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7 Commits

Author SHA1 Message Date
Zamil Majdy
3d880cd591 refactor(backend/copilot): move imports to module level
- Move KEY_WORKFLOWS and TOOL_REGISTRY imports to top of file
- Better code organization following Python conventions
2026-03-06 23:15:39 +07:00
Zamil Majdy
73f5ff9983 test(backend/copilot): add tests for auto-generated tool documentation
- Test tool documentation structure (sections, format)
- Test that all TOOL_REGISTRY tools are included
- Test workflow sections are present
- Test no duplicate tools
- Verify markdown formatting compliance
- All 6 tests passing
2026-03-06 23:15:39 +07:00
Zamil Majdy
6d9faf5f91 refactor(backend/copilot): auto-generate tool docs in supplement, simplify default prompt
- Add _generate_tool_documentation() to auto-generate tool list from TOOL_REGISTRY
- Extract KEY_WORKFLOWS constant to prompt_constants.py for maintainability
- Append auto-generated tool docs + workflow guidance to system prompt supplement
- Simplify DEFAULT_SYSTEM_PROMPT to minimal tone/style baseline (Langfuse handles details)
- Add KEY WORKFLOWS section covering MCP integration, agent creation, folder management
- Ensures tool documentation stays in sync with actual implementations
- Fix Pyright error by safely accessing description field with .get()
2026-03-06 23:10:42 +07:00
Zamil Majdy
7774717104 docs(backend/copilot): document web_search and web_fetch in tool supplement
Add clear documentation for web_search and web_fetch to the shared tool notes
that get appended to all system prompts (Langfuse or default). This ensures
the copilot knows to use web_search for general web queries instead of
incorrectly using find_block to search for web search blocks.

- web_search: For current information beyond knowledge cutoff
- web_fetch: For retrieving content from specific URLs
2026-03-06 23:10:42 +07:00
Zamil Majdy
89ed628609 fix(backend/copilot): capture tool results in transcript
Tool results (StreamToolOutputAvailable) were being added to session.messages
but NOT to transcript_builder, causing the transcript to miss tool executions.
This made the copilot claim '(no tool used)' when tools were actually called.

Now tool results are captured as user messages with tool_result content blocks,
matching the Claude API transcript format and ensuring --resume has complete
conversation history including all tool interactions.
2026-03-06 23:10:42 +07:00
Zamil Majdy
d56452898a hotfix(backend/copilot): refactor transcript to SDK-based atomic full-context model (#12318)
## Summary

Major refactor to eliminate CLI transcript race conditions and simplify
the codebase by building transcripts directly from SDK messages instead
of reading CLI files.

## Problem

The previous approach had race conditions:
- SDK reads CLI transcript file during stop hook
- CLI may not have finished writing → incomplete transcript
- Complex merge logic to detect and fix incomplete writes
- ~200 lines of synthetic entry detection and merge code

## Solution

**Atomic Full-Context Transcript Model:**
- Build transcript from SDK messages during streaming
(`TranscriptBuilder`)
- Each upload REPLACES the previous transcript entirely (atomic)
- No CLI file reading → no race conditions
- Eliminates all merge complexity

## Key Changes

### Core Refactor
- **NEW**: `transcript_builder.py` - Build JSONL from SDK messages
during streaming
- **SIMPLIFIED**: `transcript.py` - Removed merge logic, simplified
upload/download
- **SIMPLIFIED**: `service.py` - Use TranscriptBuilder, removed stop
hook callback
- **CLEANED**: `security_hooks.py` - Removed `on_stop` parameter

### Performance & Code Quality
- **orjson migration**: Use `backend.util.json` (2-3x faster than
stdlib)
- Added `fallback` parameter to `json.loads()` for cleaner error
handling
- Moved SDK imports to top-level per code style guidelines

### Bug Fixes
- Fixed garbage collection bug in background task handling
- Fixed double upload bug in timeout handling  
- Downgraded PII-risk logging from WARNING to DEBUG
- Added 30s timeout to prevent session lock hang

## Code Removed (~200 lines)

- `merge_with_previous_transcript()` - No longer needed
- `read_transcript_file()` - No longer needed
- `CapturedTranscript` dataclass - No longer needed
- `_on_stop()` callback - No longer needed
- Synthetic entry detection logic - No longer needed
- Manual append/merge logic in finally block - No longer needed

## Testing

-  All transcript tests passing (24/24)
-  Verified with real session logs showing proper transcript growth
-  Verified with Langfuse traces showing proper turn tracking (1-8)

## Transcript Growth Pattern

From session logs:
- **Turn 1**: 2 entries (initial)
- **Turn 2**: 5 entries (+3), 2257B uploaded
- **Turn N**: ~2N entries (linear growth)

Each upload is the **complete atomic state** - always REPLACES, never
incremental.

## Files Changed

```
backend/copilot/sdk/transcript_builder.py (NEW)   | +140 lines
backend/copilot/sdk/transcript.py                  | -198, +125 lines  
backend/copilot/sdk/service.py                     | -214, +160 lines
backend/copilot/sdk/security_hooks.py              | -33, +10 lines
backend/copilot/sdk/transcript_test.py             | -85, +36 lines
backend/util/json.py                               | +45 lines
```

**Net result**: -200 lines, more reliable, faster JSON operations.

## Migration Notes

This is a **breaking change** for any code that:
- Directly calls `merge_with_previous_transcript()` or
`read_transcript_file()`
- Relies on incremental transcript uploads
- Expects stop hook callbacks

All internal usage has been updated.

---

@ntindle - Tagging for autogpt-reviewer
2026-03-06 21:03:49 +07:00
Otto
3e108a813a fix(backend): Use db_manager for workspace in add_graph_execution (#12312)
When `add_graph_execution` is called from a context where the global
Prisma client isn't connected (e.g. CoPilot tools, external API), the
call to `get_or_create_workspace(user_id)` crashes with
`ClientNotConnectedError` because it directly accesses
`UserWorkspace.prisma()`.

The fix adds `workspace_db` to the existing `if prisma.is_connected()`
fallback pattern, consistent with how all other DB calls in the function
already work.

**Sentry:** AUTOGPT-SERVER-83T (and ~15 related issues going back to Jan
2026)

---
Co-authored-by: Reinier van der Leer (@Pwuts) <pwuts@agpt.co>

Co-authored-by: Reinier van der Leer (@Pwuts) <pwuts@agpt.co>
2026-03-06 08:48:15 +01:00
31 changed files with 441 additions and 787 deletions

View File

@@ -11,7 +11,7 @@ from autogpt_libs import auth
from fastapi import APIRouter, Depends, HTTPException, Query, Response, Security
from fastapi.responses import StreamingResponse
from prisma.models import UserWorkspaceFile
from pydantic import BaseModel, Field, field_validator
from pydantic import BaseModel, Field
from backend.copilot import service as chat_service
from backend.copilot import stream_registry
@@ -25,7 +25,6 @@ from backend.copilot.model import (
delete_chat_session,
get_chat_session,
get_user_sessions,
update_session_title,
)
from backend.copilot.response_model import StreamError, StreamFinish, StreamHeartbeat
from backend.copilot.tools.models import (
@@ -142,20 +141,6 @@ class CancelSessionResponse(BaseModel):
reason: str | None = None
class UpdateSessionTitleRequest(BaseModel):
"""Request model for updating a session's title."""
title: str
@field_validator("title")
@classmethod
def title_must_not_be_blank(cls, v: str) -> str:
stripped = v.strip()
if not stripped:
raise ValueError("Title must not be blank")
return stripped
# ========== Routes ==========
@@ -279,43 +264,6 @@ async def delete_session(
return Response(status_code=204)
@router.patch(
"/sessions/{session_id}/title",
summary="Update session title",
dependencies=[Security(auth.requires_user)],
status_code=200,
responses={404: {"description": "Session not found or access denied"}},
)
async def update_session_title_route(
session_id: str,
request: UpdateSessionTitleRequest,
user_id: Annotated[str, Security(auth.get_user_id)],
) -> dict:
"""
Update the title of a chat session.
Allows the user to rename their chat session.
Args:
session_id: The session ID to update.
request: Request body containing the new title.
user_id: The authenticated user's ID.
Returns:
dict: Status of the update.
Raises:
HTTPException: 404 if session not found or not owned by user.
"""
success = await update_session_title(session_id, user_id, request.title)
if not success:
raise HTTPException(
status_code=404,
detail=f"Session {session_id} not found or access denied",
)
return {"status": "ok"}
@router.get(
"/sessions/{session_id}",
)

View File

@@ -1,6 +1,4 @@
"""Tests for chat API routes: session title update and file attachment validation."""
from unittest.mock import AsyncMock
"""Tests for chat route file_ids validation and enrichment."""
import fastapi
import fastapi.testclient
@@ -19,7 +17,6 @@ TEST_USER_ID = "3e53486c-cf57-477e-ba2a-cb02dc828e1a"
@pytest.fixture(autouse=True)
def setup_app_auth(mock_jwt_user):
"""Setup auth overrides for all tests in this module"""
from autogpt_libs.auth.jwt_utils import get_jwt_payload
app.dependency_overrides[get_jwt_payload] = mock_jwt_user["get_jwt_payload"]
@@ -27,95 +24,7 @@ def setup_app_auth(mock_jwt_user):
app.dependency_overrides.clear()
def _mock_update_session_title(
mocker: pytest_mock.MockerFixture, *, success: bool = True
):
"""Mock update_session_title."""
return mocker.patch(
"backend.api.features.chat.routes.update_session_title",
new_callable=AsyncMock,
return_value=success,
)
# ─── Update title: success ─────────────────────────────────────────────
def test_update_title_success(
mocker: pytest_mock.MockerFixture,
test_user_id: str,
) -> None:
mock_update = _mock_update_session_title(mocker, success=True)
response = client.patch(
"/sessions/sess-1/title",
json={"title": "My project"},
)
assert response.status_code == 200
assert response.json() == {"status": "ok"}
mock_update.assert_called_once_with("sess-1", test_user_id, "My project")
def test_update_title_trims_whitespace(
mocker: pytest_mock.MockerFixture,
test_user_id: str,
) -> None:
mock_update = _mock_update_session_title(mocker, success=True)
response = client.patch(
"/sessions/sess-1/title",
json={"title": " trimmed "},
)
assert response.status_code == 200
mock_update.assert_called_once_with("sess-1", test_user_id, "trimmed")
# ─── Update title: blank / whitespace-only → 422 ──────────────────────
def test_update_title_blank_rejected(
test_user_id: str,
) -> None:
"""Whitespace-only titles must be rejected before hitting the DB."""
response = client.patch(
"/sessions/sess-1/title",
json={"title": " "},
)
assert response.status_code == 422
def test_update_title_empty_rejected(
test_user_id: str,
) -> None:
response = client.patch(
"/sessions/sess-1/title",
json={"title": ""},
)
assert response.status_code == 422
# ─── Update title: session not found or wrong user → 404 ──────────────
def test_update_title_not_found(
mocker: pytest_mock.MockerFixture,
test_user_id: str,
) -> None:
_mock_update_session_title(mocker, success=False)
response = client.patch(
"/sessions/sess-1/title",
json={"title": "New name"},
)
assert response.status_code == 404
# ─── file_ids Pydantic validation ─────────────────────────────────────
# ---- file_ids Pydantic validation (B1) ----
def test_stream_chat_rejects_too_many_file_ids():
@@ -183,7 +92,7 @@ def test_stream_chat_accepts_20_file_ids(mocker: pytest_mock.MockFixture):
assert response.status_code == 200
# ─── UUID format filtering ─────────────────────────────────────────────
# ---- UUID format filtering ----
def test_file_ids_filters_invalid_uuids(mocker: pytest_mock.MockFixture):
@@ -222,7 +131,7 @@ def test_file_ids_filters_invalid_uuids(mocker: pytest_mock.MockFixture):
assert call_kwargs["where"]["id"]["in"] == [valid_id]
# ─── Cross-workspace file_ids ─────────────────────────────────────────
# ---- Cross-workspace file_ids ----
def test_file_ids_scoped_to_workspace(mocker: pytest_mock.MockFixture):

View File

@@ -116,7 +116,6 @@ class LlmModel(str, Enum, metaclass=LlmModelMeta):
CLAUDE_4_5_SONNET = "claude-sonnet-4-5-20250929"
CLAUDE_4_5_HAIKU = "claude-haiku-4-5-20251001"
CLAUDE_4_6_OPUS = "claude-opus-4-6"
CLAUDE_4_6_SONNET = "claude-sonnet-4-6"
CLAUDE_3_HAIKU = "claude-3-haiku-20240307"
# AI/ML API models
AIML_API_QWEN2_5_72B = "Qwen/Qwen2.5-72B-Instruct-Turbo"
@@ -275,9 +274,6 @@ MODEL_METADATA = {
LlmModel.CLAUDE_4_6_OPUS: ModelMetadata(
"anthropic", 200000, 128000, "Claude Opus 4.6", "Anthropic", "Anthropic", 3
), # claude-opus-4-6
LlmModel.CLAUDE_4_6_SONNET: ModelMetadata(
"anthropic", 200000, 64000, "Claude Sonnet 4.6", "Anthropic", "Anthropic", 3
), # claude-sonnet-4-6
LlmModel.CLAUDE_4_5_OPUS: ModelMetadata(
"anthropic", 200000, 64000, "Claude Opus 4.5", "Anthropic", "Anthropic", 3
), # claude-opus-4-5-20251101

View File

@@ -83,8 +83,7 @@ class StagehandRecommendedLlmModel(str, Enum):
GPT41_MINI = "gpt-4.1-mini-2025-04-14"
# Anthropic
CLAUDE_4_5_SONNET = "claude-sonnet-4-5-20250929" # Keep for backwards compat
CLAUDE_4_6_SONNET = "claude-sonnet-4-6"
CLAUDE_4_5_SONNET = "claude-sonnet-4-5-20250929"
@property
def provider_name(self) -> str:
@@ -138,7 +137,7 @@ class StagehandObserveBlock(Block):
model: StagehandRecommendedLlmModel = SchemaField(
title="LLM Model",
description="LLM to use for Stagehand (provider is inferred)",
default=StagehandRecommendedLlmModel.CLAUDE_4_6_SONNET,
default=StagehandRecommendedLlmModel.CLAUDE_4_5_SONNET,
advanced=False,
)
model_credentials: AICredentials = AICredentialsField()
@@ -228,7 +227,7 @@ class StagehandActBlock(Block):
model: StagehandRecommendedLlmModel = SchemaField(
title="LLM Model",
description="LLM to use for Stagehand (provider is inferred)",
default=StagehandRecommendedLlmModel.CLAUDE_4_6_SONNET,
default=StagehandRecommendedLlmModel.CLAUDE_4_5_SONNET,
advanced=False,
)
model_credentials: AICredentials = AICredentialsField()
@@ -325,7 +324,7 @@ class StagehandExtractBlock(Block):
model: StagehandRecommendedLlmModel = SchemaField(
title="LLM Model",
description="LLM to use for Stagehand (provider is inferred)",
default=StagehandRecommendedLlmModel.CLAUDE_4_6_SONNET,
default=StagehandRecommendedLlmModel.CLAUDE_4_5_SONNET,
advanced=False,
)
model_credentials: AICredentials = AICredentialsField()

