add entrypoint to pyproject.toml

## Summary

Enables Anthropic's extended thinking feature for Claude models in
CoPilot via OpenRouter. This keeps the model's chain-of-thought
reasoning internal rather than outputting it to users.

## Problem

The CoPilot prompt was designed for a thinking agent (with
`<internal_reasoning>` tags), but extended thinking wasn't enabled on
the API side. This caused the model to output its reasoning as regular
text, leaking internal analysis to users.

## Solution

Added thinking configuration to the OpenRouter `extra_body` for
Anthropic models:
```python
extra_body["provider"] = {
    "anthropic": {
        "thinking": {
            "type": "enabled",
            "budget_tokens": config.thinking_budget_tokens,
        }
    }
}
```

## Configuration

New settings in `ChatConfig`:
| Setting | Default | Description |
|---------|---------|-------------|
| `thinking_enabled` | `True` | Enable extended thinking for Claude
models |
| `thinking_budget_tokens` | `10000` | Token budget for thinking
(1000-100000) |

## Changes

- `config.py`: Added `thinking_enabled` and `thinking_budget_tokens`
settings
- `service.py`: Added thinking config to all 3 places where `extra_body`
is built for LLM calls

## Testing

- Verify CoPilot responses no longer include internal reasoning text
- Check that Claude's extended thinking is working (should see thinking
tokens in usage)
- Confirm non-Anthropic models are unaffected

## Related

Discussion:
https://discord.com/channels/1126875755960336515/1126875756925046928/1470779843552612607

---------

Co-authored-by: Swifty <craigswift13@gmail.com>

.github/workflows/platform-fullstack-ci.yml

@@ -56,7 +56,7 @@ jobs:
         run: pnpm install --frozen-lockfile
 
   types:
-    runs-on: ubuntu-latest
+    runs-on: big-boi
     needs: setup
     strategy:
       fail-fast: false
@@ -85,7 +85,7 @@ jobs:
 
       - name: Run docker compose
         run: |
-          docker compose -f ../docker-compose.yml --profile local --profile deps_backend up -d
+          docker compose -f ../docker-compose.yml --profile local up -d deps_backend
 
       - name: Restore dependencies cache
         uses: actions/cache@v5

autogpt_platform/autogpt_libs/poetry.lock

@@ -1,4 +1,4 @@
-# This file is automatically @generated by Poetry 2.2.1 and should not be changed by hand.
+# This file is automatically @generated by Poetry 2.1.1 and should not be changed by hand.
 
 [[package]]
 name = "annotated-doc"
@@ -67,7 +67,7 @@ description = "Backport of asyncio.Runner, a context manager that controls event
 optional = false
 python-versions = "<3.11,>=3.8"
 groups = ["dev"]
-markers = "python_version == \"3.10\""
+markers = "python_version < \"3.11\""
 files = [
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+    {file = "coverage-7.13.4-cp314-cp314t-win_amd64.whl", hash = "sha256:4c7d3cc01e7350f2f0f6f7036caaf5673fb56b6998889ccfe9e1c1fe75a9c932"},
+    {file = "coverage-7.13.4-cp314-cp314t-win_arm64.whl", hash = "sha256:23e3f687cf945070d1c90f85db66d11e3025665d8dafa831301a0e0038f3db9b"},
+    {file = "coverage-7.13.4-py3-none-any.whl", hash = "sha256:1af1641e57cf7ba1bd67d677c9abdbcd6cc2ab7da3bca7fa1e2b7e50e65f2ad0"},
+    {file = "coverage-7.13.4.tar.gz", hash = "sha256:e5c8f6ed1e61a8b2dcdf31eb0b9bbf0130750ca79c1c49eb898e2ad86f5ccc91"},
 ]
 
 [package.dependencies]
@@ -523,7 +541,7 @@ description = "Backport of PEP 654 (exception groups)"
 optional = false
 python-versions = ">=3.7"
 groups = ["main", "dev"]
-markers = "python_version == \"3.10\""
+markers = "python_version < \"3.11\""
 files = [
     {file = "exceptiongroup-1.3.0-py3-none-any.whl", hash = "sha256:4d111e6e0c13d0644cad6ddaa7ed0261a0b36971f6d23e7ec9b4b9097da78a10"},
     {file = "exceptiongroup-1.3.0.tar.gz", hash = "sha256:b241f5885f560bc56a59ee63ca4c6a8bfa46ae4ad651af316d4e81817bb9fd88"},
@@ -2162,23 +2180,23 @@ testing = ["coverage (>=6.2)", "hypothesis (>=5.7.1)"]
 
 [[package]]
 name = "pytest-cov"
-version = "6.2.1"
+version = "7.0.0"
 description = "Pytest plugin for measuring coverage."
 optional = false
 python-versions = ">=3.9"
 groups = ["dev"]
 files = [
-    {file = "pytest_cov-6.2.1-py3-none-any.whl", hash = "sha256:f5bc4c23f42f1cdd23c70b1dab1bbaef4fc505ba950d53e0081d0730dd7e86d5"},
-    {file = "pytest_cov-6.2.1.tar.gz", hash = "sha256:25cc6cc0a5358204b8108ecedc51a9b57b34cc6b8c967cc2c01a4e00d8a67da2"},
+    {file = "pytest_cov-7.0.0-py3-none-any.whl", hash = "sha256:3b8e9558b16cc1479da72058bdecf8073661c7f57f7d3c5f22a1c23507f2d861"},
+    {file = "pytest_cov-7.0.0.tar.gz", hash = "sha256:33c97eda2e049a0c5298e91f519302a1334c26ac65c1a483d6206fd458361af1"},
 ]
 
 [package.dependencies]
-coverage = {version = ">=7.5", extras = ["toml"]}
+coverage = {version = ">=7.10.6", extras = ["toml"]}
 pluggy = ">=1.2"
-pytest = ">=6.2.5"
+pytest = ">=7"
 
 [package.extras]
-testing = ["fields", "hunter", "process-tests", "pytest-xdist", "virtualenv"]
+testing = ["process-tests", "pytest-xdist", "virtualenv"]
 
 [[package]]
 name = "pytest-mock"
@@ -2545,7 +2563,7 @@ description = "A lil' TOML parser"
 optional = false
 python-versions = ">=3.8"
 groups = ["dev"]
-markers = "python_version == \"3.10\""
+markers = "python_version < \"3.11\""
 files = [
     {file = "tomli-2.2.1-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:678e4fa69e4575eb77d103de3df8a895e1591b48e740211bd1067378c69e8249"},
     {file = "tomli-2.2.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:023aa114dd824ade0100497eb2318602af309e5a55595f76b626d6d9f3b7b0a6"},
@@ -2893,4 +2911,4 @@ type = ["pytest-mypy"]
 [metadata]
 lock-version = "2.1"
 python-versions = ">=3.10,<4.0"
-content-hash = "b7ac335a86aa44c3d7d2802298818b389a6f1286e3e9b7b0edb2ff06377cecaf"
+content-hash = "40eae94995dc0a388fa832ed4af9b6137f28d5b5ced3aaea70d5f91d4d9a179d"

autogpt_platform/autogpt_libs/pyproject.toml

@@ -26,7 +26,7 @@ pyright = "^1.1.408"
 pytest = "^8.4.1"
 pytest-asyncio = "^1.3.0"
 pytest-mock = "^3.15.1"
-pytest-cov = "^6.2.1"
+pytest-cov = "^7.0.0"
 ruff = "^0.15.0"
 
 [build-system]

autogpt_platform/backend/backend/api/external/v1/tools.py

@@ -15,9 +15,9 @@ from prisma.enums import APIKeyPermission
 from pydantic import BaseModel, Field
 
 from backend.api.external.middleware import require_permission
-from backend.api.features.chat.model import ChatSession
-from backend.api.features.chat.tools import find_agent_tool, run_agent_tool
-from backend.api.features.chat.tools.models import ToolResponseBase
+from backend.copilot.model import ChatSession
+from backend.copilot.tools import find_agent_tool, run_agent_tool
+from backend.copilot.tools.models import ToolResponseBase
 from backend.data.auth.base import APIAuthorizationInfo
 
 logger = logging.getLogger(__name__)

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

@@ -6,19 +6,49 @@ from collections.abc import AsyncGenerator
 from typing import Annotated
 
 from autogpt_libs import auth
-from fastapi import APIRouter, Depends, Header, HTTPException, Query, Security
+from fastapi import APIRouter, Depends, Header, HTTPException, Query, Response, Security
 from fastapi.responses import StreamingResponse
 from pydantic import BaseModel
 
+from backend.copilot import service as chat_service
+from backend.copilot import stream_registry
+from backend.copilot.completion_handler import (
+    process_operation_failure,
+    process_operation_success,
+)
+from backend.copilot.config import ChatConfig
+from backend.copilot.executor.utils import enqueue_copilot_task
+from backend.copilot.model import (
+    ChatSession,
+    create_chat_session,
+    get_chat_session,
+    get_user_sessions,
+)
+from backend.copilot.response_model import StreamFinish, StreamHeartbeat
+from backend.copilot.tools.models import (
+    AgentDetailsResponse,
+    AgentOutputResponse,
+    AgentPreviewResponse,
+    AgentSavedResponse,
+    AgentsFoundResponse,
+    BlockListResponse,
+    BlockOutputResponse,
+    ClarificationNeededResponse,
+    DocPageResponse,
+    DocSearchResultsResponse,
+    ErrorResponse,
+    ExecutionStartedResponse,
+    InputValidationErrorResponse,
+    NeedLoginResponse,
+    NoResultsResponse,
+    OperationInProgressResponse,
+    OperationPendingResponse,
+    OperationStartedResponse,
+    SetupRequirementsResponse,
+    UnderstandingUpdatedResponse,
+)
 from backend.util.exceptions import NotFoundError
 
-from . import service as chat_service
-from . import stream_registry
-from .completion_handler import process_operation_failure, process_operation_success
-from .config import ChatConfig
-from .model import ChatSession, create_chat_session, get_chat_session, get_user_sessions
-from .response_model import StreamFinish, StreamHeartbeat, StreamStart
-
 config = ChatConfig()
 
 
@@ -269,8 +299,6 @@ async def stream_chat_post(
     import time
 
     stream_start_time = time.perf_counter()
-
-    # Base log metadata (task_id added after creation)
     log_meta = {"component": "ChatStream", "session_id": session_id}
     if user_id:
         log_meta["user_id"] = user_id
@@ -281,7 +309,7 @@ async def stream_chat_post(
         extra={"json_fields": log_meta},
     )
 
-    session = await _validate_and_get_session(session_id, user_id)
+    _session = await _validate_and_get_session(session_id, user_id)  # noqa: F841
     logger.info(
         f"[TIMING] session validated in {(time.perf_counter() - stream_start_time)*1000:.1f}ms",
         extra={
@@ -316,100 +344,20 @@ async def stream_chat_post(
         },
     )
 
-    # Background task that runs the AI generation independently of SSE connection
-    async def run_ai_generation():
-        import time as time_module
+    # Enqueue the task to RabbitMQ for processing by the CoPilot executor
+    await enqueue_copilot_task(
+        task_id=task_id,
+        session_id=session_id,
+        user_id=user_id,
+        operation_id=operation_id,
+        message=request.message,
+        is_user_message=request.is_user_message,
+        context=request.context,
+    )
 
-        gen_start_time = time_module.perf_counter()
-        logger.info(
-            f"[TIMING] run_ai_generation STARTED, task={task_id}, session={session_id}, user={user_id}",
-            extra={"json_fields": log_meta},
-        )
-        first_chunk_time, ttfc = None, None
-        chunk_count = 0
-        try:
-            # Emit a start event with task_id for reconnection
-            start_chunk = StreamStart(messageId=task_id, taskId=task_id)
-            await stream_registry.publish_chunk(task_id, start_chunk)
-            logger.info(
-                f"[TIMING] StreamStart published at {(time_module.perf_counter() - gen_start_time)*1000:.1f}ms",
-                extra={
-                    "json_fields": {
-                        **log_meta,
-                        "elapsed_ms": (time_module.perf_counter() - gen_start_time)
-                        * 1000,
-                    }
-                },
-            )
-
-            logger.info(
-                "[TIMING] Calling stream_chat_completion",
-                extra={"json_fields": log_meta},
-            )
-            async for chunk in chat_service.stream_chat_completion(
-                session_id,
-                request.message,
-                is_user_message=request.is_user_message,
-                user_id=user_id,
-                session=session,  # Pass pre-fetched session to avoid double-fetch
-                context=request.context,
-            ):
-                chunk_count += 1
-                if first_chunk_time is None:
-                    first_chunk_time = time_module.perf_counter()
-                    ttfc = first_chunk_time - gen_start_time
-                    logger.info(
-                        f"[TIMING] FIRST AI CHUNK at {ttfc:.2f}s, type={type(chunk).__name__}",
-                        extra={
-                            "json_fields": {
-                                **log_meta,
-                                "chunk_type": type(chunk).__name__,
-                                "time_to_first_chunk_ms": ttfc * 1000,
-                            }
-                        },
-                    )
-                # Write to Redis (subscribers will receive via XREAD)
-                await stream_registry.publish_chunk(task_id, chunk)
-
-            gen_end_time = time_module.perf_counter()
-            total_time = (gen_end_time - gen_start_time) * 1000
-            logger.info(
-                f"[TIMING] run_ai_generation FINISHED in {total_time/1000:.1f}s; "
-                f"task={task_id}, session={session_id}, "
-                f"ttfc={ttfc or -1:.2f}s, n_chunks={chunk_count}",
-                extra={
-                    "json_fields": {
-                        **log_meta,
-                        "total_time_ms": total_time,
-                        "time_to_first_chunk_ms": (
-                            ttfc * 1000 if ttfc is not None else None
-                        ),
-                        "n_chunks": chunk_count,
-                    }
-                },
-            )
-
-            await stream_registry.mark_task_completed(task_id, "completed")
-        except Exception as e:
-            elapsed = time_module.perf_counter() - gen_start_time
-            logger.error(
-                f"[TIMING] run_ai_generation ERROR after {elapsed:.2f}s: {e}",
-                extra={
-                    "json_fields": {
-                        **log_meta,
-                        "elapsed_ms": elapsed * 1000,
-                        "error": str(e),
-                    }
-                },
-            )
-            await stream_registry.mark_task_completed(task_id, "failed")
-
-    # Start the AI generation in a background task
-    bg_task = asyncio.create_task(run_ai_generation())
-    await stream_registry.set_task_asyncio_task(task_id, bg_task)
     setup_time = (time.perf_counter() - stream_start_time) * 1000
     logger.info(
-        f"[TIMING] Background task started, setup={setup_time:.1f}ms",
+        f"[TIMING] Task enqueued to RabbitMQ, setup={setup_time:.1f}ms",
         extra={"json_fields": {**log_meta, "setup_time_ms": setup_time}},
     )
 
@@ -428,34 +376,13 @@ async def stream_chat_post(
         chunks_yielded = 0
         try:
             # Subscribe to the task stream (this replays existing messages + live updates)
-            subscribe_start = time_module.perf_counter()
-            logger.info(
-                "[TIMING] Calling subscribe_to_task",
-                extra={"json_fields": log_meta},
-            )
             subscriber_queue = await stream_registry.subscribe_to_task(
                 task_id=task_id,
                 user_id=user_id,
                 last_message_id="0-0",  # Get all messages from the beginning
             )
-            subscribe_time = (time_module.perf_counter() - subscribe_start) * 1000
-            logger.info(
-                f"[TIMING] subscribe_to_task completed in {subscribe_time:.1f}ms, "
-                f"queue_ok={subscriber_queue is not None}",
-                extra={
-                    "json_fields": {
-                        **log_meta,
-                        "duration_ms": subscribe_time,
-                        "queue_obtained": subscriber_queue is not None,
-                    }
-                },
-            )
 
             if subscriber_queue is None:
-                logger.info(
-                    "[TIMING] subscriber_queue is None, yielding finish",
-                    extra={"json_fields": log_meta},
-                )
                 yield StreamFinish().to_sse()
                 yield "data: [DONE]\n\n"
                 return
@@ -467,11 +394,7 @@ async def stream_chat_post(
             )
             while True:
                 try:
-                    queue_wait_start = time_module.perf_counter()
                     chunk = await asyncio.wait_for(subscriber_queue.get(), timeout=30.0)
-                    queue_wait_time = (
-                        time_module.perf_counter() - queue_wait_start
-                    ) * 1000
                     chunks_yielded += 1
 
                     if not first_chunk_yielded:
@@ -479,26 +402,12 @@ async def stream_chat_post(
                         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__}, "
-                            f"wait={queue_wait_time:.1f}ms",
+                            f"type={type(chunk).__name__}",
                             extra={
                                 "json_fields": {
                                     **log_meta,
                                     "chunk_type": type(chunk).__name__,
                                     "elapsed_ms": elapsed * 1000,
-                                    "queue_wait_ms": queue_wait_time,
-                                }
-                            },
-                        )
-                    elif chunks_yielded % 50 == 0:
-                        logger.info(
-                            f"[TIMING] Chunk #{chunks_yielded}, "
-                            f"type={type(chunk).__name__}",
-                            extra={
-                                "json_fields": {
-                                    **log_meta,
-                                    "chunk_number": chunks_yielded,
-                                    "chunk_type": type(chunk).__name__,
                                 }
                             },
                         )
@@ -521,13 +430,6 @@ async def stream_chat_post(
                         )
                         break
                 except asyncio.TimeoutError:
-                    # Send heartbeat to keep connection alive
-                    logger.info(
-                        f"[TIMING] Heartbeat timeout, chunks_so_far={chunks_yielded}",
-                        extra={
-                            "json_fields": {**log_meta, "chunks_so_far": chunks_yielded}
-                        },
-                    )
                     yield StreamHeartbeat().to_sse()
 
         except GeneratorExit:
@@ -592,63 +494,90 @@ async def stream_chat_post(
 @router.get(
     "/sessions/{session_id}/stream",
 )
-async def stream_chat_get(
+async def resume_session_stream(
     session_id: str,
-    message: Annotated[str, Query(min_length=1, max_length=10000)],
     user_id: str | None = Depends(auth.get_user_id),
-    is_user_message: bool = Query(default=True),
 ):
     """
-    Stream chat responses for a session (GET - legacy endpoint).
+    Resume an active stream for a session.
 
-    Streams the AI/completion responses in real time over Server-Sent Events (SSE), including:
-      - Text fragments as they are generated
-      - Tool call UI elements (if invoked)
-      - Tool execution results
+    Called by the AI SDK's ``useChat(resume: true)`` on page load.
+    Checks for an active (in-progress) task on the session and either replays
+    the full SSE stream or returns 204 No Content if nothing is running.
 
     Args:
-        session_id: The chat session identifier to associate with the streamed messages.
-        message: The user's new message to process.
+        session_id: The chat session identifier.
         user_id: Optional authenticated user ID.
-        is_user_message: Whether the message is a user message.
-    Returns:
-        StreamingResponse: SSE-formatted response chunks.
 
