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Author SHA1 Message Date
Swifty
6f9b1a8337 add crednetial error handling 2026-02-09 11:42:00 +01:00
Swifty
01ada8b85d docs: clarify dev vs master branching strategy in CLAUDE.md
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-09 11:25:09 +01:00
Swifty
2facfccbea reduce find_block return size 2026-02-09 11:11:35 +01:00
14 changed files with 472 additions and 951 deletions

View File

@@ -45,6 +45,11 @@ AutoGPT Platform is a monorepo containing:
- Backend/Frontend services use YAML anchors for consistent configuration
- Supabase services (`db/docker/docker-compose.yml`) follow the same pattern
### Branching Strategy
- **`dev`** is the main development branch. All PRs should target `dev`.
- **`master`** is the production branch. Only used for production releases.
### Creating Pull Requests
- Create the PR against the `dev` branch of the repository.

View File

@@ -45,7 +45,10 @@ async def create_chat_session(
successfulAgentRuns=SafeJson({}),
successfulAgentSchedules=SafeJson({}),
)
return await PrismaChatSession.prisma().create(data=data)
return await PrismaChatSession.prisma().create(
data=data,
include={"Messages": True},
)
async def update_chat_session(

View File

@@ -266,38 +266,12 @@ async def stream_chat_post(
"""
import asyncio
import time
stream_start_time = time.perf_counter()
# Base log metadata (task_id added after creation)
log_meta = {"component": "ChatStream", "session_id": session_id}
if user_id:
log_meta["user_id"] = user_id
logger.info(
f"[TIMING] stream_chat_post STARTED, session={session_id}, "
f"user={user_id}, message_len={len(request.message)}",
extra={"json_fields": log_meta},
)
session = await _validate_and_get_session(session_id, user_id)
logger.info(
f"[TIMING] session validated in {(time.perf_counter() - stream_start_time)*1000:.1f}ms",
extra={
"json_fields": {
**log_meta,
"duration_ms": (time.perf_counter() - stream_start_time) * 1000,
}
},
)
# Create a task in the stream registry for reconnection support
task_id = str(uuid_module.uuid4())
operation_id = str(uuid_module.uuid4())
log_meta["task_id"] = task_id
task_create_start = time.perf_counter()
await stream_registry.create_task(
task_id=task_id,
session_id=session_id,
@@ -306,46 +280,14 @@ async def stream_chat_post(
tool_name="chat",
operation_id=operation_id,
)
logger.info(
f"[TIMING] create_task completed in {(time.perf_counter() - task_create_start)*1000:.1f}ms",
extra={
"json_fields": {
**log_meta,
"duration_ms": (time.perf_counter() - task_create_start) * 1000,
}
},
)
# Background task that runs the AI generation independently of SSE connection
async def run_ai_generation():
import time as time_module
gen_start_time = time_module.perf_counter()
logger.info(
f"[TIMING] run_ai_generation STARTED, task={task_id}, session={session_id}, user={user_id}",
extra={"json_fields": log_meta},
)
first_chunk_time, ttfc = None, None
chunk_count = 0
try:
# Emit a start event with task_id for reconnection
start_chunk = StreamStart(messageId=task_id, taskId=task_id)
await stream_registry.publish_chunk(task_id, start_chunk)
logger.info(
f"[TIMING] StreamStart published at {(time_module.perf_counter() - gen_start_time)*1000:.1f}ms",
extra={
"json_fields": {
**log_meta,
"elapsed_ms": (time_module.perf_counter() - gen_start_time)
* 1000,
}
},
)
logger.info(
"[TIMING] Calling stream_chat_completion",
extra={"json_fields": log_meta},
)
async for chunk in chat_service.stream_chat_completion(
session_id,
request.message,
@@ -354,202 +296,54 @@ async def stream_chat_post(
session=session, # Pass pre-fetched session to avoid double-fetch
context=request.context,
):
chunk_count += 1
if first_chunk_time is None:
first_chunk_time = time_module.perf_counter()
ttfc = first_chunk_time - gen_start_time
logger.info(
f"[TIMING] FIRST AI CHUNK at {ttfc:.2f}s, type={type(chunk).__name__}",
extra={
"json_fields": {
**log_meta,
"chunk_type": type(chunk).__name__,
"time_to_first_chunk_ms": ttfc * 1000,
}
},
)
# Write to Redis (subscribers will receive via XREAD)
await stream_registry.publish_chunk(task_id, chunk)
gen_end_time = time_module.perf_counter()
total_time = (gen_end_time - gen_start_time) * 1000
logger.info(
f"[TIMING] run_ai_generation FINISHED in {total_time/1000:.1f}s; "
f"task={task_id}, session={session_id}, "
f"ttfc={ttfc or -1:.2f}s, n_chunks={chunk_count}",
extra={
"json_fields": {
**log_meta,
"total_time_ms": total_time,
"time_to_first_chunk_ms": (
ttfc * 1000 if ttfc is not None else None
),
"n_chunks": chunk_count,
}
},
)
# Mark task as completed
await stream_registry.mark_task_completed(task_id, "completed")
except Exception as e:
elapsed = time_module.perf_counter() - gen_start_time
logger.error(
f"[TIMING] run_ai_generation ERROR after {elapsed:.2f}s: {e}",
extra={
"json_fields": {
**log_meta,
"elapsed_ms": elapsed * 1000,
"error": str(e),
}
},
f"Error in background AI generation for session {session_id}: {e}"
)
await stream_registry.mark_task_completed(task_id, "failed")
# Start the AI generation in a background task
bg_task = asyncio.create_task(run_ai_generation())
await stream_registry.set_task_asyncio_task(task_id, bg_task)
setup_time = (time.perf_counter() - stream_start_time) * 1000
logger.info(
f"[TIMING] Background task started, setup={setup_time:.1f}ms",
extra={"json_fields": {**log_meta, "setup_time_ms": setup_time}},
)
# SSE endpoint that subscribes to the task's stream
async def event_generator() -> AsyncGenerator[str, None]:
import time as time_module
event_gen_start = time_module.perf_counter()
logger.info(
f"[TIMING] event_generator STARTED, task={task_id}, session={session_id}, "
f"user={user_id}",
extra={"json_fields": log_meta},
)
subscriber_queue = None
first_chunk_yielded = False
chunks_yielded = 0
try:
# Subscribe to the task stream (this replays existing messages + live updates)
subscribe_start = time_module.perf_counter()
logger.info(
"[TIMING] Calling subscribe_to_task",
extra={"json_fields": log_meta},
)
subscriber_queue = await stream_registry.subscribe_to_task(
task_id=task_id,
user_id=user_id,
last_message_id="0-0", # Get all messages from the beginning
)
subscribe_time = (time_module.perf_counter() - subscribe_start) * 1000
logger.info(
f"[TIMING] subscribe_to_task completed in {subscribe_time:.1f}ms, "
f"queue_ok={subscriber_queue is not None}",
extra={
"json_fields": {
**log_meta,
"duration_ms": subscribe_time,
"queue_obtained": subscriber_queue is not None,
}
},
)
if subscriber_queue is None:
logger.info(
"[TIMING] subscriber_queue is None, yielding finish",
extra={"json_fields": log_meta},
)
yield StreamFinish().to_sse()
yield "data: [DONE]\n\n"
return
# Read from the subscriber queue and yield to SSE
logger.info(
"[TIMING] Starting to read from subscriber_queue",
extra={"json_fields": log_meta},
)
while True:
try:
queue_wait_start = time_module.perf_counter()
chunk = await asyncio.wait_for(subscriber_queue.get(), timeout=30.0)
queue_wait_time = (
time_module.perf_counter() - queue_wait_start
) * 1000
chunks_yielded += 1
if not first_chunk_yielded:
first_chunk_yielded = True
elapsed = time_module.perf_counter() - event_gen_start
logger.info(
f"[TIMING] FIRST CHUNK from queue at {elapsed:.2f}s, "
f"type={type(chunk).__name__}, "
f"wait={queue_wait_time:.1f}ms",
extra={
"json_fields": {
**log_meta,
"chunk_type": type(chunk).__name__,
"elapsed_ms": elapsed * 1000,
"queue_wait_ms": queue_wait_time,
}
},
)
elif chunks_yielded % 50 == 0:
logger.info(
f"[TIMING] Chunk #{chunks_yielded}, "
f"type={type(chunk).__name__}",
extra={
"json_fields": {
**log_meta,
"chunk_number": chunks_yielded,
"chunk_type": type(chunk).__name__,
}
},
)
yield chunk.to_sse()
# Check for finish signal
if isinstance(chunk, StreamFinish):
total_time = time_module.perf_counter() - event_gen_start
logger.info(
f"[TIMING] StreamFinish received in {total_time:.2f}s; "
f"n_chunks={chunks_yielded}",
extra={
"json_fields": {
**log_meta,
"chunks_yielded": chunks_yielded,
"total_time_ms": total_time * 1000,
}
},
)
break
except asyncio.TimeoutError:
# Send heartbeat to keep connection alive
logger.info(
f"[TIMING] Heartbeat timeout, chunks_so_far={chunks_yielded}",
extra={
"json_fields": {**log_meta, "chunks_so_far": chunks_yielded}
},
)
yield StreamHeartbeat().to_sse()
except GeneratorExit:
logger.info(
f"[TIMING] GeneratorExit (client disconnected), chunks={chunks_yielded}",
extra={
"json_fields": {
**log_meta,
"chunks_yielded": chunks_yielded,
"reason": "client_disconnect",
}
},
)
pass # Client disconnected - background task continues
except Exception as e:
elapsed = (time_module.perf_counter() - event_gen_start) * 1000
logger.error(
f"[TIMING] event_generator ERROR after {elapsed:.1f}ms: {e}",
extra={
"json_fields": {**log_meta, "elapsed_ms": elapsed, "error": str(e)}
},
)
logger.error(f"Error in SSE stream for task {task_id}: {e}")
finally:
# Unsubscribe when client disconnects or stream ends to prevent resource leak
if subscriber_queue is not None:
@@ -563,18 +357,6 @@ async def stream_chat_post(
exc_info=True,
)
# AI SDK protocol termination - always yield even if unsubscribe fails
total_time = time_module.perf_counter() - event_gen_start
logger.info(
f"[TIMING] event_generator FINISHED in {total_time:.2f}s; "
f"task={task_id}, session={session_id}, n_chunks={chunks_yielded}",
extra={
"json_fields": {
**log_meta,
"total_time_ms": total_time * 1000,
"chunks_yielded": chunks_yielded,
}
},
)
yield "data: [DONE]\n\n"
return StreamingResponse(
@@ -643,7 +425,7 @@ async def stream_chat_get(
"Chat stream completed",
extra={
"session_id": session_id,
"n_chunks": chunk_count,
"chunk_count": chunk_count,
"first_chunk_type": first_chunk_type,
},
)