View File

@@ -62,8 +62,8 @@ async def _update_title_async(
"""Generate and persist a session title in the background."""
try:
title = await _generate_session_title(message, user_id, session_id)
if title and user_id:
await update_session_title(session_id, user_id, title, only_if_empty=True)
if title:
await update_session_title(session_id, title)
except Exception as e:
logger.warning("[Baseline] Failed to update session title: %s", e)

View File

@@ -81,35 +81,6 @@ async def update_chat_session(
return ChatSession.from_db(session) if session else None
async def update_chat_session_title(
session_id: str,
user_id: str,
title: str,
*,
only_if_empty: bool = False,
) -> bool:
"""Update the title of a chat session, scoped to the owning user.
Always filters by (session_id, user_id) so callers cannot mutate another
user's session even when they know the session_id.
Args:
only_if_empty: When True, uses an atomic ``UPDATE WHERE title IS NULL``
guard so auto-generated titles never overwrite a user-set title.
Returns True if a row was updated, False otherwise (session not found,
wrong user, or — when only_if_empty — title was already set).
"""
where: ChatSessionWhereInput = {"id": session_id, "userId": user_id}
if only_if_empty:
where["title"] = None
result = await PrismaChatSession.prisma().update_many(
where=where,
data={"title": title, "updatedAt": datetime.now(UTC)},
)
return result > 0
async def add_chat_message(
session_id: str,
role: str,

View File

@@ -469,16 +469,8 @@ async def upsert_chat_session(
)
db_error = e
# Save to cache (best-effort, even if DB failed).
# Title updates (update_session_title) run *outside* this lock because
# they only touch the title field, not messages. So a concurrent rename
# or auto-title may have written a newer title to Redis while this
# upsert was in progress. Always prefer the cached title to avoid
# overwriting it with the stale in-memory copy.
# Save to cache (best-effort, even if DB failed)
try:
existing_cached = await _get_session_from_cache(session.session_id)
if existing_cached and existing_cached.title:
session = session.model_copy(update={"title": existing_cached.title})
await cache_chat_session(session)
except Exception as e:
# If DB succeeded but cache failed, raise cache error
@@ -693,48 +685,30 @@ async def delete_chat_session(session_id: str, user_id: str | None = None) -> bo
return True
async def update_session_title(
session_id: str,
user_id: str,
title: str,
*,
only_if_empty: bool = False,
) -> bool:
"""Update the title of a chat session, scoped to the owning user.
async def update_session_title(session_id: str, title: str) -> bool:
"""Update only the title of a chat session.
Lightweight operation that doesn't touch messages, avoiding race conditions
with concurrent message updates.
This is a lightweight operation that doesn't touch messages, avoiding
race conditions with concurrent message updates. Use this for background
title generation instead of upsert_chat_session.
Args:
session_id: The session ID to update.
user_id: Owning user — the DB query filters on this.
title: The new title to set.
only_if_empty: When True, uses an atomic ``UPDATE WHERE title IS NULL``
so auto-generated titles never overwrite a user-set title.
Returns:
True if updated successfully, False otherwise (not found, wrong user,
or — when only_if_empty — title was already set).
True if updated successfully, False otherwise.
"""
try:
updated = await chat_db().update_chat_session_title(
session_id, user_id, title, only_if_empty=only_if_empty
)
if not updated:
result = await chat_db().update_chat_session(session_id=session_id, title=title)
if result is None:
logger.warning(f"Session {session_id} not found for title update")
return False
# Update title in cache if it exists (instead of invalidating).
# This prevents race conditions where cache invalidation causes
# the frontend to see stale DB data while streaming is still in progress.
try:
cached = await _get_session_from_cache(session_id)
if cached:
cached.title = title
await cache_chat_session(cached)
except Exception as e:
logger.warning(
f"Cache title update failed for session {session_id} (non-critical): {e}"
)
# Invalidate the cache so the next access reloads from DB with the
# updated title. This avoids a read-modify-write on the full session
# blob, which could overwrite concurrent message updates.
await invalidate_session_cache(session_id)
return True
except Exception as e:

View File

@@ -0,0 +1,29 @@
"""Prompt constants for CoPilot - workflow guidance and supplementary documentation.
This module contains workflow patterns and guidance that supplement the main system prompt.
These are appended dynamically to the prompt along with auto-generated tool documentation.
"""
# Workflow guidance for key tool patterns
# This is appended after the auto-generated tool list to provide usage patterns
KEY_WORKFLOWS = """
## KEY WORKFLOWS
### MCP Integration Workflow
When using `run_mcp_tool`:
1. **Known servers** (use directly): Notion (https://mcp.notion.com/mcp), Linear (https://mcp.linear.app/mcp), Stripe (https://mcp.stripe.com), Intercom (https://mcp.intercom.com/mcp), Cloudflare (https://mcp.cloudflare.com/mcp), Atlassian (https://mcp.atlassian.com/mcp)
2. **Unknown servers**: Use `web_search("{{service}} MCP server URL")` to find the endpoint
3. **Discovery**: Call `run_mcp_tool(server_url)` to see available tools
4. **Execution**: Call `run_mcp_tool(server_url, tool_name, tool_arguments)`
5. **Authentication**: If credentials needed, user will be prompted. When they confirm, retry immediately with same arguments.
### Agent Creation Workflow
When using `create_agent`:
1. Always check `find_library_agent` first for existing solutions
2. Call `create_agent` with description
3. **If `suggested_goal` returned**: Present to user, ask for confirmation, call again with suggested goal if accepted
4. **If `clarifying_questions` returned**: After user answers, call again with original description AND answers in `context` parameter
### Folder Management
Use folder tools (`create_folder`, `list_folders`, `move_agents_to_folder`) to organize agents in the user's library for better discoverability."""

View File

@@ -44,6 +44,7 @@ from ..model import (
update_session_title,
upsert_chat_session,
)
from ..prompt_constants import KEY_WORKFLOWS
from ..response_model import (
StreamBaseResponse,
StreamError,
@@ -59,6 +60,7 @@ from ..service import (
_generate_session_title,
_is_langfuse_configured,
)
from ..tools import TOOL_REGISTRY
from ..tools.e2b_sandbox import get_or_create_sandbox
from ..tools.sandbox import WORKSPACE_PREFIX, make_session_path
from ..tools.workspace_files import get_manager
@@ -149,8 +151,37 @@ _HEARTBEAT_INTERVAL = 10.0 # seconds
# Appended to the system prompt to inform the agent about available tools.
# The SDK built-in Bash is NOT available — use mcp__copilot__bash_exec instead,
# which has kernel-level network isolation (unshare --net).
def _generate_tool_documentation() -> str:
"""Auto-generate tool documentation from TOOL_REGISTRY.
This generates a complete list of available tools with their descriptions,
ensuring the documentation stays in sync with the actual tool implementations.
"""
docs = "\n## AVAILABLE TOOLS\n\n"
# Sort tools alphabetically for consistent output
for name in sorted(TOOL_REGISTRY.keys()):
tool = TOOL_REGISTRY[name]
schema = tool.as_openai_tool()
desc = schema["function"].get("description", "No description available")
# Format as bullet list with tool name in code style
docs += f"- **`{name}`**: {desc}\n"
# Add workflow guidance for key tools
docs += KEY_WORKFLOWS
return docs
_SHARED_TOOL_NOTES = """\
### Web search and research
- **`web_search(query)`** — Search the web for current information (uses Claude's
native web search). Use this when you need up-to-date information, facts,
statistics, or current events that are beyond your knowledge cutoff.
- **`web_fetch(url)`** — Retrieve and analyze content from a specific URL.
Use this when you have a specific URL to read (documentation, articles, etc.).
### Sharing files with the user
After saving a file to the persistent workspace with `write_workspace_file`,
share it with the user by embedding the `download_url` from the response in
@@ -444,6 +475,7 @@ def _format_sdk_content_blocks(blocks: list) -> list[dict[str, Any]]:
"""Convert SDK content blocks to transcript format.
Handles TextBlock, ToolUseBlock, ToolResultBlock, and ThinkingBlock.
Unknown block types are logged and skipped.
"""
result: list[dict[str, Any]] = []
for block in blocks or []:
@@ -474,6 +506,11 @@ def _format_sdk_content_blocks(blocks: list) -> list[dict[str, Any]]:
"signature": block.signature,
}
)
else:
logger.warning(
f"[SDK] Unknown content block type: {type(block).__name__}. "
f"This may indicate a new SDK version with additional block types."
)
return result
@@ -959,10 +996,16 @@ async def stream_chat_completion_sdk(
)
use_e2b = e2b_sandbox is not None
system_prompt = base_system_prompt + (
_E2B_TOOL_SUPPLEMENT
if use_e2b
else _LOCAL_TOOL_SUPPLEMENT.format(cwd=sdk_cwd)
# Generate tool documentation and append appropriate supplement
tool_docs = _generate_tool_documentation()
system_prompt = (
base_system_prompt
+ tool_docs
+ (
_E2B_TOOL_SUPPLEMENT
if use_e2b
else _LOCAL_TOOL_SUPPLEMENT.format(cwd=sdk_cwd)
)
)
# Process transcript download result
@@ -980,7 +1023,7 @@ async def stream_chat_completion_sdk(
)
if is_valid:
# Load previous FULL context into builder
transcript_builder.load_previous(dl.content)
transcript_builder.load_previous(dl.content, log_prefix=log_prefix)
resume_file = write_transcript_to_tempfile(
dl.content, session_id, sdk_cwd
)
@@ -1130,8 +1173,9 @@ async def stream_chat_completion_sdk(
transcript_builder.add_user_message(content=content_blocks)
else:
await client.query(query_message, session_id=session_id)
# Capture user message in transcript (text only)
transcript_builder.add_user_message(content=query_message)
# Capture actual user message in transcript (not the engineered query)
# query_message may include context wrappers, but transcript needs raw input
transcript_builder.add_user_message(content=current_message)
assistant_response = ChatMessage(role="assistant", content="")
accumulated_tool_calls: list[dict[str, Any]] = []
@@ -1209,7 +1253,7 @@ async def stream_chat_completion_sdk(
len(adapter.resolved_tool_calls),
)
# Capture AssistantMessage in transcript
# Capture SDK messages in transcript
if isinstance(sdk_msg, AssistantMessage):
content_blocks = _format_sdk_content_blocks(sdk_msg.content)
model_name = getattr(sdk_msg, "model", "")
@@ -1348,17 +1392,28 @@ async def stream_chat_completion_sdk(
has_appended_assistant = True
elif isinstance(response, StreamToolOutputAvailable):
tool_result_content = (
response.output
if isinstance(response.output, str)
else str(response.output)
)
session.messages.append(
ChatMessage(
role="tool",
content=(
response.output
if isinstance(response.output, str)
else str(response.output)
),
content=tool_result_content,
tool_call_id=response.toolCallId,
)
)
# Capture tool result in transcript as user message with tool_result content
transcript_builder.add_user_message(
content=[
{
"type": "tool_result",
"tool_use_id": response.toolCallId,
"content": tool_result_content,
}
]
)
has_tool_results = True
elif isinstance(response, StreamFinish):
@@ -1554,8 +1609,10 @@ async def stream_chat_completion_sdk(
transcript_builder.entry_count,
len(transcript_content),
)
# Create task first so we have a reference if timeout occurs
upload_task = asyncio.create_task(
# Shield upload from cancellation - let it complete even if
# the finally block is interrupted. No timeout to avoid race
# conditions where backgrounded uploads overwrite newer transcripts.
await asyncio.shield(
upload_transcript(
user_id=user_id,
session_id=session_id,
@@ -1564,19 +1621,6 @@ async def stream_chat_completion_sdk(
log_prefix=log_prefix,
)
)
try:
async with asyncio.timeout(30):
await asyncio.shield(upload_task)
except TimeoutError:
# Timeout fired but shield keeps upload running - track the
# SAME task to prevent garbage collection (no double upload)
logger.warning(
"%s Transcript upload exceeded 30s timeout, "
"continuing in background",
log_prefix,
)
_background_tasks.add(upload_task)
upload_task.add_done_callback(_background_tasks.discard)
except Exception as upload_err:
logger.error(
"%s Transcript upload failed in finally: %s",
@@ -1601,7 +1645,7 @@ async def _update_title_async(
message, user_id=user_id, session_id=session_id
)
if title and user_id:
await update_session_title(session_id, user_id, title, only_if_empty=True)
await update_session_title(session_id, title)
logger.debug(f"[SDK] Generated title for {session_id}: {title}")
except Exception as e:
logger.warning(f"[SDK] Failed to update session title: {e}")

