mirror of https://github.com/langgenius/dify.git
feat: add tool call time
This commit is contained in:
parent
152fd52cd7
commit
f3e7fea628
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@ -200,7 +200,8 @@ class AgentPattern(ABC):
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log.metadata = {
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**log.metadata,
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AgentLog.LogMetadata.FINISHED_AT: finished_at,
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AgentLog.LogMetadata.ELAPSED_TIME: finished_at - started_at,
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# Calculate elapsed time in seconds
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AgentLog.LogMetadata.ELAPSED_TIME: round(finished_at - started_at, 4),
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}
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# Add usage information if provided
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@ -160,6 +160,7 @@ class StreamEventBuffer:
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"name": tool_name or "",
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"arguments": tool_arguments or "",
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"result": "",
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"elapsed_time": None,
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}
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self.tool_calls.append(tool_call)
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idx = len(self.tool_calls) - 1
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@ -168,13 +169,14 @@ class StreamEventBuffer:
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self._last_event_type = "tool_call"
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def record_tool_result(self, tool_call_id: str, result: str) -> None:
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def record_tool_result(self, tool_call_id: str, result: str, tool_elapsed_time: float | None = None) -> None:
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"""Record a tool result event (update existing tool call)."""
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if not tool_call_id:
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return
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if tool_call_id in self._tool_call_id_map:
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idx = self._tool_call_id_map[tool_call_id]
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self.tool_calls[idx]["result"] = result
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self.tool_calls[idx]["elapsed_time"] = tool_elapsed_time
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def finalize(self) -> None:
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"""Finalize the buffer, flushing any pending data."""
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@ -523,7 +525,7 @@ class AdvancedChatAppGenerateTaskPipeline(GraphRuntimeStateSupport):
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tool_name = tool_payload.name if tool_payload and tool_payload.name else ""
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tool_arguments = tool_call.arguments if tool_call and tool_call.arguments else ""
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tool_files = tool_result.files if tool_result else []
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tool_elapsed_time = tool_result.elapsed_time if tool_result else None
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# Record stream event based on chunk type
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chunk_type = event.chunk_type or ChunkType.TEXT
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match chunk_type:
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@ -543,6 +545,7 @@ class AdvancedChatAppGenerateTaskPipeline(GraphRuntimeStateSupport):
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self._stream_buffer.record_tool_result(
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tool_call_id=tool_call_id,
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result=delta_text,
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tool_elapsed_time=tool_elapsed_time,
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)
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self._task_state.answer += delta_text
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@ -555,6 +558,7 @@ class AdvancedChatAppGenerateTaskPipeline(GraphRuntimeStateSupport):
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tool_name=tool_name or None,
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tool_arguments=tool_arguments or None,
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tool_files=tool_files,
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tool_elapsed_time=tool_elapsed_time,
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)
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def _handle_iteration_start_event(
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@ -490,6 +490,7 @@ class WorkflowAppGenerateTaskPipeline(GraphRuntimeStateSupport):
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tool_call_id = tool_payload.id if tool_payload and tool_payload.id else None
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tool_name = tool_payload.name if tool_payload and tool_payload.name else None
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tool_arguments = tool_call.arguments if tool_call else None
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tool_elapsed_time = tool_result.elapsed_time if tool_result else None
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tool_files = tool_result.files if tool_result else []
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# only publish tts message at text chunk streaming
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@ -504,6 +505,7 @@ class WorkflowAppGenerateTaskPipeline(GraphRuntimeStateSupport):
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tool_name=tool_name,
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tool_arguments=tool_arguments,
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tool_files=tool_files,
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tool_elapsed_time=tool_elapsed_time,
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)
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def _handle_agent_log_event(self, event: QueueAgentLogEvent, **kwargs) -> Generator[StreamResponse, None, None]:
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@ -676,6 +678,7 @@ class WorkflowAppGenerateTaskPipeline(GraphRuntimeStateSupport):
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tool_arguments: str | None = None,
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tool_files: list[str] | None = None,
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tool_error: str | None = None,
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tool_elapsed_time: float | None = None,
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) -> TextChunkStreamResponse:
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"""
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Handle completed event.