+    Returns:
+        StreamingResponse (SSE) when an active stream exists,
+        or 204 No Content when there is nothing to resume.
     """
-    session = await _validate_and_get_session(session_id, user_id)
+    import asyncio
+
+    active_task, _last_id = await stream_registry.get_active_task_for_session(
+        session_id, user_id
+    )
+
+    if not active_task:
+        return Response(status_code=204)
+
+    subscriber_queue = await stream_registry.subscribe_to_task(
+        task_id=active_task.task_id,
+        user_id=user_id,
+        last_message_id="0-0",  # Full replay so useChat rebuilds the message
+    )
+
+    if subscriber_queue is None:
+        return Response(status_code=204)
 
     async def event_generator() -> AsyncGenerator[str, None]:
         chunk_count = 0
         first_chunk_type: str | None = None
-        async for chunk in chat_service.stream_chat_completion(
-            session_id,
-            message,
-            is_user_message=is_user_message,
-            user_id=user_id,
-            session=session,  # Pass pre-fetched session to avoid double-fetch
-        ):
-            if chunk_count < 3:
-                logger.info(
-                    "Chat stream chunk",
-                    extra={
-                        "session_id": session_id,
-                        "chunk_type": str(chunk.type),
-                    },
+        try:
+            while True:
+                try:
+                    chunk = await asyncio.wait_for(subscriber_queue.get(), timeout=30.0)
+                    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_task(
+                    active_task.task_id, subscriber_queue
                 )
-            if not first_chunk_type:
-                first_chunk_type = str(chunk.type)
-            chunk_count += 1
-            yield chunk.to_sse()
-        logger.info(
-            "Chat stream completed",
-            extra={
-                "session_id": session_id,
-                "n_chunks": chunk_count,
-                "first_chunk_type": first_chunk_type,
-            },
-        )
-        # AI SDK protocol termination
-        yield "data: [DONE]\n\n"
+            except Exception as unsub_err:
+                logger.error(
+                    f"Error unsubscribing from task {active_task.task_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(),
@@ -656,8 +585,8 @@ async def stream_chat_get(
         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
+            "X-Accel-Buffering": "no",
+            "x-vercel-ai-ui-message-stream": "v1",
         },
     )
 
@@ -969,3 +898,42 @@ async def health_check() -> dict:
         "service": "chat",
         "version": "0.1.0",
     }
+
+
+# ========== Schema Export (for OpenAPI / Orval codegen) ==========
+
+ToolResponseUnion = (
+    AgentsFoundResponse
+    | NoResultsResponse
+    | AgentDetailsResponse
+    | SetupRequirementsResponse
+    | ExecutionStartedResponse
+    | NeedLoginResponse
+    | ErrorResponse
+    | InputValidationErrorResponse
+    | AgentOutputResponse
+    | UnderstandingUpdatedResponse
+    | AgentPreviewResponse
+    | AgentSavedResponse
+    | ClarificationNeededResponse
+    | BlockListResponse
+    | BlockOutputResponse
+    | DocSearchResultsResponse
+    | DocPageResponse
+    | OperationStartedResponse
+    | OperationPendingResponse
+    | OperationInProgressResponse
+)
+
+
+@router.get(
+    "/schema/tool-responses",
+    response_model=ToolResponseUnion,
+    include_in_schema=True,
+    summary="[Dummy] Tool response type export for codegen",
+    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() -> 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/store/hybrid_search.py

@@ -8,6 +8,7 @@ Includes BM25 reranking for improved lexical relevance.
 
 import logging
 import re
+import time
 from dataclasses import dataclass
 from typing import Any, Literal
 
@@ -362,7 +363,11 @@ async def unified_hybrid_search(
         LIMIT {limit_param} OFFSET {offset_param}
     """
 
-    results = await query_raw_with_schema(sql_query, *params)
+    try:
+        results = await query_raw_with_schema(sql_query, *params)
+    except Exception as e:
+        await _log_vector_error_diagnostics(e)
+        raise
 
     total = results[0]["total_count"] if results else 0
     # Apply BM25 reranking
@@ -686,7 +691,11 @@ async def hybrid_search(
         LIMIT {limit_param} OFFSET {offset_param}
     """
 
-    results = await query_raw_with_schema(sql_query, *params)
+    try:
+        results = await query_raw_with_schema(sql_query, *params)
+    except Exception as e:
+        await _log_vector_error_diagnostics(e)
+        raise
 
     total = results[0]["total_count"] if results else 0
 
@@ -718,6 +727,87 @@ async def hybrid_search_simple(
     return await hybrid_search(query=query, page=page, page_size=page_size)
 
 
+# ============================================================================
+# Diagnostics
+# ============================================================================
+
+# Rate limit: only log vector error diagnostics once per this interval
+_VECTOR_DIAG_INTERVAL_SECONDS = 60
+_last_vector_diag_time: float = 0
+
+
+async def _log_vector_error_diagnostics(error: Exception) -> None:
+    """Log diagnostic info when 'type vector does not exist' error occurs.
+
+    Note: Diagnostic queries use query_raw_with_schema which may run on a different
+    pooled connection than the one that failed. Session-level search_path can differ,
+    so these diagnostics show cluster-wide state, not necessarily the failed session.
+
+    Includes rate limiting to avoid log spam - only logs once per minute.
+    Caller should re-raise the error after calling this function.
+    """
+    global _last_vector_diag_time
+
+    # Check if this is the vector type error
+    error_str = str(error).lower()
+    if not (
+        "type" in error_str and "vector" in error_str and "does not exist" in error_str
+    ):
+        return
+
+    # Rate limit: only log once per interval
+    now = time.time()
+    if now - _last_vector_diag_time < _VECTOR_DIAG_INTERVAL_SECONDS:
+        return
+    _last_vector_diag_time = now
+
+    try:
+        diagnostics: dict[str, object] = {}
+
+        try:
+            search_path_result = await query_raw_with_schema("SHOW search_path")
+            diagnostics["search_path"] = search_path_result
+        except Exception as e:
+            diagnostics["search_path"] = f"Error: {e}"
+
+        try:
+            schema_result = await query_raw_with_schema("SELECT current_schema()")
+            diagnostics["current_schema"] = schema_result
+        except Exception as e:
+            diagnostics["current_schema"] = f"Error: {e}"
+
+        try:
+            user_result = await query_raw_with_schema(
+                "SELECT current_user, session_user, current_database()"
+            )
+            diagnostics["user_info"] = user_result
+        except Exception as e:
+            diagnostics["user_info"] = f"Error: {e}"
+
+        try:
+            # Check pgvector extension installation (cluster-wide, stable info)
+            ext_result = await query_raw_with_schema(
+                "SELECT extname, extversion, nspname as schema "
+                "FROM pg_extension e "
+                "JOIN pg_namespace n ON e.extnamespace = n.oid "
+                "WHERE extname = 'vector'"
+            )
+            diagnostics["pgvector_extension"] = ext_result
+        except Exception as e:
+            diagnostics["pgvector_extension"] = f"Error: {e}"
+
+        logger.error(
+            f"Vector type error diagnostics:\n"
+            f"  Error: {error}\n"
+            f"  search_path: {diagnostics.get('search_path')}\n"
+            f"  current_schema: {diagnostics.get('current_schema')}\n"
+            f"  user_info: {diagnostics.get('user_info')}\n"
+            f"  pgvector_extension: {diagnostics.get('pgvector_extension')}"
+        )
+    except Exception as diag_error:
+        logger.error(f"Failed to collect vector error diagnostics: {diag_error}")
+
+
 # Backward compatibility alias - HybridSearchWeights maps to StoreAgentSearchWeights
 # for existing code that expects the popularity parameter
 HybridSearchWeights = StoreAgentSearchWeights

autogpt_platform/backend/backend/api/rest_api.py

@@ -40,11 +40,11 @@ import backend.data.user
 import backend.integrations.webhooks.utils
 import backend.util.service
 import backend.util.settings
-from backend.api.features.chat.completion_consumer import (
+from backend.blocks.llm import DEFAULT_LLM_MODEL
+from backend.copilot.completion_consumer import (
     start_completion_consumer,
     stop_completion_consumer,
 )
-from backend.blocks.llm import DEFAULT_LLM_MODEL
 from backend.data.model import Credentials
 from backend.integrations.providers import ProviderName
 from backend.monitoring.instrumentation import instrument_fastapi

autogpt_platform/backend/backend/app.py

@@ -38,6 +38,7 @@ def main(**kwargs):
 
     from backend.api.rest_api import AgentServer
     from backend.api.ws_api import WebsocketServer
+    from backend.copilot.executor.manager import CoPilotExecutor
     from backend.executor import DatabaseManager, ExecutionManager, Scheduler
     from backend.notifications import NotificationManager
 
@@ -48,6 +49,7 @@ def main(**kwargs):
         WebsocketServer(),
         AgentServer(),
         ExecutionManager(),
+        CoPilotExecutor(),
         **kwargs,
     )
 

autogpt_platform/backend/backend/copilot/__init__.py

@@ -0,0 +1,8 @@
+"""CoPilot module - AI assistant for AutoGPT platform.
+
+This module contains the core CoPilot functionality including:
+- AI generation service (LLM calls)
+- Tool execution
+- Session management
+- Stream registry for SSE reconnection
+"""

autogpt_platform/backend/backend/copilot/completion_consumer.py

@@ -119,8 +119,9 @@ class ChatCompletionConsumer:
         """Lazily initialize Prisma client on first use."""
         if self._prisma is None:
             database_url = os.getenv("DATABASE_URL", "postgresql://localhost:5432")
-            self._prisma = Prisma(datasource={"url": database_url})
-            await self._prisma.connect()
+            prisma = Prisma(datasource={"url": database_url})
+            await prisma.connect()
+            self._prisma = prisma
             logger.info("[COMPLETION] Consumer Prisma client connected (lazy init)")
         return self._prisma
 

autogpt_platform/backend/backend/copilot/config.py

@@ -93,6 +93,12 @@ class ChatConfig(BaseSettings):
         description="Name of the prompt in Langfuse to fetch",
     )
 
+    # Extended thinking configuration for Claude models
+    thinking_enabled: bool = Field(
+        default=True,
+        description="Enable adaptive thinking for Claude models via OpenRouter",
+    )
+
     @field_validator("api_key", mode="before")
     @classmethod
     def get_api_key(cls, v):

autogpt_platform/backend/backend/copilot/executor/__init__.py

@@ -0,0 +1,5 @@
+"""CoPilot Executor - Dedicated service for AI generation and tool execution.
+
+This module contains the executor service that processes CoPilot tasks
+from RabbitMQ, following the graph executor pattern.
+"""

autogpt_platform/backend/backend/copilot/executor/__main__.py

@@ -0,0 +1,18 @@
+"""Entry point for running the CoPilot Executor service.
+
+Usage:
+    python -m backend.copilot.executor
+"""
+
+from backend.app import run_processes
+
+from .manager import CoPilotExecutor
+
+
+def main():
+    """Run the CoPilot Executor service."""
+    run_processes(CoPilotExecutor())
+
+
+if __name__ == "__main__":
+    main()

autogpt_platform/backend/backend/copilot/executor/manager.py

@@ -0,0 +1,462 @@
+"""CoPilot Executor Manager - main service for CoPilot task execution.
+
+This module contains the CoPilotExecutor class that consumes chat tasks from
+RabbitMQ and processes them using a thread pool, following the graph executor pattern.
+"""
+
+import logging
+import os
+import threading
+import time
+import uuid
+from concurrent.futures import Future, ThreadPoolExecutor
+
+from pika.adapters.blocking_connection import BlockingChannel
+from pika.spec import Basic, BasicProperties
+from prometheus_client import Gauge, start_http_server
+
+from backend.data import redis_client as redis
+from backend.data.rabbitmq import SyncRabbitMQ
+from backend.executor.cluster_lock import ClusterLock
+from backend.util.decorator import error_logged
+from backend.util.logging import TruncatedLogger
+from backend.util.process import AppProcess
+from backend.util.retry import continuous_retry, func_retry
+from backend.util.settings import Settings
+
+from .processor import execute_copilot_task, init_worker
+from .utils import (
+    COPILOT_CANCEL_QUEUE_NAME,
+    COPILOT_EXECUTION_QUEUE_NAME,
+    GRACEFUL_SHUTDOWN_TIMEOUT_SECONDS,
+    CancelCoPilotEvent,
+    CoPilotExecutionEntry,
+    create_copilot_queue_config,
+)
+
+logger = TruncatedLogger(logging.getLogger(__name__), prefix="[CoPilotExecutor]")
+settings = Settings()
+
+# Prometheus metrics
+active_tasks_gauge = Gauge(
+    "copilot_executor_active_tasks",
+    "Number of active CoPilot tasks",
+)
+pool_size_gauge = Gauge(
+    "copilot_executor_pool_size",
+    "Maximum number of CoPilot executor workers",
+)
+utilization_gauge = Gauge(
+    "copilot_executor_utilization_ratio",
+    "Ratio of active tasks to pool size",
+)
+
+
+class CoPilotExecutor(AppProcess):
+    """CoPilot Executor service for processing chat generation tasks.
+
+    This service consumes tasks from RabbitMQ, processes them using a thread pool,
+    and publishes results to Redis Streams. It follows the graph executor pattern
+    for reliable message handling and graceful shutdown.
+
+    Key features:
+    - RabbitMQ-based task distribution with manual acknowledgment
+    - Thread pool executor for concurrent task processing
+    - Cluster lock for duplicate prevention across pods
+    - Graceful shutdown with timeout for in-flight tasks
+    - FANOUT exchange for cancellation broadcast
+    """
+
+    def __init__(self):
+        super().__init__()
+        self.pool_size = settings.config.num_copilot_workers
+        self.active_tasks: dict[str, tuple[Future, threading.Event]] = {}
+        self.executor_id = str(uuid.uuid4())
+
+        self._executor = None
+        self._stop_consuming = None
+
+        self._cancel_thread = None
+        self._cancel_client = None
+        self._run_thread = None
+        self._run_client = None
+
+        self._task_locks: dict[str, ClusterLock] = {}
+
+    # ============ Main Entry Points (AppProcess interface) ============ #
+
+    def run(self):
+        """Main service loop - consume from RabbitMQ."""
+        logger.info(f"Pod assigned executor_id: {self.executor_id}")
+        logger.info(f"Spawn max-{self.pool_size} workers...")
+
+        pool_size_gauge.set(self.pool_size)
+        self._update_metrics()
+        start_http_server(settings.config.copilot_executor_port)
+
+        self.cancel_thread.start()
+        self.run_thread.start()
+
+        while True:
+            time.sleep(1e5)
+
+    def cleanup(self):
+        """Graceful shutdown with active execution waiting."""
+        pid = os.getpid()
+        logger.info(f"[cleanup {pid}] Starting graceful shutdown...")
+
+        # Signal the consumer thread to stop
+        try:
+            self.stop_consuming.set()
+            run_channel = self.run_client.get_channel()
+            run_channel.connection.add_callback_threadsafe(
+                lambda: run_channel.stop_consuming()
+            )
+            logger.info(f"[cleanup {pid}] Consumer has been signaled to stop")
+        except Exception as e:
+            logger.error(f"[cleanup {pid}] Error stopping consumer: {e}")
+
+        # Wait for active executions to complete
+        if self.active_tasks:
+            logger.info(
+                f"[cleanup {pid}] Waiting for {len(self.active_tasks)} active tasks to complete (timeout: {GRACEFUL_SHUTDOWN_TIMEOUT_SECONDS}s)..."
+            )
+
+            start_time = time.monotonic()
+            last_refresh = start_time
+            lock_refresh_interval = settings.config.cluster_lock_timeout / 10
+
+            while (
+                self.active_tasks
+                and (time.monotonic() - start_time) < GRACEFUL_SHUTDOWN_TIMEOUT_SECONDS
+            ):
+                self._cleanup_completed_tasks()
+                if not self.active_tasks:
+                    break
+
+                # Refresh cluster locks periodically
+                current_time = time.monotonic()
+                if current_time - last_refresh >= lock_refresh_interval:
+                    for lock in self._task_locks.values():
+                        try:
+                            lock.refresh()
+                        except Exception as e:
+                            logger.warning(
+                                f"[cleanup {pid}] Failed to refresh lock: {e}"
+                            )
+                    last_refresh = current_time
+
+                logger.info(
+                    f"[cleanup {pid}] {len(self.active_tasks)} tasks still active, waiting..."
+                )
+                time.sleep(10.0)
+
+        # Stop message consumers
+        if self._run_thread:
+            self._stop_message_consumers(
+                self._run_thread, self.run_client, "[cleanup][run]"
+            )
+        if self._cancel_thread:
+            self._stop_message_consumers(
+                self._cancel_thread, self.cancel_client, "[cleanup][cancel]"
+            )
+
+        # Shutdown executor
+        if self._executor:
+            logger.info(f"[cleanup {pid}] Shutting down executor...")
+            self._executor.shutdown(wait=False)
+
+        # Release any remaining locks
+        for task_id, lock in list(self._task_locks.items()):
+            try:
+                lock.release()
+                logger.info(f"[cleanup {pid}] Released lock for {task_id}")
+            except Exception as e:
+                logger.error(
+                    f"[cleanup {pid}] Failed to release lock for {task_id}: {e}"
+                )
+
+        logger.info(f"[cleanup {pid}] Graceful shutdown completed")
+
+    # ============ RabbitMQ Consumer Methods ============ #
+
+    @continuous_retry()
+    def _consume_cancel(self):
+        """Consume cancellation messages from FANOUT exchange."""
+        if self.stop_consuming.is_set() and not self.active_tasks:
+            logger.info("Stop reconnecting cancel consumer - service cleaned up")
+            return
+
+        if not self.cancel_client.is_ready:
+            self.cancel_client.disconnect()
+        self.cancel_client.connect()
+        cancel_channel = self.cancel_client.get_channel()
+        cancel_channel.basic_consume(
+            queue=COPILOT_CANCEL_QUEUE_NAME,
+            on_message_callback=self._handle_cancel_message,
+            auto_ack=True,
+        )
+        logger.info("Starting cancel message consumer...")
+        cancel_channel.start_consuming()
+        if not self.stop_consuming.is_set() or self.active_tasks:
+            raise RuntimeError("Cancel message consumer stopped unexpectedly")
+        logger.info("Cancel message consumer stopped gracefully")
+
+    @continuous_retry()
+    def _consume_run(self):
+        """Consume run messages from DIRECT exchange."""
+        if self.stop_consuming.is_set():
+            logger.info("Stop reconnecting run consumer - service cleaned up")
+            return
+
+        if not self.run_client.is_ready:
+            self.run_client.disconnect()
+        self.run_client.connect()
+        run_channel = self.run_client.get_channel()
+        run_channel.basic_qos(prefetch_count=self.pool_size)
+
+        run_channel.basic_consume(
+            queue=COPILOT_EXECUTION_QUEUE_NAME,
+            on_message_callback=self._handle_run_message,
+            auto_ack=False,
+            consumer_tag="copilot_execution_consumer",
+        )
+        run_channel.confirm_delivery()
+        logger.info("Starting to consume run messages...")
+        run_channel.start_consuming()
+        if not self.stop_consuming.is_set():
+            raise RuntimeError("Run message consumer stopped unexpectedly")
+        logger.info("Run message consumer stopped gracefully")
+
+    # ============ Message Handlers ============ #
+
+    @error_logged(swallow=True)
+    def _handle_cancel_message(
+        self,
+        _channel: BlockingChannel,
+        _method: Basic.Deliver,
+        _properties: BasicProperties,
+        body: bytes,
+    ):
+        """Handle cancel message from FANOUT exchange."""
+        request = CancelCoPilotEvent.model_validate_json(body)
+        task_id = request.task_id
+        if not task_id:
+            logger.warning("Cancel message missing 'task_id'")
+            return
+        if task_id not in self.active_tasks:
+            logger.debug(f"Cancel received for {task_id} but not active")
+            return
+
+        _, cancel_event = self.active_tasks[task_id]
+        logger.info(f"Received cancel for {task_id}")
+        if not cancel_event.is_set():
+            cancel_event.set()
+        else:
+            logger.debug(f"Cancel already set for {task_id}")
+
+    def _handle_run_message(
+        self,
+        _channel: BlockingChannel,
+        method: Basic.Deliver,
+        _properties: BasicProperties,
+        body: bytes,
+    ):
+        """Handle run message from DIRECT exchange."""
+        delivery_tag = method.delivery_tag
+
+        @func_retry
+        def ack_message(reject: bool, requeue: bool):
+            """Acknowledge or reject the message."""
+            channel = self.run_client.get_channel()
+            if reject:
+                channel.connection.add_callback_threadsafe(
+                    lambda: channel.basic_nack(delivery_tag, requeue=requeue)
+                )
+            else:
+                channel.connection.add_callback_threadsafe(
+                    lambda: channel.basic_ack(delivery_tag)
+                )
+
+        # Check if we're shutting down
+        if self.stop_consuming.is_set():
+            logger.info("Rejecting new task during shutdown")
+            ack_message(reject=True, requeue=True)
+            return
+
+        # Check if we can accept more tasks
+        self._cleanup_completed_tasks()
+        if len(self.active_tasks) >= self.pool_size:
+            ack_message(reject=True, requeue=True)
+            return
+
+        try:
+            entry = CoPilotExecutionEntry.model_validate_json(body)
+        except Exception as e:
+            logger.error(f"Could not parse run message: {e}, body={body}")
+            ack_message(reject=True, requeue=False)
+            return
+
+        task_id = entry.task_id
+
+        # Check for local duplicate
+        if task_id in self.active_tasks:
+            logger.warning(f"Task {task_id} already running locally")
+            ack_message(reject=True, requeue=True)
+            return
+
+        # Try to acquire cluster-wide lock
+        cluster_lock = ClusterLock(
+            redis=redis.get_redis(),
+            key=f"copilot_lock:{task_id}",
+            owner_id=self.executor_id,
+            timeout=settings.config.cluster_lock_timeout,
+        )
+        current_owner = cluster_lock.try_acquire()
+        if current_owner != self.executor_id:
+            if current_owner is not None:
+                logger.warning(f"Task {task_id} already running on pod {current_owner}")
+                ack_message(reject=True, requeue=False)
+            else:
+                logger.warning(
+                    f"Could not acquire lock for {task_id} - Redis unavailable"
+                )
+                ack_message(reject=True, requeue=True)
+            return
+
+        # Execute the task
+        try:
+            self._task_locks[task_id] = cluster_lock
+
+            logger.info(
+                f"Acquired cluster lock for {task_id}, executor_id={self.executor_id}"
+            )
+
+            cancel_event = threading.Event()
+            future = self.executor.submit(
+                execute_copilot_task, entry, cancel_event, cluster_lock
+            )
+            self.active_tasks[task_id] = (future, cancel_event)
+        except Exception as e:
+            logger.warning(f"Failed to setup execution for {task_id}: {e}")
+            cluster_lock.release()
+            if task_id in self._task_locks:
+                del self._task_locks[task_id]
+            ack_message(reject=True, requeue=True)
+            return
+
+        self._update_metrics()
+
+        def on_run_done(f: Future):
+            logger.info(f"Run completed for {task_id}")
+            try:
+                if exec_error := f.exception():
+                    logger.error(f"Execution for {task_id} failed: {exec_error}")
+                    ack_message(reject=True, requeue=True)
+                else:
+                    ack_message(reject=False, requeue=False)
+            except BaseException as e:
+                logger.exception(f"Error in run completion callback: {e}")
+            finally:
+                # Release the cluster lock
+                if task_id in self._task_locks:
+                    logger.info(f"Releasing cluster lock for {task_id}")
+                    self._task_locks[task_id].release()
+                    del self._task_locks[task_id]
+                self._cleanup_completed_tasks()
+
+        future.add_done_callback(on_run_done)
+
+    # ============ Helper Methods ============ #
+
+    def _cleanup_completed_tasks(self) -> list[str]:
+        """Remove completed futures from active_tasks and update metrics."""
+        completed_tasks = []
+        for task_id, (future, _) in self.active_tasks.items():
+            if future.done():
+                completed_tasks.append(task_id)
+
+        for task_id in completed_tasks:
+            logger.info(f"Cleaned up completed task {task_id}")
+            self.active_tasks.pop(task_id, None)
+
+        self._update_metrics()
+        return completed_tasks
+
+    def _update_metrics(self):
+        """Update Prometheus metrics."""
+        active_count = len(self.active_tasks)
+        active_tasks_gauge.set(active_count)
+        if self.stop_consuming.is_set():
+            utilization_gauge.set(1.0)
+        else:
+            utilization_gauge.set(
+                active_count / self.pool_size if self.pool_size > 0 else 0
+            )
+
+    def _stop_message_consumers(
+        self, thread: threading.Thread, client: SyncRabbitMQ, prefix: str
+    ):
+        """Stop a message consumer thread."""
+        try:
+            channel = client.get_channel()
+            channel.connection.add_callback_threadsafe(lambda: channel.stop_consuming())
+
+            try:
+                thread.join(timeout=300)
+            except TimeoutError:
+                logger.error(
+                    f"{prefix} Thread did not finish in time, forcing disconnect"
+                )
+
+            client.disconnect()
+            logger.info(f"{prefix} Client disconnected")
+        except Exception as e:
+            logger.error(f"{prefix} Error disconnecting client: {e}")
+
+    # ============ Lazy-initialized Properties ============ #
+
+    @property
+    def cancel_thread(self) -> threading.Thread:
+        if self._cancel_thread is None:
+            self._cancel_thread = threading.Thread(
+                target=lambda: self._consume_cancel(),
+                daemon=True,
+            )
+        return self._cancel_thread
+
+    @property
+    def run_thread(self) -> threading.Thread:
+        if self._run_thread is None:
+            self._run_thread = threading.Thread(
+                target=lambda: self._consume_run(),
+                daemon=True,
+            )
+        return self._run_thread
+
+    @property
+    def stop_consuming(self) -> threading.Event:
+        if self._stop_consuming is None:
+            self._stop_consuming = threading.Event()
+        return self._stop_consuming
+
+    @property
+    def executor(self) -> ThreadPoolExecutor:
+        if self._executor is None:
+            self._executor = ThreadPoolExecutor(
+                max_workers=self.pool_size,
+                initializer=init_worker,
+            )
+        return self._executor
+
+    @property
+    def cancel_client(self) -> SyncRabbitMQ:
+        if self._cancel_client is None:
+            self._cancel_client = SyncRabbitMQ(create_copilot_queue_config())
+        return self._cancel_client
+
+    @property
+    def run_client(self) -> SyncRabbitMQ:
+        if self._run_client is None:
+            self._run_client = SyncRabbitMQ(create_copilot_queue_config())
+        return self._run_client

