiter="\t")
+
+
+def _parse_delimited(content: str, *, delimiter: str) -> Any:
+    reader = csv.reader(io.StringIO(content), delimiter=delimiter)
+    # csv.reader never yields [] — blank lines yield [""]. Filter out
+    # rows where every cell is empty (i.e. truly blank lines).
+    rows = [row for row in reader if _row_has_content(row)]
+    if not rows:
+        return content
+    # If the declared delimiter produces only single-column rows, try
+    # sniffing the actual delimiter — catches misidentified files (e.g.
+    # a tab-delimited file with a .csv extension).
+    if len(rows[0]) == 1:
+        try:
+            dialect = csv.Sniffer().sniff(content[:8192])
+            if dialect.delimiter != delimiter:
+                reader = csv.reader(io.StringIO(content), dialect)
+                rows = [row for row in reader if _row_has_content(row)]
+        except csv.Error:
+            pass
+    if rows and len(rows[0]) >= 2:
+        return rows
+    return content
+
+
+def _row_has_content(row: list[str]) -> bool:
+    """Return True when *row* contains at least one non-empty cell.
+
+    ``csv.reader`` never yields ``[]`` — truly blank lines yield ``[""]``.
+    This predicate filters those out consistently across the initial read
+    and the sniffer-fallback re-read.
+    """
+    return any(cell for cell in row)
+
+
+def _parse_yaml(content: str) -> list | dict | str:
+    # NOTE: YAML anchor/alias expansion can amplify input beyond the 10MB cap.
+    # safe_load prevents code execution; for production hardening consider
+    # a YAML parser with expansion limits (e.g. ruamel.yaml with max_alias_count).
+    if "\n---" in content or content.startswith("---\n"):
+        # Multi-document YAML: only the first document is parsed; the rest
+        # are silently ignored by yaml.safe_load.  Warn so callers are aware.
+        logger.warning(
+            "Multi-document YAML detected (--- separator); "
+            "only the first document will be parsed."
+        )
+    return _parse_container(yaml.safe_load, content)
+
+
+def _parse_toml(content: str) -> Any:
+    parsed = tomllib.loads(content)
+    # tomllib.loads always returns a dict — return it even if empty.
+    return parsed
+
+
+_TEXT_PARSERS: dict[str, Callable[[str], Any]] = {
+    "json": _parse_json,
+    "jsonl": _parse_jsonl,
+    "csv": _parse_csv,
+    "tsv": _parse_tsv,
+    "yaml": _parse_yaml,
+    "toml": _parse_toml,
+}
+
+# ---------------------------------------------------------------------------
+# Binary-based parsers  (content: bytes → Any)
+# ---------------------------------------------------------------------------
+
+
+def _parse_parquet(content: bytes) -> list[list[Any]]:
+    import pandas as pd
+
+    df = pd.read_parquet(io.BytesIO(content))
+    return _df_to_rows(df)
+
+
+def _parse_xlsx(content: bytes) -> list[list[Any]]:
+    import pandas as pd
+
+    # Explicitly specify openpyxl engine; the default engine varies by pandas
+    # version and does not support legacy .xls (which is excluded by our format map).
+    df = pd.read_excel(io.BytesIO(content), engine="openpyxl")
+    return _df_to_rows(df)
+
+
+def _df_to_rows(df: Any) -> list[list[Any]]:
+    """Convert a DataFrame to ``list[list[Any]]`` with a header row.
+
+    NaN values are replaced with ``None`` so the result is JSON-serializable.
+    Uses explicit cell-level checking because ``df.where(df.notna(), None)``
+    silently converts ``None`` back to ``NaN`` in float64 columns.
+    """
+    header = df.columns.tolist()
+    rows = [
+        [None if _is_nan(cell) else cell for cell in row] for row in df.values.tolist()
+    ]
+    return [header] + rows
+
+
+def _is_nan(cell: Any) -> bool:
+    """Check if a cell value is NaN, handling non-scalar types (lists, dicts).
+
+    ``pd.isna()`` on a list/dict returns a boolean array which raises
+    ``ValueError`` in a boolean context.  Guard with a scalar check first.
+    """
+    import pandas as pd
+
+    return bool(pd.api.types.is_scalar(cell) and pd.isna(cell))
+
+
+_BINARY_PARSERS: dict[str, Callable[[bytes], Any]] = {
+    "parquet": _parse_parquet,
+    "xlsx": _parse_xlsx,
+}