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@ -684,18 +687,37 @@ class WorkflowAppGenerateTaskPipeline(GraphRuntimeStateSupport):
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"""
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from core.app.entities.task_entities import ChunkType as ResponseChunkType
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response_chunk_type = ResponseChunkType(chunk_type.value) if chunk_type else ResponseChunkType.TEXT
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data = TextChunkStreamResponse.Data(
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text=text,
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from_variable_selector=from_variable_selector,
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chunk_type=response_chunk_type,
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)
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if response_chunk_type == ResponseChunkType.TOOL_CALL:
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data = data.model_copy(
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update={
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"tool_call_id": tool_call_id,
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"tool_name": tool_name,
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"tool_arguments": tool_arguments,
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}
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)
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elif response_chunk_type == ResponseChunkType.TOOL_RESULT:
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data = data.model_copy(
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update={
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"tool_call_id": tool_call_id,
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"tool_name": tool_name,
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"tool_arguments": tool_arguments,
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"tool_files": tool_files,
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"tool_error": tool_error,
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"tool_elapsed_time": tool_elapsed_time,
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}
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)
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response = TextChunkStreamResponse(
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task_id=self._application_generate_entity.task_id,
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data=TextChunkStreamResponse.Data(
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text=text,
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from_variable_selector=from_variable_selector,
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chunk_type=ResponseChunkType(chunk_type.value) if chunk_type else ResponseChunkType.TEXT,
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tool_call_id=tool_call_id,
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tool_name=tool_name,
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tool_arguments=tool_arguments,
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tool_files=tool_files or [],
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tool_error=tool_error,
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),
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data=data,
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)
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return response
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@ -42,6 +42,7 @@ class ToolCallDetail(BaseModel):
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name: str = Field(..., description="Name of the tool")
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arguments: str = Field(default="", description="JSON string of tool arguments")
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result: str = Field(default="", description="Result from the tool execution")
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elapsed_time: float | None = Field(default=None, description="Elapsed time in seconds")
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class LLMGenerationDetailData(BaseModel):
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@ -130,6 +130,16 @@ class MessageStreamResponse(StreamResponse):
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"""file IDs produced by tool"""
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tool_error: str | None = None
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"""error message if tool failed"""
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tool_elapsed_time: float | None = None
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"""elapsed time spent executing the tool"""
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def model_dump(self, *args, **kwargs) -> dict[str, object]:
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kwargs.setdefault("exclude_none", True)
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return super().model_dump(*args, **kwargs)
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def model_dump_json(self, *args, **kwargs) -> str:
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kwargs.setdefault("exclude_none", True)
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return super().model_dump_json(*args, **kwargs)
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class MessageAudioStreamResponse(StreamResponse):
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@ -635,11 +645,23 @@ class TextChunkStreamResponse(StreamResponse):
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"""accumulated tool arguments JSON"""
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# Tool result fields (when chunk_type == TOOL_RESULT)
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tool_files: list[str] = Field(default_factory=list)
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tool_files: list[str] | None = None
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"""file IDs produced by tool"""
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tool_error: str | None = None
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"""error message if tool failed"""
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# Tool elapsed time fields (when chunk_type == TOOL_RESULT)
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tool_elapsed_time: float | None = None
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"""elapsed time spent executing the tool"""
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def model_dump(self, *args, **kwargs) -> dict[str, object]:
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kwargs.setdefault("exclude_none", True)
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return super().model_dump(*args, **kwargs)
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def model_dump_json(self, *args, **kwargs) -> str:
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kwargs.setdefault("exclude_none", True)
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return super().model_dump_json(*args, **kwargs)
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event: StreamEvent = StreamEvent.TEXT_CHUNK
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data: Data
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@ -238,6 +238,7 @@ class MessageCycleManager:
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tool_arguments: str | None = None,
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tool_files: list[str] | None = None,
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tool_error: str | None = None,
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tool_elapsed_time: float | None = None,
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event_type: StreamEvent | None = None,
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) -> MessageStreamResponse:
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"""
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@ -253,20 +254,39 @@ class MessageCycleManager:
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:param tool_error: error message if tool failed
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:return:
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"""
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return MessageStreamResponse(
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response = MessageStreamResponse(
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task_id=self._application_generate_entity.task_id,
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id=message_id,
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answer=answer,
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from_variable_selector=from_variable_selector,
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chunk_type=chunk_type,
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tool_call_id=tool_call_id,
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tool_name=tool_name,
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tool_arguments=tool_arguments,
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tool_files=tool_files,
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tool_error=tool_error,
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event=event_type or StreamEvent.MESSAGE,
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)
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if chunk_type:
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response = response.model_copy(update={"chunk_type": chunk_type})
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if chunk_type == "tool_call":
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response = response.model_copy(
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update={
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"tool_call_id": tool_call_id,
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"tool_name": tool_name,
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"tool_arguments": tool_arguments,
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}
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)
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elif chunk_type == "tool_result":
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response = response.model_copy(
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update={
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"tool_call_id": tool_call_id,
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"tool_name": tool_name,
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"tool_arguments": tool_arguments,
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"tool_files": tool_files,
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"tool_error": tool_error,
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"tool_elapsed_time": tool_elapsed_time,
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}
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)
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return response
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def message_replace_to_stream_response(self, answer: str, reason: str = "") -> MessageReplaceStreamResponse:
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"""
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Message replace to stream response.