autogpt_platform/backend/backend/copilot/executor/processor.py

@@ -0,0 +1,252 @@
+"""CoPilot execution processor - per-worker execution logic.
+
+This module contains the processor class that handles CoPilot task execution
+in a thread-local context, following the graph executor pattern.
+"""
+
+import asyncio
+import logging
+import threading
+import time
+
+from backend.copilot import service as copilot_service
+from backend.copilot import stream_registry
+from backend.copilot.response_model import StreamError, StreamFinish, StreamFinishStep
+from backend.executor.cluster_lock import ClusterLock
+from backend.util.decorator import error_logged
+from backend.util.logging import TruncatedLogger, configure_logging
+from backend.util.process import set_service_name
+from backend.util.retry import func_retry
+
+from .utils import CoPilotExecutionEntry, CoPilotLogMetadata
+
+logger = TruncatedLogger(logging.getLogger(__name__), prefix="[CoPilotExecutor]")
+
+
+# ============ Module Entry Points ============ #
+
+# Thread-local storage for processor instances
+_tls = threading.local()
+
+
+def execute_copilot_task(
+    entry: CoPilotExecutionEntry,
+    cancel: threading.Event,
+    cluster_lock: ClusterLock,
+):
+    """Execute a CoPilot task using the thread-local processor.
+
+    This function is the entry point called by the thread pool executor.
+
+    Args:
+        entry: The task payload
+        cancel: Threading event to signal cancellation
+        cluster_lock: Distributed lock for this execution
+    """
+    processor: CoPilotProcessor = _tls.processor
+    return processor.execute(entry, cancel, cluster_lock)
+
+
+def init_worker():
+    """Initialize the processor for the current worker thread.
+
+    This function is called by the thread pool executor when a new worker
+    thread is created. It ensures each worker has its own processor instance.
+    """
+    _tls.processor = CoPilotProcessor()
+    _tls.processor.on_executor_start()
+
+
+# ============ Processor Class ============ #
+
+
+class CoPilotProcessor:
+    """Per-worker execution logic for CoPilot tasks.
+
+    This class is instantiated once per worker thread and handles the execution
+    of CoPilot chat generation tasks. It maintains an async event loop for
+    running the async service code.
+
+    The execution flow:
+        1. CoPilot task is picked from RabbitMQ queue
+        2. Manager submits task to thread pool
+        3. Processor executes the task in its event loop
+        4. Results are published to Redis Streams
+    """
+
+    @func_retry
+    def on_executor_start(self):
+        """Initialize the processor when the worker thread starts.
+
+        This method is called once per worker thread to set up the async event
+        loop, connect to Prisma, and initialize any required resources.
+        """
+        configure_logging()
+        set_service_name("CoPilotExecutor")
+        self.tid = threading.get_ident()
+        self.execution_loop = asyncio.new_event_loop()
+        self.execution_thread = threading.Thread(
+            target=self.execution_loop.run_forever, daemon=True
+        )
+        self.execution_thread.start()
+
+        # Connect to Prisma in the worker's event loop
+        # This is required because the CoPilot service uses Prisma directly
+        # TODO: Use DatabaseManager, avoid direct Prisma connection(?)
+        asyncio.run_coroutine_threadsafe(
+            self._connect_prisma(), self.execution_loop
+        ).result(timeout=30.0)
+
+        logger.info(f"[CoPilotExecutor] Worker {self.tid} started")
+
+    async def _connect_prisma(self):
+        """Connect to Prisma database in the worker's event loop."""
+        from backend.data import db
+
+        if not db.is_connected():
+            await db.connect()
+            logger.info(f"[CoPilotExecutor] Worker {self.tid} connected to Prisma")
+
+    @error_logged(swallow=False)
+    def execute(
+        self,
+        entry: CoPilotExecutionEntry,
+        cancel: threading.Event,
+        cluster_lock: ClusterLock,
+    ):
+        """Execute a CoPilot task.
+
+        This is the main entry point for task execution. It runs the async
+        execution logic in the worker's event loop and handles errors.
+
+        Args:
+            entry: The task payload containing session and message info
+            cancel: Threading event to signal cancellation
+            cluster_lock: Distributed lock to prevent duplicate execution
+        """
+        log = CoPilotLogMetadata(
+            logging.getLogger(__name__),
+            task_id=entry.task_id,
+            session_id=entry.session_id,
+            user_id=entry.user_id,
+        )
+        log.info("Starting execution")
+
+        start_time = time.monotonic()
+
+        try:
+            # Run the async execution in our event loop
+            future = asyncio.run_coroutine_threadsafe(
+                self._execute_async(entry, cancel, cluster_lock, log),
+                self.execution_loop,
+            )
+
+            # Wait for completion, checking cancel periodically
+            while not future.done():
+                try:
+                    future.result(timeout=1.0)
+                except asyncio.TimeoutError:
+                    if cancel.is_set():
+                        log.info("Cancellation requested")
+                        future.cancel()
+                        break
+                    # Refresh cluster lock to maintain ownership
+                    cluster_lock.refresh()
+
+            if not future.cancelled():
+                # Get result to propagate any exceptions
+                future.result()
+
+            elapsed = time.monotonic() - start_time
+            log.info(f"Execution completed in {elapsed:.2f}s")
+
+        except Exception as e:
+            elapsed = time.monotonic() - start_time
+            log.error(f"Execution failed after {elapsed:.2f}s: {e}")
+            # Ensure task is marked as failed in stream registry
+            asyncio.run_coroutine_threadsafe(
+                self._mark_task_failed(entry.task_id, str(e)),
+                self.execution_loop,
+            ).result(timeout=10.0)
+            raise
+
+    async def _execute_async(
+        self,
+        entry: CoPilotExecutionEntry,
+        cancel: threading.Event,
+        cluster_lock: ClusterLock,
+        log: CoPilotLogMetadata,
+    ):
+        """Async execution logic for CoPilot task.
+
+        This method calls the existing stream_chat_completion service function
+        and publishes results to the stream registry.
+
+        Args:
+            entry: The task payload
+            cancel: Threading event to signal cancellation
+            cluster_lock: Distributed lock for refresh
+            log: Structured logger for this task
+        """
+        last_refresh = time.monotonic()
+        refresh_interval = 30.0  # Refresh lock every 30 seconds
+
+        try:
+            # Stream chat completion and publish chunks to Redis
+            async for chunk in copilot_service.stream_chat_completion(
+                session_id=entry.session_id,
+                message=entry.message if entry.message else None,
+                is_user_message=entry.is_user_message,
+                user_id=entry.user_id,
+                context=entry.context,
+                _task_id=entry.task_id,
+            ):
+                # Check for cancellation
+                if cancel.is_set():
+                    log.info("Cancelled during streaming")
+                    await stream_registry.publish_chunk(
+                        entry.task_id, StreamError(errorText="Operation cancelled")
+                    )
+                    await stream_registry.publish_chunk(
+                        entry.task_id, StreamFinishStep()
+                    )
+                    await stream_registry.publish_chunk(entry.task_id, StreamFinish())
+                    await stream_registry.mark_task_completed(
+                        entry.task_id, status="failed"
+                    )
+                    return
+
+                # Refresh cluster lock periodically
+                current_time = time.monotonic()
+                if current_time - last_refresh >= refresh_interval:
+                    cluster_lock.refresh()
+                    last_refresh = current_time
+
+                # Publish chunk to stream registry
+                await stream_registry.publish_chunk(entry.task_id, chunk)
+
+            # Mark task as completed
+            await stream_registry.mark_task_completed(entry.task_id, status="completed")
+            log.info("Task completed successfully")
+
+        except asyncio.CancelledError:
+            log.info("Task cancelled")
+            await stream_registry.mark_task_completed(entry.task_id, status="failed")
+            raise
+
+        except Exception as e:
+            log.error(f"Task failed: {e}")
+            await self._mark_task_failed(entry.task_id, str(e))
+            raise
+
+    async def _mark_task_failed(self, task_id: str, error_message: str):
+        """Mark a task as failed and publish error to stream registry."""
+        try:
+            await stream_registry.publish_chunk(
+                task_id, StreamError(errorText=error_message)
+            )
+            await stream_registry.publish_chunk(task_id, StreamFinishStep())
+            await stream_registry.publish_chunk(task_id, StreamFinish())
+            await stream_registry.mark_task_completed(task_id, status="failed")
+        except Exception as e:
+            logger.error(f"Failed to mark task {task_id} as failed: {e}")

autogpt_platform/backend/backend/copilot/executor/utils.py

@@ -0,0 +1,207 @@
+"""RabbitMQ queue configuration for CoPilot executor.
+
+Defines two exchanges and queues following the graph executor pattern:
+- 'copilot_execution' (DIRECT) for chat generation tasks
+- 'copilot_cancel' (FANOUT) for cancellation requests
+"""
+
+import logging
+
+from pydantic import BaseModel
+
+from backend.data.rabbitmq import Exchange, ExchangeType, Queue, RabbitMQConfig
+from backend.util.logging import TruncatedLogger, is_structured_logging_enabled
+
+logger = logging.getLogger(__name__)
+
+
+# ============ Logging Helper ============ #
+
+
+class CoPilotLogMetadata(TruncatedLogger):
+    """Structured logging helper for CoPilot executor.
+
+    In cloud environments (structured logging enabled), uses a simple prefix
+    and passes metadata via json_fields. In local environments, uses a detailed
+    prefix with all metadata key-value pairs for easier debugging.
+
+    Args:
+        logger: The underlying logger instance
+        max_length: Maximum log message length before truncation
+        **kwargs: Metadata key-value pairs (e.g., task_id="abc", session_id="xyz")
+            These are added to json_fields in cloud mode, or to the prefix in local mode.
+    """
+
+    def __init__(
+        self,
+        logger: logging.Logger,
+        max_length: int = 1000,
+        **kwargs: str | None,
+    ):
+        # Filter out None values
+        metadata = {k: v for k, v in kwargs.items() if v is not None}
+        metadata["component"] = "CoPilotExecutor"
+
+        if is_structured_logging_enabled():
+            prefix = "[CoPilotExecutor]"
+        else:
+            # Build prefix from metadata key-value pairs
+            meta_parts = "|".join(
+                f"{k}:{v}" for k, v in metadata.items() if k != "component"
+            )
+            prefix = (
+                f"[CoPilotExecutor|{meta_parts}]" if meta_parts else "[CoPilotExecutor]"
+            )
+
+        super().__init__(
+            logger,
+            max_length=max_length,
+            prefix=prefix,
+            metadata=metadata,
+        )
+
+
+# ============ Exchange and Queue Configuration ============ #
+
+COPILOT_EXECUTION_EXCHANGE = Exchange(
+    name="copilot_execution",
+    type=ExchangeType.DIRECT,
+    durable=True,
+    auto_delete=False,
+)
+COPILOT_EXECUTION_QUEUE_NAME = "copilot_execution_queue"
+COPILOT_EXECUTION_ROUTING_KEY = "copilot.run"
+
+COPILOT_CANCEL_EXCHANGE = Exchange(
+    name="copilot_cancel",
+    type=ExchangeType.FANOUT,
+    durable=True,
+    auto_delete=True,
+)
+COPILOT_CANCEL_QUEUE_NAME = "copilot_cancel_queue"
+
+# CoPilot operations can include extended thinking and agent generation
+# which may take 30+ minutes to complete
+COPILOT_CONSUMER_TIMEOUT_SECONDS = 60 * 60  # 1 hour
+
+# Graceful shutdown timeout - allow in-flight operations to complete
+GRACEFUL_SHUTDOWN_TIMEOUT_SECONDS = 30 * 60  # 30 minutes
+
+
+def create_copilot_queue_config() -> RabbitMQConfig:
+    """Create RabbitMQ configuration for CoPilot executor.
+
+    Defines two exchanges and queues:
+    - 'copilot_execution' (DIRECT) for chat generation tasks
+    - 'copilot_cancel' (FANOUT) for cancellation requests
+
+    Returns:
+        RabbitMQConfig with exchanges and queues defined
+    """
+    run_queue = Queue(
+        name=COPILOT_EXECUTION_QUEUE_NAME,
+        exchange=COPILOT_EXECUTION_EXCHANGE,
+        routing_key=COPILOT_EXECUTION_ROUTING_KEY,
+        durable=True,
+        auto_delete=False,
+        arguments={
+            # Extended consumer timeout for long-running LLM operations
+            # Default 30-minute timeout is insufficient for extended thinking
+            # and agent generation which can take 30+ minutes
+            "x-consumer-timeout": COPILOT_CONSUMER_TIMEOUT_SECONDS
+            * 1000,
+        },
+    )
+    cancel_queue = Queue(
+        name=COPILOT_CANCEL_QUEUE_NAME,
+        exchange=COPILOT_CANCEL_EXCHANGE,
+        routing_key="",  # not used for FANOUT
+        durable=True,
+        auto_delete=False,
+    )
+    return RabbitMQConfig(
+        vhost="/",
+        exchanges=[COPILOT_EXECUTION_EXCHANGE, COPILOT_CANCEL_EXCHANGE],
+        queues=[run_queue, cancel_queue],
+    )
+
+
+# ============ Message Models ============ #
+
+
+class CoPilotExecutionEntry(BaseModel):
+    """Task payload for CoPilot AI generation.
+
+    This model represents a chat generation task to be processed by the executor.
+    """
+
+    task_id: str
+    """Unique identifier for this task (used for stream registry)"""
+
+    session_id: str
+    """Chat session ID"""
+
+    user_id: str | None
+    """User ID (may be None for anonymous users)"""
+
+    operation_id: str
+    """Operation ID for webhook callbacks and completion tracking"""
+
+    message: str
+    """User's message to process"""
+
+    is_user_message: bool = True
+    """Whether the message is from the user (vs system/assistant)"""
+
+    context: dict[str, str] | None = None
+    """Optional context for the message (e.g., {url: str, content: str})"""
+
+
+class CancelCoPilotEvent(BaseModel):
+    """Event to cancel a CoPilot operation."""
+
+    task_id: str
+    """Task ID to cancel"""
+
+
+# ============ Queue Publishing Helpers ============ #
+
+
+async def enqueue_copilot_task(
+    task_id: str,
+    session_id: str,
+    user_id: str | None,
+    operation_id: str,
+    message: str,
+    is_user_message: bool = True,
+    context: dict[str, str] | None = None,
+) -> None:
+    """Enqueue a CoPilot task for processing by the executor service.
+
+    Args:
+        task_id: Unique identifier for this task (used for stream registry)
+        session_id: Chat session ID
+        user_id: User ID (may be None for anonymous users)
+        operation_id: Operation ID for webhook callbacks and completion tracking
+        message: User's message to process
+        is_user_message: Whether the message is from the user (vs system/assistant)
+        context: Optional context for the message (e.g., {url: str, content: str})
+    """
+    from backend.util.clients import get_async_copilot_queue
+
+    entry = CoPilotExecutionEntry(
+        task_id=task_id,
+        session_id=session_id,
+        user_id=user_id,
+        operation_id=operation_id,
+        message=message,
+        is_user_message=is_user_message,
+        context=context,
+    )
+
+    queue_client = await get_async_copilot_queue()
+    await queue_client.publish_message(
+        routing_key=COPILOT_EXECUTION_ROUTING_KEY,
+        message=entry.model_dump_json(),
+        exchange=COPILOT_EXECUTION_EXCHANGE,
+    )

autogpt_platform/backend/backend/copilot/response_model.py

@@ -18,6 +18,10 @@ class ResponseType(str, Enum):
     START = "start"
     FINISH = "finish"
 
+    # Step lifecycle (one LLM API call within a message)
+    START_STEP = "start-step"
+    FINISH_STEP = "finish-step"
+
     # Text streaming
     TEXT_START = "text-start"
     TEXT_DELTA = "text-delta"
@@ -57,6 +61,16 @@ class StreamStart(StreamBaseResponse):
         description="Task ID for SSE reconnection. Clients can reconnect using GET /tasks/{taskId}/stream",
     )
 
+    def to_sse(self) -> str:
+        """Convert to SSE format, excluding non-protocol fields like taskId."""
+        import json
+
+        data: dict[str, Any] = {
+            "type": self.type.value,
+            "messageId": self.messageId,
+        }
+        return f"data: {json.dumps(data)}\n\n"
+
 
 class StreamFinish(StreamBaseResponse):
     """End of message/stream."""
@@ -64,6 +78,26 @@ class StreamFinish(StreamBaseResponse):
     type: ResponseType = ResponseType.FINISH
 
 
+class StreamStartStep(StreamBaseResponse):
+    """Start of a step (one LLM API call within a message).
+
+    The AI SDK uses this to add a step-start boundary to message.parts,
+    enabling visual separation between multiple LLM calls in a single message.
+    """
+
+    type: ResponseType = ResponseType.START_STEP
+
+
+class StreamFinishStep(StreamBaseResponse):
+    """End of a step (one LLM API call within a message).
+
+    The AI SDK uses this to reset activeTextParts and activeReasoningParts,
+    so the next LLM call in a tool-call continuation starts with clean state.
+    """
+
+    type: ResponseType = ResponseType.FINISH_STEP
+
+
 # ========== Text Streaming ==========
 
 
@@ -117,7 +151,7 @@ class StreamToolOutputAvailable(StreamBaseResponse):
     type: ResponseType = ResponseType.TOOL_OUTPUT_AVAILABLE
     toolCallId: str = Field(..., description="Tool call ID this responds to")
     output: str | dict[str, Any] = Field(..., description="Tool execution output")
-    # Additional fields for internal use (not part of AI SDK spec but useful)
+    # Keep these for internal backend use
     toolName: str | None = Field(
         default=None, description="Name of the tool that was executed"
     )
@@ -125,6 +159,17 @@ class StreamToolOutputAvailable(StreamBaseResponse):
         default=True, description="Whether the tool execution succeeded"
     )
 
+    def to_sse(self) -> str:
+        """Convert to SSE format, excluding non-spec fields."""
+        import json
+
+        data = {
+            "type": self.type.value,
+            "toolCallId": self.toolCallId,
+            "output": self.output,
+        }
+        return f"data: {json.dumps(data)}\n\n"
+
 
 # ========== Other ==========
 

autogpt_platform/backend/backend/copilot/service.py

@@ -52,8 +52,10 @@ from .response_model import (
     StreamBaseResponse,
     StreamError,
     StreamFinish,
+    StreamFinishStep,
     StreamHeartbeat,
     StreamStart,
+    StreamStartStep,
     StreamTextDelta,
     StreamTextEnd,
     StreamTextStart,
@@ -351,6 +353,10 @@ async def stream_chat_completion(
     retry_count: int = 0,
     session: ChatSession | None = None,
     context: dict[str, str] | None = None,  # {url: str, content: str}
+    _continuation_message_id: (
+        str | None
+    ) = None,  # Internal: reuse message ID for tool call continuations
+    _task_id: str | None = None,  # Internal: task ID for SSE reconnection support
 ) -> AsyncGenerator[StreamBaseResponse, None]:
     """Main entry point for streaming chat completions with database handling.
 