autogpt_platform/backend/backend/util/file_content_parser_test.py

@@ -0,0 +1,624 @@
+"""Tests for file_content_parser — format inference and structured parsing."""
+
+import io
+import json
+
+import pytest
+
+from backend.util.file_content_parser import (
+    BINARY_FORMATS,
+    infer_format_from_uri,
+    parse_file_content,
+)
+
+# ---------------------------------------------------------------------------
+# infer_format_from_uri
+# ---------------------------------------------------------------------------
+
+
+class TestInferFormat:
+    # --- extension-based ---
+
+    def test_json_extension(self):
+        assert infer_format_from_uri("/home/user/data.json") == "json"
+
+    def test_jsonl_extension(self):
+        assert infer_format_from_uri("/tmp/events.jsonl") == "jsonl"
+
+    def test_ndjson_extension(self):
+        assert infer_format_from_uri("/tmp/events.ndjson") == "jsonl"
+
+    def test_csv_extension(self):
+        assert infer_format_from_uri("workspace:///reports/sales.csv") == "csv"
+
+    def test_tsv_extension(self):
+        assert infer_format_from_uri("/home/user/data.tsv") == "tsv"
+
+    def test_yaml_extension(self):
+        assert infer_format_from_uri("/home/user/config.yaml") == "yaml"
+
+    def test_yml_extension(self):
+        assert infer_format_from_uri("/home/user/config.yml") == "yaml"
+
+    def test_toml_extension(self):
+        assert infer_format_from_uri("/home/user/config.toml") == "toml"
+
+    def test_parquet_extension(self):
+        assert infer_format_from_uri("/data/table.parquet") == "parquet"
+
+    def test_xlsx_extension(self):
+        assert infer_format_from_uri("/data/spreadsheet.xlsx") == "xlsx"
+
+    def test_xls_extension_returns_xls_label(self):
+        # Legacy .xls is mapped so callers can produce a helpful error.
+        assert infer_format_from_uri("/data/old_spreadsheet.xls") == "xls"
+
+    def test_case_insensitive(self):
+        assert infer_format_from_uri("/data/FILE.JSON") == "json"
+        assert infer_format_from_uri("/data/FILE.CSV") == "csv"
+
+    def test_unicode_filename(self):
+        assert infer_format_from_uri("/home/user/\u30c7\u30fc\u30bf.json") == "json"
+        assert infer_format_from_uri("/home/user/\u00e9t\u00e9.csv") == "csv"
+
+    def test_unknown_extension(self):
+        assert infer_format_from_uri("/home/user/readme.txt") is None
+
+    def test_no_extension(self):
+        assert infer_format_from_uri("workspace://abc123") is None
+
+    # --- MIME-based ---
+
+    def test_mime_json(self):
+        assert infer_format_from_uri("workspace://abc123#application/json") == "json"
+
+    def test_mime_csv(self):
+        assert infer_format_from_uri("workspace://abc123#text/csv") == "csv"
+
+    def test_mime_tsv(self):
+        assert (
+            infer_format_from_uri("workspace://abc123#text/tab-separated-values")
+            == "tsv"
+        )
+
+    def test_mime_ndjson(self):
+        assert (
+            infer_format_from_uri("workspace://abc123#application/x-ndjson") == "jsonl"
+        )
+
+    def test_mime_yaml(self):
+        assert infer_format_from_uri("workspace://abc123#application/x-yaml") == "yaml"
+
+    def test_mime_xlsx(self):
+        uri = "workspace://abc123#application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
+        assert infer_format_from_uri(uri) == "xlsx"
+
+    def test_mime_parquet(self):
+        assert (
+            infer_format_from_uri("workspace://abc123#application/vnd.apache.parquet")
+            == "parquet"
+        )
+
+    def test_unknown_mime(self):
+        assert infer_format_from_uri("workspace://abc123#text/plain") is None
+
+    def test_unknown_mime_falls_through_to_extension(self):
+        # Unknown MIME (text/plain) should fall through to extension-based detection.
+        assert infer_format_from_uri("workspace:///data.csv#text/plain") == "csv"
+
+    # --- MIME takes precedence over extension ---
+
+    def test_mime_overrides_extension(self):
+        # .txt extension but JSON MIME → json
+        assert infer_format_from_uri("workspace:///file.txt#application/json") == "json"
+
+
+# ---------------------------------------------------------------------------
+# parse_file_content — JSON
+# ---------------------------------------------------------------------------
+
+
+class TestParseJson:
+    def test_array(self):
+        result = parse_file_content("[1, 2, 3]", "json")
+        assert result == [1, 2, 3]
+
+    def test_object(self):
+        result = parse_file_content('{"key": "value"}', "json")
+        assert result == {"key": "value"}
+
+    def test_nested(self):
+        content = json.dumps({"rows": [[1, 2], [3, 4]]})
+        result = parse_file_content(content, "json")
+        assert result == {"rows": [[1, 2], [3, 4]]}
+
+    def test_scalar_string_stays_as_string(self):
+        result = parse_file_content('"hello"', "json")
+        assert result == '"hello"'  # original content, not parsed
+
+    def test_scalar_number_stays_as_string(self):
+        result = parse_file_content("42", "json")
+        assert result == "42"
+
+    def test_scalar_boolean_stays_as_string(self):
+        result = parse_file_content("true", "json")
+        assert result == "true"
+
+    def test_null_stays_as_string(self):
+        result = parse_file_content("null", "json")
+        assert result == "null"
+
+    def test_invalid_json_fallback(self):
+        content = "not json at all"
+        result = parse_file_content(content, "json")
+        assert result == content
+
+    def test_empty_string_fallback(self):
+        result = parse_file_content("", "json")
+        assert result == ""
+
+    def test_bytes_input_decoded(self):
+        result = parse_file_content(b"[1, 2, 3]", "json")
+        assert result == [1, 2, 3]
+
+
+# ---------------------------------------------------------------------------
+# parse_file_content — JSONL
+# ---------------------------------------------------------------------------
+
+
+class TestParseJsonl:
+    def test_tabular_uniform_dicts_to_table_format(self):
+        """JSONL with uniform dict keys → table format (header + rows),
+        consistent with CSV/TSV/Parquet/Excel output."""
+        content = '{"name":"apple","color":"red"}\n{"name":"banana","color":"yellow"}\n{"name":"cherry","color":"red"}'
+        result = parse_file_content(content, "jsonl")
+        assert result == [
+            ["name", "color"],
+            ["apple", "red"],
+            ["banana", "yellow"],
+            ["cherry", "red"],
+        ]
+
+    def test_tabular_single_key_dicts(self):
+        """JSONL with single-key uniform dicts → table format."""
+        content = '{"a": 1}\n{"a": 2}\n{"a": 3}'
+        result = parse_file_content(content, "jsonl")
+        assert result == [["a"], [1], [2], [3]]
+
+    def test_tabular_blank_lines_skipped(self):
+        content = '{"a": 1}\n\n{"a": 2}\n'
+        result = parse_file_content(content, "jsonl")
+        assert result == [["a"], [1], [2]]
+
+    def test_heterogeneous_dicts_stay_as_list(self):
+        """JSONL with different keys across objects → list of dicts (no table)."""
+        content = '{"name":"apple"}\n{"color":"red"}\n{"size":3}'
+        result = parse_file_content(content, "jsonl")
+        assert result == [{"name": "apple"}, {"color": "red"}, {"size": 3}]
+
+    def test_partially_overlapping_keys_stay_as_list(self):
+        """JSONL dicts with partially overlapping keys → list of dicts."""
+        content = '{"name":"apple","color":"red"}\n{"name":"banana","size":"medium"}'
+        result = parse_file_content(content, "jsonl")
+        assert result == [
+            {"name": "apple", "color": "red"},
+            {"name": "banana", "size": "medium"},
+        ]
+
+    def test_mixed_types_stay_as_list(self):
+        """JSONL with non-dict lines → list of parsed values (no table)."""
+        content = '1\n"hello"\n[1,2]\n'
+        result = parse_file_content(content, "jsonl")
+        assert result == [1, "hello", [1, 2]]
+
+    def test_mixed_dicts_and_non_dicts_stay_as_list(self):
+        """JSONL mixing dicts and non-dicts → list of parsed values."""
+        content = '{"a": 1}\n42\n{"b": 2}'
+        result = parse_file_content(content, "jsonl")
+        assert result == [{"a": 1}, 42, {"b": 2}]
+
+    def test_tabular_preserves_key_order(self):
+        """Table header should follow the key order of the first object."""
+        content = '{"z": 1, "a": 2}\n{"z": 3, "a": 4}'
+        result = parse_file_content(content, "jsonl")
+        assert result[0] == ["z", "a"]  # order from first object
+        assert result[1] == [1, 2]
+        assert result[2] == [3, 4]
+
+    def test_single_dict_stays_as_list(self):
+        """Single-line JSONL with one dict → [dict], NOT a table.
+        Tabular detection requires ≥2 dicts to avoid vacuously true all()."""
+        content = '{"a": 1, "b": 2}'
+        result = parse_file_content(content, "jsonl")
+        assert result == [{"a": 1, "b": 2}]
+
+    def test_tabular_with_none_values(self):
+        """Uniform keys but some null values → table with None cells."""
+        content = '{"name":"apple","color":"red"}\n{"name":"banana","color":null}'
+        result = parse_file_content(content, "jsonl")
+        assert result == [
+            ["name", "color"],
+            ["apple", "red"],
+            ["banana", None],
+        ]
+
+    def test_empty_file_fallback(self):
+        result = parse_file_content("", "jsonl")
+        assert result == ""
+
+    def test_all_blank_lines_fallback(self):
+        result = parse_file_content("\n\n\n", "jsonl")
+        assert result == "\n\n\n"
+
+    def test_invalid_line_fallback(self):
+        content = '{"a": 1}\nnot json\n'
+        result = parse_file_content(content, "jsonl")
+        assert result == content  # fallback
+
+
+# ---------------------------------------------------------------------------
+# parse_file_content — CSV
+# ---------------------------------------------------------------------------
+
+
+class TestParseCsv:
+    def test_basic(self):
+        content = "Name,Score\nAlice,90\nBob,85"
+        result = parse_file_content(content, "csv")
+        assert result == [["Name", "Score"], ["Alice", "90"], ["Bob", "85"]]
+
+    def test_quoted_fields(self):
+        content = 'Name,Bio\nAlice,"Loves, commas"\nBob,Simple'
+        result = parse_file_content(content, "csv")
+        assert result[1] == ["Alice", "Loves, commas"]
+
+    def test_single_column_fallback(self):
+        # Only 1 column — not tabular enough.
+        content = "Name\nAlice\nBob"
+        result = parse_file_content(content, "csv")
+        assert result == content
+
+    def test_empty_rows_skipped(self):
+        content = "A,B\n\n1,2\n\n3,4"
+        result = parse_file_content(content, "csv")
+        assert result == [["A", "B"], ["1", "2"], ["3", "4"]]
+
+    def test_empty_file_fallback(self):
+        result = parse_file_content("", "csv")
+        assert result == ""
+
+    def test_utf8_bom(self):
+        """CSV with a UTF-8 BOM should parse correctly (BOM stripped by decode)."""
+        bom = "\ufeff"
+        content = bom + "Name,Score\nAlice,90\nBob,85"
+        result = parse_file_content(content, "csv")
+        # The BOM may be part of the first header cell; ensure rows are still parsed.
+        assert len(result) == 3
+        assert result[1] == ["Alice", "90"]
+        assert result[2] == ["Bob", "85"]
+
+
+# ---------------------------------------------------------------------------
+# parse_file_content — TSV
+# ---------------------------------------------------------------------------
+
+
+class TestParseTsv:
+    def test_basic(self):
+        content = "Name\tScore\nAlice\t90\nBob\t85"
+        result = parse_file_content(content, "tsv")
+        assert result == [["Name", "Score"], ["Alice", "90"], ["Bob", "85"]]
+
+    def test_single_column_fallback(self):
+        content = "Name\nAlice\nBob"
+        result = parse_file_content(content, "tsv")
+        assert result == content
+
+
+# ---------------------------------------------------------------------------
+# parse_file_content — YAML
+# ---------------------------------------------------------------------------
+
+
+class TestParseYaml:
+    def test_list(self):
+        content = "- apple\n- banana\n- cherry"
+        result = parse_file_content(content, "yaml")
+        assert result == ["apple", "banana", "cherry"]
+
+    def test_dict(self):
+        content = "name: Alice\nage: 30"
+        result = parse_file_content(content, "yaml")
+        assert result == {"name": "Alice", "age": 30}
+
+    def test_nested(self):
+        content = "users:\n  - name: Alice\n  - name: Bob"
+        result = parse_file_content(content, "yaml")
+        assert result == {"users": [{"name": "Alice"}, {"name": "Bob"}]}
+
+    def test_scalar_stays_as_string(self):
+        result = parse_file_content("hello world", "yaml")
+        assert result == "hello world"
+
+    def test_invalid_yaml_fallback(self):
+        content = ":\n  :\n    invalid: - -"
+        result = parse_file_content(content, "yaml")
+        # Malformed YAML should fall back to the original string, not raise.
+        assert result == content
+
+
+# ---------------------------------------------------------------------------
+# parse_file_content — TOML
+# ---------------------------------------------------------------------------
+
+
+class TestParseToml:
+    def test_basic(self):
+        content = '[server]\nhost = "localhost"\nport = 8080'
+        result = parse_file_content(content, "toml")
+        assert result == {"server": {"host": "localhost", "port": 8080}}
+
+    def test_flat(self):
+        content = 'name = "test"\ncount = 42'
+        result = parse_file_content(content, "toml")
+        assert result == {"name": "test", "count": 42}
+
+    def test_empty_string_returns_empty_dict(self):
+        result = parse_file_content("", "toml")
+        assert result == {}
+
+    def test_invalid_toml_fallback(self):
+        result = parse_file_content("not = [valid toml", "toml")
+        assert result == "not = [valid toml"
+
+
+# ---------------------------------------------------------------------------
+# parse_file_content — Parquet (binary)
+# ---------------------------------------------------------------------------
+
+
+try:
+    import pyarrow as _pa  # noqa: F401  # pyright: ignore[reportMissingImports]
+
+    _has_pyarrow = True
+except ImportError:
+    _has_pyarrow = False
+
+
+@pytest.mark.skipif(not _has_pyarrow, reason="pyarrow not installed")
+class TestParseParquet:
+    @pytest.fixture
+    def parquet_bytes(self) -> bytes:
+        import pandas as pd
+
+        df = pd.DataFrame({"Name": ["Alice", "Bob"], "Score": [90, 85]})
+        buf = io.BytesIO()
+        df.to_parquet(buf, index=False)
+        return buf.getvalue()
+
+    def test_basic(self, parquet_bytes: bytes):
+        result = parse_file_content(parquet_bytes, "parquet")
+        assert result == [["Name", "Score"], ["Alice", 90], ["Bob", 85]]
+
+    def test_string_input_fallback(self):
+        # Parquet is binary — string input can't be parsed.
+        result = parse_file_content("not parquet", "parquet")
+        assert result == "not parquet"
+
+    def test_invalid_bytes_fallback(self):
+        result = parse_file_content(b"not parquet bytes", "parquet")
+        assert result == b"not parquet bytes"
+
+    def test_empty_bytes_fallback(self):
+        """Empty binary input should return the empty bytes, not crash."""
+        result = parse_file_content(b"", "parquet")
+        assert result == b""
+
+    def test_nan_replaced_with_none(self):
+        """NaN values in Parquet must become None for JSON serializability."""
+        import math
+
+        import pandas as pd
+
+        df = pd.DataFrame({"A": [1.0, float("nan"), 3.0], "B": ["x", None, "z"]})
+        buf = io.BytesIO()
+        df.to_parquet(buf, index=False)
+        result = parse_file_content(buf.getvalue(), "parquet")
+        # Row with NaN in float col → None
+        assert result[2][0] is None  # float NaN → None
+        assert result[2][1] is None  # str None → None
+        # Ensure no NaN leaks
+        for row in result[1:]:
+            for cell in row:
+                if isinstance(cell, float):
+                    assert not math.isnan(cell), f"NaN leaked: {row}"
+
+
+# ---------------------------------------------------------------------------
+# parse_file_content — Excel (binary)
+# ---------------------------------------------------------------------------
+
+
+class TestParseExcel:
+    @pytest.fixture
+    def xlsx_bytes(self) -> bytes:
+        import pandas as pd
+
+        df = pd.DataFrame({"Name": ["Alice", "Bob"], "Score": [90, 85]})
+        buf = io.BytesIO()
+        df.to_excel(buf, index=False)  # type: ignore[arg-type]  # BytesIO is a valid target
+        return buf.getvalue()
+
+    def test_basic(self, xlsx_bytes: bytes):
+        result = parse_file_content(xlsx_bytes, "xlsx")
+        assert result == [["Name", "Score"], ["Alice", 90], ["Bob", 85]]
+
+    def test_string_input_fallback(self):
+        result = parse_file_content("not xlsx", "xlsx")
+        assert result == "not xlsx"
+
+    def test_invalid_bytes_fallback(self):
+        result = parse_file_content(b"not xlsx bytes", "xlsx")
+        assert result == b"not xlsx bytes"
+
+    def test_empty_bytes_fallback(self):
+        """Empty binary input should return the empty bytes, not crash."""
+        result = parse_file_content(b"", "xlsx")
+        assert result == b""
+
+    def test_nan_replaced_with_none(self):
+        """NaN values in float columns must become None for JSON serializability."""
+        import math
+
+        import pandas as pd
+
+        df = pd.DataFrame({"A": [1.0, float("nan"), 3.0], "B": ["x", "y", None]})
+        buf = io.BytesIO()
+        df.to_excel(buf, index=False)  # type: ignore[arg-type]
+        result = parse_file_content(buf.getvalue(), "xlsx")
+        # Row with NaN in float col → None, not float('nan')
+        assert result[2][0] is None  # float NaN → None
+        assert result[3][1] is None  # str None → None
+        # Ensure no NaN leaks
+        for row in result[1:]:  # skip header
+            for cell in row:
+                if isinstance(cell, float):
+                    assert not math.isnan(cell), f"NaN leaked: {row}"
+
+
+# ---------------------------------------------------------------------------
+# parse_file_content — unknown format / fallback
+# ---------------------------------------------------------------------------
+
+
+class TestFallback:
+    def test_unknown_format_returns_content(self):
+        result = parse_file_content("hello world", "xml")
+        assert result == "hello world"
+
+    def test_none_format_returns_content(self):
+        # Shouldn't normally be called with unrecognised format, but must not crash.
+        result = parse_file_content("hello", "unknown_format")
+        assert result == "hello"
+
+
+# ---------------------------------------------------------------------------
+# BINARY_FORMATS
+# ---------------------------------------------------------------------------
+
+
+class TestBinaryFormats:
+    def test_parquet_is_binary(self):
+        assert "parquet" in BINARY_FORMATS
+
+    def test_xlsx_is_binary(self):
+        assert "xlsx" in BINARY_FORMATS
+
+    def test_text_formats_not_binary(self):
+        for fmt in ("json", "jsonl", "csv", "tsv", "yaml", "toml"):
+            assert fmt not in BINARY_FORMATS
+
+
+# ---------------------------------------------------------------------------
+# MIME mapping
+# ---------------------------------------------------------------------------
+
+
+class TestMimeMapping:
+    def test_application_yaml(self):
+        assert infer_format_from_uri("workspace://abc123#application/yaml") == "yaml"
+
+
+# ---------------------------------------------------------------------------
+# CSV sniffer fallback
+# ---------------------------------------------------------------------------
+
+
+class TestCsvSnifferFallback:
+    def test_tab_delimited_with_csv_format(self):
+        """Tab-delimited content parsed as csv should use sniffer fallback."""
+        content = "Name\tScore\nAlice\t90\nBob\t85"
+        result = parse_file_content(content, "csv")
+        assert result == [["Name", "Score"], ["Alice", "90"], ["Bob", "85"]]
+
+    def test_sniffer_failure_returns_content(self):
+        """When sniffer fails, single-column falls back to raw content."""
+        content = "Name\nAlice\nBob"
+        result = parse_file_content(content, "csv")
+        assert result == content
+
+
+# ---------------------------------------------------------------------------
+# OpenpyxlInvalidFile fallback
+# ---------------------------------------------------------------------------
+
+
+class TestOpenpyxlFallback:
+    def test_invalid_xlsx_non_strict(self):
+        """Invalid xlsx bytes should fall back gracefully in non-strict mode."""
+        result = parse_file_content(b"not xlsx bytes", "xlsx")
+        assert result == b"not xlsx bytes"
+
+
+# ---------------------------------------------------------------------------
+# Header-only CSV
+# ---------------------------------------------------------------------------
+
+
+class TestHeaderOnlyCsv:
+    def test_header_only_csv_returns_header_row(self):
+        """CSV with only a header row (no data rows) should return [[header]]."""
+        content = "Name,Score"
+        result = parse_file_content(content, "csv")
+        assert result == [["Name", "Score"]]
+
+    def test_header_only_csv_with_trailing_newline(self):
+        content = "Name,Score\n"
+        result = parse_file_content(content, "csv")
+        assert result == [["Name", "Score"]]
+
+
+# ---------------------------------------------------------------------------
+# Binary format + line range (line range ignored for binary formats)
+# ---------------------------------------------------------------------------
+
+
+@pytest.mark.skipif(not _has_pyarrow, reason="pyarrow not installed")
+class TestBinaryFormatLineRange:
+    def test_parquet_ignores_line_range(self):
+        """Binary formats should parse the full file regardless of line range.
+
+        Line ranges are meaningless for binary formats (parquet/xlsx) — the
+        caller (file_ref._expand_bare_ref) passes raw bytes and the parser
+        should return the complete structured data.
+        """
+        import pandas as pd
+
+        df = pd.DataFrame({"A": [1, 2, 3], "B": [4, 5, 6]})
+        buf = io.BytesIO()
+        df.to_parquet(buf, index=False)
+        # parse_file_content itself doesn't take a line range — this tests
+        # that the full content is parsed even though the bytes could have
+        # been truncated upstream (it's not, by design).
+        result = parse_file_content(buf.getvalue(), "parquet")
+        assert result == [["A", "B"], [1, 4], [2, 5], [3, 6]]
+
+
+# ---------------------------------------------------------------------------
+# Legacy .xls UX
+# ---------------------------------------------------------------------------
+
+
+class TestXlsFallback:
+    def test_xls_returns_helpful_error_string(self):
+        """Uploading a .xls file should produce a helpful error, not garbled binary."""
+        result = parse_file_content(b"\xd0\xcf\x11\xe0garbled", "xls")
+        assert isinstance(result, str)
+        assert ".xlsx" in result
+        assert "not supported" in result.lower()
+
+    def test_xls_with_string_content(self):
+        result = parse_file_content("some text", "xls")
+        assert isinstance(result, str)
+        assert ".xlsx" in result

autogpt_platform/backend/backend/util/file_test.py

@@ -8,7 +8,12 @@ from unittest.mock import AsyncMock, MagicMock, patch
 import pytest
 
 from backend.data.execution import ExecutionContext
-from backend.util.file import store_media_file
+from backend.util.file import (
+    is_media_file_ref,
+    parse_data_uri,
+    resolve_media_content,
+    store_media_file,
+)
 from backend.util.type import MediaFileType
 
 
@@ -344,3 +349,162 @@ class TestFileCloudIntegration:
                     execution_context=make_test_context(graph_exec_id=graph_exec_id),
                     return_format="for_local_processing",
                 )
+
+
+# ---------------------------------------------------------------------------
+# is_media_file_ref
+# ---------------------------------------------------------------------------
+
+
+class TestIsMediaFileRef:
+    def test_data_uri(self):
+        assert is_media_file_ref("data:image/png;base64,iVBORw0KGg==") is True
+
+    def test_workspace_uri(self):
+        assert is_media_file_ref("workspace://abc123") is True
+
+    def test_workspace_uri_with_mime(self):
+        assert is_media_file_ref("workspace://abc123#image/png") is True
+
+    def test_http_url(self):
+        assert is_media_file_ref("http://example.com/image.png") is True
+
+    def test_https_url(self):
+        assert is_media_file_ref("https://example.com/image.png") is True
+
+    def test_plain_text(self):
+        assert is_media_file_ref("print('hello')") is False
+
+    def test_local_path(self):
+        assert is_media_file_ref("/tmp/file.txt") is False
+
+    def test_empty_string(self):
+        assert is_media_file_ref("") is False
+
+    def test_filename(self):
+        assert is_media_file_ref("image.png") is False
+
+
+# ---------------------------------------------------------------------------
+# parse_data_uri
+# ---------------------------------------------------------------------------
+
+
+class TestParseDataUri:
+    def test_valid_png(self):
+        result = parse_data_uri("data:image/png;base64,iVBORw0KGg==")
+        assert result is not None
+        mime, payload = result
+        assert mime == "image/png"
+        assert payload == "iVBORw0KGg=="
+
+    def test_valid_text(self):
+        result = parse_data_uri("data:text/plain;base64,SGVsbG8=")
+        assert result is not None
+        assert result[0] == "text/plain"
+        assert result[1] == "SGVsbG8="
+
+    def test_mime_case_normalized(self):
+        result = parse_data_uri("data:IMAGE/PNG;base64,abc")
+        assert result is not None
+        assert result[0] == "image/png"
+
+    def test_not_data_uri(self):
+        assert parse_data_uri("workspace://abc123") is None
+
+    def test_plain_text(self):
+        assert parse_data_uri("hello world") is None
+
+    def test_missing_base64(self):
+        assert parse_data_uri("data:image/png;utf-8,abc") is None
+
+    def test_empty_payload(self):
+        result = parse_data_uri("data:image/png;base64,")
+        assert result is not None
+        assert result[1] == ""
+
+
+# ---------------------------------------------------------------------------
+# resolve_media_content
+# ---------------------------------------------------------------------------
+
+
+class TestResolveMediaContent:
+    @pytest.mark.asyncio
+    async def test_plain_text_passthrough(self):
+        """Plain text content (not a media ref) passes through unchanged."""
+        ctx = make_test_context()
+        result = await resolve_media_content(
+            MediaFileType("print('hello')"),
+            ctx,
+            return_format="for_external_api",
+        )
+        assert result == "print('hello')"
+
+    @pytest.mark.asyncio
+    async def test_empty_string_passthrough(self):
+        """Empty string passes through unchanged."""
+        ctx = make_test_context()
+        result = await resolve_media_content(
+            MediaFileType(""),
+            ctx,
+            return_format="for_external_api",
+        )
+        assert result == ""
+
+    @pytest.mark.asyncio
+    async def test_media_ref_delegates_to_store(self):
+        """Media references are resolved via store_media_file."""
+        ctx = make_test_context()
+        with patch(
+            "backend.util.file.store_media_file",
+            new=AsyncMock(return_value=MediaFileType("data:image/png;base64,abc")),
+        ) as mock_store:
+            result = await resolve_media_content(
+                MediaFileType("workspace://img123"),
+                ctx,
+                return_format="for_external_api",
+            )
+        assert result == "data:image/png;base64,abc"
+        mock_store.assert_called_once_with(
+            MediaFileType("workspace://img123"),
+            ctx,
+            return_format="for_external_api",
+        )
+
+    @pytest.mark.asyncio
+    async def test_data_uri_delegates_to_store(self):
+        """Data URIs are also resolved via store_media_file."""
+        ctx = make_test_context()
+        data_uri = "data:image/png;base64,iVBORw0KGg=="
+        with patch(
+            "backend.util.file.store_media_file",
+            new=AsyncMock(return_value=MediaFileType(data_uri)),
+        ) as mock_store:
+            result = await resolve_media_content(
+                MediaFileType(data_uri),
+                ctx,
+                return_format="for_external_api",
+            )
+        assert result == data_uri
+        mock_store.assert_called_once()
+
+    @pytest.mark.asyncio
+    async def test_https_url_delegates_to_store(self):
+        """HTTPS URLs are resolved via store_media_file."""
+        ctx = make_test_context()
+        with patch(
+            "backend.util.file.store_media_file",
+            new=AsyncMock(return_value=MediaFileType("data:image/png;base64,abc")),
+        ) as mock_store:
+            result = await resolve_media_content(
+                MediaFileType("https://example.com/image.png"),
+                ctx,
+                return_format="for_local_processing",
+            )
+        assert result == "data:image/png;base64,abc"
+        mock_store.assert_called_once_with(
+            MediaFileType("https://example.com/image.png"),
+            ctx,
+            return_format="for_local_processing",
+        )

autogpt_platform/backend/backend/util/prompt.py

@@ -70,6 +70,10 @@ def _msg_tokens(msg: dict, enc) -> int:
                 # Count tool result tokens
                 tool_call_tokens += _tok_len(item.get("tool_use_id", ""), enc)
                 tool_call_tokens += _tok_len(item.get("content", ""), enc)
+            elif isinstance(item, dict) and item.get("type") == "text":
+                # Count text block tokens (standard: "text" key, fallback: "content")
+                text_val = item.get("text") or item.get("content", "")
+                tool_call_tokens += _tok_len(text_val, enc)
             elif isinstance(item, dict) and "content" in item:
                 # Other content types with content field
                 tool_call_tokens += _tok_len(item.get("content", ""), enc)
@@ -145,10 +149,16 @@ def _truncate_middle_tokens(text: str, enc, max_tok: int) -> str:
     if len(ids) <= max_tok:
         return text  # nothing to do
 