View File

@@ -7,7 +7,7 @@ from unittest.mock import AsyncMock, patch
import pytest
from .service import _prepare_file_attachments
from .service import _generate_tool_documentation, _prepare_file_attachments
@dataclass
@@ -145,3 +145,94 @@ class TestPrepareFileAttachments:
assert "Read tool" not in result.hint
assert len(result.image_blocks) == 1
class TestGenerateToolDocumentation:
"""Tests for auto-generated tool documentation from TOOL_REGISTRY."""
def test_generate_tool_documentation_structure(self):
"""Test that tool documentation has expected structure."""
docs = _generate_tool_documentation()
# Check main sections exist
assert "## AVAILABLE TOOLS" in docs
assert "## KEY WORKFLOWS" in docs
# Verify no duplicate sections
assert docs.count("## AVAILABLE TOOLS") == 1
assert docs.count("## KEY WORKFLOWS") == 1
def test_tool_documentation_includes_key_tools(self):
"""Test that documentation includes essential copilot tools."""
docs = _generate_tool_documentation()
# Core agent workflow tools
assert "`create_agent`" in docs
assert "`run_agent`" in docs
assert "`find_library_agent`" in docs
assert "`edit_agent`" in docs
# MCP integration
assert "`run_mcp_tool`" in docs
# Browser automation
assert "`browser_navigate`" in docs
# Folder management
assert "`create_folder`" in docs
def test_tool_documentation_format(self):
"""Test that each tool follows bullet list format."""
docs = _generate_tool_documentation()
lines = docs.split("\n")
tool_lines = [line for line in lines if line.strip().startswith("- **`")]
# Should have multiple tools (at least 20 from TOOL_REGISTRY)
assert len(tool_lines) >= 20
# Each tool line should have proper markdown format
for line in tool_lines:
assert line.startswith("- **`"), f"Bad format: {line}"
assert "`**:" in line, f"Missing description separator: {line}"
def test_tool_documentation_includes_workflows(self):
"""Test that key workflow patterns are documented."""
docs = _generate_tool_documentation()
# Check workflow sections
assert "MCP Integration Workflow" in docs
assert "Agent Creation Workflow" in docs
assert "Folder Management" in docs
# Check workflow details
assert "suggested_goal" in docs # Agent creation feedback loop
assert "clarifying_questions" in docs # Agent creation feedback loop
assert "run_mcp_tool(server_url)" in docs # MCP discovery pattern
def test_tool_documentation_completeness(self):
"""Test that all tools from TOOL_REGISTRY appear in documentation."""
from backend.copilot.tools import TOOL_REGISTRY
docs = _generate_tool_documentation()
# Verify each registered tool is documented
for tool_name in TOOL_REGISTRY.keys():
assert (
f"`{tool_name}`" in docs
), f"Tool '{tool_name}' missing from auto-generated documentation"
def test_tool_documentation_no_duplicate_tools(self):
"""Test that no tool appears multiple times in the list."""
from backend.copilot.tools import TOOL_REGISTRY
docs = _generate_tool_documentation()
# Extract the tools section (before KEY WORKFLOWS)
tools_section = docs.split("## KEY WORKFLOWS")[0]
# Count occurrences of each tool
for tool_name in TOOL_REGISTRY.keys():
# Count how many times this tool appears as a bullet point
count = tools_section.count(f"- **`{tool_name}`**")
assert count == 1, f"Tool '{tool_name}' appears {count} times (should be 1)"

View File

@@ -10,13 +10,14 @@ Storage is handled via ``WorkspaceStorageBackend`` (GCS in prod, local
filesystem for self-hosted) — no DB column needed.
"""
import json
import logging
import os
import re
import time
from dataclasses import dataclass
from backend.util import json
logger = logging.getLogger(__name__)
# UUIDs are hex + hyphens; strip everything else to prevent path injection.
@@ -68,17 +69,14 @@ def strip_progress_entries(content: str) -> str:
# Parse entries, keeping the original line alongside the parsed dict.
parsed: list[tuple[str, dict | None]] = []
for line in lines:
try:
parsed.append((line, json.loads(line)))
except json.JSONDecodeError:
parsed.append((line, None))
parsed.append((line, json.loads(line, fallback=None)))
# First pass: identify stripped UUIDs and build parent map.
stripped_uuids: set[str] = set()
uuid_to_parent: dict[str, str] = {}
for _line, entry in parsed:
if entry is None:
if not isinstance(entry, dict):
continue
uid = entry.get("uuid", "")
parent = entry.get("parentUuid", "")
@@ -91,7 +89,7 @@ def strip_progress_entries(content: str) -> str:
# Preserve original line when no reparenting is required.
reparented: set[str] = set()
for _line, entry in parsed:
if entry is None:
if not isinstance(entry, dict):
continue
parent = entry.get("parentUuid", "")
original_parent = parent
@@ -105,7 +103,7 @@ def strip_progress_entries(content: str) -> str:
result_lines: list[str] = []
for line, entry in parsed:
if entry is None:
if not isinstance(entry, dict):
result_lines.append(line)
continue
if entry.get("type", "") in STRIPPABLE_TYPES:
@@ -225,12 +223,11 @@ def validate_transcript(content: str | None) -> bool:
for line in lines:
if not line.strip():
continue
try:
entry = json.loads(line)
if entry.get("type") == "assistant":
has_assistant = True
except json.JSONDecodeError:
entry = json.loads(line, fallback=None)
if not isinstance(entry, dict):
return False
if entry.get("type") == "assistant":
has_assistant = True
return has_assistant
@@ -310,10 +307,8 @@ async def upload_transcript(
# Log entry types for debugging — helps identify why validation failed
entry_types: list[str] = []
for line in stripped.strip().split("\n"):
try:
entry_types.append(json.loads(line).get("type", "?"))
except json.JSONDecodeError:
entry_types.append("INVALID_JSON")
entry = json.loads(line, fallback={"type": "INVALID_JSON"})
entry_types.append(entry.get("type", "?"))
logger.warning(
"%s Skipping upload — stripped content not valid "
"(types=%s, stripped_len=%d, raw_len=%d)",
@@ -396,10 +391,10 @@ async def download_transcript(
meta_path = f"local://{mwid}/{mfid}/{mfname}"
meta_data = await storage.retrieve(meta_path)
meta = json.loads(meta_data.decode("utf-8"))
meta = json.loads(meta_data.decode("utf-8"), fallback={})
message_count = meta.get("message_count", 0)
uploaded_at = meta.get("uploaded_at", 0.0)
except (FileNotFoundError, json.JSONDecodeError, Exception):
except (FileNotFoundError, Exception):
pass # No metadata — treat as unknown (msg_count=0 → always fill gap)
logger.info(f"{log_prefix} Downloaded {len(content)}B (msg_count={message_count})")

View File

@@ -11,13 +11,16 @@ Flow:
The transcript is never incremental - always the complete atomic state.
"""
import json
import logging
from typing import Any
from uuid import uuid4
from pydantic import BaseModel
from backend.util import json
from .transcript import STRIPPABLE_TYPES
logger = logging.getLogger(__name__)
@@ -41,7 +44,7 @@ class TranscriptBuilder:
self._entries: list[TranscriptEntry] = []
self._last_uuid: str | None = None
def load_previous(self, content: str) -> None:
def load_previous(self, content: str, log_prefix: str = "[Transcript]") -> None:
"""Load complete previous transcript.
This loads the FULL previous context. As new messages come in,
@@ -51,19 +54,25 @@ class TranscriptBuilder:
if not content or not content.strip():
return
for line in content.strip().split("\n"):
lines = content.strip().split("\n")
for line_num, line in enumerate(lines, 1):
if not line.strip():
continue
try:
data = json.loads(line)
except json.JSONDecodeError:
logger.warning("Failed to parse transcript line: %s", line[:100])
data = json.loads(line, fallback=None)
if data is None:
logger.warning(
"%s Failed to parse transcript line %d/%d",
log_prefix,
line_num,
len(lines),
)
continue
# Only load conversation messages (user/assistant)
# Skip metadata entries
if data.get("type") not in ("user", "assistant"):
# Load all non-strippable entries (user/assistant/system/etc.)
# Skip only STRIPPABLE_TYPES to match strip_progress_entries() behavior
entry_type = data.get("type", "")
if entry_type in STRIPPABLE_TYPES:
continue
entry = TranscriptEntry(
@@ -76,7 +85,8 @@ class TranscriptBuilder:
self._last_uuid = entry.uuid
logger.info(
"Loaded %d entries from previous transcript (last_uuid=%s)",
"%s Loaded %d entries from previous transcript (last_uuid=%s)",
log_prefix,
len(self._entries),
self._last_uuid[:12] if self._last_uuid else None,
)

View File

@@ -1,8 +1,9 @@
"""Unit tests for JSONL transcript management utilities."""
import json
import os
from backend.util import json
from .transcript import (
STRIPPABLE_TYPES,
strip_progress_entries,
@@ -256,10 +257,9 @@ class TestStripProgressEntries:
def test_preserves_original_line_formatting(self):
"""Non-reparented entries keep their original JSON formatting."""
# Use pretty-printed JSON with spaces (as the CLI produces)
original_line = json.dumps(USER_MSG) # default formatting with spaces
compact_line = json.dumps(USER_MSG, separators=(",", ":"))
assert original_line != compact_line # precondition
# orjson produces compact JSON - test that we preserve the exact input
# when no reparenting is needed (no re-serialization)
original_line = json.dumps(USER_MSG)
content = original_line + "\n" + json.dumps(ASST_MSG) + "\n"
result = strip_progress_entries(content)

View File

@@ -34,8 +34,9 @@ client = LangfuseAsyncOpenAI(api_key=config.api_key, base_url=config.base_url)
langfuse = get_client()
# Default system prompt used when Langfuse is not configured
# This is a snapshot of the "CoPilot Prompt" from Langfuse (version 11)
DEFAULT_SYSTEM_PROMPT = """You are **Otto**, an AI Co-Pilot for AutoGPT and a Forward-Deployed Automation Engineer serving small business owners. Your mission is to help users automate business tasks with AI by delivering tangible value through working automations—not through documentation or lengthy explanations.
# Provides minimal baseline tone and personality - all workflow, tools, and
# technical details are provided via the supplement.
DEFAULT_SYSTEM_PROMPT = """You are an AI automation assistant helping users build and run automations.
Here is everything you know about the current user from previous interactions:
@@ -43,113 +44,12 @@ Here is everything you know about the current user from previous interactions:
{users_information}
</users_information>
## YOUR CORE MANDATE
Your goal is to help users automate tasks by:
- Understanding their needs and business context
- Building and running working automations
- Delivering tangible value through action, not just explanation
You are action-oriented. Your success is measured by:
- **Value Delivery**: Does the user think "wow, that was amazing" or "what was the point"?
- **Demonstrable Proof**: Show working automations, not descriptions of what's possible
- **Time Saved**: Focus on tangible efficiency gains
- **Quality Output**: Deliver results that meet or exceed expectations
## YOUR WORKFLOW
Adapt flexibly to the conversation context. Not every interaction requires all stages:
1. **Explore & Understand**: Learn about the user's business, tasks, and goals. Use `add_understanding` to capture important context that will improve future conversations.
2. **Assess Automation Potential**: Help the user understand whether and how AI can automate their task.
3. **Prepare for AI**: Provide brief, actionable guidance on prerequisites (data, access, etc.).
4. **Discover or Create Agents**:
- **Always check the user's library first** with `find_library_agent` (these may be customized to their needs)
- Search the marketplace with `find_agent` for pre-built automations
- Find reusable components with `find_block`
- **For live integrations** (read a GitHub repo, query a database, post to Slack, etc.) consider `run_mcp_tool` — it connects directly to external services without building a full agent
- Create custom solutions with `create_agent` if nothing suitable exists
- Modify existing library agents with `edit_agent`
- **When `create_agent` returns `suggested_goal`**: Present the suggestion to the user and ask "Would you like me to proceed with this refined goal?" If they accept, call `create_agent` again with the suggested goal.
- **When `create_agent` returns `clarifying_questions`**: After the user answers, call `create_agent` again with the original description AND the answers in the `context` parameter.
5. **Execute**: Run automations immediately, schedule them, or set up webhooks using `run_agent`. Test specific components with `run_block`.
6. **Show Results**: Display outputs using `agent_output`.
## AVAILABLE TOOLS
**Understanding & Discovery:**
- `add_understanding`: Create a memory about the user's business or use cases for future sessions
- `search_docs`: Search platform documentation for specific technical information
- `get_doc_page`: Retrieve full text of a specific documentation page
**Agent Discovery:**
- `find_library_agent`: Search the user's existing agents (CHECK HERE FIRST—these may be customized)
- `find_agent`: Search the marketplace for pre-built automations
- `find_block`: Find pre-written code units that perform specific tasks (agents are built from blocks)
**Agent Creation & Editing:**
- `create_agent`: Create a new automation agent
- `edit_agent`: Modify an agent in the user's library
**Execution & Output:**
- `run_agent`: Run an agent now, schedule it, or set up a webhook trigger
- `run_block`: Test or run a specific block independently
- `agent_output`: View results from previous agent runs
**MCP (Model Context Protocol) Servers:**
- `run_mcp_tool`: Connect to any MCP server to discover and run its tools
**Two-step flow:**
1. `run_mcp_tool(server_url)` → returns a list of available tools. Each tool has `name`, `description`, and `input_schema` (JSON Schema). Read `input_schema.properties` to understand what arguments are needed.
2. `run_mcp_tool(server_url, tool_name, tool_arguments)` → executes the tool. Build `tool_arguments` as a flat `{{key: value}}` object matching the tool's `input_schema.properties`.
**Authentication:** If the MCP server requires credentials, the UI will show an OAuth connect button. Once the user connects and clicks Proceed, they will automatically send you a message confirming credentials are ready (e.g. "I've connected the MCP server credentials. Please retry run_mcp_tool..."). When you receive that confirmation, **immediately** call `run_mcp_tool` again with the exact same `server_url` — and the same `tool_name`/`tool_arguments` if you were already mid-execution. Do not ask the user what to do next; just retry.
**Finding server URLs (fastest → slowest):**
1. **Known hosted servers** — use directly, no lookup:
- Notion: `https://mcp.notion.com/mcp`
- Linear: `https://mcp.linear.app/mcp`
- Stripe: `https://mcp.stripe.com`
- Intercom: `https://mcp.intercom.com/mcp`
- Cloudflare: `https://mcp.cloudflare.com/mcp`
- Atlassian (Jira/Confluence): `https://mcp.atlassian.com/mcp`
2. **`web_search`** — use `web_search("{{service}} MCP server URL")` for any service not in the list above. This is the fastest way to find unlisted servers.
3. **Registry API** — `web_fetch("https://registry.modelcontextprotocol.io/v0.1/servers?search={{query}}&limit=10")` to browse what's available. Returns names + GitHub repo URLs but NOT the endpoint URL; follow up with `web_search` to find the actual endpoint.
- **Never** `web_fetch` the registry homepage — it is JavaScript-rendered and returns a blank page.
**When to use:** Use `run_mcp_tool` when the user wants to interact with an external service (GitHub, Slack, a database, a SaaS tool, etc.) via its MCP integration. Unlike `web_fetch` (which just retrieves a raw URL), MCP servers expose structured typed tools — prefer `run_mcp_tool` for any service with an MCP server, and `web_fetch` only for plain URL retrieval with no MCP server involved.
**CRITICAL**: `run_mcp_tool` is **always available** in your tool list. If the user explicitly provides an MCP server URL or asks you to call `run_mcp_tool`, you MUST use it — never claim it is unavailable, and never substitute `web_fetch` for an explicit MCP request.
## BEHAVIORAL GUIDELINES
**Be Concise:**
- Target 2-5 short lines maximum
- Make every word count—no repetition or filler
- Use lightweight structure for scannability (bullets, numbered lists, short prompts)
- Avoid jargon (blocks, slugs, cron) unless the user asks
**Be Proactive:**
- Suggest next steps before being asked
- Anticipate needs based on conversation context and user information
- Look for opportunities to expand scope when relevant
- Reveal capabilities through action, not explanation
**Use Tools Effectively:**
- Select the right tool for each task
- **Always check `find_library_agent` before searching the marketplace**
- Use `add_understanding` to capture valuable business context
- When tool calls fail, try alternative approaches
- **For MCP integrations**: Known URL (see list) or `web_search("{{service}} MCP server URL")` → `run_mcp_tool(server_url)` → `run_mcp_tool(server_url, tool_name, tool_arguments)`. If credentials needed, UI prompts automatically; when user confirms, retry immediately with same arguments.
**Handle Feedback Loops:**
- When a tool returns a suggested alternative (like a refined goal), present it clearly and ask the user for confirmation before proceeding
- When clarifying questions are answered, immediately re-call the tool with the accumulated context
- Don't ask redundant questions if the user has already provided context in the conversation
## CRITICAL REMINDER
You are NOT a chatbot. You are NOT documentation. You are a partner who helps busy business owners get value quickly by showing proof through working automations. Bias toward action over explanation."""
Be concise, proactive, and action-oriented. Bias toward showing working solutions over lengthy explanations."""
# ---------------------------------------------------------------------------

