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https://gitee.com/wanwujie/deer-flow
synced 2026-04-04 22:52:13 +08:00
- Implement index-based grouping of tool call chunks in _process_tool_call_chunks() - Add _validate_tool_call_chunks() for debug logging and validation - Enhance _process_message_chunk() with tool call ID validation and boundary detection - Add comprehensive unit tests (17 tests) for tool call chunk processing - Fix issue where tool names were incorrectly concatenated (e.g., 'web_searchweb_search') - Ensure chunks from different tool calls (different indices) remain properly separated - Add detailed logging for debugging tool call streaming issues * update the code with suggestions of reviewing
This commit is contained in:
Willem Jiang
@@ -132,19 +132,122 @@ async def chat_stream(request: ChatRequest):
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)
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def _validate_tool_call_chunks(tool_call_chunks):
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"""Validate and log tool call chunk structure for debugging."""
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if not tool_call_chunks:
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return
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logger.debug(f"Validating tool_call_chunks: count={len(tool_call_chunks)}")
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indices_seen = set()
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tool_ids_seen = set()
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for i, chunk in enumerate(tool_call_chunks):
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index = chunk.get("index")
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tool_id = chunk.get("id")
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name = chunk.get("name", "")
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has_args = "args" in chunk
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logger.debug(
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f"Chunk {i}: index={index}, id={tool_id}, name={name}, "
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f"has_args={has_args}, type={chunk.get('type')}"
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)
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if index is not None:
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indices_seen.add(index)
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if tool_id:
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tool_ids_seen.add(tool_id)
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if len(indices_seen) > 1:
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logger.debug(
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f"Multiple indices detected: {sorted(indices_seen)} - "
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f"This may indicate consecutive tool calls"
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)
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def _process_tool_call_chunks(tool_call_chunks):
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"""Process tool call chunks and sanitize arguments."""
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"""
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Process tool call chunks with proper index-based grouping.
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This function handles the concatenation of tool call chunks that belong
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to the same tool call (same index) while properly segregating chunks
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from different tool calls (different indices).
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The issue: In streaming, LangChain's ToolCallChunk concatenates string
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attributes (name, args) when chunks have the same index. We need to:
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1. Group chunks by index
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2. Detect index collisions with different tool names
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3. Accumulate arguments for the same index
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4. Return properly segregated tool calls
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"""
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if not tool_call_chunks:
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return []
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_validate_tool_call_chunks(tool_call_chunks)
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chunks = []
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chunk_by_index = {} # Group chunks by index to handle streaming accumulation
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for chunk in tool_call_chunks:
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chunks.append(
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{
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index = chunk.get("index")
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chunk_id = chunk.get("id")
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if index is not None:
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# Create or update entry for this index
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if index not in chunk_by_index:
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chunk_by_index[index] = {
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"name": "",
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"args": "",
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"id": chunk_id or "",
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"index": index,
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"type": chunk.get("type", ""),
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}
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# Validate and accumulate tool name
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chunk_name = chunk.get("name", "")
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if chunk_name:
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stored_name = chunk_by_index[index]["name"]
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# Check for index collision with different tool names
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if stored_name and stored_name != chunk_name:
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logger.warning(
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f"Tool name mismatch detected at index {index}: "
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f"'{stored_name}' != '{chunk_name}'. "
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f"This may indicate a streaming artifact or consecutive tool calls "
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f"with the same index assignment."
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)
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# Keep the first name to prevent concatenation
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else:
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chunk_by_index[index]["name"] = chunk_name
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# Update ID if new one provided
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if chunk_id and not chunk_by_index[index]["id"]:
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chunk_by_index[index]["id"] = chunk_id
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# Accumulate arguments
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if chunk.get("args"):
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chunk_by_index[index]["args"] += chunk.get("args", "")
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else:
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# Handle chunks without explicit index (edge case)
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logger.debug(f"Chunk without index encountered: {chunk}")
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chunks.append({
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"name": chunk.get("name", ""),
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"args": sanitize_args(chunk.get("args", "")),
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"id": chunk.get("id", ""),
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"index": chunk.get("index", 0),
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"index": 0,
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"type": chunk.get("type", ""),
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}
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})
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# Convert indexed chunks to list, sorted by index for proper order
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for index in sorted(chunk_by_index.keys()):
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chunk_data = chunk_by_index[index]
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chunk_data["args"] = sanitize_args(chunk_data["args"])
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chunks.append(chunk_data)
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logger.debug(
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f"Processed tool call: index={index}, name={chunk_data['name']}, "
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f"id={chunk_data['id']}"
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)
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return chunks
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@@ -236,22 +339,63 @@ async def _process_message_chunk(message_chunk, message_metadata, thread_id, age
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if isinstance(message_chunk, ToolMessage):
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# Tool Message - Return the result of the tool call
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event_stream_message["tool_call_id"] = message_chunk.tool_call_id
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tool_call_id = message_chunk.tool_call_id
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event_stream_message["tool_call_id"] = tool_call_id
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# Validate tool_call_id for debugging
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if tool_call_id:
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logger.debug(f"Processing ToolMessage with tool_call_id: {tool_call_id}")
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else:
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logger.warning("ToolMessage received without tool_call_id")
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yield _make_event("tool_call_result", event_stream_message)
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elif isinstance(message_chunk, AIMessageChunk):
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# AI Message - Raw message tokens
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if message_chunk.tool_calls:
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# AI Message - Tool Call
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# AI Message - Tool Call (complete tool calls)
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event_stream_message["tool_calls"] = message_chunk.tool_calls
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event_stream_message["tool_call_chunks"] = _process_tool_call_chunks(
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# Process tool_call_chunks with proper index-based grouping
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processed_chunks = _process_tool_call_chunks(
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message_chunk.tool_call_chunks
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)
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if processed_chunks:
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event_stream_message["tool_call_chunks"] = processed_chunks
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logger.debug(
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f"Tool calls: {[tc.get('name') for tc in message_chunk.tool_calls]}, "
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f"Processed chunks: {len(processed_chunks)}"
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)
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yield _make_event("tool_calls", event_stream_message)
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elif message_chunk.tool_call_chunks:
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# AI Message - Tool Call Chunks
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event_stream_message["tool_call_chunks"] = _process_tool_call_chunks(
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# AI Message - Tool Call Chunks (streaming)
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processed_chunks = _process_tool_call_chunks(
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message_chunk.tool_call_chunks
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)
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# Emit separate events for chunks with different indices (tool call boundaries)
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if processed_chunks:
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prev_chunk = None
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for chunk in processed_chunks:
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current_index = chunk.get("index")
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# Log index transitions to detect tool call boundaries
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if prev_chunk is not None and current_index != prev_chunk.get("index"):
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logger.debug(
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f"Tool call boundary detected: "
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f"index {prev_chunk.get('index')} ({prev_chunk.get('name')}) -> "
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f"{current_index} ({chunk.get('name')})"
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)
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prev_chunk = chunk
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# Include all processed chunks in the event
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event_stream_message["tool_call_chunks"] = processed_chunks
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logger.debug(
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f"Streamed {len(processed_chunks)} tool call chunk(s): "
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f"{[c.get('name') for c in processed_chunks]}"
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)
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yield _make_event("tool_call_chunks", event_stream_message)
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else:
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# AI Message - Raw message tokens
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