+    # Need at least 3 tokens (head + ellipsis + tail) for meaningful truncation
+    if max_tok < 1:
+        return ""
+    mid = enc.encode(" … ")
+    if max_tok < 3:
+        return enc.decode(ids[:max_tok])
+
     # Split the allowance between the two ends:
     head = max_tok // 2 - 1  # -1 for the ellipsis
     tail = max_tok - head - 1
-    mid = enc.encode(" … ")
     return enc.decode(ids[:head] + mid + ids[-tail:])
 
 
@@ -545,6 +555,14 @@ async def _summarize_messages_llm(
                     "- Actions taken and key decisions made\n"
                     "- Technical specifics (file names, tool outputs, function signatures)\n"
                     "- Errors encountered and resolutions applied\n\n"
+                    "IMPORTANT: Preserve all concrete references verbatim — these are small but "
+                    "critical for continuing the conversation:\n"
+                    "- File paths and directory paths (e.g. /src/app/page.tsx, ./output/result.csv)\n"
+                    "- Image/media file paths from tool outputs\n"
+                    "- URLs, API endpoints, and webhook addresses\n"
+                    "- Resource IDs, session IDs, and identifiers\n"
+                    "- Tool names that were called and their key parameters\n"
+                    "- Environment variables, config keys, and credentials names (not values)\n\n"
                     "Include ONLY the sections below that have relevant content "
                     "(skip sections with nothing to report):\n\n"
                     "## 1. Primary Request and Intent\n"
@@ -552,7 +570,8 @@ async def _summarize_messages_llm(
                     "## 2. Key Technical Concepts\n"
                     "Technologies, frameworks, tools, and patterns being used or discussed.\n\n"
                     "## 3. Files and Resources Involved\n"
-                    "Specific files examined or modified, with relevant snippets and identifiers.\n\n"
+                    "Specific files examined or modified, with relevant snippets and identifiers. "
+                    "Include exact file paths, image paths from tool outputs, and resource URLs.\n\n"
                     "## 4. Errors and Fixes\n"
                     "Problems encountered, error messages, and their resolutions.\n\n"
                     "## 5. All User Messages\n"
@@ -566,7 +585,7 @@ async def _summarize_messages_llm(
             },
             {"role": "user", "content": f"Summarize:\n\n{conversation_text}"},
         ],
-        max_tokens=1500,
+        max_tokens=2000,
         temperature=0.3,
     )
 
@@ -686,11 +705,15 @@ async def compress_context(
                     msgs = [summary_msg] + recent_msgs
 
                 logger.info(
-                    f"Context summarized: {original_count} -> {total_tokens()} tokens, "
-                    f"summarized {messages_summarized} messages"
+                    "Context summarized: %d -> %d tokens, summarized %d messages",
+                    original_count,
+                    total_tokens(),
+                    messages_summarized,
                 )
             except Exception as e:
-                logger.warning(f"Summarization failed, continuing with truncation: {e}")
+                logger.warning(
+                    "Summarization failed, continuing with truncation: %s", e
+                )
                 # Fall through to content truncation
 
     # ---- STEP 2: Normalize content ----------------------------------------

autogpt_platform/backend/backend/util/settings.py

@@ -1,7 +1,6 @@
 import json
 import os
 import re
-from datetime import date
 from enum import Enum
 from typing import Any, Dict, Generic, List, Set, Tuple, Type, TypeVar
 
@@ -126,22 +125,6 @@ class Config(UpdateTrackingModel["Config"], BaseSettings):
         default=True,
         description="If the invite-only signup gate is enforced",
     )
-    nightly_copilot_callback_start_date: date = Field(
-        default=date(2026, 2, 8),
-        description="Users with sessions since this date are eligible for the one-off autopilot callback cohort.",
-    )
-    nightly_copilot_invite_cta_start_date: date = Field(
-        default=date(2026, 3, 13),
-        description="Invite CTA cohort does not run before this date.",
-    )
-    nightly_copilot_invite_cta_delay_hours: int = Field(
-        default=48,
-        description="Delay after invite creation before the invite CTA can run.",
-    )
-    nightly_copilot_callback_token_ttl_hours: int = Field(
-        default=24 * 14,
-        description="TTL for nightly copilot callback tokens.",
-    )
     enable_credit: bool = Field(
         default=False,
         description="If user credit system is enabled or not",

autogpt_platform/backend/backend/util/text.py

@@ -86,13 +86,9 @@ class TextFormatter:
             "i",
             "img",
             "li",
-            "ol",
             "p",
             "span",
             "strong",
-            "table",
-            "td",
-            "tr",
             "u",
             "ul",
         ]
@@ -102,15 +98,6 @@ class TextFormatter:
             "*": ["class", "style"],
             "a": ["href"],
             "img": ["src"],
-            "table": [
-                "align",
-                "border",
-                "cellpadding",
-                "cellspacing",
-                "role",
-                "width",
-            ],
-            "td": ["align", "bgcolor", "colspan", "height", "valign", "width"],
         }
 
     def format_string(self, template_str: str, values=None, **kwargs) -> str:

autogpt_platform/backend/backend/util/url.py

@@ -1,9 +0,0 @@
-from backend.util.settings import Settings
-
-settings = Settings()
-
-
-def get_frontend_base_url() -> str:
-    return (
-        settings.config.frontend_base_url or settings.config.platform_base_url
-    ).rstrip("/")

autogpt_platform/backend/migrations/20260313143000_add_nightly_copilot_chat_sessions/migration.sql

@@ -1,67 +0,0 @@
--- CreateEnum
-CREATE TYPE "ChatSessionStartType" AS ENUM(
-  'MANUAL',
-  'AUTOPILOT_NIGHTLY',
-  'AUTOPILOT_CALLBACK',
-  'AUTOPILOT_INVITE_CTA'
-);
-
--- AlterTable
-ALTER TABLE "ChatSession"
-ADD COLUMN "startType" "ChatSessionStartType" NOT NULL DEFAULT 'MANUAL',
-ADD COLUMN "executionTag" TEXT,
-ADD COLUMN "sessionConfig" JSONB NOT NULL DEFAULT '{}',
-ADD COLUMN "completionReport" JSONB,
-ADD COLUMN "completionReportRepairCount" INTEGER NOT NULL DEFAULT 0,
-ADD COLUMN "completionReportRepairQueuedAt" TIMESTAMP(3),
-ADD COLUMN "completedAt" TIMESTAMP(3),
-ADD COLUMN "notificationEmailSentAt" TIMESTAMP(3),
-ADD COLUMN "notificationEmailSkippedAt" TIMESTAMP(3);
-
-COMMENT ON COLUMN "ChatSession"."sessionConfig" IS 'Validated by backend.copilot.session_types.ChatSessionConfig';
-COMMENT ON COLUMN "ChatSession"."completionReport" IS 'Validated by backend.copilot.session_types.StoredCompletionReport';
-
--- CreateTable
-CREATE TABLE "ChatSessionCallbackToken"(
-  "id" TEXT NOT NULL,
-  "createdAt" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP,
-  "updatedAt" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP,
-  "userId" TEXT NOT NULL,
-  "sourceSessionId" TEXT,
-  "callbackSessionMessage" TEXT NOT NULL,
-  "expiresAt" TIMESTAMP(3) NOT NULL,
-  "consumedAt" TIMESTAMP(3),
-  "consumedSessionId" TEXT,
-  CONSTRAINT "ChatSessionCallbackToken_pkey" PRIMARY KEY("id")
-);
-
--- CreateIndex
-CREATE UNIQUE INDEX "ChatSession_userId_executionTag_key"
-ON "ChatSession"("userId",
-  "executionTag");
-
--- CreateIndex
-CREATE INDEX "ChatSession_userId_startType_updatedAt_idx"
-ON "ChatSession"("userId",
-  "startType",
-  "updatedAt");
-
--- CreateIndex
-CREATE INDEX "ChatSessionCallbackToken_userId_expiresAt_idx"
-ON "ChatSessionCallbackToken"("userId",
-  "expiresAt");
-
--- CreateIndex
-CREATE INDEX "ChatSessionCallbackToken_consumedSessionId_idx"
-ON "ChatSessionCallbackToken"("consumedSessionId");
-
--- AddForeignKey
-ALTER TABLE "ChatSessionCallbackToken" ADD CONSTRAINT "ChatSessionCallbackToken_userId_fkey" FOREIGN KEY("userId") REFERENCES "User"("id")
-ON DELETE CASCADE
-ON UPDATE CASCADE;
-
--- AddForeignKey
-ALTER TABLE "ChatSessionCallbackToken" ADD CONSTRAINT "ChatSessionCallbackToken_sourceSessionId_fkey" FOREIGN KEY("sourceSessionId") REFERENCES "ChatSession"("id")
-ON DELETE 
-CASCADE
-ON UPDATE CASCADE;

autogpt_platform/backend/poetry.lock

@@ -1360,6 +1360,18 @@ files = [
 dnspython = ">=2.0.0"
 idna = ">=2.0.0"
 
+[[package]]
+name = "et-xmlfile"
+version = "2.0.0"
+description = "An implementation of lxml.xmlfile for the standard library"
+optional = false
+python-versions = ">=3.8"
+groups = ["main"]
+files = [
+    {file = "et_xmlfile-2.0.0-py3-none-any.whl", hash = "sha256:7a91720bc756843502c3b7504c77b8fe44217c85c537d85037f0f536151b2caa"},
+    {file = "et_xmlfile-2.0.0.tar.gz", hash = "sha256:dab3f4764309081ce75662649be815c4c9081e88f0837825f90fd28317d4da54"},
+]
+
 [[package]]
 name = "exa-py"
 version = "1.16.1"
@@ -4228,6 +4240,21 @@ datalib = ["numpy (>=1)", "pandas (>=1.2.3)", "pandas-stubs (>=1.1.0.11)"]
 realtime = ["websockets (>=13,<16)"]
 voice-helpers = ["numpy (>=2.0.2)", "sounddevice (>=0.5.1)"]
 
+[[package]]
+name = "openpyxl"
+version = "3.1.5"
+description = "A Python library to read/write Excel 2010 xlsx/xlsm files"
+optional = false
+python-versions = ">=3.8"
+groups = ["main"]
+files = [
+    {file = "openpyxl-3.1.5-py2.py3-none-any.whl", hash = "sha256:5282c12b107bffeef825f4617dc029afaf41d0ea60823bbb665ef3079dc79de2"},
+    {file = "openpyxl-3.1.5.tar.gz", hash = "sha256:cf0e3cf56142039133628b5acffe8ef0c12bc902d2aadd3e0fe5878dc08d1050"},
+]
+
+[package.dependencies]
+et-xmlfile = "*"
+
 [[package]]
 name = "opentelemetry-api"
 version = "1.39.1"
@@ -5430,6 +5457,66 @@ files = [
     {file = "psycopg2_binary-2.9.11-cp39-cp39-win_amd64.whl", hash = "sha256:875039274f8a2361e5207857899706da840768e2a775bf8c65e82f60b197df02"},
 ]
 
+[[package]]
+name = "pyarrow"
+version = "23.0.1"
+description = "Python library for Apache Arrow"
+optional = false
+python-versions = ">=3.10"
+groups = ["main"]
+files = [
+    {file = "pyarrow-23.0.1-cp310-cp310-macosx_12_0_arm64.whl", hash = "sha256:3fab8f82571844eb3c460f90a75583801d14ca0cc32b1acc8c361650e006fd56"},
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+    {file = "pyarrow-23.0.1-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:e052a211c5ac9848ae15d5ec875ed0943c0221e2fcfe69eee80b604b4e703222"},
+    {file = "pyarrow-23.0.1-cp310-cp310-win_amd64.whl", hash = "sha256:5abde149bb3ce524782d838eb67ac095cd3fd6090eba051130589793f1a7f76d"},
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+    {file = "pyarrow-23.0.1.tar.gz", hash = "sha256:b8c5873e33440b2bc2f4a79d2b47017a89c5a24116c055625e6f2ee50523f019"},
+]
+
 [[package]]
 name = "pyasn1"
 version = "0.6.2"
@@ -8882,4 +8969,4 @@ cffi = ["cffi (>=1.17,<2.0) ; platform_python_implementation != \"PyPy\" and pyt
 [metadata]
 lock-version = "2.1"
 python-versions = ">=3.10,<3.14"
-content-hash = "4e4365721cd3b68c58c237353b74adae1c64233fd4446904c335f23eb866fdca"
+content-hash = "86dab25684dd46e635a33bd33281a926e5626a874ecc048c34389fecf34a87d8"

autogpt_platform/backend/pyproject.toml

@@ -37,7 +37,6 @@ jinja2 = "^3.1.6"
 jsonref = "^1.1.0"
 jsonschema = "^4.25.0"
 langfuse = "^3.14.1"
-markdown-it-py = "^3.0.0"
 launchdarkly-server-sdk = "^9.14.1"
 mem0ai = "^0.1.115"
 moviepy = "^2.1.2"
@@ -93,6 +92,8 @@ gravitas-md2gdocs = "^0.1.0"
 posthog = "^7.6.0"
 fpdf2 = "^2.8.6"
 langsmith = "^0.7.7"
+openpyxl = "^3.1.5"
+pyarrow = "^23.0.0"
 
 [tool.poetry.group.dev.dependencies]
 aiohappyeyeballs = "^2.6.1"

autogpt_platform/backend/schema.prisma

@@ -66,7 +66,6 @@ model User {
   PendingHumanReviews   PendingHumanReview[]
   Workspace             UserWorkspace?
   ClaimedInvite         InvitedUser?            @relation("InvitedUserAuthUser")
-  ChatSessionCallbackTokens ChatSessionCallbackToken[]
 
   // OAuth Provider relations
   OAuthApplications       OAuthApplication[]
@@ -88,13 +87,6 @@ enum TallyComputationStatus {
   FAILED
 }
 
-enum ChatSessionStartType {
-  MANUAL
-  AUTOPILOT_NIGHTLY
-  AUTOPILOT_CALLBACK
-  AUTOPILOT_INVITE_CTA
-}
-
 model InvitedUser {
   id        String   @id @default(uuid())
   createdAt DateTime @default(now())
@@ -256,15 +248,6 @@ model ChatSession {
   // Session metadata
   title       String?
   credentials Json    @default("{}") // Map of provider -> credential metadata
-  startType   ChatSessionStartType @default(MANUAL)
-  executionTag String?
-  sessionConfig Json @default("{}") // ChatSessionConfig payload from backend.copilot.session_types.ChatSessionConfig
-  completionReport Json? // StoredCompletionReport payload from backend.copilot.session_types.StoredCompletionReport
-  completionReportRepairCount Int @default(0)
-  completionReportRepairQueuedAt DateTime?
-  completedAt DateTime?
-  notificationEmailSentAt DateTime?
-  notificationEmailSkippedAt DateTime?
 