@@ -517,16 +523,21 @@ async def stream_chat_completion(
     # Generate unique IDs for AI SDK protocol
     import uuid as uuid_module
 
-    message_id = str(uuid_module.uuid4())
+    is_continuation = _continuation_message_id is not None
+    message_id = _continuation_message_id or str(uuid_module.uuid4())
     text_block_id = str(uuid_module.uuid4())
 
-    # Yield message start
+    # Only yield message start for the initial call, not for continuations.
     setup_time = (time.monotonic() - completion_start) * 1000
     logger.info(
         f"[TIMING] Setup complete, yielding StreamStart at {setup_time:.1f}ms",
         extra={"json_fields": {**log_meta, "setup_time_ms": setup_time}},
     )
-    yield StreamStart(messageId=message_id)
+    if not is_continuation:
+        yield StreamStart(messageId=message_id, taskId=_task_id)
+
+    # Emit start-step before each LLM call (AI SDK uses this to add step boundaries)
+    yield StreamStartStep()
 
     try:
         logger.info(
@@ -632,6 +643,10 @@ async def stream_chat_completion(
                     )
                 yield chunk
             elif isinstance(chunk, StreamFinish):
+                if has_done_tool_call:
+                    # Tool calls happened — close the step but don't send message-level finish.
+                    # The continuation will open a new step, and finish will come at the end.
+                    yield StreamFinishStep()
                 if not has_done_tool_call:
                     # Emit text-end before finish if we received text but haven't closed it
                     if has_received_text and not text_streaming_ended:
@@ -663,6 +678,8 @@ async def stream_chat_completion(
                             has_saved_assistant_message = True
 
                     has_yielded_end = True
+                    # Emit finish-step before finish (resets AI SDK text/reasoning state)
+                    yield StreamFinishStep()
                     yield chunk
             elif isinstance(chunk, StreamError):
                 has_yielded_error = True
@@ -712,6 +729,10 @@ async def stream_chat_completion(
             logger.info(
                 f"Retryable error encountered. Attempt {retry_count + 1}/{config.max_retries}"
             )
+            # Close the current step before retrying so the recursive call's
+            # StreamStartStep doesn't produce unbalanced step events.
+            if not has_yielded_end:
+                yield StreamFinishStep()
             should_retry = True
         else:
             # Non-retryable error or max retries exceeded
@@ -747,6 +768,7 @@ async def stream_chat_completion(
                 error_response = StreamError(errorText=error_message)
                 yield error_response
             if not has_yielded_end:
+                yield StreamFinishStep()
                 yield StreamFinish()
             return
 
@@ -761,6 +783,8 @@ async def stream_chat_completion(
             retry_count=retry_count + 1,
             session=session,
             context=context,
+            _continuation_message_id=message_id,  # Reuse message ID since start was already sent
+            _task_id=_task_id,
         ):
             yield chunk
         return  # Exit after retry to avoid double-saving in finally block
@@ -830,6 +854,8 @@ async def stream_chat_completion(
             session=session,  # Pass session object to avoid Redis refetch
             context=context,
             tool_call_response=str(tool_response_messages),
+            _continuation_message_id=message_id,  # Reuse message ID to avoid duplicates
+            _task_id=_task_id,
         ):
             yield chunk
 
@@ -1040,6 +1066,10 @@ async def _stream_chat_chunks(
                         :128
                     ]  # OpenRouter limit
 
+                # Enable adaptive thinking for Anthropic models via OpenRouter
+                if config.thinking_enabled and "anthropic" in model.lower():
+                    extra_body["reasoning"] = {"enabled": True}
+
                 api_call_start = time_module.perf_counter()
                 stream = await client.chat.completions.create(
                     model=model,
@@ -1686,6 +1716,7 @@ async def _execute_long_running_tool_with_streaming(
             task_id,
             StreamError(errorText=str(e)),
         )
+        await stream_registry.publish_chunk(task_id, StreamFinishStep())
         await stream_registry.publish_chunk(task_id, StreamFinish())
 
         await _update_pending_operation(
@@ -1802,6 +1833,10 @@ async def _generate_llm_continuation(
         if session_id:
             extra_body["session_id"] = session_id[:128]
 
+        # Enable adaptive thinking for Anthropic models via OpenRouter
+        if config.thinking_enabled and "anthropic" in config.model.lower():
+            extra_body["reasoning"] = {"enabled": True}
+
         retry_count = 0
         last_error: Exception | None = None
         response = None
@@ -1932,6 +1967,10 @@ async def _generate_llm_continuation_with_streaming(
         if session_id:
             extra_body["session_id"] = session_id[:128]
 
+        # Enable adaptive thinking for Anthropic models via OpenRouter
+        if config.thinking_enabled and "anthropic" in config.model.lower():
+            extra_body["reasoning"] = {"enabled": True}
+
         # Make streaming LLM call (no tools - just text response)
         from typing import cast
 
@@ -1943,6 +1982,7 @@ async def _generate_llm_continuation_with_streaming(
 
         # Publish start event
         await stream_registry.publish_chunk(task_id, StreamStart(messageId=message_id))
+        await stream_registry.publish_chunk(task_id, StreamStartStep())
         await stream_registry.publish_chunk(task_id, StreamTextStart(id=text_block_id))
 
         # Stream the response
@@ -1966,6 +2006,7 @@ async def _generate_llm_continuation_with_streaming(
 
         # Publish end events
         await stream_registry.publish_chunk(task_id, StreamTextEnd(id=text_block_id))
+        await stream_registry.publish_chunk(task_id, StreamFinishStep())
 
         if assistant_content:
             # Reload session from DB to avoid race condition with user messages
@@ -2007,4 +2048,5 @@ async def _generate_llm_continuation_with_streaming(
             task_id,
             StreamError(errorText=f"Failed to generate response: {e}"),
         )
+        await stream_registry.publish_chunk(task_id, StreamFinishStep())
         await stream_registry.publish_chunk(task_id, StreamFinish())

autogpt_platform/backend/backend/copilot/stream_registry.py

@@ -857,8 +857,10 @@ def _reconstruct_chunk(chunk_data: dict) -> StreamBaseResponse | None:
         ResponseType,
         StreamError,
         StreamFinish,
+        StreamFinishStep,
         StreamHeartbeat,
         StreamStart,
+        StreamStartStep,
         StreamTextDelta,
         StreamTextEnd,
         StreamTextStart,
@@ -872,6 +874,8 @@ def _reconstruct_chunk(chunk_data: dict) -> StreamBaseResponse | None:
     type_to_class: dict[str, type[StreamBaseResponse]] = {
         ResponseType.START.value: StreamStart,
         ResponseType.FINISH.value: StreamFinish,
+        ResponseType.START_STEP.value: StreamStartStep,
+        ResponseType.FINISH_STEP.value: StreamFinishStep,
         ResponseType.TEXT_START.value: StreamTextStart,
         ResponseType.TEXT_DELTA.value: StreamTextDelta,
         ResponseType.TEXT_END.value: StreamTextEnd,

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

@@ -3,8 +3,8 @@ from typing import TYPE_CHECKING, Any
 
 from openai.types.chat import ChatCompletionToolParam
 
-from backend.api.features.chat.model import ChatSession
-from backend.api.features.chat.tracking import track_tool_called
+from backend.copilot.model import ChatSession
+from backend.copilot.tracking import track_tool_called
 
 from .add_understanding import AddUnderstandingTool
 from .agent_output import AgentOutputTool
@@ -27,7 +27,7 @@ from .workspace_files import (
 )
 
 if TYPE_CHECKING:
-    from backend.api.features.chat.response_model import StreamToolOutputAvailable
+    from backend.copilot.response_model import StreamToolOutputAvailable
 
 logger = logging.getLogger(__name__)
 

autogpt_platform/backend/backend/copilot/tools/_test_data.py

@@ -6,11 +6,11 @@ import pytest
 from prisma.types import ProfileCreateInput
 from pydantic import SecretStr
 
-from backend.api.features.chat.model import ChatSession
 from backend.api.features.store import db as store_db
 from backend.blocks.firecrawl.scrape import FirecrawlScrapeBlock
 from backend.blocks.io import AgentInputBlock, AgentOutputBlock
 from backend.blocks.llm import AITextGeneratorBlock
+from backend.copilot.model import ChatSession
 from backend.data.db import prisma
 from backend.data.graph import Graph, Link, Node, create_graph
 from backend.data.model import APIKeyCredentials

autogpt_platform/backend/backend/copilot/tools/add_understanding.py

@@ -3,7 +3,7 @@
 import logging
 from typing import Any
 
-from backend.api.features.chat.model import ChatSession
+from backend.copilot.model import ChatSession
 from backend.data.understanding import (
     BusinessUnderstandingInput,
     upsert_business_understanding,

autogpt_platform/backend/backend/copilot/tools/agent_output.py

@@ -7,9 +7,9 @@ from typing import Any
 
 from pydantic import BaseModel, field_validator
 
-from backend.api.features.chat.model import ChatSession
 from backend.api.features.library import db as library_db
 from backend.api.features.library.model import LibraryAgent
+from backend.copilot.model import ChatSession
 from backend.data import execution as execution_db
 from backend.data.execution import ExecutionStatus, GraphExecution, GraphExecutionMeta
 

autogpt_platform/backend/backend/copilot/tools/base.py

@@ -5,8 +5,8 @@ from typing import Any
 
 from openai.types.chat import ChatCompletionToolParam
 
-from backend.api.features.chat.model import ChatSession
-from backend.api.features.chat.response_model import StreamToolOutputAvailable
+from backend.copilot.model import ChatSession
+from backend.copilot.response_model import StreamToolOutputAvailable
 
 from .models import ErrorResponse, NeedLoginResponse, ToolResponseBase
 

autogpt_platform/backend/backend/copilot/tools/create_agent.py

@@ -3,7 +3,7 @@
 import logging
 from typing import Any
 
-from backend.api.features.chat.model import ChatSession
+from backend.copilot.model import ChatSession
 
 from .agent_generator import (
     AgentGeneratorNotConfiguredError,

autogpt_platform/backend/backend/copilot/tools/customize_agent.py

@@ -3,9 +3,9 @@
 import logging
 from typing import Any
 
-from backend.api.features.chat.model import ChatSession
 from backend.api.features.store import db as store_db
 from backend.api.features.store.exceptions import AgentNotFoundError
+from backend.copilot.model import ChatSession
 
 from .agent_generator import (
     AgentGeneratorNotConfiguredError,

autogpt_platform/backend/backend/copilot/tools/edit_agent.py

@@ -3,7 +3,7 @@
 import logging
 from typing import Any
 
-from backend.api.features.chat.model import ChatSession
+from backend.copilot.model import ChatSession
 
 from .agent_generator import (
     AgentGeneratorNotConfiguredError,

autogpt_platform/backend/backend/copilot/tools/find_agent.py

@@ -2,7 +2,7 @@
 
 from typing import Any
 
-from backend.api.features.chat.model import ChatSession
+from backend.copilot.model import ChatSession
 
 from .agent_search import search_agents
 from .base import BaseTool

autogpt_platform/backend/backend/copilot/tools/find_block.py

@@ -3,16 +3,16 @@ from typing import Any
 
 from prisma.enums import ContentType
 
-from backend.api.features.chat.model import ChatSession
-from backend.api.features.chat.tools.base import BaseTool, ToolResponseBase
-from backend.api.features.chat.tools.models import (
+from backend.api.features.store.hybrid_search import unified_hybrid_search
+from backend.copilot.model import ChatSession
+from backend.copilot.tools.base import BaseTool, ToolResponseBase
+from backend.copilot.tools.models import (
     BlockInfoSummary,
     BlockInputFieldInfo,
     BlockListResponse,
     ErrorResponse,
     NoResultsResponse,
 )
-from backend.api.features.store.hybrid_search import unified_hybrid_search
 from backend.data.block import BlockType, get_block
 
 logger = logging.getLogger(__name__)

autogpt_platform/backend/backend/copilot/tools/find_block_test.py

@@ -4,12 +4,12 @@ from unittest.mock import AsyncMock, MagicMock, patch
 
 import pytest
 
-from backend.api.features.chat.tools.find_block import (
+from backend.copilot.tools.find_block import (
     COPILOT_EXCLUDED_BLOCK_IDS,
     COPILOT_EXCLUDED_BLOCK_TYPES,
     FindBlockTool,
 )
-from backend.api.features.chat.tools.models import BlockListResponse
+from backend.copilot.tools.models import BlockListResponse
 from backend.data.block import BlockType
 
 from ._test_data import make_session

autogpt_platform/backend/backend/copilot/tools/find_library_agent.py

@@ -2,7 +2,7 @@
 
 from typing import Any
 
-from backend.api.features.chat.model import ChatSession
+from backend.copilot.model import ChatSession
 
 from .agent_search import search_agents
 from .base import BaseTool

autogpt_platform/backend/backend/copilot/tools/get_doc_page.py

@@ -4,9 +4,9 @@ import logging
 from pathlib import Path
 from typing import Any
 
-from backend.api.features.chat.model import ChatSession
-from backend.api.features.chat.tools.base import BaseTool
-from backend.api.features.chat.tools.models import (
+from backend.copilot.model import ChatSession
+from backend.copilot.tools.base import BaseTool
+from backend.copilot.tools.models import (
     DocPageResponse,
     ErrorResponse,
     ToolResponseBase,

autogpt_platform/backend/backend/copilot/tools/run_agent.py

@@ -5,13 +5,10 @@ from typing import Any
 
 from pydantic import BaseModel, Field, field_validator
 
-from backend.api.features.chat.config import ChatConfig
-from backend.api.features.chat.model import ChatSession
-from backend.api.features.chat.tracking import (
-    track_agent_run_success,
-    track_agent_scheduled,
-)
 from backend.api.features.library import db as library_db
+from backend.copilot.config import ChatConfig
+from backend.copilot.model import ChatSession
+from backend.copilot.tracking import track_agent_run_success, track_agent_scheduled
 from backend.data.graph import GraphModel
 from backend.data.model import CredentialsMetaInput
 from backend.data.user import get_user_by_id

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

@@ -7,8 +7,8 @@ from typing import Any
 
 from pydantic_core import PydanticUndefined
 
-from backend.api.features.chat.model import ChatSession
-from backend.api.features.chat.tools.find_block import (
+from backend.copilot.model import ChatSession
+from backend.copilot.tools.find_block import (
     COPILOT_EXCLUDED_BLOCK_IDS,
     COPILOT_EXCLUDED_BLOCK_TYPES,
 )

autogpt_platform/backend/backend/copilot/tools/run_block_test.py

@@ -4,8 +4,8 @@ from unittest.mock import MagicMock, patch
 
 import pytest
 
-from backend.api.features.chat.tools.models import ErrorResponse
-from backend.api.features.chat.tools.run_block import RunBlockTool
+from backend.copilot.tools.models import ErrorResponse
+from backend.copilot.tools.run_block import RunBlockTool
 from backend.data.block import BlockType
 
 from ._test_data import make_session

autogpt_platform/backend/backend/copilot/tools/search_docs.py

@@ -5,16 +5,16 @@ from typing import Any
 
 from prisma.enums import ContentType
 
-from backend.api.features.chat.model import ChatSession
-from backend.api.features.chat.tools.base import BaseTool
-from backend.api.features.chat.tools.models import (
+from backend.api.features.store.hybrid_search import unified_hybrid_search
+from backend.copilot.model import ChatSession
+from backend.copilot.tools.base import BaseTool
+from backend.copilot.tools.models import (
     DocSearchResult,
     DocSearchResultsResponse,
     ErrorResponse,
     NoResultsResponse,
     ToolResponseBase,
 )
-from backend.api.features.store.hybrid_search import unified_hybrid_search
 
 logger = logging.getLogger(__name__)
 

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

@@ -6,7 +6,7 @@ from typing import Any, Optional
 
 from pydantic import BaseModel
 
-from backend.api.features.chat.model import ChatSession
+from backend.copilot.model import ChatSession
 from backend.data.workspace import get_or_create_workspace
 from backend.util.settings import Config
 from backend.util.virus_scanner import scan_content_safe

autogpt_platform/backend/backend/util/clients.py

@@ -11,7 +11,6 @@ settings = Settings()
 
 if TYPE_CHECKING:
     from openai import AsyncOpenAI
-    from supabase import AClient, Client
 
     from backend.data.execution import (
         AsyncRedisExecutionEventBus,
@@ -22,6 +21,7 @@ if TYPE_CHECKING:
     from backend.executor.scheduler import SchedulerClient
     from backend.integrations.credentials_store import IntegrationCredentialsStore
     from backend.notifications.notifications import NotificationManagerClient
+    from supabase import AClient, Client
 
 
 @thread_cached
@@ -106,6 +106,20 @@ async def get_async_execution_queue() -> "AsyncRabbitMQ":
     return client
 
 
+# ============ CoPilot Queue Helpers ============ #
+
+
+@thread_cached
+async def get_async_copilot_queue() -> "AsyncRabbitMQ":
+    """Get a thread-cached AsyncRabbitMQ CoPilot queue client."""
+    from backend.copilot.executor.utils import create_copilot_queue_config
+    from backend.data.rabbitmq import AsyncRabbitMQ
+
+    client = AsyncRabbitMQ(create_copilot_queue_config())
+    await client.connect()
+    return client
+
+
 # ============ Integration Credentials Store ============ #
 
 

autogpt_platform/backend/backend/util/settings.py

@@ -211,16 +211,23 @@ class Config(UpdateTrackingModel["Config"], BaseSettings):
         description="The port for execution manager daemon to run on",
     )
 
+    num_copilot_workers: int = Field(
+        default=10,
+        ge=1,
+        le=100,
+        description="Number of concurrent CoPilot executor workers",
+    )
+
+    copilot_executor_port: int = Field(
+        default=8008,
+        description="The port for CoPilot executor daemon to run on",
+    )
+
     execution_scheduler_port: int = Field(
         default=8003,
         description="The port for execution scheduler daemon to run on",
     )
 
-    agent_server_port: int = Field(
-        default=8004,
-        description="The port for agent server daemon to run on",
-    )
-
     database_api_port: int = Field(
         default=8005,
         description="The port for database server API to run on",

autogpt_platform/backend/poetry.lock

@@ -1382,14 +1382,14 @@ tzdata = "*"
 
 [[package]]
 name = "fastapi"
-version = "0.128.5"
+version = "0.128.6"
 description = "FastAPI framework, high performance, easy to learn, fast to code, ready for production"
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "fastapi-0.128.5-py3-none-any.whl", hash = "sha256:bceec0de8aa6564599c5bcc0593b0d287703562c848271fca8546fd2c87bf4dd"},
-    {file = "fastapi-0.128.5.tar.gz", hash = "sha256:a7173579fc162d6471e3c6fbd9a4b7610c7a3b367bcacf6c4f90d5d022cab711"},
+    {file = "fastapi-0.128.6-py3-none-any.whl", hash = "sha256:bb1c1ef87d6086a7132d0ab60869d6f1ee67283b20fbf84ec0003bd335099509"},
+    {file = "fastapi-0.128.6.tar.gz", hash = "sha256:0cb3946557e792d731b26a42b04912f16367e3c3135ea8290f620e234f2b604f"},
 ]
 
 [package.dependencies]
@@ -3078,14 +3078,14 @@ type = ["pygobject-stubs", "pytest-mypy (>=1.0.1)", "shtab", "types-pywin32"]
 