View File

@@ -371,45 +371,21 @@ async def stream_chat_completion(
ValueError: If max_context_messages is exceeded
"""
completion_start = time.monotonic()
# Build log metadata for structured logging
log_meta = {"component": "ChatService", "session_id": session_id}
if user_id:
log_meta["user_id"] = user_id
logger.info(
f"[TIMING] stream_chat_completion STARTED, session={session_id}, user={user_id}, "
f"message_len={len(message) if message else 0}, is_user={is_user_message}",
extra={
"json_fields": {
**log_meta,
"message_len": len(message) if message else 0,
"is_user_message": is_user_message,
}
},
f"Streaming chat completion for session {session_id} for message {message} and user id {user_id}. Message is user message: {is_user_message}"
)
# Only fetch from Redis if session not provided (initial call)
if session is None:
fetch_start = time.monotonic()
session = await get_chat_session(session_id, user_id)
fetch_time = (time.monotonic() - fetch_start) * 1000
logger.info(
f"[TIMING] get_chat_session took {fetch_time:.1f}ms, "
f"n_messages={len(session.messages) if session else 0}",
extra={
"json_fields": {
**log_meta,
"duration_ms": fetch_time,
"n_messages": len(session.messages) if session else 0,
}
},
f"Fetched session from Redis: {session.session_id if session else 'None'}, "
f"message_count={len(session.messages) if session else 0}"
)
else:
logger.info(
f"[TIMING] Using provided session, messages={len(session.messages)}",
extra={"json_fields": {**log_meta, "n_messages": len(session.messages)}},
f"Using provided session object: {session.session_id}, "
f"message_count={len(session.messages)}"
)
if not session:
@@ -430,25 +406,17 @@ async def stream_chat_completion(
# Track user message in PostHog
if is_user_message:
posthog_start = time.monotonic()
track_user_message(
user_id=user_id,
session_id=session_id,
message_length=len(message),
)
posthog_time = (time.monotonic() - posthog_start) * 1000
logger.info(
f"[TIMING] track_user_message took {posthog_time:.1f}ms",
extra={"json_fields": {**log_meta, "duration_ms": posthog_time}},
)
upsert_start = time.monotonic()
session = await upsert_chat_session(session)
upsert_time = (time.monotonic() - upsert_start) * 1000
logger.info(
f"[TIMING] upsert_chat_session took {upsert_time:.1f}ms",
extra={"json_fields": {**log_meta, "duration_ms": upsert_time}},
f"Upserting session: {session.session_id} with user id {session.user_id}, "
f"message_count={len(session.messages)}"
)
session = await upsert_chat_session(session)
assert session, "Session not found"
# Generate title for new sessions on first user message (non-blocking)
@@ -486,13 +454,7 @@ async def stream_chat_completion(
asyncio.create_task(_update_title())
# Build system prompt with business understanding
prompt_start = time.monotonic()
system_prompt, understanding = await _build_system_prompt(user_id)
prompt_time = (time.monotonic() - prompt_start) * 1000
logger.info(
f"[TIMING] _build_system_prompt took {prompt_time:.1f}ms",
extra={"json_fields": {**log_meta, "duration_ms": prompt_time}},
)
# Initialize variables for streaming
assistant_response = ChatMessage(
@@ -521,18 +483,9 @@ async def stream_chat_completion(
text_block_id = str(uuid_module.uuid4())
# Yield message start
setup_time = (time.monotonic() - completion_start) * 1000
logger.info(
f"[TIMING] Setup complete, yielding StreamStart at {setup_time:.1f}ms",
extra={"json_fields": {**log_meta, "setup_time_ms": setup_time}},
)
yield StreamStart(messageId=message_id)
try:
logger.info(
"[TIMING] Calling _stream_chat_chunks",
extra={"json_fields": log_meta},
)
async for chunk in _stream_chat_chunks(
session=session,
tools=tools,
@@ -940,21 +893,9 @@ async def _stream_chat_chunks(
SSE formatted JSON response objects
"""
import time as time_module
stream_chunks_start = time_module.perf_counter()
model = config.model
# Build log metadata for structured logging
log_meta = {"component": "ChatService", "session_id": session.session_id}
if session.user_id:
log_meta["user_id"] = session.user_id
logger.info(
f"[TIMING] _stream_chat_chunks STARTED, session={session.session_id}, "
f"user={session.user_id}, n_messages={len(session.messages)}",
extra={"json_fields": {**log_meta, "n_messages": len(session.messages)}},
)
logger.info("Starting pure chat stream")
messages = session.to_openai_messages()
if system_prompt:
@@ -965,18 +906,12 @@ async def _stream_chat_chunks(
messages = [system_message] + messages
# Apply context window management
context_start = time_module.perf_counter()
context_result = await _manage_context_window(
messages=messages,
model=model,
api_key=config.api_key,
base_url=config.base_url,
)
context_time = (time_module.perf_counter() - context_start) * 1000
logger.info(
f"[TIMING] _manage_context_window took {context_time:.1f}ms",
extra={"json_fields": {**log_meta, "duration_ms": context_time}},
)
if context_result.error:
if "System prompt dropped" in context_result.error:
@@ -1011,19 +946,9 @@ async def _stream_chat_chunks(
while retry_count <= MAX_RETRIES:
try:
elapsed = (time_module.perf_counter() - stream_chunks_start) * 1000
retry_info = (
f" (retry {retry_count}/{MAX_RETRIES})" if retry_count > 0 else ""
)
logger.info(
f"[TIMING] Creating OpenAI stream at {elapsed:.1f}ms{retry_info}",
extra={
"json_fields": {
**log_meta,
"elapsed_ms": elapsed,
"retry_count": retry_count,
}
},
f"Creating OpenAI chat completion stream..."
f"{f' (retry {retry_count}/{MAX_RETRIES})' if retry_count > 0 else ''}"
)
# Build extra_body for OpenRouter tracing and PostHog analytics
@@ -1040,7 +965,6 @@ async def _stream_chat_chunks(
:128
] # OpenRouter limit
api_call_start = time_module.perf_counter()
stream = await client.chat.completions.create(
model=model,
messages=cast(list[ChatCompletionMessageParam], messages),
@@ -1050,11 +974,6 @@ async def _stream_chat_chunks(
stream_options=ChatCompletionStreamOptionsParam(include_usage=True),
extra_body=extra_body,
)
api_init_time = (time_module.perf_counter() - api_call_start) * 1000
logger.info(
f"[TIMING] OpenAI stream object returned in {api_init_time:.1f}ms",
extra={"json_fields": {**log_meta, "duration_ms": api_init_time}},
)
# Variables to accumulate tool calls
tool_calls: list[dict[str, Any]] = []
@@ -1065,13 +984,10 @@ async def _stream_chat_chunks(
# Track if we've started the text block
text_started = False
first_content_chunk = True
chunk_count = 0
# Process the stream
chunk: ChatCompletionChunk
async for chunk in stream:
chunk_count += 1
if chunk.usage:
yield StreamUsage(
promptTokens=chunk.usage.prompt_tokens,
@@ -1094,23 +1010,6 @@ async def _stream_chat_chunks(
if not text_started and text_block_id:
yield StreamTextStart(id=text_block_id)
text_started = True
# Log timing for first content chunk
if first_content_chunk:
first_content_chunk = False
ttfc = (
time_module.perf_counter() - api_call_start
) * 1000
logger.info(
f"[TIMING] FIRST CONTENT CHUNK at {ttfc:.1f}ms "
f"(since API call), n_chunks={chunk_count}",
extra={
"json_fields": {
**log_meta,
"time_to_first_chunk_ms": ttfc,
"n_chunks": chunk_count,
}
},
)
# Stream the text delta
text_response = StreamTextDelta(
id=text_block_id or "",
@@ -1167,21 +1066,7 @@ async def _stream_chat_chunks(
toolName=tool_calls[idx]["function"]["name"],
)
emitted_start_for_idx.add(idx)
stream_duration = time_module.perf_counter() - api_call_start
logger.info(
f"[TIMING] OpenAI stream COMPLETE, finish_reason={finish_reason}, "
f"duration={stream_duration:.2f}s, "
f"n_chunks={chunk_count}, n_tool_calls={len(tool_calls)}",
extra={
"json_fields": {
**log_meta,
"stream_duration_ms": stream_duration * 1000,
"finish_reason": finish_reason,
"n_chunks": chunk_count,
"n_tool_calls": len(tool_calls),
}
},
)
logger.info(f"Stream complete. Finish reason: {finish_reason}")
# Yield all accumulated tool calls after the stream is complete
# This ensures all tool call arguments have been fully received
@@ -1201,12 +1086,6 @@ async def _stream_chat_chunks(
# Re-raise to trigger retry logic in the parent function
raise
total_time = (time_module.perf_counter() - stream_chunks_start) * 1000
logger.info(
f"[TIMING] _stream_chat_chunks COMPLETED in {total_time/1000:.1f}s; "
f"session={session.session_id}, user={session.user_id}",
extra={"json_fields": {**log_meta, "total_time_ms": total_time}},
)
yield StreamFinish()
return
except Exception as e:

View File

@@ -104,24 +104,6 @@ async def create_task(
Returns:
The created ActiveTask instance (metadata only)
"""
import time
start_time = time.perf_counter()
# Build log metadata for structured logging
log_meta = {
"component": "StreamRegistry",
"task_id": task_id,
"session_id": session_id,
}
if user_id:
log_meta["user_id"] = user_id
logger.info(
f"[TIMING] create_task STARTED, task={task_id}, session={session_id}, user={user_id}",
extra={"json_fields": log_meta},
)
task = ActiveTask(
task_id=task_id,
session_id=session_id,
@@ -132,18 +114,10 @@ async def create_task(
)
# Store metadata in Redis
redis_start = time.perf_counter()
redis = await get_redis_async()
redis_time = (time.perf_counter() - redis_start) * 1000
logger.info(
f"[TIMING] get_redis_async took {redis_time:.1f}ms",
extra={"json_fields": {**log_meta, "duration_ms": redis_time}},
)
meta_key = _get_task_meta_key(task_id)
op_key = _get_operation_mapping_key(operation_id)
hset_start = time.perf_counter()
await redis.hset( # type: ignore[misc]
meta_key,
mapping={
@@ -157,22 +131,12 @@ async def create_task(
"created_at": task.created_at.isoformat(),
},
)
hset_time = (time.perf_counter() - hset_start) * 1000
logger.info(
f"[TIMING] redis.hset took {hset_time:.1f}ms",
extra={"json_fields": {**log_meta, "duration_ms": hset_time}},
)
await redis.expire(meta_key, config.stream_ttl)
# Create operation_id -> task_id mapping for webhook lookups
await redis.set(op_key, task_id, ex=config.stream_ttl)
total_time = (time.perf_counter() - start_time) * 1000
logger.info(
f"[TIMING] create_task COMPLETED in {total_time:.1f}ms; task={task_id}, session={session_id}",
extra={"json_fields": {**log_meta, "total_time_ms": total_time}},
)
logger.debug(f"Created task {task_id} for session {session_id}")
return task
@@ -192,60 +156,26 @@ async def publish_chunk(
Returns:
The Redis Stream message ID
"""
import time
start_time = time.perf_counter()
chunk_type = type(chunk).__name__
chunk_json = chunk.model_dump_json()
message_id = "0-0"
# Build log metadata
log_meta = {
"component": "StreamRegistry",
"task_id": task_id,
"chunk_type": chunk_type,
}
try:
redis = await get_redis_async()
stream_key = _get_task_stream_key(task_id)
# Write to Redis Stream for persistence and real-time delivery
xadd_start = time.perf_counter()
raw_id = await redis.xadd(
stream_key,
{"data": chunk_json},
maxlen=config.stream_max_length,
)
xadd_time = (time.perf_counter() - xadd_start) * 1000
message_id = raw_id if isinstance(raw_id, str) else raw_id.decode()
# Set TTL on stream to match task metadata TTL
await redis.expire(stream_key, config.stream_ttl)
total_time = (time.perf_counter() - start_time) * 1000
# Only log timing for significant chunks or slow operations
if (
chunk_type
in ("StreamStart", "StreamFinish", "StreamTextStart", "StreamTextEnd")
or total_time > 50
):
logger.info(
f"[TIMING] publish_chunk {chunk_type} in {total_time:.1f}ms (xadd={xadd_time:.1f}ms)",
extra={
"json_fields": {
**log_meta,
"total_time_ms": total_time,
"xadd_time_ms": xadd_time,
"message_id": message_id,
}
},
)
except Exception as e:
elapsed = (time.perf_counter() - start_time) * 1000
logger.error(
f"[TIMING] Failed to publish chunk {chunk_type} after {elapsed:.1f}ms: {e}",
extra={"json_fields": {**log_meta, "elapsed_ms": elapsed, "error": str(e)}},
f"Failed to publish chunk for task {task_id}: {e}",
exc_info=True,
)
@@ -270,61 +200,24 @@ async def subscribe_to_task(
An asyncio Queue that will receive stream chunks, or None if task not found
or user doesn't have access
"""
import time
start_time = time.perf_counter()
# Build log metadata
log_meta = {"component": "StreamRegistry", "task_id": task_id}
if user_id:
log_meta["user_id"] = user_id
logger.info(
f"[TIMING] subscribe_to_task STARTED, task={task_id}, user={user_id}, last_msg={last_message_id}",
extra={"json_fields": {**log_meta, "last_message_id": last_message_id}},
)
redis_start = time.perf_counter()
redis = await get_redis_async()
meta_key = _get_task_meta_key(task_id)
meta: dict[Any, Any] = await redis.hgetall(meta_key) # type: ignore[misc]
hgetall_time = (time.perf_counter() - redis_start) * 1000
logger.info(
f"[TIMING] Redis hgetall took {hgetall_time:.1f}ms",
extra={"json_fields": {**log_meta, "duration_ms": hgetall_time}},
)
if not meta:
elapsed = (time.perf_counter() - start_time) * 1000
logger.info(
f"[TIMING] Task not found in Redis after {elapsed:.1f}ms",
extra={
"json_fields": {
**log_meta,
"elapsed_ms": elapsed,
"reason": "task_not_found",
}
},
)
logger.debug(f"Task {task_id} not found in Redis")
return None
# Note: Redis client uses decode_responses=True, so keys are strings
task_status = meta.get("status", "")
task_user_id = meta.get("user_id", "") or None
log_meta["session_id"] = meta.get("session_id", "")
# Validate ownership - if task has an owner, requester must match
if task_user_id:
if user_id != task_user_id:
logger.warning(
f"[TIMING] Access denied: user {user_id} tried to access task owned by {task_user_id}",
extra={
"json_fields": {
**log_meta,
"task_owner": task_user_id,
"reason": "access_denied",
}
},
f"User {user_id} denied access to task {task_id} "
f"owned by {task_user_id}"
)
return None
@@ -332,19 +225,7 @@ async def subscribe_to_task(
stream_key = _get_task_stream_key(task_id)
# Step 1: Replay messages from Redis Stream
xread_start = time.perf_counter()
messages = await redis.xread({stream_key: last_message_id}, block=0, count=1000)
xread_time = (time.perf_counter() - xread_start) * 1000
logger.info(
f"[TIMING] Redis xread (replay) took {xread_time:.1f}ms, status={task_status}",
extra={
"json_fields": {
**log_meta,
"duration_ms": xread_time,
"task_status": task_status,
}
},
)
replayed_count = 0
replay_last_id = last_message_id
@@ -363,48 +244,19 @@ async def subscribe_to_task(
except Exception as e:
logger.warning(f"Failed to replay message: {e}")
logger.info(
f"[TIMING] Replayed {replayed_count} messages, last_id={replay_last_id}",
extra={
"json_fields": {
**log_meta,
"n_messages_replayed": replayed_count,
"replay_last_id": replay_last_id,
}
},
)
logger.debug(f"Task {task_id}: replayed {replayed_count} messages")