   // Rate limiting counters (stored as JSON maps)
   successfulAgentRuns      Json @default("{}") // Map of graph_id -> count
@@ -275,31 +258,8 @@ model ChatSession {
   totalCompletionTokens Int @default(0)
 
   Messages ChatMessage[]
-  CallbackTokens ChatSessionCallbackToken[] @relation("ChatSessionCallbackSource")
 
   @@index([userId, updatedAt])
-  @@index([userId, startType, updatedAt])
-  @@unique([userId, executionTag])
-}
-
-model ChatSessionCallbackToken {
-  id        String   @id @default(uuid())
-  createdAt DateTime @default(now())
-  updatedAt DateTime @default(now()) @updatedAt
-
-  userId String
-  User   User @relation(fields: [userId], references: [id], onDelete: Cascade)
-
-  sourceSessionId String?
-  SourceSession   ChatSession? @relation("ChatSessionCallbackSource", fields: [sourceSessionId], references: [id], onDelete: Cascade)
-
-  callbackSessionMessage String
-  expiresAt DateTime
-  consumedAt DateTime?
-  consumedSessionId String?
-
-  @@index([userId, expiresAt])
-  @@index([consumedSessionId])
 }
 
 model ChatMessage {

autogpt_platform/frontend/src/app/(platform)/admin/copilot/components/AdminCopilotPage/AdminCopilotPage.tsx

@@ -1,318 +0,0 @@
-"use client";
-
-import { ChatSessionStartType } from "@/app/api/__generated__/models/chatSessionStartType";
-import { Badge } from "@/components/atoms/Badge/Badge";
-import { Button } from "@/components/atoms/Button/Button";
-import { Card } from "@/components/atoms/Card/Card";
-import { Input } from "@/components/atoms/Input/Input";
-import { CopilotUsersTable } from "../CopilotUsersTable/CopilotUsersTable";
-import { useAdminCopilotPage } from "../../useAdminCopilotPage";
-
-function getStartTypeLabel(startType: ChatSessionStartType) {
-  if (startType === ChatSessionStartType.AUTOPILOT_INVITE_CTA) {
-    return "CTA";
-  }
-
-  if (startType === ChatSessionStartType.AUTOPILOT_NIGHTLY) {
-    return "Nightly";
-  }
-
-  if (startType === ChatSessionStartType.AUTOPILOT_CALLBACK) {
-    return "Callback";
-  }
-
-  return startType;
-}
-
-const triggerOptions = [
-  {
-    label: "Trigger CTA",
-    description:
-      "Runs the beta invite CTA flow even if the user would not normally qualify.",
-    startType: ChatSessionStartType.AUTOPILOT_INVITE_CTA,
-    variant: "primary" as const,
-  },
-  {
-    label: "Trigger Nightly",
-    description:
-      "Runs the nightly proactive Autopilot flow immediately for the selected user.",
-    startType: ChatSessionStartType.AUTOPILOT_NIGHTLY,
-    variant: "outline" as const,
-  },
-  {
-    label: "Trigger Callback",
-    description:
-      "Runs the callback re-engagement flow without checking the normal callback cohort.",
-    startType: ChatSessionStartType.AUTOPILOT_CALLBACK,
-    variant: "secondary" as const,
-  },
-];
-
-export function AdminCopilotPage() {
-  const {
-    search,
-    selectedUser,
-    pendingTriggerType,
-    lastTriggeredSession,
-    lastEmailSweepResult,
-    searchedUsers,
-    searchErrorMessage,
-    isSearchingUsers,
-    isRefreshingUsers,
-    isTriggeringSession,
-    isSendingPendingEmails,
-    hasSearch,
-    setSearch,
-    handleSelectUser,
-    handleSendPendingEmails,
-    handleTriggerSession,
-  } = useAdminCopilotPage();
-
-  return (
-    <div className="mx-auto flex max-w-7xl flex-col gap-6 p-6">
-      <div className="flex flex-col gap-2">
-        <h1 className="text-3xl font-bold text-zinc-900">Copilot</h1>
-        <p className="max-w-3xl text-sm text-zinc-600">
-          Manually create CTA, Nightly, or Callback Copilot sessions for a
-          specific user. These controls bypass the normal eligibility checks so
-          you can test each flow directly.
-        </p>
-      </div>
-
-      <div className="grid gap-6 xl:grid-cols-[minmax(0,1.35fr),24rem]">
-        <Card className="border border-zinc-200 shadow-sm">
-          <div className="flex flex-col gap-4">
-            <Input
-              id="copilot-user-search"
-              label="Search users"
-              hint="Results update as you type"
-              placeholder="Search by email, name, or user ID"
-              value={search}
-              onChange={(event) => setSearch(event.target.value)}
-            />
-            {searchErrorMessage ? (
-              <p className="-mt-2 text-sm text-red-500">{searchErrorMessage}</p>
-            ) : null}
-            <CopilotUsersTable
-              users={searchedUsers}
-              isLoading={isSearchingUsers}
-              isRefreshing={isRefreshingUsers}
-              hasSearch={hasSearch}
-              selectedUserId={selectedUser?.id ?? null}
-              onSelectUser={handleSelectUser}
-            />
-          </div>
-        </Card>
-
-        <div className="flex flex-col gap-6">
-          <Card className="border border-zinc-200 shadow-sm">
-            <div className="flex flex-col gap-4">
-              <div className="flex items-center justify-between gap-3">
-                <h2 className="text-xl font-semibold text-zinc-900">
-                  Selected user
-                </h2>
-                {selectedUser ? <Badge variant="info">Ready</Badge> : null}
-              </div>
-
-              {selectedUser ? (
-                <div className="flex flex-col gap-3 text-sm text-zinc-600">
-                  <div>
-                    <span className="text-xs uppercase tracking-[0.18em] text-zinc-400">
-                      Email
-                    </span>
-                    <p className="mt-1 font-medium text-zinc-900">
-                      {selectedUser.email}
-                    </p>
-                  </div>
-                  <div>
-                    <span className="text-xs uppercase tracking-[0.18em] text-zinc-400">
-                      Name
-                    </span>
-                    <p className="mt-1">
-                      {selectedUser.name || "No display name"}
-                    </p>
-                  </div>
-                  <div>
-                    <span className="text-xs uppercase tracking-[0.18em] text-zinc-400">
-                      Timezone
-                    </span>
-                    <p className="mt-1">{selectedUser.timezone}</p>
-                  </div>
-                  <div>
-                    <span className="text-xs uppercase tracking-[0.18em] text-zinc-400">
-                      User ID
-                    </span>
-                    <p className="mt-1 break-all font-mono text-xs text-zinc-500">
-                      {selectedUser.id}
-                    </p>
-                  </div>
-                </div>
-              ) : (
-                <p className="text-sm text-zinc-500">
-                  Select a user from the results table to enable manual Copilot
-                  triggers.
-                </p>
-              )}
-            </div>
-          </Card>
-
-          <Card className="border border-zinc-200 shadow-sm">
-            <div className="flex flex-col gap-4">
-              <div className="flex flex-col gap-1">
-                <h2 className="text-xl font-semibold text-zinc-900">
-                  Trigger flows
-                </h2>
-                <p className="text-sm text-zinc-600">
-                  Each action creates a new session immediately for the selected
-                  user.
-                </p>
-              </div>
-
-              <div className="flex flex-col gap-3">
-                {triggerOptions.map((option) => (
-                  <div
-                    key={option.startType}
-                    className="rounded-2xl border border-zinc-200 p-4"
-                  >
-                    <div className="flex flex-col gap-3">
-                      <div className="flex flex-col gap-1">
-                        <span className="font-medium text-zinc-900">
-                          {option.label}
-                        </span>
-                        <p className="text-sm text-zinc-600">
-                          {option.description}
-                        </p>
-                      </div>
-                      <Button
-                        variant={option.variant}
-                        disabled={!selectedUser || isTriggeringSession}
-                        loading={pendingTriggerType === option.startType}
-                        onClick={() => handleTriggerSession(option.startType)}
-                      >
-                        {option.label}
-                      </Button>
-                    </div>
-                  </div>
-                ))}
-              </div>
-            </div>
-          </Card>
-
-          <Card className="border border-zinc-200 shadow-sm">
-            <div className="flex flex-col gap-4">
-              <div className="flex flex-col gap-1">
-                <h2 className="text-xl font-semibold text-zinc-900">
-                  Email follow-up
-                </h2>
-                <p className="text-sm text-zinc-600">
-                  Run the pending Copilot completion-email sweep immediately for
-                  the selected user.
-                </p>
-              </div>
-              <Button
-                variant="secondary"
-                disabled={!selectedUser || isSendingPendingEmails}
-                loading={isSendingPendingEmails}
-                onClick={handleSendPendingEmails}
-              >
-                Send pending emails
-              </Button>
-              {selectedUser && lastEmailSweepResult ? (
-                <div className="rounded-2xl border border-zinc-200 p-4 text-sm text-zinc-600">
-                  <p className="font-medium text-zinc-900">
-                    Last sweep for {selectedUser.email}
-                  </p>
-                  <div className="mt-3 grid gap-3 sm:grid-cols-2">
-                    <div>
-                      <span className="text-xs uppercase tracking-[0.18em] text-zinc-400">
-                        Candidates
-                      </span>
-                      <p className="mt-1 text-zinc-900">
-                        {lastEmailSweepResult.candidate_count}
-                      </p>
-                    </div>
-                    <div>
-                      <span className="text-xs uppercase tracking-[0.18em] text-zinc-400">
-                        Processed
-                      </span>
-                      <p className="mt-1 text-zinc-900">
-                        {lastEmailSweepResult.processed_count}
-                      </p>
-                    </div>
-                    <div>
-                      <span className="text-xs uppercase tracking-[0.18em] text-zinc-400">
-                        Sent
-                      </span>
-                      <p className="mt-1 text-zinc-900">
-                        {lastEmailSweepResult.sent_count}
-                      </p>
-                    </div>
-                    <div>
-                      <span className="text-xs uppercase tracking-[0.18em] text-zinc-400">
-                        Skipped
-                      </span>
-                      <p className="mt-1 text-zinc-900">
-                        {lastEmailSweepResult.skipped_count}
-                      </p>
-                    </div>
-                    <div>
-                      <span className="text-xs uppercase tracking-[0.18em] text-zinc-400">
-                        Repairs queued
-                      </span>
-                      <p className="mt-1 text-zinc-900">
-                        {lastEmailSweepResult.repair_queued_count}
-                      </p>
-                    </div>
-                    <div>
-                      <span className="text-xs uppercase tracking-[0.18em] text-zinc-400">
-                        Running / failed
-                      </span>
-                      <p className="mt-1 text-zinc-900">
-                        {lastEmailSweepResult.running_count} /{" "}
-                        {lastEmailSweepResult.failed_count}
-                      </p>
-                    </div>
-                  </div>
-                </div>
-              ) : null}
-            </div>
-          </Card>
-
-          {selectedUser && lastTriggeredSession ? (
-            <Card className="border border-zinc-200 shadow-sm">
-              <div className="flex flex-col gap-4">
-                <div className="flex items-center justify-between gap-3">
-                  <h2 className="text-xl font-semibold text-zinc-900">
-                    Latest session
-                  </h2>
-                  <Badge variant="success">
-                    {getStartTypeLabel(lastTriggeredSession.start_type)}
-                  </Badge>
-                </div>
-                <p className="text-sm text-zinc-600">
-                  A new Copilot session was created for {selectedUser.email}.
-                </p>
-                <div>
-                  <span className="text-xs uppercase tracking-[0.18em] text-zinc-400">
-                    Session ID
-                  </span>
-                  <p className="mt-1 break-all font-mono text-xs text-zinc-500">
-                    {lastTriggeredSession.session_id}
-                  </p>
-                </div>
-                <Button
-                  as="NextLink"
-                  href={`/copilot?sessionId=${lastTriggeredSession.session_id}&showAutopilot=1`}
-                  target="_blank"
-                  rel="noreferrer"
-                >
-                  Open session
-                </Button>
-              </div>
-            </Card>
-          ) : null}
-        </div>
-      </div>
-    </div>
-  );
-}

autogpt_platform/frontend/src/app/(platform)/admin/copilot/components/CopilotUsersTable/CopilotUsersTable.tsx

@@ -1,121 +0,0 @@
-"use client";
-
-import type { AdminCopilotUserSummary } from "@/app/api/__generated__/models/adminCopilotUserSummary";
-import { Button } from "@/components/atoms/Button/Button";
-import {
-  Table,
-  TableBody,
-  TableCell,
-  TableHead,
-  TableHeader,
-  TableRow,
-} from "@/components/__legacy__/ui/table";
-
-interface Props {
-  users: AdminCopilotUserSummary[];
-  isLoading: boolean;
-  isRefreshing: boolean;
-  hasSearch: boolean;
-  selectedUserId: string | null;
-  onSelectUser: (user: AdminCopilotUserSummary) => void;
-}
-
-function formatDate(value: Date) {
-  return value.toLocaleString();
-}
-
-export function CopilotUsersTable({
-  users,
-  isLoading,
-  isRefreshing,
-  hasSearch,
-  selectedUserId,
-  onSelectUser,
-}: Props) {
-  let emptyMessage = "Search by email, name, or user ID to find a user.";
-  if (hasSearch && isLoading) {
-    emptyMessage = "Searching users...";
-  } else if (hasSearch) {
-    emptyMessage = "No matching users found.";
-  }
-
-  return (
-    <div className="flex flex-col gap-4">
-      <div className="flex items-center justify-between gap-4">
-        <div className="flex flex-col gap-1">
-          <h2 className="text-xl font-semibold text-zinc-900">User results</h2>
-          <p className="text-sm text-zinc-600">
-            Select an existing user, then run an Autopilot flow manually.
-          </p>
-        </div>
-        <span className="text-xs uppercase tracking-[0.18em] text-zinc-400">
-          {isRefreshing
-            ? "Refreshing"
-            : `${users.length} result${users.length === 1 ? "" : "s"}`}
-        </span>
-      </div>
-
-      <div className="overflow-hidden rounded-2xl border border-zinc-200">
-        <Table>
-          <TableHeader className="bg-zinc-50">
-            <TableRow>
-              <TableHead>User</TableHead>
-              <TableHead>Timezone</TableHead>
-              <TableHead>Updated</TableHead>
-              <TableHead className="text-right">Action</TableHead>
-            </TableRow>
-          </TableHeader>
-          <TableBody>
-            {users.length === 0 ? (
-              <TableRow>
-                <TableCell
-                  colSpan={4}
-                  className="py-10 text-center text-zinc-500"
-                >
-                  {emptyMessage}
-                </TableCell>
-              </TableRow>
-            ) : (
-              users.map((user) => (
-                <TableRow key={user.id} className="align-top">
-                  <TableCell>
-                    <div className="flex flex-col gap-1">
-                      <span className="font-medium text-zinc-900">
-                        {user.email}
-                      </span>
-                      <span className="text-sm text-zinc-600">
-                        {user.name || "No display name"}
-                      </span>
-                      <span className="font-mono text-xs text-zinc-400">
-                        {user.id}
-                      </span>
-                    </div>
-                  </TableCell>
-                  <TableCell className="text-sm text-zinc-600">
-                    {user.timezone}
-                  </TableCell>
-                  <TableCell className="text-sm text-zinc-600">
-                    {formatDate(user.updated_at)}
-                  </TableCell>
-                  <TableCell>
-                    <div className="flex justify-end">
-                      <Button
-                        variant={
-                          user.id === selectedUserId ? "secondary" : "outline"
-                        }
-                        size="small"
-                        onClick={() => onSelectUser(user)}
-                      >
-                        {user.id === selectedUserId ? "Selected" : "Select"}
-                      </Button>
-                    </div>
-                  </TableCell>
-                </TableRow>
-              ))
-            )}
-          </TableBody>
-        </Table>
-      </div>
-    </div>
-  );
-}

autogpt_platform/frontend/src/app/(platform)/admin/copilot/page.tsx

@@ -1,13 +0,0 @@
-import { withRoleAccess } from "@/lib/withRoleAccess";
-import { AdminCopilotPage } from "./components/AdminCopilotPage/AdminCopilotPage";
-
-function AdminCopilot() {
-  return <AdminCopilotPage />;
-}
-
-export default async function AdminCopilotRoute() {
-  "use server";
-  const withAdminAccess = await withRoleAccess(["admin"]);
-  const ProtectedAdminCopilot = await withAdminAccess(AdminCopilot);
-  return <ProtectedAdminCopilot />;
-}

autogpt_platform/frontend/src/app/(platform)/admin/copilot/useAdminCopilotPage.ts