View File

@@ -81,7 +81,6 @@ MODEL_COST: dict[LlmModel, int] = {
LlmModel.CLAUDE_4_OPUS: 21,
LlmModel.CLAUDE_4_SONNET: 5,
LlmModel.CLAUDE_4_6_OPUS: 14,
LlmModel.CLAUDE_4_6_SONNET: 9,
LlmModel.CLAUDE_4_5_HAIKU: 4,
LlmModel.CLAUDE_4_5_OPUS: 14,
LlmModel.CLAUDE_4_5_SONNET: 9,

View File

@@ -305,7 +305,6 @@ class DatabaseManager(AppService):
delete_chat_session = _(chat_db.delete_chat_session)
get_next_sequence = _(chat_db.get_next_sequence)
update_tool_message_content = _(chat_db.update_tool_message_content)
update_chat_session_title = _(chat_db.update_chat_session_title)
class DatabaseManagerClient(AppServiceClient):
@@ -476,4 +475,3 @@ class DatabaseManagerAsyncClient(AppServiceClient):
delete_chat_session = d.delete_chat_session
get_next_sequence = d.get_next_sequence
update_tool_message_content = d.update_tool_message_content
update_chat_session_title = d.update_chat_session_title

View File

@@ -184,17 +184,17 @@ async def find_webhook_by_credentials_and_props(
credentials_id: str,
webhook_type: str,
resource: str,
events: list[str] | None = None,
events: Optional[list[str]],
) -> Webhook | None:
where: IntegrationWebhookWhereInput = {
"userId": user_id,
"credentialsId": credentials_id,
"webhookType": webhook_type,
"resource": resource,
}
if events is not None:
where["events"] = {"has_every": events}
webhook = await IntegrationWebhook.prisma().find_first(where=where)
webhook = await IntegrationWebhook.prisma().find_first(
where={
"userId": user_id,
"credentialsId": credentials_id,
"webhookType": webhook_type,
"resource": resource,
**({"events": {"has_every": events}} if events else {}),
},
)
return Webhook.from_db(webhook) if webhook else None

View File

@@ -15,6 +15,7 @@ from backend.data import graph as graph_db
from backend.data import human_review as human_review_db
from backend.data import onboarding as onboarding_db
from backend.data import user as user_db
from backend.data import workspace as workspace_db
# Import dynamic field utilities from centralized location
from backend.data.block import BlockInput, BlockOutputEntry
@@ -32,7 +33,6 @@ from backend.data.execution import (
from backend.data.graph import GraphModel, Node
from backend.data.model import USER_TIMEZONE_NOT_SET, CredentialsMetaInput, GraphInput
from backend.data.rabbitmq import Exchange, ExchangeType, Queue, RabbitMQConfig
from backend.data.workspace import get_or_create_workspace
from backend.util.clients import (
get_async_execution_event_bus,
get_async_execution_queue,
@@ -831,8 +831,9 @@ async def add_graph_execution(
udb = user_db
gdb = graph_db
odb = onboarding_db
wdb = workspace_db
else:
edb = udb = gdb = odb = get_database_manager_async_client()
edb = udb = gdb = odb = wdb = get_database_manager_async_client()
# Get or create the graph execution
if graph_exec_id:
@@ -892,7 +893,7 @@ async def add_graph_execution(
if execution_context is None:
user = await udb.get_user_by_id(user_id)
settings = await gdb.get_graph_settings(user_id=user_id, graph_id=graph_id)
workspace = await get_or_create_workspace(user_id)
workspace = await wdb.get_or_create_workspace(user_id)
execution_context = ExecutionContext(
# Execution identity

View File

@@ -368,12 +368,10 @@ async def test_add_graph_execution_is_repeatable(mocker: MockerFixture):
mock_get_event_bus = mocker.patch(
"backend.executor.utils.get_async_execution_event_bus"
)
mock_wdb = mocker.patch("backend.executor.utils.workspace_db")
mock_workspace = mocker.MagicMock()
mock_workspace.id = "test-workspace-id"
mocker.patch(
"backend.executor.utils.get_or_create_workspace",
new=mocker.AsyncMock(return_value=mock_workspace),
)
mock_wdb.get_or_create_workspace = mocker.AsyncMock(return_value=mock_workspace)
# Setup mock returns
# The function returns (graph, starting_nodes_input, compiled_nodes_input_masks, nodes_to_skip)
@@ -649,12 +647,10 @@ async def test_add_graph_execution_with_nodes_to_skip(mocker: MockerFixture):
mock_get_event_bus = mocker.patch(
"backend.executor.utils.get_async_execution_event_bus"
)
mock_wdb = mocker.patch("backend.executor.utils.workspace_db")
mock_workspace = mocker.MagicMock()
mock_workspace.id = "test-workspace-id"
mocker.patch(
"backend.executor.utils.get_or_create_workspace",
new=mocker.AsyncMock(return_value=mock_workspace),
)
mock_wdb.get_or_create_workspace = mocker.AsyncMock(return_value=mock_workspace)
# Setup returns - include nodes_to_skip in the tuple
mock_validate.return_value = (

View File

@@ -76,6 +76,7 @@ class TelegramWebhooksManager(BaseWebhooksManager):
credentials_id=credentials.id,
webhook_type=webhook_type,
resource=resource,
events=None, # Ignore events for this lookup
):
# Re-register with Telegram using the same URL but new allowed_updates
ingress_url = webhook_ingress_url(self.PROVIDER_NAME, existing.id)
@@ -142,6 +143,10 @@ class TelegramWebhooksManager(BaseWebhooksManager):
elif "video" in message:
event_type = "message.video"
else:
logger.warning(
"Unknown Telegram webhook payload type; "
f"message.keys() = {message.keys()}"
)
event_type = "message.other"
elif "edited_message" in payload:
event_type = "message.edited_message"

View File

@@ -72,19 +72,58 @@ def dumps(
T = TypeVar("T")
@overload
def loads(data: str | bytes, *args, target_type: Type[T], **kwargs) -> T: ...
# Sentinel value to detect when fallback is not provided
_NO_FALLBACK = object()
@overload
def loads(data: str | bytes, *args, **kwargs) -> Any: ...
def loads(
data: str | bytes, *args, target_type: Type[T], fallback: T | None = None, **kwargs
) -> T:
pass
@overload
def loads(data: str | bytes, *args, fallback: Any = None, **kwargs) -> Any:
pass
def loads(
data: str | bytes, *args, target_type: Type[T] | None = None, **kwargs
data: str | bytes,
*args,
target_type: Type[T] | None = None,
fallback: Any = _NO_FALLBACK,
**kwargs,
) -> Any:
parsed = orjson.loads(data)
"""Parse JSON with optional fallback on decode errors.
Args:
data: JSON string or bytes to parse
target_type: Optional type to validate/cast result to
fallback: Value to return on JSONDecodeError. If not provided, raises.
**kwargs: Additional arguments (unused, for compatibility)
Returns:
Parsed JSON data, or fallback value if parsing fails
Raises:
orjson.JSONDecodeError: Only if fallback is not provided
Examples:
>>> loads('{"valid": "json"}')
{'valid': 'json'}
>>> loads('invalid json', fallback=None)
None
>>> loads('invalid json', fallback={})
{}
>>> loads('invalid json') # raises orjson.JSONDecodeError
"""
try:
parsed = orjson.loads(data)
except orjson.JSONDecodeError:
if fallback is not _NO_FALLBACK:
return fallback
raise
if target_type:
return type_match(parsed, target_type)

View File

@@ -3,7 +3,6 @@ import {
getGetV2ListSessionsQueryKey,
useDeleteV2DeleteSession,
useGetV2ListSessions,
usePatchV2UpdateSessionTitle,
} from "@/app/api/__generated__/endpoints/chat/chat";
import { Button } from "@/components/atoms/Button/Button";
import { LoadingSpinner } from "@/components/atoms/LoadingSpinner/LoadingSpinner";
@@ -18,6 +17,7 @@ import { toast } from "@/components/molecules/Toast/use-toast";
import {
Sidebar,
SidebarContent,
SidebarFooter,
SidebarHeader,
SidebarTrigger,
useSidebar,
@@ -25,9 +25,8 @@ import {
import { cn } from "@/lib/utils";
import { DotsThree, PlusCircleIcon, PlusIcon } from "@phosphor-icons/react";
import { useQueryClient } from "@tanstack/react-query";
import { AnimatePresence, motion } from "framer-motion";
import { motion } from "framer-motion";
import { parseAsString, useQueryState } from "nuqs";
import { useEffect, useRef, useState } from "react";
import { useCopilotUIStore } from "../../store";
import { DeleteChatDialog } from "../DeleteChatDialog/DeleteChatDialog";
@@ -66,39 +65,6 @@ export function ChatSidebar() {
},
});
const [editingSessionId, setEditingSessionId] = useState<string | null>(null);
const [editingTitle, setEditingTitle] = useState("");
const renameInputRef = useRef<HTMLInputElement>(null);
const renameCancelledRef = useRef(false);
const { mutate: renameSession } = usePatchV2UpdateSessionTitle({
mutation: {
onSuccess: () => {
queryClient.invalidateQueries({
queryKey: getGetV2ListSessionsQueryKey(),
});
setEditingSessionId(null);
},
onError: (error) => {
toast({
title: "Failed to rename chat",
description:
error instanceof Error ? error.message : "An error occurred",
variant: "destructive",
});
setEditingSessionId(null);
},
},
});
// Auto-focus the rename input when editing starts
useEffect(() => {
if (editingSessionId && renameInputRef.current) {
renameInputRef.current.focus();
renameInputRef.current.select();
}
}, [editingSessionId]);
const sessions =
sessionsResponse?.status === 200 ? sessionsResponse.data.sessions : [];
@@ -110,26 +76,6 @@ export function ChatSidebar() {
setSessionId(id);
}
function handleRenameClick(
e: React.MouseEvent,
id: string,
title: string | null | undefined,
) {
e.stopPropagation();
renameCancelledRef.current = false;
setEditingSessionId(id);
setEditingTitle(title || "");
}
function handleRenameSubmit(id: string) {
const trimmed = editingTitle.trim();
if (trimmed) {
renameSession({ sessionId: id, data: { title: trimmed } });
} else {
setEditingSessionId(null);
}
}
function handleDeleteClick(
e: React.MouseEvent,
id: string,
@@ -214,42 +160,29 @@ export function ChatSidebar() {
</motion.div>
</SidebarHeader>
)}
{!isCollapsed && (
<SidebarHeader className="shrink-0 px-4 pb-4 pt-4 shadow-[0_4px_6px_-1px_rgba(0,0,0,0.05)]">
<motion.div
initial={{ opacity: 0 }}
animate={{ opacity: 1 }}
transition={{ duration: 0.2, delay: 0.1 }}
className="flex flex-col gap-3 px-3"
>
<div className="flex items-center justify-between">
<Text variant="h3" size="body-medium">
Your chats
</Text>
<div className="relative left-6">
<SidebarTrigger />
</div>
</div>
<Button
variant="primary"
size="small"
onClick={handleNewChat}
className="w-full"
leftIcon={<PlusIcon className="h-4 w-4" weight="bold" />}
>
New Chat
</Button>
</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="flex flex-col gap-1"
className="mt-4 flex flex-col gap-1"
>
{isLoadingSessions ? (
<div className="flex min-h-[30rem] items-center justify-center py-4">
@@ -270,105 +203,76 @@ export function ChatSidebar() {
: "hover:bg-zinc-50",
)}
>
{editingSessionId === session.id ? (
<div className="px-3 py-2.5">
<input
ref={renameInputRef}
type="text"
aria-label="Rename chat"
value={editingTitle}
onChange={(e) => setEditingTitle(e.target.value)}
onKeyDown={(e) => {
if (e.key === "Enter") {
e.currentTarget.blur();
} else if (e.key === "Escape") {
renameCancelledRef.current = true;
setEditingSessionId(null);
}
}}
onBlur={() => {
if (renameCancelledRef.current) {
renameCancelledRef.current = false;
return;
}
handleRenameSubmit(session.id);
}}
className="w-full rounded border border-zinc-300 bg-white px-2 py-1 text-sm text-zinc-800 outline-none focus:border-purple-500 focus:ring-1 focus:ring-purple-500"
/>
</div>
) : (
<button
onClick={() => handleSelectSession(session.id)}
className="w-full px-3 py-2.5 pr-10 text-left"
>
<div className="flex min-w-0 max-w-full 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",
)}
>
<AnimatePresence mode="wait" initial={false}>
<motion.span
key={session.title || "untitled"}
initial={{ opacity: 0, y: 4 }}
animate={{ opacity: 1, y: 0 }}
exit={{ opacity: 0, y: -4 }}
transition={{ duration: 0.2 }}
className="block truncate"
>
{session.title || "Untitled chat"}
</motion.span>
</AnimatePresence>
</Text>
</div>
<Text variant="small" className="text-neutral-400">
{formatDate(session.updated_at)}
<button
onClick={() => handleSelectSession(session.id)}
className="w-full px-3 py-2.5 pr-10 text-left"
>
<div className="flex min-w-0 max-w-full 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>
</button>
)}
{editingSessionId !== session.id && (
<DropdownMenu>
<DropdownMenuTrigger asChild>
<button
onClick={(e) => e.stopPropagation()}
className="absolute right-2 top-1/2 -translate-y-1/2 rounded-full p-1.5 text-zinc-600 transition-all hover:bg-neutral-100"
aria-label="More actions"
>
<DotsThree className="h-4 w-4" />
</button>
</DropdownMenuTrigger>
<DropdownMenuContent align="end">
<DropdownMenuItem
onClick={(e) =>
handleRenameClick(e, session.id, session.title)
}
>
Rename
</DropdownMenuItem>
<DropdownMenuItem
onClick={(e) =>
handleDeleteClick(e, session.id, session.title)
}
disabled={isDeleting}
className="text-red-600 focus:bg-red-50 focus:text-red-600"
>
Delete chat
</DropdownMenuItem>
</DropdownMenuContent>
</DropdownMenu>
)}
<Text variant="small" className="text-neutral-400">
{formatDate(session.updated_at)}
</Text>
</div>
</button>
<DropdownMenu>
<DropdownMenuTrigger asChild>
<button
onClick={(e) => e.stopPropagation()}
className="absolute right-2 top-1/2 -translate-y-1/2 rounded-full p-1.5 text-zinc-600 transition-all hover:bg-neutral-100"
aria-label="More actions"
>
<DotsThree className="h-4 w-4" />
</button>
</DropdownMenuTrigger>
<DropdownMenuContent align="end">
<DropdownMenuItem
onClick={(e) =>
handleDeleteClick(e, session.id, session.title)
}
disabled={isDeleting}
className="text-red-600 focus:bg-red-50 focus:text-red-600"
>
Delete chat
</DropdownMenuItem>
</DropdownMenuContent>
</DropdownMenu>
</div>
))
)}
</motion.div>
)}
</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>
<DeleteChatDialog