# Step 2: If task is still running, start stream listener for live updates
if task_status == "running":
logger.info(
"[TIMING] Task still running, starting _stream_listener",
extra={"json_fields": {**log_meta, "task_status": task_status}},
)
listener_task = asyncio.create_task(
_stream_listener(task_id, subscriber_queue, replay_last_id, log_meta)
_stream_listener(task_id, subscriber_queue, replay_last_id)
)
# Track listener task for cleanup on unsubscribe
_listener_tasks[id(subscriber_queue)] = (task_id, listener_task)
else:
# Task is completed/failed - add finish marker
logger.info(
f"[TIMING] Task already {task_status}, adding StreamFinish",
extra={"json_fields": {**log_meta, "task_status": task_status}},
)
await subscriber_queue.put(StreamFinish())
total_time = (time.perf_counter() - start_time) * 1000
logger.info(
f"[TIMING] subscribe_to_task COMPLETED in {total_time:.1f}ms; task={task_id}, "
f"n_messages_replayed={replayed_count}",
extra={
"json_fields": {
**log_meta,
"total_time_ms": total_time,
"n_messages_replayed": replayed_count,
}
},
)
return subscriber_queue
@@ -412,7 +264,6 @@ async def _stream_listener(
task_id: str,
subscriber_queue: asyncio.Queue[StreamBaseResponse],
last_replayed_id: str,
log_meta: dict | None = None,
) -> None:
"""Listen to Redis Stream for new messages using blocking XREAD.
@@ -423,27 +274,10 @@ async def _stream_listener(
task_id: Task ID to listen for
subscriber_queue: Queue to deliver messages to
last_replayed_id: Last message ID from replay (continue from here)
log_meta: Structured logging metadata
"""
import time
start_time = time.perf_counter()
# Use provided log_meta or build minimal one
if log_meta is None:
log_meta = {"component": "StreamRegistry", "task_id": task_id}
logger.info(
f"[TIMING] _stream_listener STARTED, task={task_id}, last_id={last_replayed_id}",
extra={"json_fields": {**log_meta, "last_replayed_id": last_replayed_id}},
)
queue_id = id(subscriber_queue)
# Track the last successfully delivered message ID for recovery hints
last_delivered_id = last_replayed_id
messages_delivered = 0
first_message_time = None
xread_count = 0
try:
redis = await get_redis_async()
@@ -453,39 +287,9 @@ async def _stream_listener(
while True:
# Block for up to 30 seconds waiting for new messages
# This allows periodic checking if task is still running
xread_start = time.perf_counter()
xread_count += 1
messages = await redis.xread(
{stream_key: current_id}, block=30000, count=100
)
xread_time = (time.perf_counter() - xread_start) * 1000
if messages:
msg_count = sum(len(msgs) for _, msgs in messages)
logger.info(
f"[TIMING] xread #{xread_count} returned {msg_count} messages in {xread_time:.1f}ms",
extra={
"json_fields": {
**log_meta,
"xread_count": xread_count,
"n_messages": msg_count,
"duration_ms": xread_time,
}
},
)
elif xread_time > 1000:
# Only log timeouts (30s blocking)
logger.info(
f"[TIMING] xread #{xread_count} timeout after {xread_time:.1f}ms",
extra={
"json_fields": {
**log_meta,
"xread_count": xread_count,
"duration_ms": xread_time,
"reason": "timeout",
}
},
)
if not messages:
# Timeout - check if task is still running
@@ -522,30 +326,10 @@ async def _stream_listener(
)
# Update last delivered ID on successful delivery
last_delivered_id = current_id
messages_delivered += 1
if first_message_time is None:
first_message_time = time.perf_counter()
elapsed = (first_message_time - start_time) * 1000
logger.info(
f"[TIMING] FIRST live message at {elapsed:.1f}ms, type={type(chunk).__name__}",
extra={
"json_fields": {
**log_meta,
"elapsed_ms": elapsed,
"chunk_type": type(chunk).__name__,
}
},
)
except asyncio.TimeoutError:
logger.warning(
f"[TIMING] Subscriber queue full, delivery timed out after {QUEUE_PUT_TIMEOUT}s",
extra={
"json_fields": {
**log_meta,
"timeout_s": QUEUE_PUT_TIMEOUT,
"reason": "queue_full",
}
},
f"Subscriber queue full for task {task_id}, "
f"message delivery timed out after {QUEUE_PUT_TIMEOUT}s"
)
# Send overflow error with recovery info
try:
@@ -567,44 +351,15 @@ async def _stream_listener(
# Stop listening on finish
if isinstance(chunk, StreamFinish):
total_time = (time.perf_counter() - start_time) * 1000
logger.info(
f"[TIMING] StreamFinish received in {total_time/1000:.1f}s; delivered={messages_delivered}",
extra={
"json_fields": {
**log_meta,
"total_time_ms": total_time,
"messages_delivered": messages_delivered,
}
},
)
return
except Exception as e:
logger.warning(
f"Error processing stream message: {e}",
extra={"json_fields": {**log_meta, "error": str(e)}},
)
logger.warning(f"Error processing stream message: {e}")
except asyncio.CancelledError:
elapsed = (time.perf_counter() - start_time) * 1000
logger.info(
f"[TIMING] _stream_listener CANCELLED after {elapsed:.1f}ms, delivered={messages_delivered}",
extra={
"json_fields": {
**log_meta,
"elapsed_ms": elapsed,
"messages_delivered": messages_delivered,
"reason": "cancelled",
}
},
)
logger.debug(f"Stream listener cancelled for task {task_id}")
raise # Re-raise to propagate cancellation
except Exception as e:
elapsed = (time.perf_counter() - start_time) * 1000
logger.error(
f"[TIMING] _stream_listener ERROR after {elapsed:.1f}ms: {e}",
extra={"json_fields": {**log_meta, "elapsed_ms": elapsed, "error": str(e)}},
)
logger.error(f"Stream listener error for task {task_id}: {e}")
# On error, send finish to unblock subscriber
try:
await asyncio.wait_for(
@@ -613,24 +368,10 @@ async def _stream_listener(
)
except (asyncio.TimeoutError, asyncio.QueueFull):
logger.warning(
"Could not deliver finish event after error",
extra={"json_fields": log_meta},
f"Could not deliver finish event for task {task_id} after error"
)
finally:
# Clean up listener task mapping on exit
total_time = (time.perf_counter() - start_time) * 1000
logger.info(
f"[TIMING] _stream_listener FINISHED in {total_time/1000:.1f}s; task={task_id}, "
f"delivered={messages_delivered}, xread_count={xread_count}",
extra={
"json_fields": {
**log_meta,
"total_time_ms": total_time,
"messages_delivered": messages_delivered,
"xread_count": xread_count,
}
},
)
_listener_tasks.pop(queue_id, None)