@@ -1,182 +0,0 @@
-"use client";
-
-import type { AdminCopilotUserSummary } from "@/app/api/__generated__/models/adminCopilotUserSummary";
-import { ChatSessionStartType } from "@/app/api/__generated__/models/chatSessionStartType";
-import type { SendCopilotEmailsResponse } from "@/app/api/__generated__/models/sendCopilotEmailsResponse";
-import type { TriggerCopilotSessionResponse } from "@/app/api/__generated__/models/triggerCopilotSessionResponse";
-import { okData } from "@/app/api/helpers";
-import { customMutator } from "@/app/api/mutators/custom-mutator";
-import {
-  useGetV2SearchCopilotUsers,
-  usePostV2TriggerCopilotSession,
-} from "@/app/api/__generated__/endpoints/admin/admin";
-import { useToast } from "@/components/molecules/Toast/use-toast";
-import { ApiError } from "@/lib/autogpt-server-api/helpers";
-import { useMutation } from "@tanstack/react-query";
-import { useDeferredValue, useState } from "react";
-
-function getErrorMessage(error: unknown) {
-  if (error instanceof ApiError) {
-    if (
-      typeof error.response === "object" &&
-      error.response !== null &&
-      "detail" in error.response &&
-      typeof error.response.detail === "string"
-    ) {
-      return error.response.detail;
-    }
-
-    return error.message;
-  }
-
-  if (error instanceof Error) {
-    return error.message;
-  }
-
-  return "Something went wrong";
-}
-
-export function useAdminCopilotPage() {
-  const { toast } = useToast();
-  const [search, setSearch] = useState("");
-  const [selectedUser, setSelectedUser] =
-    useState<AdminCopilotUserSummary | null>(null);
-  const [pendingTriggerType, setPendingTriggerType] =
-    useState<ChatSessionStartType | null>(null);
-  const [lastTriggeredSession, setLastTriggeredSession] =
-    useState<TriggerCopilotSessionResponse | null>(null);
-  const [lastEmailSweepResult, setLastEmailSweepResult] =
-    useState<SendCopilotEmailsResponse | null>(null);
-
-  const deferredSearch = useDeferredValue(search);
-  const normalizedSearch = deferredSearch.trim();
-
-  const searchUsersQuery = useGetV2SearchCopilotUsers(
-    normalizedSearch ? { search: normalizedSearch, limit: 20 } : undefined,
-    {
-      query: {
-        enabled: normalizedSearch.length > 0,
-        select: okData,
-      },
-    },
-  );
-
-  const triggerCopilotSessionMutation = usePostV2TriggerCopilotSession({
-    mutation: {
-      onSuccess: (response) => {
-        setPendingTriggerType(null);
-        const session = okData(response) ?? null;
-        setLastTriggeredSession(session);
-        toast({
-          title: "Copilot session created",
-          variant: "default",
-        });
-      },
-      onError: (error) => {
-        setPendingTriggerType(null);
-        toast({
-          title: getErrorMessage(error),
-          variant: "destructive",
-        });
-      },
-    },
-  });
-
-  const sendPendingCopilotEmailsMutation = useMutation({
-    mutationKey: ["sendPendingCopilotEmails"],
-    mutationFn: async (userId: string) =>
-      customMutator<{
-        data: SendCopilotEmailsResponse;
-        status: number;
-        headers: Headers;
-      }>("/api/users/admin/copilot/send-emails", {
-        method: "POST",
-        body: JSON.stringify({ user_id: userId }),
-      }),
-    onSuccess: (response) => {
-      const result = okData(response) ?? null;
-      setLastEmailSweepResult(result);
-      if (!result) {
-        toast({
-          title: "Email sweep completed",
-          variant: "default",
-        });
-        return;
-      }
-
-      toast({
-        title:
-          result.sent_count > 0
-            ? `Sent ${result.sent_count} Copilot email${result.sent_count === 1 ? "" : "s"}`
-            : "Email sweep completed",
-        description: [
-          `${result.candidate_count} candidate${result.candidate_count === 1 ? "" : "s"}`,
-          `${result.sent_count} sent`,
-          `${result.skipped_count} skipped`,
-          `${result.repair_queued_count} repairs queued`,
-          `${result.running_count} still running`,
-          `${result.failed_count} failed`,
-        ].join(" • "),
-        variant: "default",
-      });
-    },
-    onError: (error: unknown) => {
-      toast({
-        title: getErrorMessage(error),
-        variant: "destructive",
-      });
-    },
-  });
-
-  function handleSelectUser(user: AdminCopilotUserSummary) {
-    setSelectedUser(user);
-    setLastTriggeredSession(null);
-    setLastEmailSweepResult(null);
-  }
-
-  function handleTriggerSession(startType: ChatSessionStartType) {
-    if (!selectedUser) {
-      return;
-    }
-
-    setPendingTriggerType(startType);
-    setLastTriggeredSession(null);
-    triggerCopilotSessionMutation.mutate({
-      data: {
-        user_id: selectedUser.id,
-        start_type: startType,
-      },
-    });
-  }
-
-  function handleSendPendingEmails() {
-    if (!selectedUser) {
-      return;
-    }
-
-    setLastEmailSweepResult(null);
-    sendPendingCopilotEmailsMutation.mutate(selectedUser.id);
-  }
-
-  return {
-    search,
-    selectedUser,
-    pendingTriggerType,
-    lastTriggeredSession,
-    lastEmailSweepResult,
-    searchedUsers: searchUsersQuery.data?.users ?? [],
-    searchErrorMessage: searchUsersQuery.error
-      ? getErrorMessage(searchUsersQuery.error)
-      : null,
-    isSearchingUsers: searchUsersQuery.isLoading,
-    isRefreshingUsers:
-      searchUsersQuery.isFetching && !searchUsersQuery.isLoading,
-    isTriggeringSession: triggerCopilotSessionMutation.isPending,
-    isSendingPendingEmails: sendPendingCopilotEmailsMutation.isPending,
-    hasSearch: normalizedSearch.length > 0,
-    setSearch,
-    handleSelectUser,
-    handleTriggerSession,
-    handleSendPendingEmails,
-  };
-}

autogpt_platform/frontend/src/app/(platform)/admin/layout.tsx

@@ -8,7 +8,6 @@ import {
   MagnifyingGlassIcon,
   FileTextIcon,
   SlidersHorizontalIcon,
-  LightningIcon,
 } from "@phosphor-icons/react";
 
 const sidebarLinkGroups = [
@@ -34,11 +33,6 @@ const sidebarLinkGroups = [
         href: "/admin/impersonation",
         icon: <MagnifyingGlassIcon size={24} />,
       },
-      {
-        text: "Copilot",
-        href: "/admin/copilot",
-        icon: <LightningIcon size={24} />,
-      },
       {
         text: "Execution Analytics",
         href: "/admin/execution-analytics",

autogpt_platform/frontend/src/app/(platform)/copilot/components/ChatSidebar/ChatSidebar.tsx

@@ -23,22 +23,25 @@ import {
   useSidebar,
 } from "@/components/ui/sidebar";
 import { cn } from "@/lib/utils";
-import { DotsThree, PlusCircleIcon, PlusIcon } from "@phosphor-icons/react";
+import {
+  CheckCircle,
+  DotsThree,
+  PlusCircleIcon,
+  PlusIcon,
+} from "@phosphor-icons/react";
 import { useQueryClient } from "@tanstack/react-query";
-import { motion } from "framer-motion";
+import { AnimatePresence, motion } from "framer-motion";
 import { parseAsString, useQueryState } from "nuqs";
 import { useEffect, useRef, useState } from "react";
-import { getSessionListParams } from "../../helpers";
 import { useCopilotUIStore } from "../../store";
-import { SessionListItem } from "../SessionListItem/SessionListItem";
 import { NotificationToggle } from "./components/NotificationToggle/NotificationToggle";
 import { DeleteChatDialog } from "../DeleteChatDialog/DeleteChatDialog";
+import { PulseLoader } from "../PulseLoader/PulseLoader";
 
 export function ChatSidebar() {
   const { state } = useSidebar();
   const isCollapsed = state === "collapsed";
   const [sessionId, setSessionId] = useQueryState("sessionId", parseAsString);
-  const listSessionsParams = getSessionListParams();
   const {
     sessionToDelete,
     setSessionToDelete,
@@ -49,9 +52,7 @@ export function ChatSidebar() {
   const queryClient = useQueryClient();
 
   const { data: sessionsResponse, isLoading: isLoadingSessions } =
-    useGetV2ListSessions(listSessionsParams, {
-      query: { refetchInterval: 10_000 },
-    });
+    useGetV2ListSessions({ limit: 50 }, { query: { refetchInterval: 10_000 } });
 
   const { mutate: deleteSession, isPending: isDeleting } =
     useDeleteV2DeleteSession({
@@ -179,6 +180,31 @@ export function ChatSidebar() {
     }
   }
 
+  function formatDate(dateString: string) {
+    const date = new Date(dateString);
+    const now = new Date();
+    const diffMs = now.getTime() - date.getTime();
+    const diffDays = Math.floor(diffMs / (1000 * 60 * 60 * 24));
+
+    if (diffDays === 0) return "Today";
+    if (diffDays === 1) return "Yesterday";
+    if (diffDays < 7) return `${diffDays} days ago`;
+
+    const day = date.getDate();
+    const ordinal =
+      day % 10 === 1 && day !== 11
+        ? "st"
+        : day % 10 === 2 && day !== 12
+          ? "nd"
+          : day % 10 === 3 && day !== 13
+            ? "rd"
+            : "th";
+    const month = date.toLocaleDateString("en-US", { month: "short" });
+    const year = date.getFullYear();
+
+    return `${day}${ordinal} ${month} ${year}`;
+  }
+
   return (
     <>
       <Sidebar
@@ -269,17 +295,17 @@ export function ChatSidebar() {
                   No conversations yet
                 </p>
               ) : (
-                sessions.map((session) =>
-                  editingSessionId === session.id ? (
-                    <div
-                      key={session.id}
-                      className={cn(
-                        "group relative w-full rounded-lg transition-colors",
-                        session.id === sessionId
-                          ? "bg-zinc-100"
-                          : "hover:bg-zinc-50",
-                      )}
-                    >
+                sessions.map((session) => (
+                  <div
+                    key={session.id}
+                    className={cn(
+                      "group relative w-full rounded-lg transition-colors",
+                      session.id === sessionId
+                        ? "bg-zinc-100"
+                        : "hover:bg-zinc-50",
+                    )}
+                  >
+                    {editingSessionId === session.id ? (
                       <div className="px-3 py-2.5">
                         <input
                           ref={renameInputRef}
@@ -305,49 +331,87 @@ export function ChatSidebar() {
                           className="w-full rounded border border-zinc-300 bg-white px-2 py-1 text-sm text-zinc-800 outline-none focus:border-purple-500 focus:ring-1 focus:ring-purple-500"
                         />
                       </div>
-                    </div>
-                  ) : (
-                    <SessionListItem
-                      key={session.id}
-                      session={session}
-                      currentSessionId={sessionId}
-                      isCompleted={completedSessionIDs.has(session.id)}
-                      onSelect={handleSelectSession}
-                      variant="sidebar"
-                      actionSlot={
-                        <DropdownMenu>
-                          <DropdownMenuTrigger asChild>
-                            <button
-                              onClick={(e) => e.stopPropagation()}
-                              className="rounded-full p-1.5 text-zinc-600 transition-all hover:bg-neutral-100"
-                              aria-label="More actions"
+                    ) : (
+                      <button
+                        onClick={() => handleSelectSession(session.id)}
+                        className="w-full px-3 py-2.5 pr-10 text-left"
+                      >
+                        <div className="flex min-w-0 max-w-full items-center gap-2">
+                          <div className="min-w-0 flex-1">
+                            <Text
+                              variant="body"
+                              className={cn(
+                                "truncate font-normal",
+                                session.id === sessionId
+                                  ? "text-zinc-600"
+                                  : "text-zinc-800",
+                              )}
                             >
-                              <DotsThree className="h-4 w-4" />
-                            </button>
-                          </DropdownMenuTrigger>
-                          <DropdownMenuContent align="end">
-                            <DropdownMenuItem
-                              onClick={(e) =>
-                                handleRenameClick(e, session.id, session.title)
-                              }
-                            >
-                              Rename
-                            </DropdownMenuItem>
-                            <DropdownMenuItem
-                              onClick={(e) =>
-                                handleDeleteClick(e, session.id, session.title)
-                              }
-                              disabled={isDeleting}
-                              className="text-red-600 focus:bg-red-50 focus:text-red-600"
-                            >
-                              Delete chat
-                            </DropdownMenuItem>
-                          </DropdownMenuContent>
-                        </DropdownMenu>
-                      }
-                    />
-                  ),
-                )
+                              <AnimatePresence mode="wait" initial={false}>
+                                <motion.span
+                                  key={session.title || "untitled"}
+                                  initial={{ opacity: 0, y: 4 }}
+                                  animate={{ opacity: 1, y: 0 }}
+                                  exit={{ opacity: 0, y: -4 }}
+                                  transition={{ duration: 0.2 }}
+                                  className="block truncate"
+                                >
+                                  {session.title || "Untitled chat"}
+                                </motion.span>
+                              </AnimatePresence>
+                            </Text>
+                            <Text variant="small" className="text-neutral-400">
+                              {formatDate(session.updated_at)}
+                            </Text>
+                          </div>
+                          {session.is_processing &&
+                            session.id !== sessionId &&
+                            !completedSessionIDs.has(session.id) && (
+                              <PulseLoader size={16} className="shrink-0" />
+                            )}
+                          {completedSessionIDs.has(session.id) &&
+                            session.id !== sessionId && (
+                              <CheckCircle
+                                className="h-4 w-4 shrink-0 text-green-500"
+                                weight="fill"
+                              />
+                            )}
+                        </div>
+                      </button>
+                    )}
+                    {editingSessionId !== session.id && (
+                      <DropdownMenu>
+                        <DropdownMenuTrigger asChild>
+                          <button
+                            onClick={(e) => e.stopPropagation()}
+                            className="absolute right-2 top-1/2 -translate-y-1/2 rounded-full p-1.5 text-zinc-600 transition-all hover:bg-neutral-100"
+                            aria-label="More actions"
+                          >
+                            <DotsThree className="h-4 w-4" />
+                          </button>
+                        </DropdownMenuTrigger>
+                        <DropdownMenuContent align="end">
+                          <DropdownMenuItem
+                            onClick={(e) =>
+                              handleRenameClick(e, session.id, session.title)
+                            }
+                          >
+                            Rename
+                          </DropdownMenuItem>
+                          <DropdownMenuItem
+                            onClick={(e) =>
+                              handleDeleteClick(e, session.id, session.title)
+                            }
+                            disabled={isDeleting}
+                            className="text-red-600 focus:bg-red-50 focus:text-red-600"
+                          >
+                            Delete chat
+                          </DropdownMenuItem>
+                        </DropdownMenuContent>
+                      </DropdownMenu>
+                    )}
+                  </div>
+                ))
               )}
             </motion.div>
           )}

autogpt_platform/frontend/src/app/(platform)/copilot/components/MobileDrawer/MobileDrawer.tsx