View File

@@ -29,6 +29,7 @@ export function DeleteChatDialog({
}
},
}}
onClose={isDeleting ? undefined : onCancel}
>
<Dialog.Content>
<Text variant="body">

View File

@@ -71,17 +71,6 @@ export function MobileDrawer({
<X width="1rem" height="1rem" />
</Button>
</div>
<div className="mt-2">
<Button
variant="primary"
size="small"
onClick={onNewChat}
className="w-full"
leftIcon={<PlusIcon width="1rem" height="1rem" />}
>
New Chat
</Button>
</div>
</div>
<div
className={cn(
@@ -131,6 +120,19 @@ export function MobileDrawer({
))
)}
</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>

View File

@@ -2,7 +2,6 @@ import {
getGetV2ListSessionsQueryKey,
useDeleteV2DeleteSession,
useGetV2ListSessions,
type getV2ListSessionsResponse,
} from "@/app/api/__generated__/endpoints/chat/chat";
import { toast } from "@/components/molecules/Toast/use-toast";
import { useBreakpoint } from "@/lib/hooks/useBreakpoint";
@@ -16,9 +15,6 @@ import { useCopilotUIStore } from "./store";
import { useChatSession } from "./useChatSession";
import { useCopilotStream } from "./useCopilotStream";
const TITLE_POLL_INTERVAL_MS = 2_000;
const TITLE_POLL_MAX_ATTEMPTS = 5;
interface UploadedFile {
file_id: string;
name: string;
@@ -262,52 +258,6 @@ export function useCopilotPage() {
const sessions =
sessionsResponse?.status === 200 ? sessionsResponse.data.sessions : [];
// Start title polling when stream ends cleanly — sidebar title animates in
const titlePollRef = useRef<ReturnType<typeof setInterval>>();
const prevStatusRef = useRef(status);
useEffect(() => {
const prev = prevStatusRef.current;
prevStatusRef.current = status;
const wasActive = prev === "streaming" || prev === "submitted";
const isNowReady = status === "ready";
if (!wasActive || !isNowReady || !sessionId || isReconnecting) return;
queryClient.invalidateQueries({
queryKey: getGetV2ListSessionsQueryKey({ limit: 50 }),
});
const sid = sessionId;
let attempts = 0;
clearInterval(titlePollRef.current);
titlePollRef.current = setInterval(() => {
const data = queryClient.getQueryData<getV2ListSessionsResponse>(
getGetV2ListSessionsQueryKey({ limit: 50 }),
);
const hasTitle =
data?.status === 200 &&
data.data.sessions.some((s) => s.id === sid && s.title);
if (hasTitle || attempts >= TITLE_POLL_MAX_ATTEMPTS) {
clearInterval(titlePollRef.current);
titlePollRef.current = undefined;
return;
}
attempts += 1;
queryClient.invalidateQueries({
queryKey: getGetV2ListSessionsQueryKey({ limit: 50 }),
});
}, TITLE_POLL_INTERVAL_MS);
}, [status, sessionId, isReconnecting, queryClient]);
// Clean up polling on session change or unmount
useEffect(() => {
return () => {
clearInterval(titlePollRef.current);
titlePollRef.current = undefined;
};
}, [sessionId]);
// --- Mobile drawer handlers ---
function handleOpenDrawer() {
setDrawerOpen(true);

View File

@@ -53,8 +53,6 @@ export function getPaginationNextPageNumber(
if (!hasValidPaginationInfo(lastPage)) return undefined;
const { pagination } = lastPage.data;
if (!pagination) return undefined;
const hasMore =
pagination.current_page * pagination.page_size < pagination.total_items;
return hasMore ? pagination.current_page + 1 : undefined;

View File

@@ -1305,59 +1305,6 @@
}
}
},
"/api/chat/sessions/{session_id}/title": {
"patch": {
"tags": ["v2", "chat", "chat"],
"summary": "Update session title",
"description": "Update the title of a chat session.\n\nAllows the user to rename their chat session.\n\nArgs:\n session_id: The session ID to update.\n request: Request body containing the new title.\n user_id: The authenticated user's ID.\n\nReturns:\n dict: Status of the update.\n\nRaises:\n HTTPException: 404 if session not found or not owned by user.",
"operationId": "patchV2Update session title",
"security": [{ "HTTPBearerJWT": [] }],
"parameters": [
{
"name": "session_id",
"in": "path",
"required": true,
"schema": { "type": "string", "title": "Session Id" }
}
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/UpdateSessionTitleRequest"
}
}
}
},
"responses": {
"200": {
"description": "Successful Response",
"content": {
"application/json": {
"schema": {
"type": "object",
"additionalProperties": true,
"title": "Response Patchv2Update Session Title"
}
}
}
},
"401": {
"$ref": "#/components/responses/HTTP401NotAuthenticatedError"
},
"404": { "description": "Session not found or access denied" },
"422": {
"description": "Validation Error",
"content": {
"application/json": {
"schema": { "$ref": "#/components/schemas/HTTPValidationError" }
}
}
}
}
}
},
"/api/credits": {
"get": {
"tags": ["v1", "credits"],
@@ -13344,13 +13291,6 @@
"required": ["permissions"],
"title": "UpdatePermissionsRequest"
},
"UpdateSessionTitleRequest": {
"properties": { "title": { "type": "string", "title": "Title" } },
"type": "object",
"required": ["title"],
"title": "UpdateSessionTitleRequest",
"description": "Request model for updating a session's title."
},
"UpdateTimezoneRequest": {
"properties": {
"timezone": {

View File

@@ -183,7 +183,7 @@ body[data-google-picker-open="true"] [data-dialog-content] {
/* Streamdown external link dialog: "Open link" button */
[data-streamdown="link-safety-modal"] button:last-of-type {
color: white;
color: black;
}
/* CoPilot chat table styling — remove left/right borders, increase padding */

View File

@@ -7,9 +7,6 @@ import {
TooltipContent,
TooltipTrigger,
} from "@/components/atoms/Tooltip/BaseTooltip";
import { Button as AtomButton } from "@/components/atoms/Button/Button";
import { Text } from "@/components/atoms/Text/Text";
import { Dialog } from "@/components/molecules/Dialog/Dialog";
import { cn } from "@/lib/utils";
import { cjk } from "@streamdown/cjk";
import { code } from "@/lib/streamdown-code-plugin";
@@ -19,7 +16,6 @@ import type { UIMessage } from "ai";
import { ChevronLeftIcon, ChevronRightIcon } from "lucide-react";
import type { ComponentProps, HTMLAttributes, ReactElement } from "react";
import { createContext, memo, useContext, useEffect, useState } from "react";
import type { LinkSafetyModalProps } from "streamdown";
import { Streamdown } from "streamdown";
export type MessageProps = HTMLAttributes<HTMLDivElement> & {
@@ -311,46 +307,6 @@ function isSameOriginLink(url: string): boolean {
}
}
function ExternalLinkModal({
url,
isOpen,
onClose,
onConfirm,
}: LinkSafetyModalProps) {
return (
<Dialog
title="Open external link"
styling={{ maxWidth: "30rem", minWidth: "auto" }}
controlled={{
isOpen,
set: async (open) => {
if (!open) onClose();
},
}}
>
<Dialog.Content>
<Text variant="body">
You&apos;re about to visit an external website:
</Text>
<Text
variant="small"
className="mt-2 break-all rounded-md bg-neutral-100 p-3 font-mono"
>
{url}
</Text>
<Dialog.Footer>
<AtomButton variant="secondary" onClick={onClose}>
Cancel
</AtomButton>
<AtomButton variant="primary" onClick={onConfirm}>
Open link
</AtomButton>
</Dialog.Footer>
</Dialog.Content>
</Dialog>
);
}
export const MessageResponse = memo(
({ className, ...props }: MessageResponseProps) => (
<Streamdown
@@ -362,7 +318,6 @@ export const MessageResponse = memo(
linkSafety={{
enabled: true,
onLinkCheck: isSameOriginLink,
renderModal: (modalProps) => <ExternalLinkModal {...modalProps} />,
}}
{...props}
/>