View File

@@ -54,7 +54,8 @@ class FindBlockTool(BaseTool):
"Blocks are reusable components that perform specific tasks like "
"sending emails, making API calls, processing text, etc. "
"IMPORTANT: Use this tool FIRST to get the block's 'id' before calling run_block. "
"The response includes each block's id, required_inputs, and input_schema."
"The response includes each block's id, required_inputs, "
"and output_fields."
)
@property
@@ -123,7 +124,7 @@ class FindBlockTool(BaseTool):
session_id=session_id,
)
# Enrich results with full block information
# Enrich results with block information
blocks: list[BlockInfoSummary] = []
for result in results:
block_id = result["content_id"]
@@ -141,8 +142,8 @@ class FindBlockTool(BaseTool):
continue
# Get input/output schemas
input_schema = {}
output_schema = {}
input_schema: dict[str, Any] = {}
output_schema: dict[str, Any] = {}
try:
input_schema = block.input_schema.jsonschema()
except Exception as e:
@@ -160,26 +161,28 @@ class FindBlockTool(BaseTool):
e,
)
# Get categories from block instance
categories = []
if hasattr(block, "categories") and block.categories:
categories = [cat.value for cat in block.categories]
# Get credential field names to exclude from required inputs
credentials_fields: set[str] = set()
try:
credentials_fields = set(
block.input_schema.get_credentials_fields().keys()
)
except Exception as e:
logger.debug(
"Failed to get credentials fields for block %s: %s",
block_id,
e,
)
# Extract required inputs for easier use
# Extract input fields (excluding credentials)
required_inputs: list[BlockInputFieldInfo] = []
if input_schema:
properties = input_schema.get("properties", {})
required_fields = set(input_schema.get("required", []))
# Get credential field names to exclude from required inputs
credentials_fields = set(
block.input_schema.get_credentials_fields().keys()
)
for field_name, field_schema in properties.items():
# Skip credential fields - they're handled separately
if field_name in credentials_fields:
continue
required_inputs.append(
BlockInputFieldInfo(
name=field_name,
@@ -190,15 +193,26 @@ class FindBlockTool(BaseTool):
)
)
# Extract output fields
output_fields: list[BlockInputFieldInfo] = []
if output_schema:
out_props = output_schema.get("properties", {})
for field_name, field_schema in out_props.items():
output_fields.append(
BlockInputFieldInfo(
name=field_name,
type=field_schema.get("type", "string"),
description=field_schema.get("description", ""),
)
)
blocks.append(
BlockInfoSummary(
id=block_id,
name=block.name,
description=block.description or "",
categories=categories,
input_schema=input_schema,
output_schema=output_schema,
required_inputs=required_inputs,
output_fields=output_fields,
)
)
@@ -227,8 +241,8 @@ class FindBlockTool(BaseTool):
return BlockListResponse(
message=(
f"Found {len(blocks)} block(s) matching '{query}'. "
"To execute a block, use run_block with the block's 'id' field "
"and provide 'input_data' matching the block's input_schema."
"To execute a block, use run_block with the block's 'id' "
"and provide 'input_data' matching required_inputs."
),
blocks=blocks,
count=len(blocks),