@@ -1,7 +1,10 @@
+import type { SessionSummaryResponse } from "@/app/api/__generated__/models/sessionSummaryResponse";
 import { Button } from "@/components/atoms/Button/Button";
+import { Text } from "@/components/atoms/Text/Text";
 import { scrollbarStyles } from "@/components/styles/scrollbars";
 import { cn } from "@/lib/utils";
 import {
+  CheckCircle,
   PlusIcon,
   SpeakerHigh,
   SpeakerSlash,
@@ -9,9 +12,8 @@ import {
   X,
 } from "@phosphor-icons/react";
 import { Drawer } from "vaul";
-import type { SessionSummaryResponse } from "@/app/api/__generated__/models/sessionSummaryResponse";
 import { useCopilotUIStore } from "../../store";
-import { SessionListItem } from "../SessionListItem/SessionListItem";
+import { PulseLoader } from "../PulseLoader/PulseLoader";
 
 interface Props {
   isOpen: boolean;
@@ -24,6 +26,31 @@ interface Props {
   onOpenChange: (open: boolean) => void;
 }
 
+function formatDate(dateString: string) {
+  const date = new Date(dateString);
+  const now = new Date();
+  const diffMs = now.getTime() - date.getTime();
+  const diffDays = Math.floor(diffMs / (1000 * 60 * 60 * 24));
+
+  if (diffDays === 0) return "Today";
+  if (diffDays === 1) return "Yesterday";
+  if (diffDays < 7) return `${diffDays} days ago`;
+
+  const day = date.getDate();
+  const ordinal =
+    day % 10 === 1 && day !== 11
+      ? "st"
+      : day % 10 === 2 && day !== 12
+        ? "nd"
+        : day % 10 === 3 && day !== 13
+          ? "rd"
+          : "th";
+  const month = date.toLocaleDateString("en-US", { month: "short" });
+  const year = date.getFullYear();
+
+  return `${day}${ordinal} ${month} ${year}`;
+}
+
 export function MobileDrawer({
   isOpen,
   sessions,
@@ -107,19 +134,52 @@ export function MobileDrawer({
               </p>
             ) : (
               sessions.map((session) => (
-                <SessionListItem
+                <button
                   key={session.id}
-                  session={session}
-                  currentSessionId={currentSessionId}
-                  isCompleted={completedSessionIDs.has(session.id)}
-                  variant="drawer"
-                  onSelect={(selectedSessionId) => {
-                    onSelectSession(selectedSessionId);
-                    if (completedSessionIDs.has(selectedSessionId)) {
-                      clearCompletedSession(selectedSessionId);
+                  onClick={() => {
+                    onSelectSession(session.id);
+                    if (completedSessionIDs.has(session.id)) {
+                      clearCompletedSession(session.id);
                     }
                   }}
-                />
+                  className={cn(
+                    "w-full rounded-lg px-3 py-2.5 text-left transition-colors",
+                    session.id === currentSessionId
+                      ? "bg-zinc-100"
+                      : "hover:bg-zinc-50",
+                  )}
+                >
+                  <div className="flex min-w-0 max-w-full flex-col overflow-hidden">
+                    <div className="flex min-w-0 max-w-full items-center gap-1.5">
+                      <Text
+                        variant="body"
+                        className={cn(
+                          "truncate font-normal",
+                          session.id === currentSessionId
+                            ? "text-zinc-600"
+                            : "text-zinc-800",
+                        )}
+                      >
+                        {session.title || "Untitled chat"}
+                      </Text>
+                      {session.is_processing &&
+                        !completedSessionIDs.has(session.id) &&
+                        session.id !== currentSessionId && (
+                          <PulseLoader size={8} className="shrink-0" />
+                        )}
+                      {completedSessionIDs.has(session.id) &&
+                        session.id !== currentSessionId && (
+                          <CheckCircle
+                            className="h-4 w-4 shrink-0 text-green-500"
+                            weight="fill"
+                          />
+                        )}
+                    </div>
+                    <Text variant="small" className="text-neutral-400">
+                      {formatDate(session.updated_at)}
+                    </Text>
+                  </div>
+                </button>
               ))
             )}
           </div>

autogpt_platform/frontend/src/app/(platform)/copilot/components/SessionListItem/SessionListItem.tsx

@@ -1,148 +0,0 @@
-"use client";
-
-import type { SessionSummaryResponse } from "@/app/api/__generated__/models/sessionSummaryResponse";
-import { Badge } from "@/components/atoms/Badge/Badge";
-import { Text } from "@/components/atoms/Text/Text";
-import { cn } from "@/lib/utils";
-import { CheckCircle } from "@phosphor-icons/react";
-import { AnimatePresence, motion } from "framer-motion";
-import type { ReactNode } from "react";
-import {
-  formatSessionDate,
-  getSessionStartTypeLabel,
-  isNonManualSessionStartType,
-} from "../../helpers";
-import { PulseLoader } from "../PulseLoader/PulseLoader";
-
-interface Props {
-  actionSlot?: ReactNode;
-  currentSessionId: string | null;
-  isCompleted: boolean;
-  onSelect: (sessionId: string) => void;
-  session: SessionSummaryResponse;
-  variant?: "sidebar" | "drawer";
-}
-
-export function SessionListItem({
-  actionSlot,
-  currentSessionId,
-  isCompleted,
-  onSelect,
-  session,
-  variant = "sidebar",
-}: Props) {
-  const isActive = session.id === currentSessionId;
-  const showProcessing = session.is_processing && !isCompleted && !isActive;
-  const showCompleted = isCompleted && !isActive;
-  const startTypeLabel = isNonManualSessionStartType(session.start_type)
-    ? getSessionStartTypeLabel(session.start_type)
-    : null;
-
-  if (variant === "drawer") {
-    return (
-      <button
-        onClick={() => onSelect(session.id)}
-        className={cn(
-          "w-full rounded-lg px-3 py-2.5 text-left transition-colors",
-          isActive ? "bg-zinc-100" : "hover:bg-zinc-50",
-        )}
-      >
-        <div className="flex min-w-0 max-w-full flex-col overflow-hidden">
-          <div className="flex min-w-0 max-w-full items-center gap-1.5">
-            <Text
-              variant="body"
-              className={cn(
-                "truncate font-normal",
-                isActive ? "text-zinc-600" : "text-zinc-800",
-              )}
-            >
-              {session.title || "Untitled chat"}
-            </Text>
-            {showProcessing ? (
-              <PulseLoader size={8} className="shrink-0" />
-            ) : null}
-            {showCompleted ? (
-              <CheckCircle
-                className="h-4 w-4 shrink-0 text-green-500"
-                weight="fill"
-              />
-            ) : null}
-          </div>
-          {startTypeLabel ? (
-            <div className="mt-1">
-              <Badge variant="info" size="small">
-                {startTypeLabel}
-              </Badge>
-            </div>
-          ) : null}
-          <Text variant="small" className="text-neutral-400">
-            {formatSessionDate(session.updated_at)}
-          </Text>
-        </div>
-      </button>
-    );
-  }
-
-  return (
-    <div
-      className={cn(
-        "group relative w-full rounded-lg transition-colors",
-        isActive ? "bg-zinc-100" : "hover:bg-zinc-50",
-      )}
-    >
-      <button
-        onClick={() => onSelect(session.id)}
-        className="w-full px-3 py-2.5 pr-10 text-left"
-      >
-        <div className="flex min-w-0 max-w-full items-center gap-2">
-          <div className="min-w-0 flex-1">
-            <Text
-              variant="body"
-              className={cn(
-                "truncate font-normal",
-                isActive ? "text-zinc-600" : "text-zinc-800",
-              )}
-            >
-              <AnimatePresence mode="wait" initial={false}>
-                <motion.span
-                  key={session.title || "untitled"}
-                  initial={{ opacity: 0, y: 4 }}
-                  animate={{ opacity: 1, y: 0 }}
-                  exit={{ opacity: 0, y: -4 }}
-                  transition={{ duration: 0.2 }}
-                  className="block truncate"
-                >
-                  {session.title || "Untitled chat"}
-                </motion.span>
-              </AnimatePresence>
-            </Text>
-            {startTypeLabel ? (
-              <div className="mt-1">
-                <Badge variant="info" size="small">
-                  {startTypeLabel}
-                </Badge>
-              </div>
-            ) : null}
-            <Text variant="small" className="text-neutral-400">
-              {formatSessionDate(session.updated_at)}
-            </Text>
-          </div>
-          {showProcessing ? (
-            <PulseLoader size={16} className="shrink-0" />
-          ) : null}
-          {showCompleted ? (
-            <CheckCircle
-              className="h-4 w-4 shrink-0 text-green-500"
-              weight="fill"
-            />
-          ) : null}
-        </div>
-      </button>
-      {actionSlot ? (
-        <div className="absolute right-2 top-1/2 -translate-y-1/2">
-          {actionSlot}
-        </div>
-      ) : null}
-    </div>
-  );
-}

autogpt_platform/frontend/src/app/(platform)/copilot/helpers.ts

@@ -1,65 +1,5 @@
-import type { GetV2ListSessionsParams } from "@/app/api/__generated__/models/getV2ListSessionsParams";
-import {
-  ChatSessionStartType,
-  type ChatSessionStartType as ChatSessionStartTypeValue,
-} from "@/app/api/__generated__/models/chatSessionStartType";
 import type { UIMessage } from "ai";
 
-export const COPILOT_SESSION_LIST_LIMIT = 50;
-
-export function getSessionListParams(): GetV2ListSessionsParams {
-  return {
-    limit: COPILOT_SESSION_LIST_LIMIT,
-    with_auto: true,
-  };
-}
-
-export function isNonManualSessionStartType(
-  startType: ChatSessionStartTypeValue | null | undefined,
-): boolean {
-  return startType != null && startType !== ChatSessionStartType.MANUAL;
-}
-
-export function getSessionStartTypeLabel(
-  startType: ChatSessionStartTypeValue,
-): string | null {
-  switch (startType) {
-    case ChatSessionStartType.AUTOPILOT_NIGHTLY:
-      return "Nightly";
-    case ChatSessionStartType.AUTOPILOT_CALLBACK:
-      return "Callback";
-    case ChatSessionStartType.AUTOPILOT_INVITE_CTA:
-      return "Invite CTA";
-    default:
-      return null;
-  }
-}
-
-export function formatSessionDate(dateString: string): string {
-  const date = new Date(dateString);
-  const now = new Date();
-  const diffMs = now.getTime() - date.getTime();
-  const diffDays = Math.floor(diffMs / (1000 * 60 * 60 * 24));
-
-  if (diffDays === 0) return "Today";
-  if (diffDays === 1) return "Yesterday";
-  if (diffDays < 7) return `${diffDays} days ago`;
-
-  const day = date.getDate();
-  const ordinal =
-    day % 10 === 1 && day !== 11
-      ? "st"
-      : day % 10 === 2 && day !== 12
-        ? "nd"
-        : day % 10 === 3 && day !== 13
-          ? "rd"
-          : "th";
-  const month = date.toLocaleDateString("en-US", { month: "short" });
-  const year = date.getFullYear();
-
-  return `${day}${ordinal} ${month} ${year}`;
-}
-
 /** Mark any in-progress tool parts as completed/errored so spinners stop. */
 export function resolveInProgressTools(
   messages: UIMessage[],

autogpt_platform/frontend/src/app/(platform)/copilot/useCallbackToken.ts

@@ -1,93 +0,0 @@
-import { usePostV2ConsumeCallbackTokenRoute } from "@/app/api/__generated__/endpoints/chat/chat";
-import { toast } from "@/components/molecules/Toast/use-toast";
-import { useQueryClient } from "@tanstack/react-query";
-import { parseAsString, useQueryState } from "nuqs";
-import { useEffect, useState } from "react";
-import { getGetV2ListSessionsQueryKey } from "@/app/api/__generated__/endpoints/chat/chat";
-
-interface Props {
-  isLoggedIn: boolean;
-  onConsumed: (sessionId: string) => void;
-  onClearAutopilot: () => void;
-}
-
-export function useCallbackToken({
-  isLoggedIn,
-  onConsumed,
-  onClearAutopilot,
-}: Props) {
-  const queryClient = useQueryClient();
-  const [callbackToken, setCallbackToken] = useQueryState(
-    "callbackToken",
-    parseAsString,
-  );
-  const [consumedTokens, setConsumedTokens] = useState<Set<string>>(
-    () => new Set(),
-  );
-  const { mutateAsync: consumeCallbackToken, isPending } =
-    usePostV2ConsumeCallbackTokenRoute();
-
-  const hasConsumedToken =
-    callbackToken != null && consumedTokens.has(callbackToken);
-
-  useEffect(() => {
-    if (!isLoggedIn || !callbackToken || hasConsumedToken) {
-      return;
-    }
-
-    let isCancelled = false;
-    const token = callbackToken;
-    setConsumedTokens((current) => new Set(current).add(token));
-
-    void consumeCallbackToken({ data: { token } })
-      .then((response) => {
-        if (isCancelled) {
-          return;
-        }
-        if (response.status !== 200 || !response.data?.session_id) {
-          throw new Error("Failed to open callback session");
-        }
-
-        onConsumed(response.data.session_id);
-        onClearAutopilot();
-        void setCallbackToken(null);
-        queryClient.invalidateQueries({
-          queryKey: getGetV2ListSessionsQueryKey(),
-        });
-      })
-      .catch((error) => {
-        if (isCancelled) {
-          return;
-        }
-        setConsumedTokens((current) => {
-          const next = new Set(current);
-          next.delete(token);
-          return next;
-        });
-        void setCallbackToken(null);
-        toast({
-          title: "Unable to open callback session",
-          description:
-            error instanceof Error ? error.message : "Please try again.",
-          variant: "destructive",
-        });
-      });
-
-    return () => {
-      isCancelled = true;
-    };
-  }, [
-    callbackToken,
-    consumeCallbackToken,
-    hasConsumedToken,
-    isLoggedIn,
-    onClearAutopilot,
-    onConsumed,
-    queryClient,
-    setCallbackToken,
-  ]);
-
-  return {
-    isConsumingCallbackToken: isPending,
-  };
-}

autogpt_platform/frontend/src/app/(platform)/copilot/useChatSession.ts

@@ -4,7 +4,6 @@ import {
   useGetV2GetSession,
   usePostV2CreateSession,
 } from "@/app/api/__generated__/endpoints/chat/chat";
-import type { ChatSessionStartType } from "@/app/api/__generated__/models/chatSessionStartType";
 import { toast } from "@/components/molecules/Toast/use-toast";
 import * as Sentry from "@sentry/nextjs";
 import { useQueryClient } from "@tanstack/react-query";
@@ -71,14 +70,6 @@ export function useChatSession() {
     );
   }, [sessionQuery.data, sessionId, hasActiveStream]);
 
