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open-swe[bot]
@@ -515,15 +515,15 @@ def create_react_agent(
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actual_schema = response_format
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if isinstance(response_format, tuple):
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_, actual_schema = response_format
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# Get the schema name for the tool
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if hasattr(actual_schema, '__name__'):
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if hasattr(actual_schema, "__name__"):
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response_tool_name = actual_schema.__name__
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elif isinstance(actual_schema, dict) and 'title' in actual_schema:
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response_tool_name = actual_schema['title']
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elif isinstance(actual_schema, dict) and "title" in actual_schema:
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response_tool_name = actual_schema["title"]
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else:
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response_tool_name = "ResponseSchema"
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# Add the schema as a tool for binding to the model
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tool_classes.append(actual_schema)
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@@ -570,7 +570,9 @@ def create_react_agent(
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if is_dynamic_model:
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resolved_model = model(state, runtime) # type: ignore[operator]
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if (
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_should_bind_tools(resolved_model, tool_classes, num_builtin=len(llm_builtin_tools)) # type: ignore[arg-type]
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_should_bind_tools(
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resolved_model, tool_classes, num_builtin=len(llm_builtin_tools)
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) # type: ignore[arg-type]
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and len(tool_classes + llm_builtin_tools) > 0
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):
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resolved_model = cast(BaseChatModel, resolved_model).bind_tools(
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@@ -587,7 +589,9 @@ def create_react_agent(
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if is_async_dynamic_model:
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resolved_model = await model(state, runtime) # type: ignore[misc,operator]
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if (
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_should_bind_tools(resolved_model, tool_classes, num_builtin=len(llm_builtin_tools)) # type: ignore[arg-type]
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_should_bind_tools(
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resolved_model, tool_classes, num_builtin=len(llm_builtin_tools)
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) # type: ignore[arg-type]
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and len(tool_classes + llm_builtin_tools) > 0
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):
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resolved_model = cast(BaseChatModel, resolved_model).bind_tools(
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@@ -597,7 +601,9 @@ def create_react_agent(
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elif is_dynamic_model:
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resolved_model = model(state, runtime) # type: ignore[operator]
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if (
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_should_bind_tools(resolved_model, tool_classes, num_builtin=len(llm_builtin_tools)) # type: ignore[arg-type]
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_should_bind_tools(
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resolved_model, tool_classes, num_builtin=len(llm_builtin_tools)
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) # type: ignore[arg-type]
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and len(tool_classes + llm_builtin_tools) > 0
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):
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resolved_model = cast(BaseChatModel, resolved_model).bind_tools(
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@@ -731,54 +737,51 @@ def create_react_agent(
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else:
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input_schema = state_schema
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def respond(
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state: StateSchema, runtime: Runtime[ContextT], config: RunnableConfig
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) -> StateSchema:
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"""Handle structured response creation when response schema tool is called."""
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messages = _get_state_value(state, "messages")
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last_message = messages[-1]
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if not isinstance(last_message, AIMessage) or not last_message.tool_calls:
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raise ValueError("Expected last message to be AIMessage with tool calls")
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# Find the response schema tool call
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response_tool_call = None
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for tool_call in last_message.tool_calls:
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if tool_call["name"] == response_tool_name:
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response_tool_call = tool_call
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break
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if response_tool_call is None:
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raise ValueError(f"Expected tool call with name '{response_tool_name}'")
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# Extract the actual schema from tuple if needed
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actual_schema = response_format
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if isinstance(response_format, tuple):
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_, actual_schema = response_format
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# Coerce tool call arguments into response schema
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try:
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if hasattr(actual_schema, '__call__'):
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if hasattr(actual_schema, "__call__"):
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# For BaseModel classes
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structured_response = actual_schema(**response_tool_call["args"])
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else:
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# For dict schemas, just return the args
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structured_response = response_tool_call["args"]
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except Exception as e:
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raise ValueError(f"Failed to coerce tool call args into response schema: {e}")
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raise ValueError(
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f"Failed to coerce tool call args into response schema: {e}"
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)
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# Create artificial tool message
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tool_message = ToolMessage(
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content="Here is your structured response",
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tool_call_id=response_tool_call["id"]
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tool_call_id=response_tool_call["id"],
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)
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return {
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"messages": [tool_message],
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"structured_response": structured_response
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}
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return {"messages": [tool_message], "structured_response": structured_response}
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async def arespond(
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state: StateSchema, runtime: Runtime[ContextT], config: RunnableConfig
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@@ -786,46 +789,45 @@ def create_react_agent(
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"""Async handle structured response creation when response schema tool is called."""
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messages = _get_state_value(state, "messages")
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last_message = messages[-1]
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if not isinstance(last_message, AIMessage) or not last_message.tool_calls:
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raise ValueError("Expected last message to be AIMessage with tool calls")
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# Find the response schema tool call
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response_tool_call = None
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for tool_call in last_message.tool_calls:
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if tool_call["name"] == response_tool_name:
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response_tool_call = tool_call
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break
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if response_tool_call is None:
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raise ValueError(f"Expected tool call with name '{response_tool_name}'")
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# Extract the actual schema from tuple if needed
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actual_schema = response_format
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if isinstance(response_format, tuple):
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_, actual_schema = response_format
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# Coerce tool call arguments into response schema
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try:
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if hasattr(actual_schema, '__call__'):
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if hasattr(actual_schema, "__call__"):
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# For BaseModel classes
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structured_response = actual_schema(**response_tool_call["args"])
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else:
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# For dict schemas, just return the args
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structured_response = response_tool_call["args"]
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except Exception as e:
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raise ValueError(f"Failed to coerce tool call args into response schema: {e}")
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raise ValueError(
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f"Failed to coerce tool call args into response schema: {e}"
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)
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# Create artificial tool message
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tool_message = ToolMessage(
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content="Here is your structured response",
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tool_call_id=response_tool_call["id"]
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tool_call_id=response_tool_call["id"],
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)
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return {
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"messages": [tool_message],
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"structured_response": structured_response
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}
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return {"messages": [tool_message], "structured_response": structured_response}
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if not tool_calling_enabled:
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# Define a new graph
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@@ -885,7 +887,7 @@ def create_react_agent(
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for tool_call in last_message.tool_calls:
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if tool_call["name"] == response_tool_name:
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return "respond"
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if version == "v1":
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return "tools"
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elif version == "v2":
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@@ -1042,14 +1044,3 @@ __all__ = [
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"AgentStateWithStructuredResponse",
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"AgentStateWithStructuredResponsePydantic",
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]
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