View File

@@ -65,7 +65,7 @@ The result routes data to yes_output or no_output, enabling intelligent branchin
| condition | A plaintext English description of the condition to evaluate | str | Yes |
| yes_value | (Optional) Value to output if the condition is true. If not provided, input_value will be used. | Yes Value | No |
| no_value | (Optional) Value to output if the condition is false. If not provided, input_value will be used. | No Value | No |
| model | The language model to use for evaluating the condition. | "o3-mini" \| "o3-2025-04-16" \| "o1" \| "o1-mini" \| "gpt-5.2-2025-12-11" \| "gpt-5.1-2025-11-13" \| "gpt-5-2025-08-07" \| "gpt-5-mini-2025-08-07" \| "gpt-5-nano-2025-08-07" \| "gpt-5-chat-latest" \| "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "gpt-4o-mini" \| "gpt-4o" \| "gpt-4-turbo" \| "gpt-3.5-turbo" \| "claude-opus-4-1-20250805" \| "claude-opus-4-20250514" \| "claude-sonnet-4-20250514" \| "claude-opus-4-5-20251101" \| "claude-sonnet-4-5-20250929" \| "claude-haiku-4-5-20251001" \| "claude-opus-4-6" \| "claude-sonnet-4-6" \| "claude-3-haiku-20240307" \| "Qwen/Qwen2.5-72B-Instruct-Turbo" \| "nvidia/llama-3.1-nemotron-70b-instruct" \| "meta-llama/Llama-3.3-70B-Instruct-Turbo" \| "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo" \| "meta-llama/Llama-3.2-3B-Instruct-Turbo" \| "llama-3.3-70b-versatile" \| "llama-3.1-8b-instant" \| "llama3.3" \| "llama3.2" \| "llama3" \| "llama3.1:405b" \| "dolphin-mistral:latest" \| "openai/gpt-oss-120b" \| "openai/gpt-oss-20b" \| "google/gemini-2.5-pro-preview-03-25" \| "google/gemini-3-pro-preview" \| "google/gemini-2.5-flash" \| "google/gemini-2.0-flash-001" \| "google/gemini-2.5-flash-lite-preview-06-17" \| "google/gemini-2.0-flash-lite-001" \| "mistralai/mistral-nemo" \| "cohere/command-r-08-2024" \| "cohere/command-r-plus-08-2024" \| "deepseek/deepseek-chat" \| "deepseek/deepseek-r1-0528" \| "perplexity/sonar" \| "perplexity/sonar-pro" \| "perplexity/sonar-deep-research" \| "nousresearch/hermes-3-llama-3.1-405b" \| "nousresearch/hermes-3-llama-3.1-70b" \| "amazon/nova-lite-v1" \| "amazon/nova-micro-v1" \| "amazon/nova-pro-v1" \| "microsoft/wizardlm-2-8x22b" \| "gryphe/mythomax-l2-13b" \| "meta-llama/llama-4-scout" \| "meta-llama/llama-4-maverick" \| "x-ai/grok-4" \| "x-ai/grok-4-fast" \| "x-ai/grok-4.1-fast" \| "x-ai/grok-code-fast-1" \| "moonshotai/kimi-k2" \| "qwen/qwen3-235b-a22b-thinking-2507" \| "qwen/qwen3-coder" \| "Llama-4-Scout-17B-16E-Instruct-FP8" \| "Llama-4-Maverick-17B-128E-Instruct-FP8" \| "Llama-3.3-8B-Instruct" \| "Llama-3.3-70B-Instruct" \| "v0-1.5-md" \| "v0-1.5-lg" \| "v0-1.0-md" | No |
| model | The language model to use for evaluating the condition. | "o3-mini" \| "o3-2025-04-16" \| "o1" \| "o1-mini" \| "gpt-5.2-2025-12-11" \| "gpt-5.1-2025-11-13" \| "gpt-5-2025-08-07" \| "gpt-5-mini-2025-08-07" \| "gpt-5-nano-2025-08-07" \| "gpt-5-chat-latest" \| "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "gpt-4o-mini" \| "gpt-4o" \| "gpt-4-turbo" \| "gpt-3.5-turbo" \| "claude-opus-4-1-20250805" \| "claude-opus-4-20250514" \| "claude-sonnet-4-20250514" \| "claude-opus-4-5-20251101" \| "claude-sonnet-4-5-20250929" \| "claude-haiku-4-5-20251001" \| "claude-opus-4-6" \| "claude-3-haiku-20240307" \| "Qwen/Qwen2.5-72B-Instruct-Turbo" \| "nvidia/llama-3.1-nemotron-70b-instruct" \| "meta-llama/Llama-3.3-70B-Instruct-Turbo" \| "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo" \| "meta-llama/Llama-3.2-3B-Instruct-Turbo" \| "llama-3.3-70b-versatile" \| "llama-3.1-8b-instant" \| "llama3.3" \| "llama3.2" \| "llama3" \| "llama3.1:405b" \| "dolphin-mistral:latest" \| "openai/gpt-oss-120b" \| "openai/gpt-oss-20b" \| "google/gemini-2.5-pro-preview-03-25" \| "google/gemini-3-pro-preview" \| "google/gemini-2.5-flash" \| "google/gemini-2.0-flash-001" \| "google/gemini-2.5-flash-lite-preview-06-17" \| "google/gemini-2.0-flash-lite-001" \| "mistralai/mistral-nemo" \| "cohere/command-r-08-2024" \| "cohere/command-r-plus-08-2024" \| "deepseek/deepseek-chat" \| "deepseek/deepseek-r1-0528" \| "perplexity/sonar" \| "perplexity/sonar-pro" \| "perplexity/sonar-deep-research" \| "nousresearch/hermes-3-llama-3.1-405b" \| "nousresearch/hermes-3-llama-3.1-70b" \| "amazon/nova-lite-v1" \| "amazon/nova-micro-v1" \| "amazon/nova-pro-v1" \| "microsoft/wizardlm-2-8x22b" \| "gryphe/mythomax-l2-13b" \| "meta-llama/llama-4-scout" \| "meta-llama/llama-4-maverick" \| "x-ai/grok-4" \| "x-ai/grok-4-fast" \| "x-ai/grok-4.1-fast" \| "x-ai/grok-code-fast-1" \| "moonshotai/kimi-k2" \| "qwen/qwen3-235b-a22b-thinking-2507" \| "qwen/qwen3-coder" \| "Llama-4-Scout-17B-16E-Instruct-FP8" \| "Llama-4-Maverick-17B-128E-Instruct-FP8" \| "Llama-3.3-8B-Instruct" \| "Llama-3.3-70B-Instruct" \| "v0-1.5-md" \| "v0-1.5-lg" \| "v0-1.0-md" | No |
### Outputs
@@ -103,7 +103,7 @@ The block sends the entire conversation history to the chosen LLM, including sys
|-------|-------------|------|----------|
| prompt | The prompt to send to the language model. | str | No |
| messages | List of messages in the conversation. | List[Any] | Yes |
| model | The language model to use for the conversation. | "o3-mini" \| "o3-2025-04-16" \| "o1" \| "o1-mini" \| "gpt-5.2-2025-12-11" \| "gpt-5.1-2025-11-13" \| "gpt-5-2025-08-07" \| "gpt-5-mini-2025-08-07" \| "gpt-5-nano-2025-08-07" \| "gpt-5-chat-latest" \| "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "gpt-4o-mini" \| "gpt-4o" \| "gpt-4-turbo" \| "gpt-3.5-turbo" \| "claude-opus-4-1-20250805" \| "claude-opus-4-20250514" \| "claude-sonnet-4-20250514" \| "claude-opus-4-5-20251101" \| "claude-sonnet-4-5-20250929" \| "claude-haiku-4-5-20251001" \| "claude-opus-4-6" \| "claude-sonnet-4-6" \| "claude-3-haiku-20240307" \| "Qwen/Qwen2.5-72B-Instruct-Turbo" \| "nvidia/llama-3.1-nemotron-70b-instruct" \| "meta-llama/Llama-3.3-70B-Instruct-Turbo" \| "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo" \| "meta-llama/Llama-3.2-3B-Instruct-Turbo" \| "llama-3.3-70b-versatile" \| "llama-3.1-8b-instant" \| "llama3.3" \| "llama3.2" \| "llama3" \| "llama3.1:405b" \| "dolphin-mistral:latest" \| "openai/gpt-oss-120b" \| "openai/gpt-oss-20b" \| "google/gemini-2.5-pro-preview-03-25" \| "google/gemini-3-pro-preview" \| "google/gemini-2.5-flash" \| "google/gemini-2.0-flash-001" \| "google/gemini-2.5-flash-lite-preview-06-17" \| "google/gemini-2.0-flash-lite-001" \| "mistralai/mistral-nemo" \| "cohere/command-r-08-2024" \| "cohere/command-r-plus-08-2024" \| "deepseek/deepseek-chat" \| "deepseek/deepseek-r1-0528" \| "perplexity/sonar" \| "perplexity/sonar-pro" \| "perplexity/sonar-deep-research" \| "nousresearch/hermes-3-llama-3.1-405b" \| "nousresearch/hermes-3-llama-3.1-70b" \| "amazon/nova-lite-v1" \| "amazon/nova-micro-v1" \| "amazon/nova-pro-v1" \| "microsoft/wizardlm-2-8x22b" \| "gryphe/mythomax-l2-13b" \| "meta-llama/llama-4-scout" \| "meta-llama/llama-4-maverick" \| "x-ai/grok-4" \| "x-ai/grok-4-fast" \| "x-ai/grok-4.1-fast" \| "x-ai/grok-code-fast-1" \| "moonshotai/kimi-k2" \| "qwen/qwen3-235b-a22b-thinking-2507" \| "qwen/qwen3-coder" \| "Llama-4-Scout-17B-16E-Instruct-FP8" \| "Llama-4-Maverick-17B-128E-Instruct-FP8" \| "Llama-3.3-8B-Instruct" \| "Llama-3.3-70B-Instruct" \| "v0-1.5-md" \| "v0-1.5-lg" \| "v0-1.0-md" | No |
| model | The language model to use for the conversation. | "o3-mini" \| "o3-2025-04-16" \| "o1" \| "o1-mini" \| "gpt-5.2-2025-12-11" \| "gpt-5.1-2025-11-13" \| "gpt-5-2025-08-07" \| "gpt-5-mini-2025-08-07" \| "gpt-5-nano-2025-08-07" \| "gpt-5-chat-latest" \| "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "gpt-4o-mini" \| "gpt-4o" \| "gpt-4-turbo" \| "gpt-3.5-turbo" \| "claude-opus-4-1-20250805" \| "claude-opus-4-20250514" \| "claude-sonnet-4-20250514" \| "claude-opus-4-5-20251101" \| "claude-sonnet-4-5-20250929" \| "claude-haiku-4-5-20251001" \| "claude-opus-4-6" \| "claude-3-haiku-20240307" \| "Qwen/Qwen2.5-72B-Instruct-Turbo" \| "nvidia/llama-3.1-nemotron-70b-instruct" \| "meta-llama/Llama-3.3-70B-Instruct-Turbo" \| "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo" \| "meta-llama/Llama-3.2-3B-Instruct-Turbo" \| "llama-3.3-70b-versatile" \| "llama-3.1-8b-instant" \| "llama3.3" \| "llama3.2" \| "llama3" \| "llama3.1:405b" \| "dolphin-mistral:latest" \| "openai/gpt-oss-120b" \| "openai/gpt-oss-20b" \| "google/gemini-2.5-pro-preview-03-25" \| "google/gemini-3-pro-preview" \| "google/gemini-2.5-flash" \| "google/gemini-2.0-flash-001" \| "google/gemini-2.5-flash-lite-preview-06-17" \| "google/gemini-2.0-flash-lite-001" \| "mistralai/mistral-nemo" \| "cohere/command-r-08-2024" \| "cohere/command-r-plus-08-2024" \| "deepseek/deepseek-chat" \| "deepseek/deepseek-r1-0528" \| "perplexity/sonar" \| "perplexity/sonar-pro" \| "perplexity/sonar-deep-research" \| "nousresearch/hermes-3-llama-3.1-405b" \| "nousresearch/hermes-3-llama-3.1-70b" \| "amazon/nova-lite-v1" \| "amazon/nova-micro-v1" \| "amazon/nova-pro-v1" \| "microsoft/wizardlm-2-8x22b" \| "gryphe/mythomax-l2-13b" \| "meta-llama/llama-4-scout" \| "meta-llama/llama-4-maverick" \| "x-ai/grok-4" \| "x-ai/grok-4-fast" \| "x-ai/grok-4.1-fast" \| "x-ai/grok-code-fast-1" \| "moonshotai/kimi-k2" \| "qwen/qwen3-235b-a22b-thinking-2507" \| "qwen/qwen3-coder" \| "Llama-4-Scout-17B-16E-Instruct-FP8" \| "Llama-4-Maverick-17B-128E-Instruct-FP8" \| "Llama-3.3-8B-Instruct" \| "Llama-3.3-70B-Instruct" \| "v0-1.5-md" \| "v0-1.5-lg" \| "v0-1.0-md" | No |
| max_tokens | The maximum number of tokens to generate in the chat completion. | int | No |
| ollama_host | Ollama host for local models | str | No |
@@ -257,7 +257,7 @@ The block formulates a prompt based on the given focus or source data, sends it
|-------|-------------|------|----------|
| focus | The focus of the list to generate. | str | No |
| source_data | The data to generate the list from. | str | No |
| model | The language model to use for generating the list. | "o3-mini" \| "o3-2025-04-16" \| "o1" \| "o1-mini" \| "gpt-5.2-2025-12-11" \| "gpt-5.1-2025-11-13" \| "gpt-5-2025-08-07" \| "gpt-5-mini-2025-08-07" \| "gpt-5-nano-2025-08-07" \| "gpt-5-chat-latest" \| "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "gpt-4o-mini" \| "gpt-4o" \| "gpt-4-turbo" \| "gpt-3.5-turbo" \| "claude-opus-4-1-20250805" \| "claude-opus-4-20250514" \| "claude-sonnet-4-20250514" \| "claude-opus-4-5-20251101" \| "claude-sonnet-4-5-20250929" \| "claude-haiku-4-5-20251001" \| "claude-opus-4-6" \| "claude-sonnet-4-6" \| "claude-3-haiku-20240307" \| "Qwen/Qwen2.5-72B-Instruct-Turbo" \| "nvidia/llama-3.1-nemotron-70b-instruct" \| "meta-llama/Llama-3.3-70B-Instruct-Turbo" \| "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo" \| "meta-llama/Llama-3.2-3B-Instruct-Turbo" \| "llama-3.3-70b-versatile" \| "llama-3.1-8b-instant" \| "llama3.3" \| "llama3.2" \| "llama3" \| "llama3.1:405b" \| "dolphin-mistral:latest" \| "openai/gpt-oss-120b" \| "openai/gpt-oss-20b" \| "google/gemini-2.5-pro-preview-03-25" \| "google/gemini-3-pro-preview" \| "google/gemini-2.5-flash" \| "google/gemini-2.0-flash-001" \| "google/gemini-2.5-flash-lite-preview-06-17" \| "google/gemini-2.0-flash-lite-001" \| "mistralai/mistral-nemo" \| "cohere/command-r-08-2024" \| "cohere/command-r-plus-08-2024" \| "deepseek/deepseek-chat" \| "deepseek/deepseek-r1-0528" \| "perplexity/sonar" \| "perplexity/sonar-pro" \| "perplexity/sonar-deep-research" \| "nousresearch/hermes-3-llama-3.1-405b" \| "nousresearch/hermes-3-llama-3.1-70b" \| "amazon/nova-lite-v1" \| "amazon/nova-micro-v1" \| "amazon/nova-pro-v1" \| "microsoft/wizardlm-2-8x22b" \| "gryphe/mythomax-l2-13b" \| "meta-llama/llama-4-scout" \| "meta-llama/llama-4-maverick" \| "x-ai/grok-4" \| "x-ai/grok-4-fast" \| "x-ai/grok-4.1-fast" \| "x-ai/grok-code-fast-1" \| "moonshotai/kimi-k2" \| "qwen/qwen3-235b-a22b-thinking-2507" \| "qwen/qwen3-coder" \| "Llama-4-Scout-17B-16E-Instruct-FP8" \| "Llama-4-Maverick-17B-128E-Instruct-FP8" \| "Llama-3.3-8B-Instruct" \| "Llama-3.3-70B-Instruct" \| "v0-1.5-md" \| "v0-1.5-lg" \| "v0-1.0-md" | No |
| model | The language model to use for generating the list. | "o3-mini" \| "o3-2025-04-16" \| "o1" \| "o1-mini" \| "gpt-5.2-2025-12-11" \| "gpt-5.1-2025-11-13" \| "gpt-5-2025-08-07" \| "gpt-5-mini-2025-08-07" \| "gpt-5-nano-2025-08-07" \| "gpt-5-chat-latest" \| "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "gpt-4o-mini" \| "gpt-4o" \| "gpt-4-turbo" \| "gpt-3.5-turbo" \| "claude-opus-4-1-20250805" \| "claude-opus-4-20250514" \| "claude-sonnet-4-20250514" \| "claude-opus-4-5-20251101" \| "claude-sonnet-4-5-20250929" \| "claude-haiku-4-5-20251001" \| "claude-opus-4-6" \| "claude-3-haiku-20240307" \| "Qwen/Qwen2.5-72B-Instruct-Turbo" \| "nvidia/llama-3.1-nemotron-70b-instruct" \| "meta-llama/Llama-3.3-70B-Instruct-Turbo" \| "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo" \| "meta-llama/Llama-3.2-3B-Instruct-Turbo" \| "llama-3.3-70b-versatile" \| "llama-3.1-8b-instant" \| "llama3.3" \| "llama3.2" \| "llama3" \| "llama3.1:405b" \| "dolphin-mistral:latest" \| "openai/gpt-oss-120b" \| "openai/gpt-oss-20b" \| "google/gemini-2.5-pro-preview-03-25" \| "google/gemini-3-pro-preview" \| "google/gemini-2.5-flash" \| "google/gemini-2.0-flash-001" \| "google/gemini-2.5-flash-lite-preview-06-17" \| "google/gemini-2.0-flash-lite-001" \| "mistralai/mistral-nemo" \| "cohere/command-r-08-2024" \| "cohere/command-r-plus-08-2024" \| "deepseek/deepseek-chat" \| "deepseek/deepseek-r1-0528" \| "perplexity/sonar" \| "perplexity/sonar-pro" \| "perplexity/sonar-deep-research" \| "nousresearch/hermes-3-llama-3.1-405b" \| "nousresearch/hermes-3-llama-3.1-70b" \| "amazon/nova-lite-v1" \| "amazon/nova-micro-v1" \| "amazon/nova-pro-v1" \| "microsoft/wizardlm-2-8x22b" \| "gryphe/mythomax-l2-13b" \| "meta-llama/llama-4-scout" \| "meta-llama/llama-4-maverick" \| "x-ai/grok-4" \| "x-ai/grok-4-fast" \| "x-ai/grok-4.1-fast" \| "x-ai/grok-code-fast-1" \| "moonshotai/kimi-k2" \| "qwen/qwen3-235b-a22b-thinking-2507" \| "qwen/qwen3-coder" \| "Llama-4-Scout-17B-16E-Instruct-FP8" \| "Llama-4-Maverick-17B-128E-Instruct-FP8" \| "Llama-3.3-8B-Instruct" \| "Llama-3.3-70B-Instruct" \| "v0-1.5-md" \| "v0-1.5-lg" \| "v0-1.0-md" | No |
| max_retries | Maximum number of retries for generating a valid list. | int | No |
| force_json_output | Whether to force the LLM to produce a JSON-only response. This can increase the block's reliability, but may also reduce the quality of the response because it prohibits the LLM from reasoning before providing its JSON response. | bool | No |
| max_tokens | The maximum number of tokens to generate in the chat completion. | int | No |
@@ -424,7 +424,7 @@ The block sends the input prompt to a chosen LLM, along with any system prompts
| prompt | The prompt to send to the language model. | str | Yes |
| expected_format | Expected format of the response. If provided, the response will be validated against this format. The keys should be the expected fields in the response, and the values should be the description of the field. | Dict[str, str] | Yes |
| list_result | Whether the response should be a list of objects in the expected format. | bool | No |
| model | The language model to use for answering the prompt. | "o3-mini" \| "o3-2025-04-16" \| "o1" \| "o1-mini" \| "gpt-5.2-2025-12-11" \| "gpt-5.1-2025-11-13" \| "gpt-5-2025-08-07" \| "gpt-5-mini-2025-08-07" \| "gpt-5-nano-2025-08-07" \| "gpt-5-chat-latest" \| "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "gpt-4o-mini" \| "gpt-4o" \| "gpt-4-turbo" \| "gpt-3.5-turbo" \| "claude-opus-4-1-20250805" \| "claude-opus-4-20250514" \| "claude-sonnet-4-20250514" \| "claude-opus-4-5-20251101" \| "claude-sonnet-4-5-20250929" \| "claude-haiku-4-5-20251001" \| "claude-opus-4-6" \| "claude-sonnet-4-6" \| "claude-3-haiku-20240307" \| "Qwen/Qwen2.5-72B-Instruct-Turbo" \| "nvidia/llama-3.1-nemotron-70b-instruct" \| "meta-llama/Llama-3.3-70B-Instruct-Turbo" \| "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo" \| "meta-llama/Llama-3.2-3B-Instruct-Turbo" \| "llama-3.3-70b-versatile" \| "llama-3.1-8b-instant" \| "llama3.3" \| "llama3.2" \| "llama3" \| "llama3.1:405b" \| "dolphin-mistral:latest" \| "openai/gpt-oss-120b" \| "openai/gpt-oss-20b" \| "google/gemini-2.5-pro-preview-03-25" \| "google/gemini-3-pro-preview" \| "google/gemini-2.5-flash" \| "google/gemini-2.0-flash-001" \| "google/gemini-2.5-flash-lite-preview-06-17" \| "google/gemini-2.0-flash-lite-001" \| "mistralai/mistral-nemo" \| "cohere/command-r-08-2024" \| "cohere/command-r-plus-08-2024" \| "deepseek/deepseek-chat" \| "deepseek/deepseek-r1-0528" \| "perplexity/sonar" \| "perplexity/sonar-pro" \| "perplexity/sonar-deep-research" \| "nousresearch/hermes-3-llama-3.1-405b" \| "nousresearch/hermes-3-llama-3.1-70b" \| "amazon/nova-lite-v1" \| "amazon/nova-micro-v1" \| "amazon/nova-pro-v1" \| "microsoft/wizardlm-2-8x22b" \| "gryphe/mythomax-l2-13b" \| "meta-llama/llama-4-scout" \| "meta-llama/llama-4-maverick" \| "x-ai/grok-4" \| "x-ai/grok-4-fast" \| "x-ai/grok-4.1-fast" \| "x-ai/grok-code-fast-1" \| "moonshotai/kimi-k2" \| "qwen/qwen3-235b-a22b-thinking-2507" \| "qwen/qwen3-coder" \| "Llama-4-Scout-17B-16E-Instruct-FP8" \| "Llama-4-Maverick-17B-128E-Instruct-FP8" \| "Llama-3.3-8B-Instruct" \| "Llama-3.3-70B-Instruct" \| "v0-1.5-md" \| "v0-1.5-lg" \| "v0-1.0-md" | No |