-  const sessionStartType = useMemo<ChatSessionStartType | null>(() => {
-    if (sessionQuery.data?.status !== 200) {
-      return null;
-    }
-
-    return sessionQuery.data.data.start_type;
-  }, [sessionQuery.data]);
-
   const { mutateAsync: createSessionMutation, isPending: isCreatingSession } =
     usePostV2CreateSession({
       mutation: {
@@ -130,7 +121,6 @@ export function useChatSession() {
   return {
     sessionId,
     setSessionId,
-    sessionStartType,
     hydratedMessages,
     hasActiveStream,
     isLoadingSession: sessionQuery.isLoading,

autogpt_platform/frontend/src/app/(platform)/copilot/useCopilotPage.ts

@@ -2,24 +2,34 @@ import {
   getGetV2ListSessionsQueryKey,
   useDeleteV2DeleteSession,
   useGetV2ListSessions,
+  type getV2ListSessionsResponse,
 } from "@/app/api/__generated__/endpoints/chat/chat";
 import { toast } from "@/components/molecules/Toast/use-toast";
+import { uploadFileDirect } from "@/lib/direct-upload";
 import { useBreakpoint } from "@/lib/hooks/useBreakpoint";
 import { useSupabase } from "@/lib/supabase/hooks/useSupabase";
 import { useQueryClient } from "@tanstack/react-query";
-import { getSessionListParams } from "./helpers";
+import type { FileUIPart } from "ai";
+import { useEffect, useRef, useState } from "react";
 import { useCopilotUIStore } from "./store";
-import { useCallbackToken } from "./useCallbackToken";
 import { useChatSession } from "./useChatSession";
-import { useFileUpload } from "./useFileUpload";
 import { useCopilotNotifications } from "./useCopilotNotifications";
 import { useCopilotStream } from "./useCopilotStream";
-import { useTitlePolling } from "./useTitlePolling";
+
+const TITLE_POLL_INTERVAL_MS = 2_000;
+const TITLE_POLL_MAX_ATTEMPTS = 5;
+
+interface UploadedFile {
+  file_id: string;
+  name: string;
+  mime_type: string;
+}
 
 export function useCopilotPage() {
   const { isUserLoading, isLoggedIn } = useSupabase();
+  const [isUploadingFiles, setIsUploadingFiles] = useState(false);
+  const [pendingMessage, setPendingMessage] = useState<string | null>(null);
   const queryClient = useQueryClient();
-  const listSessionsParams = getSessionListParams();
 
   const { sessionToDelete, setSessionToDelete, isDrawerOpen, setDrawerOpen } =
     useCopilotUIStore();
@@ -29,7 +39,7 @@ export function useCopilotPage() {
     setSessionId,
     hydratedMessages,
     hasActiveStream,
-    isLoadingSession: isLoadingCurrentSession,
+    isLoadingSession,
     isSessionError,
     createSession,
     isCreatingSession,
@@ -83,33 +93,198 @@ export function useCopilotPage() {
   const isMobile =
     breakpoint === "base" || breakpoint === "sm" || breakpoint === "md";
 
-  const { isConsumingCallbackToken } = useCallbackToken({
-    isLoggedIn,
-    onConsumed: setSessionId,
-    onClearAutopilot() {},
-  });
+  const pendingFilesRef = useRef<File[]>([]);
 
-  const { isUploadingFiles, onSend } = useFileUpload({
-    createSession,
-    isUserStoppingRef,
-    sendMessage,
-    sessionId,
-  });
+  // --- Send pending message after session creation ---
+  useEffect(() => {
+    if (!sessionId || pendingMessage === null) return;
+    const msg = pendingMessage;
+    const files = pendingFilesRef.current;
+    setPendingMessage(null);
+    pendingFilesRef.current = [];
+
+    if (files.length > 0) {
+      setIsUploadingFiles(true);
+      void uploadFiles(files, sessionId)
+        .then((uploaded) => {
+          if (uploaded.length === 0) {
+            toast({
+              title: "File upload failed",
+              description: "Could not upload any files. Please try again.",
+              variant: "destructive",
+            });
+            return;
+          }
+          const fileParts = buildFileParts(uploaded);
+          sendMessage({
+            text: msg,
+            files: fileParts.length > 0 ? fileParts : undefined,
+          });
+        })
+        .finally(() => setIsUploadingFiles(false));
+    } else {
+      sendMessage({ text: msg });
+    }
+  }, [sessionId, pendingMessage, sendMessage]);
+
+  async function uploadFiles(
+    files: File[],
+    sid: string,
+  ): Promise<UploadedFile[]> {
+    const results = await Promise.allSettled(
+      files.map(async (file) => {
+        try {
+          const data = await uploadFileDirect(file, sid);
+          if (!data.file_id) throw new Error("No file_id returned");
+          return {
+            file_id: data.file_id,
+            name: data.name || file.name,
+            mime_type: data.mime_type || "application/octet-stream",
+          } as UploadedFile;
+        } catch (err) {
+          console.error("File upload failed:", err);
+          toast({
+            title: "File upload failed",
+            description: file.name,
+            variant: "destructive",
+          });
+          throw err;
+        }
+      }),
+    );
+    return results
+      .filter(
+        (r): r is PromiseFulfilledResult<UploadedFile> =>
+          r.status === "fulfilled",
+      )
+      .map((r) => r.value);
+  }
+
+  function buildFileParts(uploaded: UploadedFile[]): FileUIPart[] {
+    return uploaded.map((f) => ({
+      type: "file" as const,
+      mediaType: f.mime_type,
+      filename: f.name,
+      url: `/api/proxy/api/workspace/files/${f.file_id}/download`,
+    }));
+  }
+
+  async function onSend(message: string, files?: File[]) {
+    const trimmed = message.trim();
+    if (!trimmed && (!files || files.length === 0)) return;
+
+    // Client-side file limits
+    if (files && files.length > 0) {
+      const MAX_FILES = 10;
+      const MAX_FILE_SIZE_BYTES = 100 * 1024 * 1024; // 100 MB
+
+      if (files.length > MAX_FILES) {
+        toast({
+          title: "Too many files",
+          description: `You can attach up to ${MAX_FILES} files at once.`,
+          variant: "destructive",
+        });
+        return;
+      }
+
+      const oversized = files.filter((f) => f.size > MAX_FILE_SIZE_BYTES);
+      if (oversized.length > 0) {
+        toast({
+          title: "File too large",
+          description: `${oversized[0].name} exceeds the 100 MB limit.`,
+          variant: "destructive",
+        });
+        return;
+      }
+    }
+
+    isUserStoppingRef.current = false;
+
+    if (sessionId) {
+      if (files && files.length > 0) {
+        setIsUploadingFiles(true);
+        try {
+          const uploaded = await uploadFiles(files, sessionId);
+          if (uploaded.length === 0) {
+            // All uploads failed — abort send so chips revert to editable
+            throw new Error("All file uploads failed");
+          }
+          const fileParts = buildFileParts(uploaded);
+          sendMessage({
+            text: trimmed || "",
+            files: fileParts.length > 0 ? fileParts : undefined,
+          });
+        } finally {
+          setIsUploadingFiles(false);
+        }
+      } else {
+        sendMessage({ text: trimmed });
+      }
+      return;
+    }
+
+    setPendingMessage(trimmed || "");
+    if (files && files.length > 0) {
+      pendingFilesRef.current = files;
+    }
+    await createSession();
+  }
 
   // --- Session list (for mobile drawer & sidebar) ---
   const { data: sessionsResponse, isLoading: isLoadingSessions } =
-    useGetV2ListSessions(listSessionsParams, {
-      query: { enabled: !isUserLoading && isLoggedIn },
-    });
+    useGetV2ListSessions(
+      { limit: 50 },
+      { query: { enabled: !isUserLoading && isLoggedIn } },
+    );
 
   const sessions =
     sessionsResponse?.status === 200 ? sessionsResponse.data.sessions : [];
 
-  useTitlePolling({
-    isReconnecting,
-    sessionId,
-    status,
-  });
+  // Start title polling when stream ends cleanly — sidebar title animates in
+  const titlePollRef = useRef<ReturnType<typeof setInterval>>();
+  const prevStatusRef = useRef(status);
+
+  useEffect(() => {
+    const prev = prevStatusRef.current;
+    prevStatusRef.current = status;
+
+    const wasActive = prev === "streaming" || prev === "submitted";
+    const isNowReady = status === "ready";
+
+    if (!wasActive || !isNowReady || !sessionId || isReconnecting) return;
+
+    queryClient.invalidateQueries({
+      queryKey: getGetV2ListSessionsQueryKey({ limit: 50 }),
+    });
+    const sid = sessionId;
+    let attempts = 0;
+    clearInterval(titlePollRef.current);
+    titlePollRef.current = setInterval(() => {
+      const data = queryClient.getQueryData<getV2ListSessionsResponse>(
+        getGetV2ListSessionsQueryKey({ limit: 50 }),
+      );
+      const hasTitle =
+        data?.status === 200 &&
+        data.data.sessions.some((s) => s.id === sid && s.title);
+      if (hasTitle || attempts >= TITLE_POLL_MAX_ATTEMPTS) {
+        clearInterval(titlePollRef.current);
+        titlePollRef.current = undefined;
+        return;
+      }
+      attempts += 1;
+      queryClient.invalidateQueries({
+        queryKey: getGetV2ListSessionsQueryKey({ limit: 50 }),
+      });
+    }, TITLE_POLL_INTERVAL_MS);
+  }, [status, sessionId, isReconnecting, queryClient]);
+
+  // Clean up polling on session change or unmount
+  useEffect(() => {
+    return () => {
+      clearInterval(titlePollRef.current);
+      titlePollRef.current = undefined;
+    };
+  }, [sessionId]);
 
   // --- Mobile drawer handlers ---
   function handleOpenDrawer() {
@@ -159,7 +334,7 @@ export function useCopilotPage() {
     error,
     stop,
     isReconnecting,
-    isLoadingSession: isLoadingCurrentSession || isConsumingCallbackToken,
+    isLoadingSession,
     isSessionError,
     isCreatingSession,
     isUploadingFiles,

autogpt_platform/frontend/src/app/(platform)/copilot/useFileUpload.ts

@@ -1,178 +0,0 @@
-import { uploadFileDirect } from "@/lib/direct-upload";
-import type { FileUIPart } from "ai";
-import { toast } from "@/components/molecules/Toast/use-toast";
-import { useEffect, useRef, useState, type MutableRefObject } from "react";
-
-const MAX_FILES = 10;
-const MAX_FILE_SIZE_BYTES = 100 * 1024 * 1024;
-
-interface UploadedFile {
-  file_id: string;
-  name: string;
-  mime_type: string;
-}
-
-interface SendMessageInput {
-  text: string;
-  files?: FileUIPart[];
-}
-
-interface Props {
-  createSession: () => Promise<unknown>;
-  isUserStoppingRef: MutableRefObject<boolean>;
-  sendMessage: (input: SendMessageInput) => void;
-  sessionId: string | null;
-}
-
-async function uploadFiles(
-  files: File[],
-  sessionId: string,
-): Promise<UploadedFile[]> {
-  const results = await Promise.allSettled(
-    files.map(async (file) => {
-      try {
-        const data = await uploadFileDirect(file, sessionId);
-        if (!data.file_id) throw new Error("No file_id returned");
-        return {
-          file_id: data.file_id,
-          name: data.name || file.name,
-          mime_type: data.mime_type || "application/octet-stream",
-        } satisfies UploadedFile;
-      } catch (error) {
-        console.error("File upload failed:", error);
-        toast({
-          title: "File upload failed",
-          description: file.name,
-          variant: "destructive",
-        });
-        throw error;
-      }
-    }),
-  );
-
-  return results
-    .filter(
-      (result): result is PromiseFulfilledResult<UploadedFile> =>
-        result.status === "fulfilled",
-    )
-    .map((result) => result.value);
-}
-
-function buildFileParts(uploaded: UploadedFile[]): FileUIPart[] {
-  return uploaded.map((file) => ({
-    type: "file" as const,
-    mediaType: file.mime_type,
-    filename: file.name,
-    url: `/api/proxy/api/workspace/files/${file.file_id}/download`,
-  }));
-}
-
-export function useFileUpload({
-  createSession,
-  isUserStoppingRef,
-  sendMessage,
-  sessionId,
-}: Props) {
-  const [isUploadingFiles, setIsUploadingFiles] = useState(false);
-  const [pendingMessage, setPendingMessage] = useState<string | null>(null);
-  const pendingFilesRef = useRef<File[]>([]);
-
-  useEffect(() => {
-    if (!sessionId || pendingMessage === null) {
-      return;
-    }
-
-    const message = pendingMessage;
-    const files = pendingFilesRef.current;
-    setPendingMessage(null);
-    pendingFilesRef.current = [];
-
-    if (files.length === 0) {
-      sendMessage({ text: message });
-      return;
-    }
-
-    setIsUploadingFiles(true);
-    void uploadFiles(files, sessionId)
-      .then((uploaded) => {
-        if (uploaded.length === 0) {
-          toast({
-            title: "File upload failed",
-            description: "Could not upload any files. Please try again.",
-            variant: "destructive",
-          });
-          return;
-        }
-
-        const fileParts = buildFileParts(uploaded);
-        sendMessage({
-          text: message,
-          files: fileParts.length > 0 ? fileParts : undefined,
-        });
-      })
-      .finally(() => setIsUploadingFiles(false));
-  }, [pendingMessage, sendMessage, sessionId]);
-
-  async function onSend(message: string, files?: File[]) {
-    const trimmed = message.trim();
-    if (!trimmed && (!files || files.length === 0)) {
-      return;
-    }
-
-    if (files && files.length > 0) {
-      if (files.length > MAX_FILES) {
-        toast({
-          title: "Too many files",
-          description: `You can attach up to ${MAX_FILES} files at once.`,
-          variant: "destructive",
-        });
-        return;
-      }
-
-      const oversized = files.filter((file) => file.size > MAX_FILE_SIZE_BYTES);
-      if (oversized.length > 0) {
-        toast({
-          title: "File too large",
-          description: `${oversized[0].name} exceeds the 100 MB limit.`,
-          variant: "destructive",
-        });
-        return;
-      }
-    }
-
-    isUserStoppingRef.current = false;
-
-    if (sessionId) {
-      if (!files || files.length === 0) {
-        sendMessage({ text: trimmed });
-        return;
-      }
-
-      setIsUploadingFiles(true);
-      try {
-        const uploaded = await uploadFiles(files, sessionId);
-        if (uploaded.length === 0) {
-          throw new Error("All file uploads failed");
-        }
-
-        const fileParts = buildFileParts(uploaded);
-        sendMessage({
-          text: trimmed || "",
-          files: fileParts.length > 0 ? fileParts : undefined,
-        });
-      } finally {
-        setIsUploadingFiles(false);
-      }
-      return;
-    }
-
-    setPendingMessage(trimmed || "");
-    pendingFilesRef.current = files ?? [];
-    await createSession();
-  }
-
-  return {
-    isUploadingFiles,
-    onSend,
-  };
-}