View File

@@ -18,7 +18,13 @@ _TEST_USER_ID = "test-user-find-block"
def make_mock_block(
block_id: str, name: str, block_type: BlockType, disabled: bool = False
block_id: str,
name: str,
block_type: BlockType,
disabled: bool = False,
input_schema: dict | None = None,
output_schema: dict | None = None,
credentials_fields: dict | None = None,
):
"""Create a mock block for testing."""
mock = MagicMock()
@@ -28,10 +34,13 @@ def make_mock_block(
mock.block_type = block_type
mock.disabled = disabled
mock.input_schema = MagicMock()
mock.input_schema.jsonschema.return_value = {"properties": {}, "required": []}
mock.input_schema.get_credentials_fields.return_value = {}
mock.input_schema.jsonschema.return_value = input_schema or {
"properties": {},
"required": [],
}
mock.input_schema.get_credentials_fields.return_value = credentials_fields or {}
mock.output_schema = MagicMock()
mock.output_schema.jsonschema.return_value = {}
mock.output_schema.jsonschema.return_value = output_schema or {}
mock.categories = []
return mock
@@ -137,3 +146,240 @@ class TestFindBlockFiltering:
assert isinstance(response, BlockListResponse)
assert len(response.blocks) == 1
assert response.blocks[0].id == "normal-block-id"
@pytest.mark.asyncio(loop_scope="session")
async def test_response_size_average_chars_per_block(self):
"""Measure average chars per block in the serialized response."""
session = make_session(user_id=_TEST_USER_ID)
# Realistic block definitions modeled after real blocks
block_defs = [
{
"id": "http-block-id",
"name": "Send Web Request",
"input_schema": {
"properties": {
"url": {
"type": "string",
"description": "The URL to send the request to",
},
"method": {
"type": "string",
"description": "The HTTP method to use",
},
"headers": {
"type": "object",
"description": "Headers to include in the request",
},
"json_format": {
"type": "boolean",
"description": "If true, send the body as JSON",
},
"body": {
"type": "object",
"description": "Form/JSON body payload",
},
"credentials": {
"type": "object",
"description": "HTTP credentials",
},
},
"required": ["url", "method"],
},
"output_schema": {
"properties": {
"response": {
"type": "object",
"description": "The response from the server",
},
"client_error": {
"type": "object",
"description": "Errors on 4xx status codes",
},
"server_error": {
"type": "object",
"description": "Errors on 5xx status codes",
},
"error": {
"type": "string",
"description": "Errors for all other exceptions",
},
},
},
"credentials_fields": {"credentials": True},
},
{
"id": "email-block-id",
"name": "Send Email",
"input_schema": {
"properties": {
"to_email": {
"type": "string",
"description": "Recipient email address",
},
"subject": {
"type": "string",
"description": "Subject of the email",
},
"body": {
"type": "string",
"description": "Body of the email",
},
"config": {
"type": "object",
"description": "SMTP Config",
},
"credentials": {
"type": "object",
"description": "SMTP credentials",
},
},
"required": ["to_email", "subject", "body", "credentials"],
},
"output_schema": {
"properties": {
"status": {
"type": "string",
"description": "Status of the email sending operation",
},
"error": {
"type": "string",
"description": "Error message if sending failed",
},
},
},
"credentials_fields": {"credentials": True},
},
{
"id": "claude-code-block-id",
"name": "Claude Code",
"input_schema": {
"properties": {
"e2b_credentials": {
"type": "object",
"description": "API key for E2B platform",
},
"anthropic_credentials": {
"type": "object",
"description": "API key for Anthropic",
},
"prompt": {
"type": "string",
"description": "Task or instruction for Claude Code",
},
"timeout": {
"type": "integer",
"description": "Sandbox timeout in seconds",
},
"setup_commands": {
"type": "array",
"description": "Shell commands to run before execution",
},
"working_directory": {
"type": "string",
"description": "Working directory for Claude Code",
},
"session_id": {
"type": "string",
"description": "Session ID to resume a conversation",
},
"sandbox_id": {
"type": "string",
"description": "Sandbox ID to reconnect to",
},
"conversation_history": {
"type": "string",
"description": "Previous conversation history",
},
"dispose_sandbox": {
"type": "boolean",
"description": "Whether to dispose sandbox after execution",
},
},
"required": [
"e2b_credentials",
"anthropic_credentials",
"prompt",
],
},
"output_schema": {
"properties": {
"response": {
"type": "string",
"description": "Output from Claude Code execution",
},
"files": {
"type": "array",
"description": "Files created/modified by Claude Code",
},
"conversation_history": {
"type": "string",
"description": "Full conversation history",
},
"session_id": {
"type": "string",
"description": "Session ID for this conversation",
},
"sandbox_id": {
"type": "string",
"description": "ID of the sandbox instance",
},
"error": {
"type": "string",
"description": "Error message if execution failed",
},
},
},
"credentials_fields": {
"e2b_credentials": True,
"anthropic_credentials": True,
},
},
]
search_results = [
{"content_id": d["id"], "score": 0.9 - i * 0.1}
for i, d in enumerate(block_defs)
]
mock_blocks = {
d["id"]: make_mock_block(
block_id=d["id"],
name=d["name"],
block_type=BlockType.STANDARD,
input_schema=d["input_schema"],
output_schema=d["output_schema"],
credentials_fields=d["credentials_fields"],
)
for d in block_defs
}
with patch(
"backend.api.features.chat.tools.find_block.unified_hybrid_search",
new_callable=AsyncMock,
return_value=(search_results, len(search_results)),
), patch(
"backend.api.features.chat.tools.find_block.get_block",
side_effect=lambda bid: mock_blocks.get(bid),
):
tool = FindBlockTool()
response = await tool._execute(
user_id=_TEST_USER_ID, session=session, query="test"
)
assert isinstance(response, BlockListResponse)
assert response.count == len(block_defs)
total_chars = len(response.model_dump_json())
avg_chars = total_chars // response.count
# Print for visibility in test output
print(f"\nTotal response size: {total_chars} chars")
print(f"Number of blocks: {response.count}")
print(f"Average chars per block: {avg_chars}")
# The old response was ~90K for 10 blocks (~9K per block).
# With the optimized format (no raw JSON schemas) we expect ~1.5K per block.
assert avg_chars < 2000, (
f"Average chars per block ({avg_chars}) exceeds 2000. "
f"Total response: {total_chars} chars for {response.count} blocks."
)

View File

@@ -1,29 +0,0 @@
"""Shared helpers for chat tools."""
from typing import Any
def get_inputs_from_schema(
input_schema: dict[str, Any],
exclude_fields: set[str] | None = None,
) -> list[dict[str, Any]]:
"""Extract input field info from JSON schema."""
if not isinstance(input_schema, dict):
return []
exclude = exclude_fields or set()
properties = input_schema.get("properties", {})
required = set(input_schema.get("required", []))
return [
{
"name": name,
"title": schema.get("title", name),
"type": schema.get("type", "string"),
"description": schema.get("description", ""),
"required": name in required,
"default": schema.get("default"),
}
for name, schema in properties.items()
if name not in exclude
]

View File

@@ -334,13 +334,14 @@ class BlockInfoSummary(BaseModel):
id: str
name: str
description: str
categories: list[str]
input_schema: dict[str, Any]
output_schema: dict[str, Any]
required_inputs: list[BlockInputFieldInfo] = Field(
default_factory=list,
description="List of required input fields for this block",
)
output_fields: list[BlockInputFieldInfo] = Field(
default_factory=list,
description="Output fields produced by this block",
)
class BlockListResponse(ToolResponseBase):
@@ -350,10 +351,6 @@ class BlockListResponse(ToolResponseBase):
blocks: list[BlockInfoSummary]
count: int
query: str
usage_hint: str = Field(
default="To execute a block, call run_block with block_id set to the block's "
"'id' field and input_data containing the required fields from input_schema."
)
class BlockOutputResponse(ToolResponseBase):

View File

@@ -24,7 +24,6 @@ from backend.util.timezone_utils import (
)
from .base import BaseTool
from .helpers import get_inputs_from_schema
from .models import (
AgentDetails,
AgentDetailsResponse,
@@ -262,7 +261,7 @@ class RunAgentTool(BaseTool):
),
requirements={
"credentials": requirements_creds_list,
"inputs": get_inputs_from_schema(graph.input_schema),
"inputs": self._get_inputs_list(graph.input_schema),
"execution_modes": self._get_execution_modes(graph),
},
),
@@ -370,6 +369,22 @@ class RunAgentTool(BaseTool):
session_id=session_id,
)
def _get_inputs_list(self, input_schema: dict[str, Any]) -> list[dict[str, Any]]:
"""Extract inputs list from schema."""
inputs_list = []
if isinstance(input_schema, dict) and "properties" in input_schema:
for field_name, field_schema in input_schema["properties"].items():
inputs_list.append(
{
"name": field_name,
"title": field_schema.get("title", field_name),
"type": field_schema.get("type", "string"),
"description": field_schema.get("description", ""),
"required": field_name in input_schema.get("required", []),
}
)
return inputs_list
def _get_execution_modes(self, graph: GraphModel) -> list[str]:
"""Get available execution modes for the graph."""
trigger_info = graph.trigger_setup_info
@@ -383,7 +398,7 @@ class RunAgentTool(BaseTool):
suffix: str,
) -> str:
"""Build a message describing available inputs for an agent."""
inputs_list = get_inputs_from_schema(graph.input_schema)
inputs_list = self._get_inputs_list(graph.input_schema)
required_names = [i["name"] for i in inputs_list if i["required"]]
optional_names = [i["name"] for i in inputs_list if not i["required"]]