| model | The language model to use for answering the prompt. | "o3-mini" \| "o3-2025-04-16" \| "o1" \| "o1-mini" \| "gpt-5.2-2025-12-11" \| "gpt-5.1-2025-11-13" \| "gpt-5-2025-08-07" \| "gpt-5-mini-2025-08-07" \| "gpt-5-nano-2025-08-07" \| "gpt-5-chat-latest" \| "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "gpt-4o-mini" \| "gpt-4o" \| "gpt-4-turbo" \| "gpt-3.5-turbo" \| "claude-opus-4-1-20250805" \| "claude-opus-4-20250514" \| "claude-sonnet-4-20250514" \| "claude-opus-4-5-20251101" \| "claude-sonnet-4-5-20250929" \| "claude-haiku-4-5-20251001" \| "claude-opus-4-6" \| "claude-3-haiku-20240307" \| "Qwen/Qwen2.5-72B-Instruct-Turbo" \| "nvidia/llama-3.1-nemotron-70b-instruct" \| "meta-llama/Llama-3.3-70B-Instruct-Turbo" \| "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo" \| "meta-llama/Llama-3.2-3B-Instruct-Turbo" \| "llama-3.3-70b-versatile" \| "llama-3.1-8b-instant" \| "llama3.3" \| "llama3.2" \| "llama3" \| "llama3.1:405b" \| "dolphin-mistral:latest" \| "openai/gpt-oss-120b" \| "openai/gpt-oss-20b" \| "google/gemini-2.5-pro-preview-03-25" \| "google/gemini-3-pro-preview" \| "google/gemini-2.5-flash" \| "google/gemini-2.0-flash-001" \| "google/gemini-2.5-flash-lite-preview-06-17" \| "google/gemini-2.0-flash-lite-001" \| "mistralai/mistral-nemo" \| "cohere/command-r-08-2024" \| "cohere/command-r-plus-08-2024" \| "deepseek/deepseek-chat" \| "deepseek/deepseek-r1-0528" \| "perplexity/sonar" \| "perplexity/sonar-pro" \| "perplexity/sonar-deep-research" \| "nousresearch/hermes-3-llama-3.1-405b" \| "nousresearch/hermes-3-llama-3.1-70b" \| "amazon/nova-lite-v1" \| "amazon/nova-micro-v1" \| "amazon/nova-pro-v1" \| "microsoft/wizardlm-2-8x22b" \| "gryphe/mythomax-l2-13b" \| "meta-llama/llama-4-scout" \| "meta-llama/llama-4-maverick" \| "x-ai/grok-4" \| "x-ai/grok-4-fast" \| "x-ai/grok-4.1-fast" \| "x-ai/grok-code-fast-1" \| "moonshotai/kimi-k2" \| "qwen/qwen3-235b-a22b-thinking-2507" \| "qwen/qwen3-coder" \| "Llama-4-Scout-17B-16E-Instruct-FP8" \| "Llama-4-Maverick-17B-128E-Instruct-FP8" \| "Llama-3.3-8B-Instruct" \| "Llama-3.3-70B-Instruct" \| "v0-1.5-md" \| "v0-1.5-lg" \| "v0-1.0-md" | No |
| force_json_output | Whether to force the LLM to produce a JSON-only response. This can increase the block's reliability, but may also reduce the quality of the response because it prohibits the LLM from reasoning before providing its JSON response. | bool | No |
| sys_prompt | The system prompt to provide additional context to the model. | str | No |
| conversation_history | The conversation history to provide context for the prompt. | List[Dict[str, Any]] | No |
@@ -464,7 +464,7 @@ The block sends the input prompt to a chosen LLM, processes the response, and re
| Input | Description | Type | Required |
|-------|-------------|------|----------|
| prompt | The prompt to send to the language model. You can use any of the {keys} from Prompt Values to fill in the prompt with values from the prompt values dictionary by putting them in curly braces. | str | Yes |
| model | The language model to use for answering the prompt. | "o3-mini" \| "o3-2025-04-16" \| "o1" \| "o1-mini" \| "gpt-5.2-2025-12-11" \| "gpt-5.1-2025-11-13" \| "gpt-5-2025-08-07" \| "gpt-5-mini-2025-08-07" \| "gpt-5-nano-2025-08-07" \| "gpt-5-chat-latest" \| "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "gpt-4o-mini" \| "gpt-4o" \| "gpt-4-turbo" \| "gpt-3.5-turbo" \| "claude-opus-4-1-20250805" \| "claude-opus-4-20250514" \| "claude-sonnet-4-20250514" \| "claude-opus-4-5-20251101" \| "claude-sonnet-4-5-20250929" \| "claude-haiku-4-5-20251001" \| "claude-opus-4-6" \| "claude-sonnet-4-6" \| "claude-3-haiku-20240307" \| "Qwen/Qwen2.5-72B-Instruct-Turbo" \| "nvidia/llama-3.1-nemotron-70b-instruct" \| "meta-llama/Llama-3.3-70B-Instruct-Turbo" \| "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo" \| "meta-llama/Llama-3.2-3B-Instruct-Turbo" \| "llama-3.3-70b-versatile" \| "llama-3.1-8b-instant" \| "llama3.3" \| "llama3.2" \| "llama3" \| "llama3.1:405b" \| "dolphin-mistral:latest" \| "openai/gpt-oss-120b" \| "openai/gpt-oss-20b" \| "google/gemini-2.5-pro-preview-03-25" \| "google/gemini-3-pro-preview" \| "google/gemini-2.5-flash" \| "google/gemini-2.0-flash-001" \| "google/gemini-2.5-flash-lite-preview-06-17" \| "google/gemini-2.0-flash-lite-001" \| "mistralai/mistral-nemo" \| "cohere/command-r-08-2024" \| "cohere/command-r-plus-08-2024" \| "deepseek/deepseek-chat" \| "deepseek/deepseek-r1-0528" \| "perplexity/sonar" \| "perplexity/sonar-pro" \| "perplexity/sonar-deep-research" \| "nousresearch/hermes-3-llama-3.1-405b" \| "nousresearch/hermes-3-llama-3.1-70b" \| "amazon/nova-lite-v1" \| "amazon/nova-micro-v1" \| "amazon/nova-pro-v1" \| "microsoft/wizardlm-2-8x22b" \| "gryphe/mythomax-l2-13b" \| "meta-llama/llama-4-scout" \| "meta-llama/llama-4-maverick" \| "x-ai/grok-4" \| "x-ai/grok-4-fast" \| "x-ai/grok-4.1-fast" \| "x-ai/grok-code-fast-1" \| "moonshotai/kimi-k2" \| "qwen/qwen3-235b-a22b-thinking-2507" \| "qwen/qwen3-coder" \| "Llama-4-Scout-17B-16E-Instruct-FP8" \| "Llama-4-Maverick-17B-128E-Instruct-FP8" \| "Llama-3.3-8B-Instruct" \| "Llama-3.3-70B-Instruct" \| "v0-1.5-md" \| "v0-1.5-lg" \| "v0-1.0-md" | No |
| model | The language model to use for answering the prompt. | "o3-mini" \| "o3-2025-04-16" \| "o1" \| "o1-mini" \| "gpt-5.2-2025-12-11" \| "gpt-5.1-2025-11-13" \| "gpt-5-2025-08-07" \| "gpt-5-mini-2025-08-07" \| "gpt-5-nano-2025-08-07" \| "gpt-5-chat-latest" \| "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "gpt-4o-mini" \| "gpt-4o" \| "gpt-4-turbo" \| "gpt-3.5-turbo" \| "claude-opus-4-1-20250805" \| "claude-opus-4-20250514" \| "claude-sonnet-4-20250514" \| "claude-opus-4-5-20251101" \| "claude-sonnet-4-5-20250929" \| "claude-haiku-4-5-20251001" \| "claude-opus-4-6" \| "claude-3-haiku-20240307" \| "Qwen/Qwen2.5-72B-Instruct-Turbo" \| "nvidia/llama-3.1-nemotron-70b-instruct" \| "meta-llama/Llama-3.3-70B-Instruct-Turbo" \| "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo" \| "meta-llama/Llama-3.2-3B-Instruct-Turbo" \| "llama-3.3-70b-versatile" \| "llama-3.1-8b-instant" \| "llama3.3" \| "llama3.2" \| "llama3" \| "llama3.1:405b" \| "dolphin-mistral:latest" \| "openai/gpt-oss-120b" \| "openai/gpt-oss-20b" \| "google/gemini-2.5-pro-preview-03-25" \| "google/gemini-3-pro-preview" \| "google/gemini-2.5-flash" \| "google/gemini-2.0-flash-001" \| "google/gemini-2.5-flash-lite-preview-06-17" \| "google/gemini-2.0-flash-lite-001" \| "mistralai/mistral-nemo" \| "cohere/command-r-08-2024" \| "cohere/command-r-plus-08-2024" \| "deepseek/deepseek-chat" \| "deepseek/deepseek-r1-0528" \| "perplexity/sonar" \| "perplexity/sonar-pro" \| "perplexity/sonar-deep-research" \| "nousresearch/hermes-3-llama-3.1-405b" \| "nousresearch/hermes-3-llama-3.1-70b" \| "amazon/nova-lite-v1" \| "amazon/nova-micro-v1" \| "amazon/nova-pro-v1" \| "microsoft/wizardlm-2-8x22b" \| "gryphe/mythomax-l2-13b" \| "meta-llama/llama-4-scout" \| "meta-llama/llama-4-maverick" \| "x-ai/grok-4" \| "x-ai/grok-4-fast" \| "x-ai/grok-4.1-fast" \| "x-ai/grok-code-fast-1" \| "moonshotai/kimi-k2" \| "qwen/qwen3-235b-a22b-thinking-2507" \| "qwen/qwen3-coder" \| "Llama-4-Scout-17B-16E-Instruct-FP8" \| "Llama-4-Maverick-17B-128E-Instruct-FP8" \| "Llama-3.3-8B-Instruct" \| "Llama-3.3-70B-Instruct" \| "v0-1.5-md" \| "v0-1.5-lg" \| "v0-1.0-md" | No |
| sys_prompt | The system prompt to provide additional context to the model. | str | No |
| retry | Number of times to retry the LLM call if the response does not match the expected format. | int | No |
| prompt_values | Values used to fill in the prompt. The values can be used in the prompt by putting them in a double curly braces, e.g. {{variable_name}}. | Dict[str, str] | No |
@@ -501,7 +501,7 @@ The block splits the input text into smaller chunks, sends each chunk to an LLM
| Input | Description | Type | Required |
|-------|-------------|------|----------|
| text | The text to summarize. | str | Yes |
| model | The language model to use for summarizing the text. | "o3-mini" \| "o3-2025-04-16" \| "o1" \| "o1-mini" \| "gpt-5.2-2025-12-11" \| "gpt-5.1-2025-11-13" \| "gpt-5-2025-08-07" \| "gpt-5-mini-2025-08-07" \| "gpt-5-nano-2025-08-07" \| "gpt-5-chat-latest" \| "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "gpt-4o-mini" \| "gpt-4o" \| "gpt-4-turbo" \| "gpt-3.5-turbo" \| "claude-opus-4-1-20250805" \| "claude-opus-4-20250514" \| "claude-sonnet-4-20250514" \| "claude-opus-4-5-20251101" \| "claude-sonnet-4-5-20250929" \| "claude-haiku-4-5-20251001" \| "claude-opus-4-6" \| "claude-sonnet-4-6" \| "claude-3-haiku-20240307" \| "Qwen/Qwen2.5-72B-Instruct-Turbo" \| "nvidia/llama-3.1-nemotron-70b-instruct" \| "meta-llama/Llama-3.3-70B-Instruct-Turbo" \| "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo" \| "meta-llama/Llama-3.2-3B-Instruct-Turbo" \| "llama-3.3-70b-versatile" \| "llama-3.1-8b-instant" \| "llama3.3" \| "llama3.2" \| "llama3" \| "llama3.1:405b" \| "dolphin-mistral:latest" \| "openai/gpt-oss-120b" \| "openai/gpt-oss-20b" \| "google/gemini-2.5-pro-preview-03-25" \| "google/gemini-3-pro-preview" \| "google/gemini-2.5-flash" \| "google/gemini-2.0-flash-001" \| "google/gemini-2.5-flash-lite-preview-06-17" \| "google/gemini-2.0-flash-lite-001" \| "mistralai/mistral-nemo" \| "cohere/command-r-08-2024" \| "cohere/command-r-plus-08-2024" \| "deepseek/deepseek-chat" \| "deepseek/deepseek-r1-0528" \| "perplexity/sonar" \| "perplexity/sonar-pro" \| "perplexity/sonar-deep-research" \| "nousresearch/hermes-3-llama-3.1-405b" \| "nousresearch/hermes-3-llama-3.1-70b" \| "amazon/nova-lite-v1" \| "amazon/nova-micro-v1" \| "amazon/nova-pro-v1" \| "microsoft/wizardlm-2-8x22b" \| "gryphe/mythomax-l2-13b" \| "meta-llama/llama-4-scout" \| "meta-llama/llama-4-maverick" \| "x-ai/grok-4" \| "x-ai/grok-4-fast" \| "x-ai/grok-4.1-fast" \| "x-ai/grok-code-fast-1" \| "moonshotai/kimi-k2" \| "qwen/qwen3-235b-a22b-thinking-2507" \| "qwen/qwen3-coder" \| "Llama-4-Scout-17B-16E-Instruct-FP8" \| "Llama-4-Maverick-17B-128E-Instruct-FP8" \| "Llama-3.3-8B-Instruct" \| "Llama-3.3-70B-Instruct" \| "v0-1.5-md" \| "v0-1.5-lg" \| "v0-1.0-md" | No |
| model | The language model to use for summarizing the text. | "o3-mini" \| "o3-2025-04-16" \| "o1" \| "o1-mini" \| "gpt-5.2-2025-12-11" \| "gpt-5.1-2025-11-13" \| "gpt-5-2025-08-07" \| "gpt-5-mini-2025-08-07" \| "gpt-5-nano-2025-08-07" \| "gpt-5-chat-latest" \| "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "gpt-4o-mini" \| "gpt-4o" \| "gpt-4-turbo" \| "gpt-3.5-turbo" \| "claude-opus-4-1-20250805" \| "claude-opus-4-20250514" \| "claude-sonnet-4-20250514" \| "claude-opus-4-5-20251101" \| "claude-sonnet-4-5-20250929" \| "claude-haiku-4-5-20251001" \| "claude-opus-4-6" \| "claude-3-haiku-20240307" \| "Qwen/Qwen2.5-72B-Instruct-Turbo" \| "nvidia/llama-3.1-nemotron-70b-instruct" \| "meta-llama/Llama-3.3-70B-Instruct-Turbo" \| "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo" \| "meta-llama/Llama-3.2-3B-Instruct-Turbo" \| "llama-3.3-70b-versatile" \| "llama-3.1-8b-instant" \| "llama3.3" \| "llama3.2" \| "llama3" \| "llama3.1:405b" \| "dolphin-mistral:latest" \| "openai/gpt-oss-120b" \| "openai/gpt-oss-20b" \| "google/gemini-2.5-pro-preview-03-25" \| "google/gemini-3-pro-preview" \| "google/gemini-2.5-flash" \| "google/gemini-2.0-flash-001" \| "google/gemini-2.5-flash-lite-preview-06-17" \| "google/gemini-2.0-flash-lite-001" \| "mistralai/mistral-nemo" \| "cohere/command-r-08-2024" \| "cohere/command-r-plus-08-2024" \| "deepseek/deepseek-chat" \| "deepseek/deepseek-r1-0528" \| "perplexity/sonar" \| "perplexity/sonar-pro" \| "perplexity/sonar-deep-research" \| "nousresearch/hermes-3-llama-3.1-405b" \| "nousresearch/hermes-3-llama-3.1-70b" \| "amazon/nova-lite-v1" \| "amazon/nova-micro-v1" \| "amazon/nova-pro-v1" \| "microsoft/wizardlm-2-8x22b" \| "gryphe/mythomax-l2-13b" \| "meta-llama/llama-4-scout" \| "meta-llama/llama-4-maverick" \| "x-ai/grok-4" \| "x-ai/grok-4-fast" \| "x-ai/grok-4.1-fast" \| "x-ai/grok-code-fast-1" \| "moonshotai/kimi-k2" \| "qwen/qwen3-235b-a22b-thinking-2507" \| "qwen/qwen3-coder" \| "Llama-4-Scout-17B-16E-Instruct-FP8" \| "Llama-4-Maverick-17B-128E-Instruct-FP8" \| "Llama-3.3-8B-Instruct" \| "Llama-3.3-70B-Instruct" \| "v0-1.5-md" \| "v0-1.5-lg" \| "v0-1.0-md" | No |
| focus | The topic to focus on in the summary | str | No |
| style | The style of the summary to generate. | "concise" \| "detailed" \| "bullet points" \| "numbered list" | No |
| max_tokens | The maximum number of tokens to generate in the chat completion. | int | No |
@@ -763,7 +763,7 @@ Configure agent_mode_max_iterations to control loop behavior: 0 for single decis
| Input | Description | Type | Required |
|-------|-------------|------|----------|
| prompt | The prompt to send to the language model. | str | Yes |
| model | The language model to use for answering the prompt. | "o3-mini" \| "o3-2025-04-16" \| "o1" \| "o1-mini" \| "gpt-5.2-2025-12-11" \| "gpt-5.1-2025-11-13" \| "gpt-5-2025-08-07" \| "gpt-5-mini-2025-08-07" \| "gpt-5-nano-2025-08-07" \| "gpt-5-chat-latest" \| "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "gpt-4o-mini" \| "gpt-4o" \| "gpt-4-turbo" \| "gpt-3.5-turbo" \| "claude-opus-4-1-20250805" \| "claude-opus-4-20250514" \| "claude-sonnet-4-20250514" \| "claude-opus-4-5-20251101" \| "claude-sonnet-4-5-20250929" \| "claude-haiku-4-5-20251001" \| "claude-opus-4-6" \| "claude-sonnet-4-6" \| "claude-3-haiku-20240307" \| "Qwen/Qwen2.5-72B-Instruct-Turbo" \| "nvidia/llama-3.1-nemotron-70b-instruct" \| "meta-llama/Llama-3.3-70B-Instruct-Turbo" \| "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo" \| "meta-llama/Llama-3.2-3B-Instruct-Turbo" \| "llama-3.3-70b-versatile" \| "llama-3.1-8b-instant" \| "llama3.3" \| "llama3.2" \| "llama3" \| "llama3.1:405b" \| "dolphin-mistral:latest" \| "openai/gpt-oss-120b" \| "openai/gpt-oss-20b" \| "google/gemini-2.5-pro-preview-03-25" \| "google/gemini-3-pro-preview" \| "google/gemini-2.5-flash" \| "google/gemini-2.0-flash-001" \| "google/gemini-2.5-flash-lite-preview-06-17" \| "google/gemini-2.0-flash-lite-001" \| "mistralai/mistral-nemo" \| "cohere/command-r-08-2024" \| "cohere/command-r-plus-08-2024" \| "deepseek/deepseek-chat" \| "deepseek/deepseek-r1-0528" \| "perplexity/sonar" \| "perplexity/sonar-pro" \| "perplexity/sonar-deep-research" \| "nousresearch/hermes-3-llama-3.1-405b" \| "nousresearch/hermes-3-llama-3.1-70b" \| "amazon/nova-lite-v1" \| "amazon/nova-micro-v1" \| "amazon/nova-pro-v1" \| "microsoft/wizardlm-2-8x22b" \| "gryphe/mythomax-l2-13b" \| "meta-llama/llama-4-scout" \| "meta-llama/llama-4-maverick" \| "x-ai/grok-4" \| "x-ai/grok-4-fast" \| "x-ai/grok-4.1-fast" \| "x-ai/grok-code-fast-1" \| "moonshotai/kimi-k2" \| "qwen/qwen3-235b-a22b-thinking-2507" \| "qwen/qwen3-coder" \| "Llama-4-Scout-17B-16E-Instruct-FP8" \| "Llama-4-Maverick-17B-128E-Instruct-FP8" \| "Llama-3.3-8B-Instruct" \| "Llama-3.3-70B-Instruct" \| "v0-1.5-md" \| "v0-1.5-lg" \| "v0-1.0-md" | No |
| model | The language model to use for answering the prompt. | "o3-mini" \| "o3-2025-04-16" \| "o1" \| "o1-mini" \| "gpt-5.2-2025-12-11" \| "gpt-5.1-2025-11-13" \| "gpt-5-2025-08-07" \| "gpt-5-mini-2025-08-07" \| "gpt-5-nano-2025-08-07" \| "gpt-5-chat-latest" \| "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "gpt-4o-mini" \| "gpt-4o" \| "gpt-4-turbo" \| "gpt-3.5-turbo" \| "claude-opus-4-1-20250805" \| "claude-opus-4-20250514" \| "claude-sonnet-4-20250514" \| "claude-opus-4-5-20251101" \| "claude-sonnet-4-5-20250929" \| "claude-haiku-4-5-20251001" \| "claude-opus-4-6" \| "claude-3-haiku-20240307" \| "Qwen/Qwen2.5-72B-Instruct-Turbo" \| "nvidia/llama-3.1-nemotron-70b-instruct" \| "meta-llama/Llama-3.3-70B-Instruct-Turbo" \| "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo" \| "meta-llama/Llama-3.2-3B-Instruct-Turbo" \| "llama-3.3-70b-versatile" \| "llama-3.1-8b-instant" \| "llama3.3" \| "llama3.2" \| "llama3" \| "llama3.1:405b" \| "dolphin-mistral:latest" \| "openai/gpt-oss-120b" \| "openai/gpt-oss-20b" \| "google/gemini-2.5-pro-preview-03-25" \| "google/gemini-3-pro-preview" \| "google/gemini-2.5-flash" \| "google/gemini-2.0-flash-001" \| "google/gemini-2.5-flash-lite-preview-06-17" \| "google/gemini-2.0-flash-lite-001" \| "mistralai/mistral-nemo" \| "cohere/command-r-08-2024" \| "cohere/command-r-plus-08-2024" \| "deepseek/deepseek-chat" \| "deepseek/deepseek-r1-0528" \| "perplexity/sonar" \| "perplexity/sonar-pro" \| "perplexity/sonar-deep-research" \| "nousresearch/hermes-3-llama-3.1-405b" \| "nousresearch/hermes-3-llama-3.1-70b" \| "amazon/nova-lite-v1" \| "amazon/nova-micro-v1" \| "amazon/nova-pro-v1" \| "microsoft/wizardlm-2-8x22b" \| "gryphe/mythomax-l2-13b" \| "meta-llama/llama-4-scout" \| "meta-llama/llama-4-maverick" \| "x-ai/grok-4" \| "x-ai/grok-4-fast" \| "x-ai/grok-4.1-fast" \| "x-ai/grok-code-fast-1" \| "moonshotai/kimi-k2" \| "qwen/qwen3-235b-a22b-thinking-2507" \| "qwen/qwen3-coder" \| "Llama-4-Scout-17B-16E-Instruct-FP8" \| "Llama-4-Maverick-17B-128E-Instruct-FP8" \| "Llama-3.3-8B-Instruct" \| "Llama-3.3-70B-Instruct" \| "v0-1.5-md" \| "v0-1.5-lg" \| "v0-1.0-md" | No |
| multiple_tool_calls | Whether to allow multiple tool calls in a single response. | bool | No |
| sys_prompt | The system prompt to provide additional context to the model. | str | No |
| conversation_history | The conversation history to provide context for the prompt. | List[Dict[str, Any]] | No |