autogpt_platform/frontend/src/app/(platform)/copilot/useTitlePolling.ts

@@ -1,72 +0,0 @@
-import {
-  getGetV2ListSessionsQueryKey,
-  type getV2ListSessionsResponse,
-} from "@/app/api/__generated__/endpoints/chat/chat";
-import { useQueryClient } from "@tanstack/react-query";
-import { useEffect, useRef } from "react";
-import { getSessionListParams } from "./helpers";
-
-const TITLE_POLL_INTERVAL_MS = 2_000;
-const TITLE_POLL_MAX_ATTEMPTS = 5;
-
-interface Props {
-  isReconnecting: boolean;
-  sessionId: string | null;
-  status: string;
-}
-
-export function useTitlePolling({ isReconnecting, sessionId, status }: Props) {
-  const queryClient = useQueryClient();
-  const previousStatusRef = useRef(status);
-
-  useEffect(() => {
-    const previousStatus = previousStatusRef.current;
-    previousStatusRef.current = status;
-
-    const wasActive =
-      previousStatus === "streaming" || previousStatus === "submitted";
-    const isNowReady = status === "ready";
-
-    if (!wasActive || !isNowReady || !sessionId || isReconnecting) {
-      return;
-    }
-
-    const params = getSessionListParams();
-    const queryKey = getGetV2ListSessionsQueryKey(params);
-    let attempts = 0;
-    let timeoutId: ReturnType<typeof setTimeout> | undefined;
-    let isCancelled = false;
-
-    const poll = () => {
-      if (isCancelled) {
-        return;
-      }
-
-      const data =
-        queryClient.getQueryData<getV2ListSessionsResponse>(queryKey);
-      const hasTitle =
-        data?.status === 200 &&
-        data.data.sessions.some(
-          (session) => session.id === sessionId && session.title,
-        );
-
-      if (hasTitle || attempts >= TITLE_POLL_MAX_ATTEMPTS) {
-        return;
-      }
-
-      attempts += 1;
-      queryClient.invalidateQueries({ queryKey });
-      timeoutId = setTimeout(poll, TITLE_POLL_INTERVAL_MS);
-    };
-
-    queryClient.invalidateQueries({ queryKey });
-    timeoutId = setTimeout(poll, TITLE_POLL_INTERVAL_MS);
-
-    return () => {
-      isCancelled = true;
-      if (timeoutId) {
-        clearTimeout(timeoutId);
-      }
-    };
-  }, [isReconnecting, queryClient, sessionId, status]);
-}

autogpt_platform/frontend/src/app/api/openapi.json

@@ -1030,16 +1030,6 @@
               "default": 0,
               "title": "Offset"
             }
-          },
-          {
-            "name": "with_auto",
-            "in": "query",
-            "required": false,
-            "schema": {
-              "type": "boolean",
-              "default": false,
-              "title": "With Auto"
-            }
           }
         ],
         "responses": {
@@ -1089,47 +1079,6 @@
         }
       }
     },
-    "/api/chat/sessions/callback-token/consume": {
-      "post": {
-        "tags": ["v2", "chat", "chat"],
-        "summary": "Consume Callback Token Route",
-        "operationId": "postV2ConsumeCallbackTokenRoute",
-        "requestBody": {
-          "content": {
-            "application/json": {
-              "schema": {
-                "$ref": "#/components/schemas/ConsumeCallbackTokenRequest"
-              }
-            }
-          },
-          "required": true
-        },
-        "responses": {
-          "200": {
-            "description": "Successful Response",
-            "content": {
-              "application/json": {
-                "schema": {
-                  "$ref": "#/components/schemas/ConsumeCallbackTokenResponse"
-                }
-              }
-            }
-          },
-          "401": {
-            "$ref": "#/components/responses/HTTP401NotAuthenticatedError"
-          },
-          "422": {
-            "description": "Validation Error",
-            "content": {
-              "application/json": {
-                "schema": { "$ref": "#/components/schemas/HTTPValidationError" }
-              }
-            }
-          }
-        },
-        "security": [{ "HTTPBearerJWT": [] }]
-      }
-    },
     "/api/chat/sessions/{session_id}": {
       "delete": {
         "tags": ["v2", "chat", "chat"],
@@ -6721,145 +6670,6 @@
         }
       }
     },
-    "/api/users/admin/copilot/send-emails": {
-      "post": {
-        "tags": ["v2", "admin", "users", "admin"],
-        "summary": "Send Pending Copilot Emails",
-        "operationId": "postV2SendPendingCopilotEmails",
-        "requestBody": {
-          "content": {
-            "application/json": {
-              "schema": {
-                "$ref": "#/components/schemas/SendCopilotEmailsRequest"
-              }
-            }
-          },
-          "required": true
-        },
-        "responses": {
-          "200": {
-            "description": "Successful Response",
-            "content": {
-              "application/json": {
-                "schema": {
-                  "$ref": "#/components/schemas/SendCopilotEmailsResponse"
-                }
-              }
-            }
-          },
-          "401": {
-            "$ref": "#/components/responses/HTTP401NotAuthenticatedError"
-          },
-          "422": {
-            "description": "Validation Error",
-            "content": {
-              "application/json": {
-                "schema": { "$ref": "#/components/schemas/HTTPValidationError" }
-              }
-            }
-          }
-        },
-        "security": [{ "HTTPBearerJWT": [] }]
-      }
-    },
-    "/api/users/admin/copilot/trigger": {
-      "post": {
-        "tags": ["v2", "admin", "users", "admin"],
-        "summary": "Trigger Copilot Session",
-        "operationId": "postV2TriggerCopilotSession",
-        "requestBody": {
-          "content": {
-            "application/json": {
-              "schema": {
-                "$ref": "#/components/schemas/TriggerCopilotSessionRequest"
-              }
-            }
-          },
-          "required": true
-        },
-        "responses": {
-          "200": {
-            "description": "Successful Response",
-            "content": {
-              "application/json": {
-                "schema": {
-                  "$ref": "#/components/schemas/TriggerCopilotSessionResponse"
-                }
-              }
-            }
-          },
-          "401": {
-            "$ref": "#/components/responses/HTTP401NotAuthenticatedError"
-          },
-          "422": {
-            "description": "Validation Error",
-            "content": {
-              "application/json": {
-                "schema": { "$ref": "#/components/schemas/HTTPValidationError" }
-              }
-            }
-          }
-        },
-        "security": [{ "HTTPBearerJWT": [] }]
-      }
-    },
-    "/api/users/admin/copilot/users": {
-      "get": {
-        "tags": ["v2", "admin", "users", "admin"],
-        "summary": "Search Copilot Users",
-        "operationId": "getV2SearchCopilotUsers",
-        "security": [{ "HTTPBearerJWT": [] }],
-        "parameters": [
-          {
-            "name": "search",
-            "in": "query",
-            "required": false,
-            "schema": {
-              "type": "string",
-              "description": "Search by email, name, or user ID",
-              "default": "",
-              "title": "Search"
-            },
-            "description": "Search by email, name, or user ID"
-          },
-          {
-            "name": "limit",
-            "in": "query",
-            "required": false,
-            "schema": {
-              "type": "integer",
-              "maximum": 50,
-              "minimum": 1,
-              "default": 20,
-              "title": "Limit"
-            }
-          }
-        ],
-        "responses": {
-          "200": {
-            "description": "Successful Response",
-            "content": {
-              "application/json": {
-                "schema": {
-                  "$ref": "#/components/schemas/AdminCopilotUsersResponse"
-                }
-              }
-            }
-          },
-          "401": {
-            "$ref": "#/components/responses/HTTP401NotAuthenticatedError"
-          },
-          "422": {
-            "description": "Validation Error",
-            "content": {
-              "application/json": {
-                "schema": { "$ref": "#/components/schemas/HTTPValidationError" }
-              }
-            }
-          }
-        }
-      }
-    },
     "/api/users/admin/invited-users": {
       "get": {
         "tags": ["v2", "admin", "users", "admin"],
@@ -7460,42 +7270,6 @@
         "required": ["new_balance", "transaction_key"],
         "title": "AddUserCreditsResponse"
       },
-      "AdminCopilotUserSummary": {
-        "properties": {
-          "id": { "type": "string", "title": "Id" },
-          "email": { "type": "string", "title": "Email" },
-          "name": {
-            "anyOf": [{ "type": "string" }, { "type": "null" }],
-            "title": "Name"
-          },
-          "timezone": { "type": "string", "title": "Timezone" },
-          "created_at": {
-            "type": "string",
-            "format": "date-time",
-            "title": "Created At"
-          },
-          "updated_at": {
-            "type": "string",
-            "format": "date-time",
-            "title": "Updated At"
-          }
-        },
-        "type": "object",
-        "required": ["id", "email", "timezone", "created_at", "updated_at"],
-        "title": "AdminCopilotUserSummary"
-      },
-      "AdminCopilotUsersResponse": {
-        "properties": {
-          "users": {
-            "items": { "$ref": "#/components/schemas/AdminCopilotUserSummary" },
-            "type": "array",
-            "title": "Users"
-          }
-        },
-        "type": "object",
-        "required": ["users"],
-        "title": "AdminCopilotUsersResponse"
-      },
       "AgentDetails": {
         "properties": {
           "id": { "type": "string", "title": "Id" },
@@ -7509,12 +7283,14 @@
           "inputs": {
             "additionalProperties": true,
             "type": "object",
-            "title": "Inputs"
+            "title": "Inputs",
+            "default": {}
           },
           "credentials": {
             "items": { "$ref": "#/components/schemas/CredentialsMetaInput" },
             "type": "array",
-            "title": "Credentials"
+            "title": "Credentials",
+            "default": []
           },
           "execution_options": {
             "$ref": "#/components/schemas/ExecutionOptions"
@@ -8091,17 +7867,20 @@
           "inputs": {
             "additionalProperties": true,
             "type": "object",
-            "title": "Inputs"
+            "title": "Inputs",
+            "default": {}
           },
           "outputs": {
             "additionalProperties": true,
             "type": "object",
-            "title": "Outputs"
+            "title": "Outputs",
+            "default": {}
           },
           "credentials": {
             "items": { "$ref": "#/components/schemas/CredentialsMetaInput" },
             "type": "array",
-            "title": "Credentials"
+            "title": "Credentials",
+            "default": []
           }
         },
         "type": "object",
@@ -8640,16 +8419,6 @@
         "required": ["query", "conversation_history", "message_id"],
         "title": "ChatRequest"
       },
-      "ChatSessionStartType": {
-        "type": "string",
-        "enum": [
-          "MANUAL",
-          "AUTOPILOT_NIGHTLY",
-          "AUTOPILOT_CALLBACK",
-          "AUTOPILOT_INVITE_CTA"
-        ],
-        "title": "ChatSessionStartType"
-      },
       "ClarificationNeededResponse": {
         "properties": {
           "type": {
@@ -8686,20 +8455,6 @@
         "title": "ClarifyingQuestion",
         "description": "A question that needs user clarification."
       },
-      "ConsumeCallbackTokenRequest": {
-        "properties": { "token": { "type": "string", "title": "Token" } },
-        "type": "object",
-        "required": ["token"],
-        "title": "ConsumeCallbackTokenRequest"
-      },
-      "ConsumeCallbackTokenResponse": {
-        "properties": {
-          "session_id": { "type": "string", "title": "Session Id" }
-        },
-        "type": "object",
-        "required": ["session_id"],
-        "title": "ConsumeCallbackTokenResponse"
-      },
       "ContentType": {
         "type": "string",
         "enum": [
@@ -11123,7 +10878,8 @@
           "suggestions": {
             "items": { "type": "string" },
             "type": "array",
-            "title": "Suggestions"
+            "title": "Suggestions",
+            "default": []
           },
           "name": { "type": "string", "title": "Name", "default": "no_results" }
         },
@@ -12159,7 +11915,6 @@
           "error",
           "no_results",
           "need_login",
-          "completion_report_saved",
           "agents_found",
           "agent_details",
           "setup_requirements",
@@ -12416,37 +12171,6 @@
         "required": ["items", "search_id", "total_items", "pagination"],
         "title": "SearchResponse"
       },
-      "SendCopilotEmailsRequest": {
-        "properties": { "user_id": { "type": "string", "title": "User Id" } },
-        "type": "object",
-        "required": ["user_id"],
-        "title": "SendCopilotEmailsRequest"
-      },
-      "SendCopilotEmailsResponse": {
-        "properties": {
-          "candidate_count": { "type": "integer", "title": "Candidate Count" },
-          "processed_count": { "type": "integer", "title": "Processed Count" },
-          "sent_count": { "type": "integer", "title": "Sent Count" },
-          "skipped_count": { "type": "integer", "title": "Skipped Count" },
-          "repair_queued_count": {
-            "type": "integer",
-            "title": "Repair Queued Count"
-          },
-          "running_count": { "type": "integer", "title": "Running Count" },
-          "failed_count": { "type": "integer", "title": "Failed Count" }
-        },
-        "type": "object",
-        "required": [
-          "candidate_count",
-          "processed_count",
-          "sent_count",
-          "skipped_count",
-          "repair_queued_count",
-          "running_count",
-          "failed_count"
-        ],
-        "title": "SendCopilotEmailsResponse"
-      },
       "SessionDetailResponse": {
         "properties": {
           "id": { "type": "string", "title": "Id" },
@@ -12456,11 +12180,6 @@
             "anyOf": [{ "type": "string" }, { "type": "null" }],
             "title": "User Id"
           },
-          "start_type": { "$ref": "#/components/schemas/ChatSessionStartType" },
-          "execution_tag": {
-            "anyOf": [{ "type": "string" }, { "type": "null" }],
-            "title": "Execution Tag"
-          },
           "messages": {
             "items": { "additionalProperties": true, "type": "object" },
             "type": "array",
@@ -12474,14 +12193,7 @@
           }
         },
         "type": "object",
-        "required": [
-          "id",
-          "created_at",
-          "updated_at",
-          "user_id",
-          "start_type",
-          "messages"
-        ],
+        "required": ["id", "created_at", "updated_at", "user_id", "messages"],
         "title": "SessionDetailResponse",
         "description": "Response model providing complete details for a chat session, including messages."
       },
@@ -12494,21 +12206,10 @@
             "anyOf": [{ "type": "string" }, { "type": "null" }],
             "title": "Title"
           },
-          "start_type": { "$ref": "#/components/schemas/ChatSessionStartType" },
-          "execution_tag": {
-            "anyOf": [{ "type": "string" }, { "type": "null" }],
-            "title": "Execution Tag"
-          },
           "is_processing": { "type": "boolean", "title": "Is Processing" }
         },
         "type": "object",
-        "required": [
-          "id",
-          "created_at",
-          "updated_at",
-          "start_type",
-          "is_processing"
-        ],
+        "required": ["id", "created_at", "updated_at", "is_processing"],
         "title": "SessionSummaryResponse",
         "description": "Response model for a session summary (without messages)."
       },
@@ -14139,24 +13840,6 @@
         "required": ["transactions", "next_transaction_time"],
         "title": "TransactionHistory"
       },
-      "TriggerCopilotSessionRequest": {
-        "properties": {
-          "user_id": { "type": "string", "title": "User Id" },
-          "start_type": { "$ref": "#/components/schemas/ChatSessionStartType" }
-        },
-        "type": "object",
-        "required": ["user_id", "start_type"],
-        "title": "TriggerCopilotSessionRequest"
-      },
-      "TriggerCopilotSessionResponse": {
-        "properties": {
-          "session_id": { "type": "string", "title": "Session Id" },
-          "start_type": { "$ref": "#/components/schemas/ChatSessionStartType" }
-        },
-        "type": "object",
-        "required": ["session_id", "start_type"],
-        "title": "TriggerCopilotSessionResponse"
-      },
       "TriggeredPresetSetupRequest": {
         "properties": {
           "name": { "type": "string", "title": "Name" },
@@ -15088,7 +14771,8 @@
           "missing_credentials": {
             "additionalProperties": true,
             "type": "object",
-            "title": "Missing Credentials"
+            "title": "Missing Credentials",
+            "default": {}
           },
           "ready_to_run": {
             "type": "boolean",