View File

@@ -12,15 +12,14 @@ from backend.api.features.chat.tools.find_block import (
COPILOT_EXCLUDED_BLOCK_IDS,
COPILOT_EXCLUDED_BLOCK_TYPES,
)
from backend.data.block import AnyBlockSchema, get_block
from backend.data.block import get_block
from backend.data.execution import ExecutionContext
from backend.data.model import CredentialsFieldInfo, CredentialsMetaInput
from backend.data.model import CredentialsMetaInput
from backend.data.workspace import get_or_create_workspace
from backend.integrations.creds_manager import IntegrationCredentialsManager
from backend.util.exceptions import BlockError
from .base import BaseTool
from .helpers import get_inputs_from_schema
from .models import (
BlockOutputResponse,
ErrorResponse,
@@ -29,10 +28,7 @@ from .models import (
ToolResponseBase,
UserReadiness,
)
from .utils import (
build_missing_credentials_from_field_info,
match_credentials_to_requirements,
)
from .utils import build_missing_credentials_from_field_info
logger = logging.getLogger(__name__)
@@ -81,6 +77,91 @@ class RunBlockTool(BaseTool):
def requires_auth(self) -> bool:
return True
async def _check_block_credentials(
self,
user_id: str,
block: Any,
input_data: dict[str, Any] | None = None,
) -> tuple[dict[str, CredentialsMetaInput], list[CredentialsMetaInput]]:
"""
Check if user has required credentials for a block.
Args:
user_id: User ID
block: Block to check credentials for
input_data: Input data for the block (used to determine provider via discriminator)
Returns:
tuple[matched_credentials, missing_credentials]
"""
matched_credentials: dict[str, CredentialsMetaInput] = {}
missing_credentials: list[CredentialsMetaInput] = []
input_data = input_data or {}
# Get credential field info from block's input schema
credentials_fields_info = block.input_schema.get_credentials_fields_info()
if not credentials_fields_info:
return matched_credentials, missing_credentials
# Get user's available credentials
creds_manager = IntegrationCredentialsManager()
available_creds = await creds_manager.store.get_all_creds(user_id)
for field_name, field_info in credentials_fields_info.items():
effective_field_info = field_info
if field_info.discriminator and field_info.discriminator_mapping:
# Get discriminator from input, falling back to schema default
discriminator_value = input_data.get(field_info.discriminator)
if discriminator_value is None:
field = block.input_schema.model_fields.get(
field_info.discriminator
)
if field and field.default is not PydanticUndefined:
discriminator_value = field.default
if (
discriminator_value
and discriminator_value in field_info.discriminator_mapping
):
effective_field_info = field_info.discriminate(discriminator_value)
logger.debug(
f"Discriminated provider for {field_name}: "
f"{discriminator_value} -> {effective_field_info.provider}"
)
matching_cred = next(
(
cred
for cred in available_creds
if cred.provider in effective_field_info.provider
and cred.type in effective_field_info.supported_types
),
None,
)
if matching_cred:
matched_credentials[field_name] = CredentialsMetaInput(
id=matching_cred.id,
provider=matching_cred.provider, # type: ignore
type=matching_cred.type,
title=matching_cred.title,
)
else:
# Create a placeholder for the missing credential
provider = next(iter(effective_field_info.provider), "unknown")
cred_type = next(iter(effective_field_info.supported_types), "api_key")
missing_credentials.append(
CredentialsMetaInput(
id=field_name,
provider=provider, # type: ignore
type=cred_type, # type: ignore
title=field_name.replace("_", " ").title(),
)
)
return matched_credentials, missing_credentials
async def _execute(
self,
user_id: str | None,
@@ -151,8 +232,8 @@ class RunBlockTool(BaseTool):
logger.info(f"Executing block {block.name} ({block_id}) for user {user_id}")
creds_manager = IntegrationCredentialsManager()
matched_credentials, missing_credentials = (
await self._resolve_block_credentials(user_id, block, input_data)
matched_credentials, missing_credentials = await self._check_block_credentials(
user_id, block, input_data
)
if missing_credentials:
@@ -281,75 +362,29 @@ class RunBlockTool(BaseTool):
session_id=session_id,
)
async def _resolve_block_credentials(
self,
user_id: str,
block: AnyBlockSchema,
input_data: dict[str, Any] | None = None,
) -> tuple[dict[str, CredentialsMetaInput], list[CredentialsMetaInput]]:
"""
Resolve credentials for a block by matching user's available credentials.
Args:
user_id: User ID
block: Block to resolve credentials for
input_data: Input data for the block (used to determine provider via discriminator)
Returns:
tuple of (matched_credentials, missing_credentials) - matched credentials
are used for block execution, missing ones indicate setup requirements.
"""
input_data = input_data or {}
requirements = self._resolve_discriminated_credentials(block, input_data)
if not requirements:
return {}, []
return await match_credentials_to_requirements(user_id, requirements)
def _get_inputs_list(self, block: AnyBlockSchema) -> list[dict[str, Any]]:
def _get_inputs_list(self, block: Any) -> list[dict[str, Any]]:
"""Extract non-credential inputs from block schema."""
inputs_list = []
schema = block.input_schema.jsonschema()
properties = schema.get("properties", {})
required_fields = set(schema.get("required", []))
# Get credential field names to exclude
credentials_fields = set(block.input_schema.get_credentials_fields().keys())
return get_inputs_from_schema(schema, exclude_fields=credentials_fields)
def _resolve_discriminated_credentials(
self,
block: AnyBlockSchema,
input_data: dict[str, Any],
) -> dict[str, CredentialsFieldInfo]:
"""Resolve credential requirements, applying discriminator logic where needed."""
credentials_fields_info = block.input_schema.get_credentials_fields_info()
if not credentials_fields_info:
return {}
for field_name, field_schema in properties.items():
# Skip credential fields
if field_name in credentials_fields:
continue
resolved: dict[str, CredentialsFieldInfo] = {}
inputs_list.append(
{
"name": field_name,
"title": field_schema.get("title", field_name),
"type": field_schema.get("type", "string"),
"description": field_schema.get("description", ""),
"required": field_name in required_fields,
}
)
for field_name, field_info in credentials_fields_info.items():
effective_field_info = field_info
if field_info.discriminator and field_info.discriminator_mapping:
discriminator_value = input_data.get(field_info.discriminator)
if discriminator_value is None:
field = block.input_schema.model_fields.get(
field_info.discriminator
)
if field and field.default is not PydanticUndefined:
discriminator_value = field.default
if (
discriminator_value
and discriminator_value in field_info.discriminator_mapping
):
effective_field_info = field_info.discriminate(discriminator_value)
# For host-scoped credentials, add the discriminator value
# (e.g., URL) so _credential_is_for_host can match it
effective_field_info.discriminator_values.add(discriminator_value)
logger.debug(
f"Discriminated provider for {field_name}: "
f"{discriminator_value} -> {effective_field_info.provider}"
)
resolved[field_name] = effective_field_info
return resolved
return inputs_list