View File

@@ -20,7 +20,7 @@ Configure timeouts for DOM settlement and page loading. Variables can be passed
| Input | Description | Type | Required |
|-------|-------------|------|----------|
| browserbase_project_id | Browserbase project ID (required if using Browserbase) | str | Yes |
| model | LLM to use for Stagehand (provider is inferred) | "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "claude-sonnet-4-5-20250929" \| "claude-sonnet-4-6" | No |
| model | LLM to use for Stagehand (provider is inferred) | "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "claude-sonnet-4-5-20250929" | No |
| url | URL to navigate to. | str | Yes |
| action | Action to perform. Suggested actions are: click, fill, type, press, scroll, select from dropdown. For multi-step actions, add an entry for each step. | List[str] | Yes |
| variables | Variables to use in the action. Variables contains data you want the action to use. | Dict[str, str] | No |
@@ -65,7 +65,7 @@ Supports searching within iframes and configurable timeouts for dynamic content
| Input | Description | Type | Required |
|-------|-------------|------|----------|
| browserbase_project_id | Browserbase project ID (required if using Browserbase) | str | Yes |
| model | LLM to use for Stagehand (provider is inferred) | "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "claude-sonnet-4-5-20250929" \| "claude-sonnet-4-6" | No |
| model | LLM to use for Stagehand (provider is inferred) | "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "claude-sonnet-4-5-20250929" | No |
| url | URL to navigate to. | str | Yes |
| instruction | Natural language description of elements or actions to discover. | str | Yes |
| iframes | Whether to search within iframes. If True, Stagehand will search for actions within iframes. | bool | No |
@@ -106,7 +106,7 @@ Use this to explore a page's interactive elements before building automated work
| Input | Description | Type | Required |
|-------|-------------|------|----------|
| browserbase_project_id | Browserbase project ID (required if using Browserbase) | str | Yes |
| model | LLM to use for Stagehand (provider is inferred) | "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "claude-sonnet-4-5-20250929" \| "claude-sonnet-4-6" | No |
| model | LLM to use for Stagehand (provider is inferred) | "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "claude-sonnet-4-5-20250929" | No |
| url | URL to navigate to. | str | Yes |
| instruction | Natural language description of elements or actions to discover. | str | Yes |
| iframes | Whether to search within iframes. If True, Stagehand will search for actions within iframes. | bool | No |