 [[package]]
 name = "langfuse"
-version = "3.13.0"
+version = "3.14.1"
 description = "A client library for accessing langfuse"
 optional = false
 python-versions = "<4.0,>=3.10"
 groups = ["main"]
 files = [
-    {file = "langfuse-3.13.0-py3-none-any.whl", hash = "sha256:71912ddac1cc831a65df895eae538a556f564c094ae51473e747426e9ded1a9d"},
-    {file = "langfuse-3.13.0.tar.gz", hash = "sha256:dacea8111ca4442e97dbfec4f8d676cf9709b35357a26e468f8887b95de0012f"},
+    {file = "langfuse-3.14.1-py3-none-any.whl", hash = "sha256:17bed605dbfc9947cbd1738a715f6d27c1b80b6da9f2946586171958fa5820d0"},
+    {file = "langfuse-3.14.1.tar.gz", hash = "sha256:404a6104cd29353d7829aa417ec46565b04917e5599afdda96c5b0865f4bc991"},
 ]
 
 [package.dependencies]
@@ -8440,4 +8440,4 @@ 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 = "14686ee0e2dc446a75d0db145b08dc410dc31c357e25085bb0f9b0174711c4b1"
+content-hash = "fc135114e01de39c8adf70f6132045e7d44a19473c1279aee0978de65aad1655"

autogpt_platform/backend/pyproject.toml

@@ -21,7 +21,7 @@ cryptography = "^46.0"
 discord-py = "^2.5.2"
 e2b-code-interpreter = "^1.5.2"
 elevenlabs = "^1.50.0"
-fastapi = "^0.128.5"
+fastapi = "^0.128.6"
 feedparser = "^6.0.11"
 flake8 = "^7.3.0"
 google-api-python-client = "^2.177.0"
@@ -34,7 +34,7 @@ html2text = "^2024.2.26"
 jinja2 = "^3.1.6"
 jsonref = "^1.1.0"
 jsonschema = "^4.25.0"
-langfuse = "^3.11.0"
+langfuse = "^3.14.1"
 launchdarkly-server-sdk = "^9.14.1"
 mem0ai = "^0.1.115"
 moviepy = "^2.1.2"
@@ -116,6 +116,7 @@ ws = "backend.ws:main"
 scheduler = "backend.scheduler:main"
 notification = "backend.notification:main"
 executor = "backend.exec:main"
+copilot-executor = "backend.copilot.executor.__main__:main"
 cli = "backend.cli:main"
 format = "linter:format"
 lint = "linter:lint"

autogpt_platform/backend/test/agent_generator/test_core_integration.py

@@ -9,10 +9,8 @@ from unittest.mock import AsyncMock, patch
 
 import pytest
 
-from backend.api.features.chat.tools.agent_generator import core
-from backend.api.features.chat.tools.agent_generator.core import (
-    AgentGeneratorNotConfiguredError,
-)
+from backend.copilot.tools.agent_generator import core
+from backend.copilot.tools.agent_generator.core import AgentGeneratorNotConfiguredError
 
 
 class TestServiceNotConfigured:

autogpt_platform/backend/test/agent_generator/test_library_agents.py

@@ -9,7 +9,7 @@ from unittest.mock import AsyncMock, MagicMock, patch
 
 import pytest
 
-from backend.api.features.chat.tools.agent_generator import core
+from backend.copilot.tools.agent_generator import core
 
 
 class TestGetLibraryAgentsForGeneration:

autogpt_platform/backend/test/agent_generator/test_service.py

@@ -10,7 +10,7 @@ from unittest.mock import AsyncMock, MagicMock, patch
 import httpx
 import pytest
 
-from backend.api.features.chat.tools.agent_generator import service
+from backend.copilot.tools.agent_generator import service
 
 
 class TestServiceConfiguration:

autogpt_platform/docker-compose.platform.yml

@@ -158,6 +158,41 @@ services:
         max-size: "10m"
         max-file: "3"
 
+  copilot_executor:
+    build:
+      context: ../
+      dockerfile: autogpt_platform/backend/Dockerfile
+      target: server
+    command: ["python", "-m", "backend.copilot.executor"]
+    develop:
+      watch:
+        - path: ./
+          target: autogpt_platform/backend/
+          action: rebuild
+    depends_on:
+      redis:
+        condition: service_healthy
+      rabbitmq:
+        condition: service_healthy
+      db:
+        condition: service_healthy
+      migrate:
+        condition: service_completed_successfully
+      database_manager:
+        condition: service_started
+    <<: *backend-env-files
+    environment:
+      <<: *backend-env
+    ports:
+      - "8008:8008"
+    networks:
+      - app-network
+    logging:
+      driver: json-file
+      options:
+        max-size: "10m"
+        max-file: "3"
+
   websocket_server:
     build:
       context: ../

autogpt_platform/docker-compose.yml

@@ -53,6 +53,12 @@ services:
       file: ./docker-compose.platform.yml
       service: executor
 
+  copilot_executor:
+    <<: *agpt-services
+    extends:
+      file: ./docker-compose.platform.yml
+      service: copilot_executor
+
   websocket_server:
     <<: *agpt-services
     extends:
@@ -174,5 +180,6 @@ services:
       - deps
       - rest_server
       - executor
+      - copilot_executor
       - websocket_server
       - database_manager

autogpt_platform/frontend/Dockerfile

@@ -25,8 +25,12 @@ RUN if [ -f .env.production ]; then \
       cp .env.default .env; \
     fi
 RUN pnpm run generate:api
+# Disable source-map generation in Docker builds to halve webpack memory usage.
+# Source maps are only useful when SENTRY_AUTH_TOKEN is set (Vercel deploys);
+# the Docker image never uploads them, so generating them just wastes RAM.
+ENV NEXT_PUBLIC_SOURCEMAPS="false"
 # In CI, we want NEXT_PUBLIC_PW_TEST=true during build so Next.js inlines it
-RUN if [ "$NEXT_PUBLIC_PW_TEST" = "true" ]; then NEXT_PUBLIC_PW_TEST=true NODE_OPTIONS="--max-old-space-size=4096" pnpm build; else NODE_OPTIONS="--max-old-space-size=4096" pnpm build; fi
+RUN if [ "$NEXT_PUBLIC_PW_TEST" = "true" ]; then NEXT_PUBLIC_PW_TEST=true NODE_OPTIONS="--max-old-space-size=8192" pnpm build; else NODE_OPTIONS="--max-old-space-size=8192" pnpm build; fi
 
 # Prod stage - based on NextJS reference Dockerfile https://github.com/vercel/next.js/blob/64271354533ed16da51be5dce85f0dbd15f17517/examples/with-docker/Dockerfile
 FROM node:21-alpine AS prod

autogpt_platform/frontend/next.config.mjs

@@ -1,8 +1,12 @@
 import { withSentryConfig } from "@sentry/nextjs";
 
+// Allow Docker builds to skip source-map generation (halves memory usage).
+// Defaults to true so Vercel/local builds are unaffected.
+const enableSourceMaps = process.env.NEXT_PUBLIC_SOURCEMAPS !== "false";
+
 /** @type {import('next').NextConfig} */
 const nextConfig = {
-  productionBrowserSourceMaps: true,
+  productionBrowserSourceMaps: enableSourceMaps,
   // Externalize OpenTelemetry packages to fix Turbopack HMR issues
   serverExternalPackages: [
     "@opentelemetry/instrumentation",
@@ -14,9 +18,37 @@ const nextConfig = {
     serverActions: {
       bodySizeLimit: "256mb",
     },
-    // Increase body size limit for API routes (file uploads) - 256MB to match backend limit
-    proxyClientMaxBodySize: "256mb",
     middlewareClientMaxBodySize: "256mb",
+    // Limit parallel webpack workers to reduce peak memory during builds.
+    cpus: 2,
+  },
+  // Work around cssnano "Invalid array length" bug in Next.js's bundled
+  // cssnano-simple comment parser when processing very large CSS chunks.
+  // CSS is still bundled correctly; gzip handles most of the size savings anyway.
+  webpack: (config, { dev }) => {
+    if (!dev) {
+      // Next.js adds CssMinimizerPlugin internally (after user config), so we
+      // can't filter it from config.plugins. Instead, intercept the webpack
+      // compilation hooks and replace the buggy plugin's tap with a no-op.
+      config.plugins.push({
+        apply(compiler) {
+          compiler.hooks.compilation.tap(
+            "DisableCssMinimizer",
+            (compilation) => {
+              compilation.hooks.processAssets.intercept({
+                register: (tap) => {
+                  if (tap.name === "CssMinimizerPlugin") {
+                    return { ...tap, fn: async () => {} };
+                  }
+                  return tap;
+                },
+              });
+            },
+          );
+        },
+      });
+    }
+    return config;
   },
   images: {
     domains: [
@@ -54,9 +86,16 @@ const nextConfig = {
   transpilePackages: ["geist"],
 };
 
-const isDevelopmentBuild = process.env.NODE_ENV !== "production";
+// Only run the Sentry webpack plugin when we can actually upload source maps
+// (i.e. on Vercel with SENTRY_AUTH_TOKEN set). The Sentry *runtime* SDK
+// (imported in app code) still captures errors without the plugin.
+// Skipping the plugin saves ~1 GB of peak memory during `next build`.
+const skipSentryPlugin =
+  process.env.NODE_ENV !== "production" ||
+  !enableSourceMaps ||
+  !process.env.SENTRY_AUTH_TOKEN;
 
-export default isDevelopmentBuild
+export default skipSentryPlugin
   ? nextConfig
   : withSentryConfig(nextConfig, {
       // For all available options, see:
@@ -96,7 +135,7 @@ export default isDevelopmentBuild
 
       // This helps Sentry with sourcemaps... https://docs.sentry.io/platforms/javascript/guides/nextjs/sourcemaps/
       sourcemaps: {
-        disable: false,
+        disable: !enableSourceMaps,
         assets: [".next/**/*.js", ".next/**/*.js.map"],
         ignore: ["**/node_modules/**"],
         deleteSourcemapsAfterUpload: false, // Source is public anyway :)

autogpt_platform/frontend/package.json

@@ -7,7 +7,7 @@
   },
   "scripts": {
     "dev": "pnpm run generate:api:force && next dev --turbo",
-    "build": "next build",
+    "build": "cross-env NODE_OPTIONS=--max-old-space-size=16384 next build",
     "start": "next start",
     "start:standalone": "cd .next/standalone && node server.js",
     "lint": "next lint && prettier --check .",
@@ -30,6 +30,7 @@
     "defaults"
   ],
   "dependencies": {
+    "@ai-sdk/react": "3.0.61",
     "@faker-js/faker": "10.0.0",
     "@hookform/resolvers": "5.2.2",
     "@next/third-parties": "15.4.6",
@@ -60,6 +61,10 @@
     "@rjsf/utils": "6.1.2",
     "@rjsf/validator-ajv8": "6.1.2",
     "@sentry/nextjs": "10.27.0",
+    "@streamdown/cjk": "1.0.1",
+    "@streamdown/code": "1.0.1",
+    "@streamdown/math": "1.0.1",
+    "@streamdown/mermaid": "1.0.1",
     "@supabase/ssr": "0.7.0",
     "@supabase/supabase-js": "2.78.0",
     "@tanstack/react-query": "5.90.6",
@@ -68,6 +73,7 @@
     "@vercel/analytics": "1.5.0",
     "@vercel/speed-insights": "1.2.0",
     "@xyflow/react": "12.9.2",
+    "ai": "6.0.59",
     "boring-avatars": "1.11.2",
     "class-variance-authority": "0.7.1",
     "clsx": "2.1.1",
@@ -87,7 +93,6 @@
     "launchdarkly-react-client-sdk": "3.9.0",
     "lodash": "4.17.21",
     "lucide-react": "0.552.0",
-    "moment": "2.30.1",
     "next": "15.4.10",
     "next-themes": "0.4.6",
     "nuqs": "2.7.2",
@@ -112,9 +117,11 @@
     "remark-math": "6.0.0",
     "shepherd.js": "14.5.1",
     "sonner": "2.0.7",
+    "streamdown": "2.1.0",
     "tailwind-merge": "2.6.0",
     "tailwind-scrollbar": "3.1.0",
     "tailwindcss-animate": "1.0.7",
+    "use-stick-to-bottom": "1.1.2",
     "uuid": "11.1.0",
     "vaul": "1.1.2",
     "zod": "3.25.76",
@@ -172,7 +179,8 @@
   },
   "pnpm": {
     "overrides": {
-      "@opentelemetry/instrumentation": "0.209.0"
+      "@opentelemetry/instrumentation": "0.209.0",
+      "lodash-es": "4.17.23"
     }
   },
   "packageManager": "pnpm@10.20.0+sha512.cf9998222162dd85864d0a8102e7892e7ba4ceadebbf5a31f9c2fce48dfce317a9c53b9f6464d1ef9042cba2e02ae02a9f7c143a2b438cd93c91840f0192b9dd"

autogpt_platform/frontend/src/app/(platform)/build/components/NewControlPanel/NewBlockMenu/BlockMenuSearchBar/useBlockMenuSearchBar.ts

@@ -1,4 +1,4 @@
-import { debounce } from "lodash";
+import debounce from "lodash/debounce";
 import { useCallback, useEffect, useRef, useState } from "react";
 import { useBlockMenuStore } from "../../../../stores/blockMenuStore";
 import { getQueryClient } from "@/lib/react-query/queryClient";

autogpt_platform/frontend/src/app/(platform)/build/components/NewControlPanel/NewBlockMenu/HorizontalScroll.tsx

@@ -70,10 +70,10 @@ export const HorizontalScroll: React.FC<HorizontalScrollAreaProps> = ({
           {children}
         </div>
         {canScrollLeft && (
-          <div className="pointer-events-none absolute inset-y-0 left-0 w-8 bg-gradient-to-r from-white via-white/80 to-white/0" />
+          <div className="pointer-events-none absolute inset-y-0 left-0 w-8 bg-gradient-to-r from-background via-background/80 to-background/0" />
         )}
         {canScrollRight && (
-          <div className="pointer-events-none absolute inset-y-0 right-0 w-8 bg-gradient-to-l from-white via-white/80 to-white/0" />
+          <div className="pointer-events-none absolute inset-y-0 right-0 w-8 bg-gradient-to-l from-background via-background/80 to-background/0" />
         )}
         {canScrollLeft && (
           <button

autogpt_platform/frontend/src/app/(platform)/copilot/CopilotPage.tsx

@@ -0,0 +1,76 @@
+"use client";
+
+import { LoadingSpinner } from "@/components/atoms/LoadingSpinner/LoadingSpinner";
+import { SidebarProvider } from "@/components/ui/sidebar";
+import { ChatContainer } from "./components/ChatContainer/ChatContainer";
+import { ChatSidebar } from "./components/ChatSidebar/ChatSidebar";
+import { MobileDrawer } from "./components/MobileDrawer/MobileDrawer";
+import { MobileHeader } from "./components/MobileHeader/MobileHeader";
+import { useCopilotPage } from "./useCopilotPage";
+
+export function CopilotPage() {
+  const {
+    sessionId,
+    messages,
+    status,
+    error,
+    stop,
+    createSession,
+    onSend,
+    isLoadingSession,
+    isCreatingSession,
+    isUserLoading,
+    isLoggedIn,
+    // Mobile drawer
+    isMobile,
+    isDrawerOpen,
+    sessions,
+    isLoadingSessions,
+    handleOpenDrawer,
+    handleCloseDrawer,
+    handleDrawerOpenChange,
+    handleSelectSession,
+    handleNewChat,
+  } = useCopilotPage();
+
+  if (isUserLoading || !isLoggedIn) {
+    return <LoadingSpinner size="large" cover />;
+  }
+
+  return (
+    <SidebarProvider
+      defaultOpen={true}
+      className="h-[calc(100vh-72px)] min-h-0"
+    >
+      {!isMobile && <ChatSidebar />}
+      <div className="relative flex h-full w-full flex-col overflow-hidden bg-[#f8f8f9] px-0">
+        {isMobile && <MobileHeader onOpenDrawer={handleOpenDrawer} />}
+        <div className="flex-1 overflow-hidden">
+          <ChatContainer
+            messages={messages}
+            status={status}
+            error={error}
+            sessionId={sessionId}
+            isLoadingSession={isLoadingSession}
+            isCreatingSession={isCreatingSession}
+            onCreateSession={createSession}
+            onSend={onSend}
+            onStop={stop}
+          />
+        </div>
+      </div>
+      {isMobile && (
+        <MobileDrawer
+          isOpen={isDrawerOpen}
+          sessions={sessions}
+          currentSessionId={sessionId}
+          isLoading={isLoadingSessions}
+          onSelectSession={handleSelectSession}
+          onNewChat={handleNewChat}
+          onClose={handleCloseDrawer}
+          onOpenChange={handleDrawerOpenChange}
+        />
+      )}
+    </SidebarProvider>
+  );
+}

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

@@ -0,0 +1,74 @@
+"use client";
+import { ChatInput } from "@/app/(platform)/copilot/components/ChatInput/ChatInput";
+import { UIDataTypes, UIMessage, UITools } from "ai";
+import { LayoutGroup, motion } from "framer-motion";
+import { ChatMessagesContainer } from "../ChatMessagesContainer/ChatMessagesContainer";
+import { CopilotChatActionsProvider } from "../CopilotChatActionsProvider/CopilotChatActionsProvider";
+import { EmptySession } from "../EmptySession/EmptySession";
+
+export interface ChatContainerProps {
+  messages: UIMessage<unknown, UIDataTypes, UITools>[];
+  status: string;
+  error: Error | undefined;
+  sessionId: string | null;
+  isLoadingSession: boolean;
+  isCreatingSession: boolean;
+  onCreateSession: () => void | Promise<string>;
+  onSend: (message: string) => void | Promise<void>;
+  onStop: () => void;
+}
+export const ChatContainer = ({
+  messages,
+  status,
+  error,
+  sessionId,
+  isLoadingSession,
+  isCreatingSession,
+  onCreateSession,
+  onSend,
+  onStop,
+}: ChatContainerProps) => {
+  const inputLayoutId = "copilot-2-chat-input";
+
+  return (
+    <CopilotChatActionsProvider onSend={onSend}>
+      <LayoutGroup id="copilot-2-chat-layout">
+        <div className="flex h-full min-h-0 w-full flex-col bg-[#f8f8f9] px-2 lg:px-0">
+          {sessionId ? (
+            <div className="mx-auto flex h-full min-h-0 w-full max-w-3xl flex-col">
+              <ChatMessagesContainer
+                messages={messages}
+                status={status}
+                error={error}
+                isLoading={isLoadingSession}
+              />
+              <motion.div
+                initial={{ opacity: 0 }}
+                animate={{ opacity: 1 }}
+                transition={{ duration: 0.3 }}
+                className="relative px-3 pb-2 pt-2"
+              >
+                <div className="pointer-events-none absolute left-0 right-0 top-[-18px] z-10 h-6 bg-gradient-to-b from-transparent to-[#f8f8f9]" />
+                <ChatInput
+                  inputId="chat-input-session"
+                  onSend={onSend}
+                  disabled={status === "streaming"}
+                  isStreaming={status === "streaming"}
+                  onStop={onStop}
+                  placeholder="What else can I help with?"
+                />
+              </motion.div>
+            </div>
+          ) : (
+            <EmptySession
+              inputLayoutId={inputLayoutId}
+              isCreatingSession={isCreatingSession}
+              onCreateSession={onCreateSession}
+              onSend={onSend}
+            />
+          )}
+        </div>
+      </LayoutGroup>
+    </CopilotChatActionsProvider>
+  );
+};

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

@@ -6,17 +6,19 @@ import {
   MicrophoneIcon,
   StopIcon,
 } from "@phosphor-icons/react";
+import { ChangeEvent, useCallback } from "react";
 import { RecordingIndicator } from "./components/RecordingIndicator";
 import { useChatInput } from "./useChatInput";
 import { useVoiceRecording } from "./useVoiceRecording";
 
 export interface Props {
-  onSend: (message: string) => void;
+  onSend: (message: string) => void | Promise<void>;
   disabled?: boolean;
   isStreaming?: boolean;
   onStop?: () => void;
   placeholder?: string;
   className?: string;
+  inputId?: string;
 }
 
 export function ChatInput({
@@ -26,14 +28,14 @@ export function ChatInput({
   onStop,
   placeholder = "Type your message...",
   className,
+  inputId = "chat-input",
 }: Props) {
-  const inputId = "chat-input";
   const {
     value,
     setValue,
     handleKeyDown: baseHandleKeyDown,
     handleSubmit,
-    handleChange,
+    handleChange: baseHandleChange,
     hasMultipleLines,
   } = useChatInput({
     onSend,
@@ -60,6 +62,15 @@ export function ChatInput({
     inputId,
   });
 
+  // Block text changes when recording
+  const handleChange = useCallback(
+    (e: ChangeEvent<HTMLTextAreaElement>) => {
+      if (isRecording) return;
+      baseHandleChange(e);
+    },
+    [isRecording, baseHandleChange],
+  );
+
   return (
     <form onSubmit={handleSubmit} className={cn("relative flex-1", className)}>
       <div className="relative">

autogpt_platform/frontend/src/app/(platform)/copilot/components/ChatInput/useChatInput.ts

@@ -21,6 +21,7 @@ export function useChatInput({
 }: Args) {
   const [value, setValue] = useState("");
   const [hasMultipleLines, setHasMultipleLines] = useState(false);
+  const [isSending, setIsSending] = useState(false);
 
   useEffect(
     function focusOnMount() {
@@ -100,34 +101,40 @@ export function useChatInput({
     }
   }, [value, maxRows, inputId]);
 