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@ -22,6 +22,7 @@ class ToolResult(BaseModel):
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output: str | None = Field(default=None, description="Tool output text, error or success message")
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files: list[str] = Field(default_factory=list, description="File produced by tool")
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status: ToolResultStatus | None = Field(default=ToolResultStatus.SUCCESS, description="Tool execution status")
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elapsed_time: float | None = Field(default=None, description="Elapsed seconds spent executing the tool")
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class ToolCallResult(BaseModel):
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@ -31,3 +32,4 @@ class ToolCallResult(BaseModel):
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output: str | None = Field(default=None, description="Tool output text, error or success message")
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files: list[File] = Field(default_factory=list, description="File produced by tool")
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status: ToolResultStatus = Field(default=ToolResultStatus.SUCCESS, description="Tool execution status")
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elapsed_time: float | None = Field(default=None, description="Elapsed seconds spent executing the tool")
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@ -580,9 +580,10 @@ class Node(Generic[NodeDataT]):
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from core.workflow.entities import ToolResult, ToolResultStatus
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from core.workflow.graph_events import ChunkType
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tool_result = event.tool_result
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status: ToolResultStatus = (
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tool_result.status if tool_result and tool_result.status is not None else ToolResultStatus.SUCCESS
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tool_result = event.tool_result or ToolResult()
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status: ToolResultStatus = tool_result.status or ToolResultStatus.SUCCESS
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tool_result = tool_result.model_copy(
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update={"status": status, "files": tool_result.files or []},
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)
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return NodeRunStreamChunkEvent(
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@ -593,13 +594,7 @@ class Node(Generic[NodeDataT]):
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chunk=event.chunk,
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is_final=event.is_final,
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chunk_type=ChunkType.TOOL_RESULT,
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tool_result=ToolResult(
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id=tool_result.id if tool_result else None,
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name=tool_result.name if tool_result else None,
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output=tool_result.output if tool_result else None,
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files=tool_result.files if tool_result else [],
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status=status,
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),
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tool_result=tool_result,
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)
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@_dispatch.register
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@ -1649,6 +1649,7 @@ class LLMNode(Node[LLMNodeData]):
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"output": tool_call.output,
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"files": files,
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"status": tool_call.status.value if hasattr(tool_call.status, "value") else tool_call.status,
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"elapsed_time": tool_call.elapsed_time,
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}
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def _flush_thought_segment(self, buffers: StreamBuffers, trace_state: TraceState) -> None:
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@ -1707,6 +1708,7 @@ class LLMNode(Node[LLMNodeData]):
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id=tool_call_id,
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name=tool_name,
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arguments=tool_arguments,
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elapsed_time=output.metadata.get(AgentLog.LogMetadata.ELAPSED_TIME) if output.metadata else None,
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),
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)
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trace_state.trace_segments.append(tool_call_segment)
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@ -1755,6 +1757,7 @@ class LLMNode(Node[LLMNodeData]):
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id=tool_call_id,
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name=tool_name,
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arguments=None,
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elapsed_time=output.metadata.get(AgentLog.LogMetadata.ELAPSED_TIME) if output.metadata else None,
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),
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)
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if existing_tool_segment is None:
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@ -1767,6 +1770,7 @@ class LLMNode(Node[LLMNodeData]):
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id=tool_call_id,
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name=tool_name,
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arguments=None,
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elapsed_time=output.metadata.get(AgentLog.LogMetadata.ELAPSED_TIME) if output.metadata else None,
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)
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tool_call_segment.tool_call.output = (
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str(tool_output) if tool_output is not None else str(tool_error) if tool_error is not None else None
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@ -1785,6 +1789,7 @@ class LLMNode(Node[LLMNodeData]):
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output=result_output,
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files=tool_files,
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status=ToolResultStatus.ERROR if tool_error else ToolResultStatus.SUCCESS,
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elapsed_time=output.metadata.get(AgentLog.LogMetadata.ELAPSED_TIME) if output.metadata else None,
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),
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is_final=False,
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)
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@ -1960,6 +1965,7 @@ class LLMNode(Node[LLMNodeData]):
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arguments=json.dumps(tool_args) if tool_args else "",
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output=result_text,
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status=status,
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elapsed_time=log.metadata.get(AgentLog.LogMetadata.ELAPSED_TIME) if log.metadata else None,
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)
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)
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