View File

@@ -8,7 +8,6 @@ from backend.api.features.library import model as library_model
from backend.api.features.store import db as store_db
from backend.data.graph import GraphModel
from backend.data.model import (
Credentials,
CredentialsFieldInfo,
CredentialsMetaInput,
HostScopedCredentials,
@@ -224,99 +223,6 @@ async def get_or_create_library_agent(
return library_agents[0]
async def match_credentials_to_requirements(
user_id: str,
requirements: dict[str, CredentialsFieldInfo],
) -> tuple[dict[str, CredentialsMetaInput], list[CredentialsMetaInput]]:
"""
Match user's credentials against a dictionary of credential requirements.
This is the core matching logic shared by both graph and block credential matching.
"""
matched: dict[str, CredentialsMetaInput] = {}
missing: list[CredentialsMetaInput] = []
if not requirements:
return matched, missing
available_creds = await get_user_credentials(user_id)
for field_name, field_info in requirements.items():
matching_cred = find_matching_credential(available_creds, field_info)
if matching_cred:
try:
matched[field_name] = create_credential_meta_from_match(matching_cred)
except Exception as e:
logger.error(
f"Failed to create CredentialsMetaInput for field '{field_name}': "
f"provider={matching_cred.provider}, type={matching_cred.type}, "
f"credential_id={matching_cred.id}",
exc_info=True,
)
provider = next(iter(field_info.provider), "unknown")
cred_type = next(iter(field_info.supported_types), "api_key")
missing.append(
CredentialsMetaInput(
id=field_name,
provider=provider, # type: ignore
type=cred_type, # type: ignore
title=f"{field_name} (validation failed: {e})",
)
)
else:
provider = next(iter(field_info.provider), "unknown")
cred_type = next(iter(field_info.supported_types), "api_key")
missing.append(
CredentialsMetaInput(
id=field_name,
provider=provider, # type: ignore
type=cred_type, # type: ignore
title=field_name.replace("_", " ").title(),
)
)
return matched, missing
async def get_user_credentials(user_id: str) -> list[Credentials]:
"""Get all available credentials for a user."""
creds_manager = IntegrationCredentialsManager()
return await creds_manager.store.get_all_creds(user_id)
def find_matching_credential(
available_creds: list[Credentials],
field_info: CredentialsFieldInfo,
) -> Credentials | None:
"""Find a credential that matches the required provider, type, scopes, and host."""
for cred in available_creds:
if cred.provider not in field_info.provider:
continue
if cred.type not in field_info.supported_types:
continue
if cred.type == "oauth2" and not _credential_has_required_scopes(
cred, field_info
):
continue
if cred.type == "host_scoped" and not _credential_is_for_host(cred, field_info):
continue
return cred
return None
def create_credential_meta_from_match(
matching_cred: Credentials,
) -> CredentialsMetaInput:
"""Create a CredentialsMetaInput from a matched credential."""
return CredentialsMetaInput(
id=matching_cred.id,
provider=matching_cred.provider, # type: ignore
type=matching_cred.type,
title=matching_cred.title,
)
async def match_user_credentials_to_graph(
user_id: str,
graph: GraphModel,
@@ -425,6 +331,8 @@ def _credential_has_required_scopes(
# If no scopes are required, any credential matches
if not requirements.required_scopes:
return True
# Check that credential scopes are a superset of required scopes
return set(credential.scopes).issuperset(requirements.required_scopes)

View File

@@ -1,4 +1,3 @@
import asyncio
import logging
from abc import ABC, abstractmethod
from enum import Enum
@@ -226,10 +225,6 @@ class SyncRabbitMQ(RabbitMQBase):
class AsyncRabbitMQ(RabbitMQBase):
"""Asynchronous RabbitMQ client"""
def __init__(self, config: RabbitMQConfig):
super().__init__(config)
self._reconnect_lock: asyncio.Lock | None = None
@property
def is_connected(self) -> bool:
return bool(self._connection and not self._connection.is_closed)
@@ -240,17 +235,7 @@ class AsyncRabbitMQ(RabbitMQBase):
@conn_retry("AsyncRabbitMQ", "Acquiring async connection")
async def connect(self):
if self.is_connected and self._channel and not self._channel.is_closed:
return
if (
self.is_connected
and self._connection
and (self._channel is None or self._channel.is_closed)
):
self._channel = await self._connection.channel()
await self._channel.set_qos(prefetch_count=1)
await self.declare_infrastructure()
if self.is_connected:
return
self._connection = await aio_pika.connect_robust(
@@ -306,46 +291,24 @@ class AsyncRabbitMQ(RabbitMQBase):
exchange, routing_key=queue.routing_key or queue.name
)
@property
def _lock(self) -> asyncio.Lock:
if self._reconnect_lock is None:
self._reconnect_lock = asyncio.Lock()
return self._reconnect_lock
async def _ensure_channel(self) -> aio_pika.abc.AbstractChannel:
"""Get a valid channel, reconnecting if the current one is stale.
Uses a lock to prevent concurrent reconnection attempts from racing.
"""
if self.is_ready:
return self._channel # type: ignore # is_ready guarantees non-None
async with self._lock:
# Double-check after acquiring lock
if self.is_ready:
return self._channel # type: ignore
self._channel = None
await self.connect()
if self._channel is None:
raise RuntimeError("Channel should be established after connect")
return self._channel
async def _publish_once(
@func_retry
async def publish_message(
self,
routing_key: str,
message: str,
exchange: Optional[Exchange] = None,
persistent: bool = True,
) -> None:
channel = await self._ensure_channel()
if not self.is_ready:
await self.connect()
if self._channel is None:
raise RuntimeError("Channel should be established after connect")
if exchange:
exchange_obj = await channel.get_exchange(exchange.name)
exchange_obj = await self._channel.get_exchange(exchange.name)
else:
exchange_obj = channel.default_exchange
exchange_obj = self._channel.default_exchange
await exchange_obj.publish(
aio_pika.Message(
@@ -359,23 +322,9 @@ class AsyncRabbitMQ(RabbitMQBase):
routing_key=routing_key,
)
@func_retry
async def publish_message(
self,
routing_key: str,
message: str,
exchange: Optional[Exchange] = None,
persistent: bool = True,
) -> None:
try:
await self._publish_once(routing_key, message, exchange, persistent)
except aio_pika.exceptions.ChannelInvalidStateError:
logger.warning(
"RabbitMQ channel invalid, forcing reconnect and retrying publish"
)
async with self._lock:
self._channel = None
await self._publish_once(routing_key, message, exchange, persistent)
async def get_channel(self) -> aio_pika.abc.AbstractChannel:
return await self._ensure_channel()
if not self.is_ready:
await self.connect()
if self._channel is None:
raise RuntimeError("Channel should be established after connect")
return self._channel

View File

@@ -104,31 +104,7 @@ export function FileInput(props: Props) {
return false;
}
const getFileLabelFromValue = (val: unknown): string => {
// Handle object format from external API: { name, type, size, data }
if (val && typeof val === "object") {
const obj = val as Record<string, unknown>;
if (typeof obj.name === "string") {
return getFileLabel(
obj.name,
typeof obj.type === "string" ? obj.type : "",
);
}
if (typeof obj.type === "string") {
const mimeParts = obj.type.split("/");
if (mimeParts.length > 1) {
return `${mimeParts[1].toUpperCase()} file`;
}
return `${obj.type} file`;
}
return "File";
}
// Handle string values (data URIs or file paths)
if (typeof val !== "string") {
return "File";
}
const getFileLabelFromValue = (val: string) => {
if (val.startsWith("data:")) {
const matches = val.match(/^data:([^;]+);/);
if (matches?.[1]) {