-  const handleSend = () => {
-    if (disabled || !value.trim()) return;
-    onSend(value.trim());
-    setValue("");
-    setHasMultipleLines(false);
-    const textarea = document.getElementById(inputId) as HTMLTextAreaElement;
-    const wrapper = document.getElementById(
-      `${inputId}-wrapper`,
-    ) as HTMLDivElement;
-    if (textarea) {
-      textarea.style.height = "auto";
+  async function handleSend() {
+    if (disabled || isSending || !value.trim()) return;
+
+    setIsSending(true);
+    try {
+      await onSend(value.trim());
+      setValue("");
+      setHasMultipleLines(false);
+      const textarea = document.getElementById(inputId) as HTMLTextAreaElement;
+      const wrapper = document.getElementById(
+        `${inputId}-wrapper`,
+      ) as HTMLDivElement;
+      if (textarea) {
+        textarea.style.height = "auto";
+      }
+      if (wrapper) {
+        wrapper.style.height = "";
+        wrapper.style.maxHeight = "";
+      }
+    } finally {
+      setIsSending(false);
     }
-    if (wrapper) {
-      wrapper.style.height = "";
-      wrapper.style.maxHeight = "";
-    }
-  };
+  }
 
   function handleKeyDown(event: KeyboardEvent<HTMLTextAreaElement>) {
     if (event.key === "Enter" && !event.shiftKey) {
       event.preventDefault();
-      handleSend();
+      void handleSend();
     }
   }
 
   function handleSubmit(e: FormEvent<HTMLFormElement>) {
     e.preventDefault();
-    handleSend();
+    void handleSend();
   }
 
   function handleChange(e: ChangeEvent<HTMLTextAreaElement>) {
@@ -142,5 +149,6 @@ export function useChatInput({
     handleSubmit,
     handleChange,
     hasMultipleLines,
+    isSending,
   };
 }

autogpt_platform/frontend/src/app/(platform)/copilot/components/ChatInput/useVoiceRecording.ts

@@ -38,9 +38,13 @@ export function useVoiceRecording({
   const streamRef = useRef<MediaStream | null>(null);
   const isRecordingRef = useRef(false);
 
-  const isSupported =
-    typeof window !== "undefined" &&
-    !!(navigator.mediaDevices && navigator.mediaDevices.getUserMedia);
+  const [isSupported, setIsSupported] = useState(false);
+
+  useEffect(() => {
+    setIsSupported(
+      !!(navigator.mediaDevices && navigator.mediaDevices.getUserMedia),
+    );
+  }, []);
 
   const clearTimer = useCallback(() => {
     if (timerRef.current) {
@@ -214,17 +218,33 @@ export function useVoiceRecording({
 
   const handleKeyDown = useCallback(
     (event: KeyboardEvent<HTMLTextAreaElement>) => {
-      if (event.key === " " && !value.trim() && !isTranscribing) {
+      // Allow space to toggle recording (start when empty, stop when recording)
+      if (event.key === " " && !isTranscribing) {
+        if (isRecordingRef.current) {
+          // Stop recording on space
+          event.preventDefault();
+          stopRecording();
+          return;
+        } else if (!value.trim()) {
+          // Start recording on space when input is empty
+          event.preventDefault();
+          void startRecording();
+          return;
+        }
+      }
+      // Block all key events when recording (except space handled above)
+      if (isRecordingRef.current) {
         event.preventDefault();
-        toggleRecording();
         return;
       }
       baseHandleKeyDown(event);
     },
-    [value, isTranscribing, toggleRecording, baseHandleKeyDown],
+    [value, isTranscribing, stopRecording, startRecording, baseHandleKeyDown],
   );
 
   const showMicButton = isSupported;
+  // Don't include isRecording in disabled state - we need key events to work
+  // Text input is blocked via handleKeyDown instead
   const isInputDisabled = disabled || isStreaming || isTranscribing;
 
   // Cleanup on unmount

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

@@ -0,0 +1,274 @@
+import { getGetWorkspaceDownloadFileByIdUrl } from "@/app/api/__generated__/endpoints/workspace/workspace";
+import {
+  Conversation,
+  ConversationContent,
+  ConversationScrollButton,
+} from "@/components/ai-elements/conversation";
+import {
+  Message,
+  MessageContent,
+  MessageResponse,
+} from "@/components/ai-elements/message";
+import { LoadingSpinner } from "@/components/atoms/LoadingSpinner/LoadingSpinner";
+import { ToolUIPart, UIDataTypes, UIMessage, UITools } from "ai";
+import { useEffect, useState } from "react";
+import { CreateAgentTool } from "../../tools/CreateAgent/CreateAgent";
+import { EditAgentTool } from "../../tools/EditAgent/EditAgent";
+import { FindAgentsTool } from "../../tools/FindAgents/FindAgents";
+import { FindBlocksTool } from "../../tools/FindBlocks/FindBlocks";
+import { RunAgentTool } from "../../tools/RunAgent/RunAgent";
+import { RunBlockTool } from "../../tools/RunBlock/RunBlock";
+import { SearchDocsTool } from "../../tools/SearchDocs/SearchDocs";
+import { ViewAgentOutputTool } from "../../tools/ViewAgentOutput/ViewAgentOutput";
+
+// ---------------------------------------------------------------------------
+// Workspace media support
+// ---------------------------------------------------------------------------
+
+/**
+ * Resolve workspace:// URLs in markdown text to proxy download URLs.
+ * Detects MIME type from the hash fragment (e.g. workspace://id#video/mp4)
+ * and prefixes the alt text with "video:" so the custom img component can
+ * render a <video> element instead.
+ */
+function resolveWorkspaceUrls(text: string): string {
+  return text.replace(
+    /!\[([^\]]*)\]\(workspace:\/\/([^)#\s]+)(?:#([^)\s]*))?\)/g,
+    (_match, alt: string, fileId: string, mimeHint?: string) => {
+      const apiPath = getGetWorkspaceDownloadFileByIdUrl(fileId);
+      const url = `/api/proxy${apiPath}`;
+      if (mimeHint?.startsWith("video/")) {
+        return `![video:${alt || "Video"}](${url})`;
+      }
+      return `![${alt || "Image"}](${url})`;
+    },
+  );
+}
+
+/**
+ * Custom img component for Streamdown that renders <video> elements
+ * for workspace video files (detected via "video:" alt-text prefix).
+ * Falls back to <video> when an <img> fails to load for workspace files.
+ */
+function WorkspaceMediaImage(props: React.JSX.IntrinsicElements["img"]) {
+  const { src, alt, ...rest } = props;
+  const [imgFailed, setImgFailed] = useState(false);
+  const isWorkspace = src?.includes("/workspace/files/") ?? false;
+
+  if (!src) return null;
+
+  if (alt?.startsWith("video:") || (imgFailed && isWorkspace)) {
+    return (
+      <span className="my-2 inline-block">
+        <video
+          controls
+          className="h-auto max-w-full rounded-md border border-zinc-200"
+          preload="metadata"
+        >
+          <source src={src} />
+          Your browser does not support the video tag.
+        </video>
+      </span>
+    );
+  }
+
+  return (
+    // eslint-disable-next-line @next/next/no-img-element
+    <img
+      src={src}
+      alt={alt || "Image"}
+      className="h-auto max-w-full rounded-md border border-zinc-200"
+      loading="lazy"
+      onError={() => {
+        if (isWorkspace) setImgFailed(true);
+      }}
+      {...rest}
+    />
+  );
+}
+
+/** Stable components override for Streamdown (avoids re-creating on every render). */
+const STREAMDOWN_COMPONENTS = { img: WorkspaceMediaImage };
+
+const THINKING_PHRASES = [
+  "Thinking...",
+  "Considering this...",
+  "Working through this...",
+  "Analyzing your request...",
+  "Reasoning...",
+  "Looking into it...",
+  "Processing your request...",
+  "Mulling this over...",
+  "Piecing it together...",
+  "On it...",
+];
+
+function getRandomPhrase() {
+  return THINKING_PHRASES[Math.floor(Math.random() * THINKING_PHRASES.length)];
+}
+
+interface ChatMessagesContainerProps {
+  messages: UIMessage<unknown, UIDataTypes, UITools>[];
+  status: string;
+  error: Error | undefined;
+  isLoading: boolean;
+}
+
+export const ChatMessagesContainer = ({
+  messages,
+  status,
+  error,
+  isLoading,
+}: ChatMessagesContainerProps) => {
+  const [thinkingPhrase, setThinkingPhrase] = useState(getRandomPhrase);
+
+  useEffect(() => {
+    if (status === "submitted") {
+      setThinkingPhrase(getRandomPhrase());
+    }
+  }, [status]);
+
+  const lastMessage = messages[messages.length - 1];
+  const lastAssistantHasVisibleContent =
+    lastMessage?.role === "assistant" &&
+    lastMessage.parts.some(
+      (p) =>
+        (p.type === "text" && p.text.trim().length > 0) ||
+        p.type.startsWith("tool-"),
+    );
+
+  const showThinking =
+    status === "submitted" ||
+    (status === "streaming" && !lastAssistantHasVisibleContent);
+
+  return (
+    <Conversation className="min-h-0 flex-1">
+      <ConversationContent className="gap-6 px-3 py-6">
+        {isLoading && messages.length === 0 && (
+          <div className="flex flex-1 items-center justify-center">
+            <LoadingSpinner size="large" className="text-neutral-400" />
+          </div>
+        )}
+        {messages.map((message, messageIndex) => {
+          const isLastAssistant =
+            messageIndex === messages.length - 1 &&
+            message.role === "assistant";
+          const messageHasVisibleContent = message.parts.some(
+            (p) =>
+              (p.type === "text" && p.text.trim().length > 0) ||
+              p.type.startsWith("tool-"),
+          );
+
+          return (
+            <Message from={message.role} key={message.id}>
+              <MessageContent
+                className={
+                  "text-[1rem] leading-relaxed " +
+                  "group-[.is-user]:rounded-xl group-[.is-user]:bg-purple-100 group-[.is-user]:px-3 group-[.is-user]:py-2.5 group-[.is-user]:text-slate-900 group-[.is-user]:[border-bottom-right-radius:0] " +
+                  "group-[.is-assistant]:bg-transparent group-[.is-assistant]:text-slate-900"
+                }
+              >
+                {message.parts.map((part, i) => {
+                  switch (part.type) {
+                    case "text":
+                      return (
+                        <MessageResponse
+                          key={`${message.id}-${i}`}
+                          components={STREAMDOWN_COMPONENTS}
+                        >
+                          {resolveWorkspaceUrls(part.text)}
+                        </MessageResponse>
+                      );
+                    case "tool-find_block":
+                      return (
+                        <FindBlocksTool
+                          key={`${message.id}-${i}`}
+                          part={part as ToolUIPart}
+                        />
+                      );
+                    case "tool-find_agent":
+                    case "tool-find_library_agent":
+                      return (
+                        <FindAgentsTool
+                          key={`${message.id}-${i}`}
+                          part={part as ToolUIPart}
+                        />
+                      );
+                    case "tool-search_docs":
+                    case "tool-get_doc_page":
+                      return (
+                        <SearchDocsTool
+                          key={`${message.id}-${i}`}
+                          part={part as ToolUIPart}
+                        />
+                      );
+                    case "tool-run_block":
+                      return (
+                        <RunBlockTool
+                          key={`${message.id}-${i}`}
+                          part={part as ToolUIPart}
+                        />
+                      );
+                    case "tool-run_agent":
+                    case "tool-schedule_agent":
+                      return (
+                        <RunAgentTool
+                          key={`${message.id}-${i}`}
+                          part={part as ToolUIPart}
+                        />
+                      );
+                    case "tool-create_agent":
+                      return (
+                        <CreateAgentTool
+                          key={`${message.id}-${i}`}
+                          part={part as ToolUIPart}
+                        />
+                      );
+                    case "tool-edit_agent":
+                      return (
+                        <EditAgentTool
+                          key={`${message.id}-${i}`}
+                          part={part as ToolUIPart}
+                        />
+                      );
+                    case "tool-view_agent_output":
+                      return (
+                        <ViewAgentOutputTool
+                          key={`${message.id}-${i}`}
+                          part={part as ToolUIPart}
+                        />
+                      );
+                    default:
+                      return null;
+                  }
+                })}
+                {isLastAssistant &&
+                  !messageHasVisibleContent &&
+                  showThinking && (
+                    <span className="inline-block animate-shimmer bg-gradient-to-r from-neutral-400 via-neutral-600 to-neutral-400 bg-[length:200%_100%] bg-clip-text text-transparent">
+                      {thinkingPhrase}
+                    </span>
+                  )}
+              </MessageContent>
+            </Message>
+          );
+        })}
+        {showThinking && lastMessage?.role !== "assistant" && (
+          <Message from="assistant">
+            <MessageContent className="text-[1rem] leading-relaxed">
+              <span className="inline-block animate-shimmer bg-gradient-to-r from-neutral-400 via-neutral-600 to-neutral-400 bg-[length:200%_100%] bg-clip-text text-transparent">
+                {thinkingPhrase}
+              </span>
+            </MessageContent>
+          </Message>
+        )}
+        {error && (
+          <div className="rounded-lg bg-red-50 p-3 text-red-600">
+            Error: {error.message}
+          </div>
+        )}
+      </ConversationContent>
+      <ConversationScrollButton />
+    </Conversation>
+  );
+};

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

@@ -0,0 +1,188 @@
+"use client";
+import { useGetV2ListSessions } from "@/app/api/__generated__/endpoints/chat/chat";
+import { Button } from "@/components/atoms/Button/Button";
+import { LoadingSpinner } from "@/components/atoms/LoadingSpinner/LoadingSpinner";
+import { Text } from "@/components/atoms/Text/Text";
+import {
+  Sidebar,
+  SidebarContent,
+  SidebarFooter,
+  SidebarHeader,
+  SidebarTrigger,
+  useSidebar,
+} from "@/components/ui/sidebar";
+import { cn } from "@/lib/utils";
+import { PlusCircleIcon, PlusIcon } from "@phosphor-icons/react";
+import { motion } from "framer-motion";
+import { parseAsString, useQueryState } from "nuqs";
+
+export function ChatSidebar() {
+  const { state } = useSidebar();
+  const isCollapsed = state === "collapsed";
+  const [sessionId, setSessionId] = useQueryState("sessionId", parseAsString);
+
+  const { data: sessionsResponse, isLoading: isLoadingSessions } =
+    useGetV2ListSessions({ limit: 50 });
+
+  const sessions =
+    sessionsResponse?.status === 200 ? sessionsResponse.data.sessions : [];
+
+  function handleNewChat() {
+    setSessionId(null);
+  }
+
+  function handleSelectSession(id: string) {
+    setSessionId(id);
+  }
+
+  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
+      variant="inset"
+      collapsible="icon"
+      className="!top-[50px] !h-[calc(100vh-50px)] border-r border-zinc-100 px-0"
+    >
+      {isCollapsed && (
+        <SidebarHeader
+          className={cn(
+            "flex",
+            isCollapsed
+              ? "flex-row items-center justify-between gap-y-4 md:flex-col md:items-start md:justify-start"
+              : "flex-row items-center justify-between",
+          )}
+        >
+          <motion.div
+            key={isCollapsed ? "header-collapsed" : "header-expanded"}
+            className="flex flex-col items-center gap-3 pt-4"
+            initial={{ opacity: 0, filter: "blur(3px)" }}
+            animate={{ opacity: 1, filter: "blur(0px)" }}
+            transition={{ type: "spring", bounce: 0.2 }}
+          >
+            <div className="flex flex-col items-center gap-2">
+              <SidebarTrigger />
+              <Button
+                variant="ghost"
+                onClick={handleNewChat}
+                style={{ minWidth: "auto", width: "auto" }}
+              >
+                <PlusCircleIcon className="!size-5" />
+                <span className="sr-only">New Chat</span>
+              </Button>
+            </div>
+          </motion.div>
+        </SidebarHeader>
+      )}
+      <SidebarContent className="gap-4 overflow-y-auto px-4 py-4 [-ms-overflow-style:none] [scrollbar-width:none] [&::-webkit-scrollbar]:hidden">
+        {!isCollapsed && (
+          <motion.div
+            initial={{ opacity: 0 }}
+            animate={{ opacity: 1 }}
+            transition={{ duration: 0.2, delay: 0.1 }}
+            className="flex items-center justify-between px-3"
+          >
+            <Text variant="h3" size="body-medium">
+              Your chats
+            </Text>
+            <div className="relative left-6">
+              <SidebarTrigger />
+            </div>
+          </motion.div>
+        )}
+
+        {!isCollapsed && (
+          <motion.div
+            initial={{ opacity: 0 }}
+            animate={{ opacity: 1 }}
+            transition={{ duration: 0.2, delay: 0.15 }}
+            className="mt-4 flex flex-col gap-1"
+          >
+            {isLoadingSessions ? (
+              <div className="flex items-center justify-center py-4">
+                <LoadingSpinner size="small" className="text-neutral-400" />
+              </div>
+            ) : sessions.length === 0 ? (
+              <p className="py-4 text-center text-sm text-neutral-500">
+                No conversations yet
+              </p>
+            ) : (
+              sessions.map((session) => (
+                <button
+                  key={session.id}
+                  onClick={() => handleSelectSession(session.id)}
+                  className={cn(
+                    "w-full rounded-lg px-3 py-2.5 text-left transition-colors",
+                    session.id === sessionId
+                      ? "bg-zinc-100"
+                      : "hover:bg-zinc-50",
+                  )}
+                >
+                  <div className="flex min-w-0 max-w-full flex-col overflow-hidden">
+                    <div className="min-w-0 max-w-full">
+                      <Text
+                        variant="body"
+                        className={cn(
+                          "truncate font-normal",
+                          session.id === sessionId
+                            ? "text-zinc-600"
+                            : "text-zinc-800",
+                        )}
+                      >
+                        {session.title || `Untitled chat`}
+                      </Text>
+                    </div>
+                    <Text variant="small" className="text-neutral-400">
+                      {formatDate(session.updated_at)}
+                    </Text>
+                  </div>
+                </button>
+              ))
+            )}
+          </motion.div>
+        )}
+      </SidebarContent>
+      {!isCollapsed && sessionId && (
+        <SidebarFooter className="shrink-0 bg-zinc-50 p-3 pb-1 shadow-[0_-4px_6px_-1px_rgba(0,0,0,0.05)]">
+          <motion.div
+            initial={{ opacity: 0 }}
+            animate={{ opacity: 1 }}
+            transition={{ duration: 0.2, delay: 0.2 }}
+          >
+            <Button
+              variant="primary"
+              size="small"
+              onClick={handleNewChat}
+              className="w-full"
+              leftIcon={<PlusIcon className="h-4 w-4" weight="bold" />}
+            >
+              New Chat
+            </Button>
+          </motion.div>
+        </SidebarFooter>
+      )}
+    </Sidebar>
+  );
+}

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

@@ -0,0 +1,16 @@
+"use client";
+
+import { CopilotChatActionsContext } from "./useCopilotChatActions";
+
+interface Props {
+  onSend: (message: string) => void | Promise<void>;
+  children: React.ReactNode;
+}
+
+export function CopilotChatActionsProvider({ onSend, children }: Props) {
+  return (
+    <CopilotChatActionsContext.Provider value={{ onSend }}>
+      {children}
+    </CopilotChatActionsContext.Provider>
+  );
+}

autogpt_platform/frontend/src/app/(platform)/copilot/components/CopilotChatActionsProvider/useCopilotChatActions.ts

@@ -0,0 +1,23 @@
+"use client";
+
+import { createContext, useContext } from "react";
+
+interface CopilotChatActions {
+  onSend: (message: string) => void | Promise<void>;
+}
+
+const CopilotChatActionsContext = createContext<CopilotChatActions | null>(
+  null,
+);
+
+export function useCopilotChatActions(): CopilotChatActions {
+  const ctx = useContext(CopilotChatActionsContext);
+  if (!ctx) {
+    throw new Error(
+      "useCopilotChatActions must be used within CopilotChatActionsProvider",
+    );
+  }
+  return ctx;
+}
+
+export { CopilotChatActionsContext };

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

@@ -1,99 +0,0 @@
-"use client";
-
-import { ChatLoader } from "@/components/contextual/Chat/components/ChatLoader/ChatLoader";
-import { Text } from "@/components/atoms/Text/Text";
-import { NAVBAR_HEIGHT_PX } from "@/lib/constants";
-import type { ReactNode } from "react";
-import { DesktopSidebar } from "./components/DesktopSidebar/DesktopSidebar";
-import { MobileDrawer } from "./components/MobileDrawer/MobileDrawer";
-import { MobileHeader } from "./components/MobileHeader/MobileHeader";
-import { useCopilotShell } from "./useCopilotShell";
-
-interface Props {
-  children: ReactNode;
-}
-
-export function CopilotShell({ children }: Props) {
-  const {
-    isMobile,
-    isDrawerOpen,
-    isLoading,
-    isCreatingSession,
-    isLoggedIn,
-    hasActiveSession,
-    sessions,
-    currentSessionId,
-    handleOpenDrawer,
-    handleCloseDrawer,
-    handleDrawerOpenChange,
-    handleNewChatClick,
-    handleSessionClick,
-    hasNextPage,
-    isFetchingNextPage,
-    fetchNextPage,
-  } = useCopilotShell();
-
-  if (!isLoggedIn) {
-    return (
-      <div className="flex h-full items-center justify-center">
-        <ChatLoader />
-      </div>
-    );
-  }
-
-  return (
-    <div
-      className="flex overflow-hidden bg-[#EFEFF0]"
-      style={{ height: `calc(100vh - ${NAVBAR_HEIGHT_PX}px)` }}
-    >
-      {!isMobile && (
-        <DesktopSidebar
-          sessions={sessions}
-          currentSessionId={currentSessionId}
-          isLoading={isLoading}
-          hasNextPage={hasNextPage}
-          isFetchingNextPage={isFetchingNextPage}
-          onSelectSession={handleSessionClick}
-          onFetchNextPage={fetchNextPage}
-          onNewChat={handleNewChatClick}
-          hasActiveSession={Boolean(hasActiveSession)}
-        />
-      )}
-
-      <div className="relative flex min-h-0 flex-1 flex-col">
-        {isMobile && <MobileHeader onOpenDrawer={handleOpenDrawer} />}
-        <div className="flex min-h-0 flex-1 flex-col">
-          {isCreatingSession ? (
-            <div className="flex h-full flex-1 flex-col items-center justify-center bg-[#f8f8f9]">
-              <div className="flex flex-col items-center gap-4">
-                <ChatLoader />
-                <Text variant="body" className="text-zinc-500">
-                  Creating your chat...
-                </Text>
-              </div>
-            </div>
-          ) : (
-            children
-          )}
-        </div>
-      </div>
-
-      {isMobile && (
-        <MobileDrawer
-          isOpen={isDrawerOpen}
-          sessions={sessions}
-          currentSessionId={currentSessionId}
-          isLoading={isLoading}
-          hasNextPage={hasNextPage}
-          isFetchingNextPage={isFetchingNextPage}
-          onSelectSession={handleSessionClick}
-          onFetchNextPage={fetchNextPage}
-          onNewChat={handleNewChatClick}
-          onClose={handleCloseDrawer}
-          onOpenChange={handleDrawerOpenChange}
-          hasActiveSession={Boolean(hasActiveSession)}
-        />
-      )}
-    </div>
-  );
-}

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

@@ -1,70 +0,0 @@
-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 { Plus } from "@phosphor-icons/react";
-import { SessionsList } from "../SessionsList/SessionsList";
-
-interface Props {
-  sessions: SessionSummaryResponse[];
-  currentSessionId: string | null;
-  isLoading: boolean;
-  hasNextPage: boolean;
-  isFetchingNextPage: boolean;
-  onSelectSession: (sessionId: string) => void;
-  onFetchNextPage: () => void;
-  onNewChat: () => void;
-  hasActiveSession: boolean;
-}
-
-export function DesktopSidebar({
-  sessions,
-  currentSessionId,
-  isLoading,
-  hasNextPage,
-  isFetchingNextPage,
-  onSelectSession,
-  onFetchNextPage,
-  onNewChat,
-  hasActiveSession,
-}: Props) {
-  return (
-    <aside className="flex h-full w-80 flex-col border-r border-zinc-100 bg-zinc-50">
-      <div className="shrink-0 px-6 py-4">
-        <Text variant="h3" size="body-medium">
-          Your chats
-        </Text>
-      </div>
-      <div
-        className={cn(
-          "flex min-h-0 flex-1 flex-col overflow-y-auto px-3 py-3",
-          scrollbarStyles,
-        )}
-      >
-        <SessionsList
-          sessions={sessions}
-          currentSessionId={currentSessionId}
-          isLoading={isLoading}
-          hasNextPage={hasNextPage}
-          isFetchingNextPage={isFetchingNextPage}
-          onSelectSession={onSelectSession}
-          onFetchNextPage={onFetchNextPage}
-        />
-      </div>
-      {hasActiveSession && (
-        <div className="shrink-0 bg-zinc-50 p-3 shadow-[0_-4px_6px_-1px_rgba(0,0,0,0.05)]">
-          <Button
-            variant="primary"
-            size="small"
-            onClick={onNewChat}
-            className="w-full"
-            leftIcon={<Plus width="1rem" height="1rem" />}
-          >
-            New Chat
-          </Button>
-        </div>
-      )}
-    </aside>
-  );
-}

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

@@ -1,91 +0,0 @@
-import type { SessionSummaryResponse } from "@/app/api/__generated__/models/sessionSummaryResponse";
-import { Button } from "@/components/atoms/Button/Button";
-import { scrollbarStyles } from "@/components/styles/scrollbars";
-import { cn } from "@/lib/utils";
-import { PlusIcon, X } from "@phosphor-icons/react";
-import { Drawer } from "vaul";
-import { SessionsList } from "../SessionsList/SessionsList";
-
-interface Props {
-  isOpen: boolean;
-  sessions: SessionSummaryResponse[];
-  currentSessionId: string | null;
-  isLoading: boolean;
-  hasNextPage: boolean;
-  isFetchingNextPage: boolean;
-  onSelectSession: (sessionId: string) => void;
-  onFetchNextPage: () => void;
-  onNewChat: () => void;
-  onClose: () => void;
-  onOpenChange: (open: boolean) => void;
-  hasActiveSession: boolean;
-}
-
-export function MobileDrawer({
-  isOpen,
-  sessions,
-  currentSessionId,
-  isLoading,
-  hasNextPage,
-  isFetchingNextPage,
-  onSelectSession,
-  onFetchNextPage,
-  onNewChat,
-  onClose,
-  onOpenChange,
-  hasActiveSession,
-}: Props) {
-  return (
-    <Drawer.Root open={isOpen} onOpenChange={onOpenChange} direction="left">
-      <Drawer.Portal>
-        <Drawer.Overlay className="fixed inset-0 z-[60] bg-black/10 backdrop-blur-sm" />
-        <Drawer.Content className="fixed left-0 top-0 z-[70] flex h-full w-80 flex-col border-r border-zinc-200 bg-zinc-50">
-          <div className="shrink-0 border-b border-zinc-200 p-4">
-            <div className="flex items-center justify-between">
-              <Drawer.Title className="text-lg font-semibold text-zinc-800">
-                Your chats
-              </Drawer.Title>
-              <Button
-                variant="icon"
-                size="icon"
-                aria-label="Close sessions"
-                onClick={onClose}
-              >
-                <X width="1.25rem" height="1.25rem" />
-              </Button>
-            </div>
-          </div>
-          <div
-            className={cn(
-              "flex min-h-0 flex-1 flex-col overflow-y-auto px-3 py-3",
-              scrollbarStyles,
-            )}
-          >
-            <SessionsList
-              sessions={sessions}
-              currentSessionId={currentSessionId}
-              isLoading={isLoading}
-              hasNextPage={hasNextPage}
-              isFetchingNextPage={isFetchingNextPage}
-              onSelectSession={onSelectSession}
-              onFetchNextPage={onFetchNextPage}
-            />
-          </div>
-          {hasActiveSession && (
-            <div className="shrink-0 bg-white p-3 shadow-[0_-4px_6px_-1px_rgba(0,0,0,0.05)]">
-              <Button
-                variant="primary"
-                size="small"
-                onClick={onNewChat}
-                className="w-full"
-                leftIcon={<PlusIcon width="1rem" height="1rem" />}
-              >
-                New Chat
-              </Button>
-            </div>
-          )}
-        </Drawer.Content>
-      </Drawer.Portal>
-    </Drawer.Root>
-  );
-}

autogpt_platform/frontend/src/app/(platform)/copilot/components/CopilotShell/components/MobileDrawer/useMobileDrawer.ts

@@ -1,24 +0,0 @@
-import { useState } from "react";
-
-export function useMobileDrawer() {
-  const [isDrawerOpen, setIsDrawerOpen] = useState(false);
-
-  const handleOpenDrawer = () => {
-    setIsDrawerOpen(true);
-  };
-
-  const handleCloseDrawer = () => {
-    setIsDrawerOpen(false);
-  };
-
-  const handleDrawerOpenChange = (open: boolean) => {
-    setIsDrawerOpen(open);
-  };
-
-  return {
-    isDrawerOpen,
-    handleOpenDrawer,
-    handleCloseDrawer,
-    handleDrawerOpenChange,
-  };
-}

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

@@ -1,80 +0,0 @@
-import type { SessionSummaryResponse } from "@/app/api/__generated__/models/sessionSummaryResponse";
-import { Skeleton } from "@/components/__legacy__/ui/skeleton";
-import { Text } from "@/components/atoms/Text/Text";
-import { InfiniteList } from "@/components/molecules/InfiniteList/InfiniteList";
-import { cn } from "@/lib/utils";
-import { getSessionTitle } from "../../helpers";
-
-interface Props {
-  sessions: SessionSummaryResponse[];
-  currentSessionId: string | null;
-  isLoading: boolean;
-  hasNextPage: boolean;
-  isFetchingNextPage: boolean;
-  onSelectSession: (sessionId: string) => void;
-  onFetchNextPage: () => void;
-}
-
-export function SessionsList({
-  sessions,
-  currentSessionId,
-  isLoading,
-  hasNextPage,
-  isFetchingNextPage,
-  onSelectSession,
-  onFetchNextPage,
-}: Props) {
-  if (isLoading) {
-    return (
-      <div className="space-y-1">
-        {Array.from({ length: 5 }).map((_, i) => (
-          <div key={i} className="rounded-lg px-3 py-2.5">
-            <Skeleton className="h-5 w-full" />
-          </div>
-        ))}
-      </div>
-    );
-  }
-
-  if (sessions.length === 0) {
-    return (
-      <div className="flex h-full items-center justify-center">
-        <Text variant="body" className="text-zinc-500">
-          You don&apos;t have previous chats
-        </Text>
-      </div>
-    );
-  }
-
-  return (
-    <InfiniteList
-      items={sessions}
-      hasMore={hasNextPage}
-      isFetchingMore={isFetchingNextPage}
-      onEndReached={onFetchNextPage}
-      className="space-y-1"
-      renderItem={(session) => {
-        const isActive = session.id === currentSessionId;
-        return (
-          <button
-            onClick={() => onSelectSession(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",
-            )}
-          >
-            <Text
-              variant="body"
-              className={cn(
-                "font-normal",
-                isActive ? "text-zinc-600" : "text-zinc-800",
-              )}
-            >
-              {getSessionTitle(session)}
-            </Text>
-          </button>
-        );
-      }}
-    />
-  );
-}

autogpt_platform/frontend/src/app/(platform)/copilot/components/CopilotShell/components/SessionsList/useSessionsPagination.ts

@@ -1,91 +0,0 @@
-import { useGetV2ListSessions } from "@/app/api/__generated__/endpoints/chat/chat";
-import type { SessionSummaryResponse } from "@/app/api/__generated__/models/sessionSummaryResponse";
-import { okData } from "@/app/api/helpers";
-import { useEffect, useState } from "react";
-
-const PAGE_SIZE = 50;
-
-export interface UseSessionsPaginationArgs {
-  enabled: boolean;
-}
-
-export function useSessionsPagination({ enabled }: UseSessionsPaginationArgs) {
-  const [offset, setOffset] = useState(0);
-
-  const [accumulatedSessions, setAccumulatedSessions] = useState<
-    SessionSummaryResponse[]
-  >([]);
-
-  const [totalCount, setTotalCount] = useState<number | null>(null);
-
-  const { data, isLoading, isFetching, isError } = useGetV2ListSessions(
-    { limit: PAGE_SIZE, offset },
-    {
-      query: {
-        enabled: enabled && offset >= 0,
-      },
-    },
-  );
-
-  useEffect(() => {
-    const responseData = okData(data);
-    if (responseData) {
-      const newSessions = responseData.sessions;
-      const total = responseData.total;
-      setTotalCount(total);
-
-      if (offset === 0) {
-        setAccumulatedSessions(newSessions);
-      } else {
-        setAccumulatedSessions((prev) => [...prev, ...newSessions]);
-      }
-    } else if (!enabled) {
-      setAccumulatedSessions([]);
-      setTotalCount(null);
-    }
-  }, [data, offset, enabled]);
-
-  const hasNextPage =
-    totalCount !== null && accumulatedSessions.length < totalCount;
-
-  const areAllSessionsLoaded =
-    totalCount !== null &&
-    accumulatedSessions.length >= totalCount &&
-    !isFetching &&
-    !isLoading;
-
-  useEffect(() => {
-    if (
-      hasNextPage &&
-      !isFetching &&
-      !isLoading &&
-      !isError &&
-      totalCount !== null
-    ) {
-      setOffset((prev) => prev + PAGE_SIZE);
-    }
-  }, [hasNextPage, isFetching, isLoading, isError, totalCount]);
-
-  const fetchNextPage = () => {
-    if (hasNextPage && !isFetching) {
-      setOffset((prev) => prev + PAGE_SIZE);
-    }
-  };
-
-  const reset = () => {
-    // Only reset the offset - keep existing sessions visible during refetch
-    // The effect will replace sessions when new data arrives at offset 0
-    setOffset(0);
-  };
-
-  return {
-    sessions: accumulatedSessions,
-    isLoading,
-    isFetching,
-    hasNextPage,
-    areAllSessionsLoaded,
-    totalCount,
-    fetchNextPage,
-    reset,
-  };
-}

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

@@ -1,106 +0,0 @@
-import type { SessionDetailResponse } from "@/app/api/__generated__/models/sessionDetailResponse";
-import type { SessionSummaryResponse } from "@/app/api/__generated__/models/sessionSummaryResponse";
-import { format, formatDistanceToNow, isToday } from "date-fns";
-
-export function convertSessionDetailToSummary(session: SessionDetailResponse) {
-  return {
-    id: session.id,
-    created_at: session.created_at,
-    updated_at: session.updated_at,
-    title: undefined,
-  };
-}
-
-export function filterVisibleSessions(sessions: SessionSummaryResponse[]) {
-  const fiveMinutesAgo = Date.now() - 5 * 60 * 1000;
-  return sessions.filter((session) => {
-    const hasBeenUpdated = session.updated_at !== session.created_at;
-
-    if (hasBeenUpdated) return true;
-
-    const isRecentlyCreated =
-      new Date(session.created_at).getTime() > fiveMinutesAgo;
-
-    return isRecentlyCreated;
-  });
-}
-
-export function getSessionTitle(session: SessionSummaryResponse) {
-  if (session.title) return session.title;
-
-  const isNewSession = session.updated_at === session.created_at;
-
-  if (isNewSession) {
-    const createdDate = new Date(session.created_at);
-    if (isToday(createdDate)) {
-      return "Today";
-    }
-    return format(createdDate, "MMM d, yyyy");
-  }
-
-  return "Untitled Chat";
-}
-
-export function getSessionUpdatedLabel(session: SessionSummaryResponse) {
-  if (!session.updated_at) return "";
-  return formatDistanceToNow(new Date(session.updated_at), { addSuffix: true });
-}
-
-export function mergeCurrentSessionIntoList(
-  accumulatedSessions: SessionSummaryResponse[],
-  currentSessionId: string | null,
-  currentSessionData: SessionDetailResponse | null | undefined,
-  recentlyCreatedSessions?: Map<string, SessionSummaryResponse>,
-) {
-  const filteredSessions: SessionSummaryResponse[] = [];
-  const addedIds = new Set<string>();
-
-  if (accumulatedSessions.length > 0) {
-    const visibleSessions = filterVisibleSessions(accumulatedSessions);
-
-    if (currentSessionId) {
-      const currentInAll = accumulatedSessions.find(
-        (s) => s.id === currentSessionId,
-      );
-      if (currentInAll) {
-        const isInVisible = visibleSessions.some(
-          (s) => s.id === currentSessionId,
-        );
-        if (!isInVisible) {
-          filteredSessions.push(currentInAll);
-          addedIds.add(currentInAll.id);
-        }
-      }
-    }
-
-    for (const session of visibleSessions) {
-      if (!addedIds.has(session.id)) {
-        filteredSessions.push(session);
-        addedIds.add(session.id);
-      }
-    }
-  }
-
-  if (currentSessionId && currentSessionData) {
-    if (!addedIds.has(currentSessionId)) {
-      const summarySession = convertSessionDetailToSummary(currentSessionData);
-      filteredSessions.unshift(summarySession);
-      addedIds.add(currentSessionId);
-    }
-  }
-
-  if (recentlyCreatedSessions) {
-    for (const [sessionId, sessionData] of recentlyCreatedSessions) {
-      if (!addedIds.has(sessionId)) {
-        filteredSessions.unshift(sessionData);
-        addedIds.add(sessionId);
-      }
-    }
-  }
-
-  return filteredSessions;
-}
-
-export function getCurrentSessionId(searchParams: URLSearchParams) {
-  return searchParams.get("sessionId");
-}

autogpt_platform/frontend/src/app/(platform)/copilot/components/CopilotShell/useCopilotShell.ts

@@ -1,124 +0,0 @@
-"use client";
-
-import {
-  getGetV2GetSessionQueryKey,
-  getGetV2ListSessionsQueryKey,
-  useGetV2GetSession,
-} from "@/app/api/__generated__/endpoints/chat/chat";
-import { okData } from "@/app/api/helpers";
-import { useChatStore } from "@/components/contextual/Chat/chat-store";
-import { useBreakpoint } from "@/lib/hooks/useBreakpoint";
-import { useSupabase } from "@/lib/supabase/hooks/useSupabase";
-import { useQueryClient } from "@tanstack/react-query";
-import { usePathname, useSearchParams } from "next/navigation";
-import { useCopilotStore } from "../../copilot-page-store";
-import { useCopilotSessionId } from "../../useCopilotSessionId";
-import { useMobileDrawer } from "./components/MobileDrawer/useMobileDrawer";
-import { getCurrentSessionId } from "./helpers";
-import { useShellSessionList } from "./useShellSessionList";
-
-export function useCopilotShell() {
-  const pathname = usePathname();
-  const searchParams = useSearchParams();
-  const queryClient = useQueryClient();
-  const breakpoint = useBreakpoint();
-  const { isLoggedIn } = useSupabase();
-  const isMobile =
-    breakpoint === "base" || breakpoint === "sm" || breakpoint === "md";
-
-  const { urlSessionId, setUrlSessionId } = useCopilotSessionId();
-
-  const isOnHomepage = pathname === "/copilot";
-  const paramSessionId = searchParams.get("sessionId");
-
-  const {
-    isDrawerOpen,
-    handleOpenDrawer,
-    handleCloseDrawer,
-    handleDrawerOpenChange,
-  } = useMobileDrawer();
-
-  const paginationEnabled = !isMobile || isDrawerOpen || !!paramSessionId;
-
-  const currentSessionId = getCurrentSessionId(searchParams);
-
-  const { data: currentSessionData } = useGetV2GetSession(
-    currentSessionId || "",
-    {
-      query: {
-        enabled: !!currentSessionId,
-        select: okData,
-      },
-    },
-  );
-
-  const {
-    sessions,
-    isLoading,
-    isSessionsFetching,
-    hasNextPage,
-    fetchNextPage,
-    resetPagination,
-    recentlyCreatedSessionsRef,
-  } = useShellSessionList({
-    paginationEnabled,
-    currentSessionId,
-    currentSessionData,
-    isOnHomepage,
-    paramSessionId,
-  });
-
-  const stopStream = useChatStore((s) => s.stopStream);
-  const isCreatingSession = useCopilotStore((s) => s.isCreatingSession);
-
-  function handleSessionClick(sessionId: string) {
-    if (sessionId === currentSessionId) return;
-
-    // Stop current stream - SSE reconnection allows resuming later
-    if (currentSessionId) {
-      stopStream(currentSessionId);
-    }
-
-    if (recentlyCreatedSessionsRef.current.has(sessionId)) {
-      queryClient.invalidateQueries({
-        queryKey: getGetV2GetSessionQueryKey(sessionId),
-      });
-    }
-    setUrlSessionId(sessionId, { shallow: false });
-    if (isMobile) handleCloseDrawer();
-  }
-
-  function handleNewChatClick() {
-    // Stop current stream - SSE reconnection allows resuming later
-    if (currentSessionId) {
-      stopStream(currentSessionId);
-    }
-
-    resetPagination();
-    queryClient.invalidateQueries({
-      queryKey: getGetV2ListSessionsQueryKey(),
-    });
-    setUrlSessionId(null, { shallow: false });
-    if (isMobile) handleCloseDrawer();
-  }
-
-  return {
-    isMobile,
-    isDrawerOpen,
-    isLoggedIn,
-    hasActiveSession:
-      Boolean(currentSessionId) && (!isOnHomepage || Boolean(paramSessionId)),
-    isLoading: isLoading || isCreatingSession,
-    isCreatingSession,
-    sessions,
-    currentSessionId: urlSessionId,
-    handleOpenDrawer,
-    handleCloseDrawer,
-    handleDrawerOpenChange,
-    handleNewChatClick,
-    handleSessionClick,
-    hasNextPage,
-    isFetchingNextPage: isSessionsFetching,
-    fetchNextPage,
-  };
-}

autogpt_platform/frontend/src/app/(platform)/copilot/components/CopilotShell/useShellSessionList.ts

@@ -1,113 +0,0 @@
-import { getGetV2ListSessionsQueryKey } from "@/app/api/__generated__/endpoints/chat/chat";
-import type { SessionDetailResponse } from "@/app/api/__generated__/models/sessionDetailResponse";
-import type { SessionSummaryResponse } from "@/app/api/__generated__/models/sessionSummaryResponse";
-import { useChatStore } from "@/components/contextual/Chat/chat-store";
-import { useQueryClient } from "@tanstack/react-query";
-import { useEffect, useMemo, useRef } from "react";
-import { useSessionsPagination } from "./components/SessionsList/useSessionsPagination";
-import {
-  convertSessionDetailToSummary,
-  filterVisibleSessions,
-  mergeCurrentSessionIntoList,
-} from "./helpers";
-
-interface UseShellSessionListArgs {
-  paginationEnabled: boolean;
-  currentSessionId: string | null;
-  currentSessionData: SessionDetailResponse | null | undefined;
-  isOnHomepage: boolean;
-  paramSessionId: string | null;
-}
-
-export function useShellSessionList({
-  paginationEnabled,
-  currentSessionId,
-  currentSessionData,
-  isOnHomepage,
-  paramSessionId,
-}: UseShellSessionListArgs) {
-  const queryClient = useQueryClient();
-  const onStreamComplete = useChatStore((s) => s.onStreamComplete);
-
-  const {
-    sessions: accumulatedSessions,
-    isLoading: isSessionsLoading,
-    isFetching: isSessionsFetching,
-    hasNextPage,
-    fetchNextPage,
-    reset: resetPagination,
-  } = useSessionsPagination({
-    enabled: paginationEnabled,
-  });
-
-  const recentlyCreatedSessionsRef = useRef<
-    Map<string, SessionSummaryResponse>
-  >(new Map());
-
-  useEffect(() => {
-    if (isOnHomepage && !paramSessionId) {
-      queryClient.invalidateQueries({
-        queryKey: getGetV2ListSessionsQueryKey(),
-      });
-    }
-  }, [isOnHomepage, paramSessionId, queryClient]);
-
-  useEffect(() => {
-    if (currentSessionId && currentSessionData) {
-      const isNewSession =
-        currentSessionData.updated_at === currentSessionData.created_at;
-      const isNotInAccumulated = !accumulatedSessions.some(
-        (s) => s.id === currentSessionId,
-      );
-      if (isNewSession || isNotInAccumulated) {
-        const summary = convertSessionDetailToSummary(currentSessionData);
-        recentlyCreatedSessionsRef.current.set(currentSessionId, summary);
-      }
-    }
-  }, [currentSessionId, currentSessionData, accumulatedSessions]);
-
-  useEffect(() => {
-    for (const sessionId of recentlyCreatedSessionsRef.current.keys()) {
-      if (accumulatedSessions.some((s) => s.id === sessionId)) {
-        recentlyCreatedSessionsRef.current.delete(sessionId);
-      }
-    }
-  }, [accumulatedSessions]);
-
-  useEffect(() => {
-    const unsubscribe = onStreamComplete(() => {
-      queryClient.invalidateQueries({
-        queryKey: getGetV2ListSessionsQueryKey(),
-      });
-    });
-    return unsubscribe;
-  }, [onStreamComplete, queryClient]);
-
-  const sessions = useMemo(
-    () =>
-      mergeCurrentSessionIntoList(
-        accumulatedSessions,
-        currentSessionId,
-        currentSessionData,
-        recentlyCreatedSessionsRef.current,
-      ),
-    [accumulatedSessions, currentSessionId, currentSessionData],
-  );
-
-  const visibleSessions = useMemo(
-    () => filterVisibleSessions(sessions),
-    [sessions],
-  );
-
-  const isLoading = isSessionsLoading && accumulatedSessions.length === 0;
-
-  return {
-    sessions: visibleSessions,
-    isLoading,
-    isSessionsFetching,
-    hasNextPage,
-    fetchNextPage,
-    resetPagination,
-    recentlyCreatedSessionsRef,
-  };
-}

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

@@ -0,0 +1,111 @@
+"use client";
+
+import { ChatInput } from "@/app/(platform)/copilot/components/ChatInput/ChatInput";
+import { Button } from "@/components/atoms/Button/Button";
+import { Text } from "@/components/atoms/Text/Text";
+import { useSupabase } from "@/lib/supabase/hooks/useSupabase";
+import { SpinnerGapIcon } from "@phosphor-icons/react";
+import { motion } from "framer-motion";
+import { useEffect, useState } from "react";
+import {
+  getGreetingName,
+  getInputPlaceholder,
+  getQuickActions,
+} from "./helpers";
+
+interface Props {
+  inputLayoutId: string;
+  isCreatingSession: boolean;
+  onCreateSession: () => void | Promise<string>;
+  onSend: (message: string) => void | Promise<void>;
+}
+
+export function EmptySession({
+  inputLayoutId,
+  isCreatingSession,
+  onSend,
+}: Props) {
+  const { user } = useSupabase();
+  const greetingName = getGreetingName(user);
+  const quickActions = getQuickActions();
+  const [loadingAction, setLoadingAction] = useState<string | null>(null);
+  const [inputPlaceholder, setInputPlaceholder] = useState(
+    getInputPlaceholder(),
+  );
+
+  useEffect(() => {
+    setInputPlaceholder(getInputPlaceholder(window.innerWidth));
+  }, [window.innerWidth]);
+
+  async function handleQuickActionClick(action: string) {
+    if (isCreatingSession || loadingAction) return;
+
+    setLoadingAction(action);
+    try {
+      await onSend(action);
+    } finally {
+      setLoadingAction(null);
+    }
+  }
+
+  return (
+    <div className="flex h-full flex-1 items-center justify-center overflow-y-auto bg-[#f8f8f9] px-0 py-5 md:px-6 md:py-10">
+      <motion.div
+        className="w-full max-w-3xl text-center"
+        initial={{ opacity: 0 }}
+        animate={{ opacity: 1 }}
+        transition={{ duration: 0.3 }}
+      >
+        <div className="mx-auto max-w-3xl">
+          <Text variant="h3" className="mb-1 !text-[1.375rem] text-zinc-700">
+            Hey, <span className="text-violet-600">{greetingName}</span>
+          </Text>
+          <Text variant="h3" className="mb-8 !font-normal">
+            Tell me about your work — I&apos;ll find what to automate.
+          </Text>
+
+          <div className="mb-6">
+            <motion.div
+              layoutId={inputLayoutId}
+              transition={{ type: "spring", bounce: 0.2, duration: 0.65 }}
+              className="w-full px-2"
+            >
+              <ChatInput
+                inputId="chat-input-empty"
+                onSend={onSend}
+                disabled={isCreatingSession}
+                placeholder={inputPlaceholder}
+                className="w-full"
+              />
+            </motion.div>
+          </div>
+        </div>
+
+        <div className="flex flex-wrap items-center justify-center gap-3 overflow-x-auto [-ms-overflow-style:none] [scrollbar-width:none] [&::-webkit-scrollbar]:hidden">
+          {quickActions.map((action) => (
+            <Button
+              key={action}
+              type="button"
+              variant="outline"
+              size="small"
+              onClick={() => void handleQuickActionClick(action)}
+              disabled={isCreatingSession || loadingAction !== null}
+              aria-busy={loadingAction === action}
+              leftIcon={
+                loadingAction === action ? (
+                  <SpinnerGapIcon
+                    className="h-4 w-4 animate-spin"
+                    weight="bold"
+                  />
+                ) : null
+              }
+              className="h-auto shrink-0 border-zinc-300 px-3 py-2 text-[.9rem] text-zinc-600"
+            >
+              {action}
+            </Button>
+          ))}
+        </div>
+      </motion.div>
+    </div>
+  );
+}

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

@@ -1,6 +1,26 @@
-import type { User } from "@supabase/supabase-js";
+import { User } from "@supabase/supabase-js";
 
-export function getGreetingName(user?: User | null): string {
+export function getInputPlaceholder(width?: number) {
+  if (!width) return "What's your role and what eats up most of your day?";
+
+  if (width < 500) {
+    return "I'm a chef and I hate...";
+  }
+  if (width <= 1080) {
+    return "What's your role and what eats up most of your day?";
+  }
+  return "What's your role and what eats up most of your day? e.g. 'I'm a recruiter and I hate...'";
+}
+
+export function getQuickActions() {
+  return [
+    "I don't know where to start, just ask me stuff",
+    "I do the same thing every week and it's killing me",
+    "Help me find where I'm wasting my time",
+  ];
+}
+
+export function getGreetingName(user?: User | null) {
   if (!user) return "there";
   const metadata = user.user_metadata as Record<string, unknown> | undefined;
   const fullName = metadata?.full_name;
@@ -16,30 +36,3 @@ export function getGreetingName(user?: User | null): string {
   }
   return "there";
 }
-
-export function buildCopilotChatUrl(prompt: string): string {
-  const trimmed = prompt.trim();
-  if (!trimmed) return "/copilot/chat";
-  const encoded = encodeURIComponent(trimmed);
-  return `/copilot/chat?prompt=${encoded}`;
-}
-
-export function getQuickActions(): string[] {
-  return [
-    "I don't know where to start, just ask me stuff",
-    "I do the same thing every week and it's killing me",
-    "Help me find where I'm wasting my time",
-  ];
-}
-
-export function getInputPlaceholder(width?: number) {
-  if (!width) return "What's your role and what eats up most of your day?";
-
-  if (width < 500) {
-    return "I'm a chef and I hate...";
-  }
-  if (width <= 1080) {
-    return "What's your role and what eats up most of your day?";
-  }
-  return "What's your role and what eats up most of your day? e.g. 'I'm a recruiter and I hate...'";
-}

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

@@ -0,0 +1,140 @@
+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 { PlusIcon, SpinnerGapIcon, X } from "@phosphor-icons/react";
+import { Drawer } from "vaul";
+
+interface Props {
+  isOpen: boolean;
+  sessions: SessionSummaryResponse[];
+  currentSessionId: string | null;
+  isLoading: boolean;
+  onSelectSession: (sessionId: string) => void;
+  onNewChat: () => void;
+  onClose: () => void;
+  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,
+  currentSessionId,
+  isLoading,
+  onSelectSession,
+  onNewChat,
+  onClose,
+  onOpenChange,
+}: Props) {
+  return (
+    <Drawer.Root open={isOpen} onOpenChange={onOpenChange} direction="left">
+      <Drawer.Portal>
+        <Drawer.Overlay className="fixed inset-0 z-[60] bg-black/10 backdrop-blur-sm" />
+        <Drawer.Content className="fixed left-0 top-0 z-[70] flex h-full w-80 flex-col border-r border-zinc-200 bg-zinc-50">
+          <div className="shrink-0 border-b border-zinc-200 px-4 py-2">
+            <div className="flex items-center justify-between">
+              <Drawer.Title className="text-lg font-semibold text-zinc-800">
+                Your chats
+              </Drawer.Title>
+              <Button
+                variant="icon"
+                size="icon"
+                aria-label="Close sessions"
+                onClick={onClose}
+              >
+                <X width="1rem" height="1rem" />
+              </Button>
+            </div>
+          </div>
+          <div
+            className={cn(
+              "flex min-h-0 flex-1 flex-col gap-1 overflow-y-auto px-3 py-3",
+              scrollbarStyles,
+            )}
+          >
+            {isLoading ? (
+              <div className="flex items-center justify-center py-4">
+                <SpinnerGapIcon className="h-5 w-5 animate-spin text-neutral-400" />
+              </div>
+            ) : sessions.length === 0 ? (
+              <p className="py-4 text-center text-sm text-neutral-500">
+                No conversations yet
+              </p>
+            ) : (
+              sessions.map((session) => (
+                <button
+                  key={session.id}
+                  onClick={() => onSelectSession(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="min-w-0 max-w-full">
+                      <Text
+                        variant="body"
+                        className={cn(
+                          "truncate font-normal",
+                          session.id === currentSessionId
+                            ? "text-zinc-600"
+                            : "text-zinc-800",
+                        )}
+                      >
+                        {session.title || "Untitled chat"}
+                      </Text>
+                    </div>
+                    <Text variant="small" className="text-neutral-400">
+                      {formatDate(session.updated_at)}
+                    </Text>
+                  </div>
+                </button>
+              ))
+            )}
+          </div>
+          {currentSessionId && (
+            <div className="shrink-0 bg-white p-3 shadow-[0_-4px_6px_-1px_rgba(0,0,0,0.05)]">
+              <Button
+                variant="primary"
+                size="small"
+                onClick={onNewChat}
+                className="w-full"
+                leftIcon={<PlusIcon width="1rem" height="1rem" />}
+              >
+                New Chat
+              </Button>
+            </div>
+          )}
+        </Drawer.Content>
+      </Drawer.Portal>
+    </Drawer.Root>
+  );
+}

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

@@ -0,0 +1,54 @@
+import { cn } from "@/lib/utils";
+import { AnimatePresence, motion } from "framer-motion";
+
+interface Props {
+  text: string;
+  className?: string;
+}
+
+export function MorphingTextAnimation({ text, className }: Props) {
+  const letters = text.split("");
+
+  return (
+    <div className={cn(className)}>
+      <AnimatePresence mode="popLayout" initial={false}>
+        <motion.div key={text} className="whitespace-nowrap">
+          <motion.span className="inline-flex overflow-hidden">
+            {letters.map((char, index) => (
+              <motion.span
+                key={`${text}-${index}`}
+                initial={{
+                  opacity: 0,
+                  y: 8,
+                  rotateX: "80deg",
+                  filter: "blur(6px)",
+                }}
+                animate={{
+                  opacity: 1,
+                  y: 0,
+                  rotateX: "0deg",
+                  filter: "blur(0px)",
+                }}
+                exit={{
+                  opacity: 0,
+                  y: -8,
+                  rotateX: "-80deg",
+                  filter: "blur(6px)",
+                }}
+                style={{ willChange: "transform" }}
+                transition={{
+                  delay: 0.015 * index,
+                  type: "spring",
+                  bounce: 0.5,
+                }}
+                className="inline-block"
+              >
+                {char === " " ? "\u00A0" : char}
+              </motion.span>
+            ))}
+          </motion.span>
+        </motion.div>
+      </AnimatePresence>
+    </div>
+  );
+}

autogpt_platform/frontend/src/app/(platform)/copilot/components/OrbitLoader/OrbitLoader.module.css

@@ -0,0 +1,69 @@
+.loader {
+  position: relative;
+  animation: rotate 1s infinite;
+}
+
+.loader::before,
+.loader::after {
+  border-radius: 50%;
+  content: "";
+  display: block;
+  /* 40% of container size */
+  height: 40%;
+  width: 40%;
+}
+
+.loader::before {
+  animation: ball1 1s infinite;
+  background-color: #a1a1aa; /* zinc-400 */
+  box-shadow: calc(var(--spacing)) 0 0 #18181b; /* zinc-900 */
+  margin-bottom: calc(var(--gap));
+}
+
+.loader::after {
+  animation: ball2 1s infinite;
+  background-color: #18181b; /* zinc-900 */
+  box-shadow: calc(var(--spacing)) 0 0 #a1a1aa; /* zinc-400 */
+}
+
+@keyframes rotate {
+  0% {
+    transform: rotate(0deg) scale(0.8);
+  }
+  50% {
+    transform: rotate(360deg) scale(1.2);
+  }
+  100% {
+    transform: rotate(720deg) scale(0.8);
+  }
+}
+
+@keyframes ball1 {
+  0% {
+    box-shadow: calc(var(--spacing)) 0 0 #18181b;
+  }
+  50% {
+    box-shadow: 0 0 0 #18181b;
+    margin-bottom: 0;
+    transform: translate(calc(var(--spacing) / 2), calc(var(--spacing) / 2));
+  }
+  100% {
+    box-shadow: calc(var(--spacing)) 0 0 #18181b;
+    margin-bottom: calc(var(--gap));
+  }
+}
+
+@keyframes ball2 {
+  0% {
+    box-shadow: calc(var(--spacing)) 0 0 #a1a1aa;
+  }
+  50% {
+    box-shadow: 0 0 0 #a1a1aa;
+    margin-top: calc(var(--ball-size) * -1);
+    transform: translate(calc(var(--spacing) / 2), calc(var(--spacing) / 2));
+  }
+  100% {
+    box-shadow: calc(var(--spacing)) 0 0 #a1a1aa;
+    margin-top: 0;
+  }
+}

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

@@ -0,0 +1,28 @@
+import { cn } from "@/lib/utils";
+import styles from "./OrbitLoader.module.css";
+
+interface Props {
+  size?: number;
+  className?: string;
+}
+
+export function OrbitLoader({ size = 24, className }: Props) {
+  const ballSize = Math.round(size * 0.4);
+  const spacing = Math.round(size * 0.6);
+  const gap = Math.round(size * 0.2);
+
+  return (
+    <div
+      className={cn(styles.loader, className)}
+      style={
+        {
+          width: size,
+          height: size,
+          "--ball-size": `${ballSize}px`,
+          "--spacing": `${spacing}px`,
+          "--gap": `${gap}px`,
+        } as React.CSSProperties
+      }
+    />
+  );
+}

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

@@ -0,0 +1,26 @@
+import { cn } from "@/lib/utils";
+
+interface Props {
+  value: number;
+  label?: string;
+  className?: string;
+}
+
+export function ProgressBar({ value, label, className }: Props) {
+  const clamped = Math.min(100, Math.max(0, value));
+
+  return (
+    <div className={cn("flex flex-col gap-1.5", className)}>
+      <div className="flex items-center justify-between text-xs text-neutral-500">
+        <span>{label ?? "Working on it..."}</span>
+        <span>{Math.round(clamped)}%</span>
+      </div>
+      <div className="h-2 w-full overflow-hidden rounded-full bg-neutral-200">
+        <div
+          className="h-full rounded-full bg-neutral-900 transition-[width] duration-300 ease-out"
+          style={{ width: `${clamped}%` }}
+        />
+      </div>
+    </div>
+  );
+}

autogpt_platform/frontend/src/app/(platform)/copilot/components/PulseLoader/PulseLoader.module.css

@@ -0,0 +1,34 @@
+.loader {
+  position: relative;
+  display: inline-block;
+  flex-shrink: 0;
+}
+
+.loader::before,
+.loader::after {
+  content: "";
+  box-sizing: border-box;
+  width: 100%;
+  height: 100%;
+  border-radius: 50%;
+  background: currentColor;
+  position: absolute;
+  left: 0;
+  top: 0;
+  animation: ripple 2s linear infinite;
+}
+
+.loader::after {
+  animation-delay: 1s;
+}
+
+@keyframes ripple {
+  0% {
+    transform: scale(0);
+    opacity: 1;
+  }
+  100% {
+    transform: scale(1);
+    opacity: 0;
+  }
+}

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

@@ -0,0 +1,16 @@
+import { cn } from "@/lib/utils";
+import styles from "./PulseLoader.module.css";
+
+interface Props {
+  size?: number;
+  className?: string;
+}
+
+export function PulseLoader({ size = 24, className }: Props) {
+  return (
+    <div
+      className={cn(styles.loader, className)}
+      style={{ width: size, height: size }}
+    />
+  );
+}

autogpt_platform/frontend/src/app/(platform)/copilot/components/SpinnerLoader/SpinnerLoader.module.css

@@ -0,0 +1,57 @@
+.loader {
+  position: relative;
+  display: inline-block;
+  flex-shrink: 0;
+  transform: rotateZ(45deg);
+  perspective: 1000px;
+  border-radius: 50%;
+  color: currentColor;
+}
+
+.loader::before,
+.loader::after {
+  content: "";
+  display: block;
+  position: absolute;
+  top: 0;
+  left: 0;
+  width: inherit;
+  height: inherit;
+  border-radius: 50%;
+  transform: rotateX(70deg);
+  animation: spin 1s linear infinite;
+}
+
+.loader::after {
+  color: var(--spinner-accent, #a855f7);
+  transform: rotateY(70deg);
+  animation-delay: 0.4s;
+}
+
+@keyframes spin {
+  0%,
+  100% {
+    box-shadow: 0.2em 0 0 0 currentColor;
+  }
+  12% {
+    box-shadow: 0.2em 0.2em 0 0 currentColor;
+  }
+  25% {
+    box-shadow: 0 0.2em 0 0 currentColor;
+  }
+  37% {
+    box-shadow: -0.2em 0.2em 0 0 currentColor;
+  }
+  50% {
+    box-shadow: -0.2em 0 0 0 currentColor;
+  }
+  62% {
+    box-shadow: -0.2em -0.2em 0 0 currentColor;
+  }
+  75% {
+    box-shadow: 0 -0.2em 0 0 currentColor;
+  }
+  87% {
+    box-shadow: 0.2em -0.2em 0 0 currentColor;
+  }
+}