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groq[patch]: Make stream robust to ToolMessage (#20417)
```python from langchain.agents import AgentExecutor, create_tool_calling_agent, tool from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder from langchain_groq import ChatGroq prompt = ChatPromptTemplate.from_messages( [ ("system", "You are a helpful assistant"), ("human", "{input}"), MessagesPlaceholder("agent_scratchpad"), ] ) model = ChatGroq(model_name="mixtral-8x7b-32768", temperature=0) @tool def magic_function(input: int) -> int: """Applies a magic function to an input.""" return input + 2 tools = [magic_function] agent = create_tool_calling_agent(model, tools, prompt) agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True) agent_executor.invoke({"input": "what is the value of magic_function(3)?"}) ``` ``` > Entering new AgentExecutor chain... Invoking: `magic_function` with `{'input': 3}` 5The value of magic\_function(3) is 5. > Finished chain. {'input': 'what is the value of magic_function(3)?', 'output': 'The value of magic\\_function(3) is 5.'} ```
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@ -287,7 +287,7 @@ class ChatGroq(BaseChatModel):
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"id": rtc.get("id"),
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"index": rtc.get("index"),
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}
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for rtc in message.additional_kwargs["tool_calls"]
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for rtc in message.additional_kwargs.get("tool_calls", [])
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]
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chunk_ = ChatGenerationChunk(
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message=AIMessageChunk(
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@ -358,7 +358,7 @@ class ChatGroq(BaseChatModel):
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"id": rtc.get("id"),
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"index": rtc.get("index"),
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}
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for rtc in message.additional_kwargs["tool_calls"]
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for rtc in message.additional_kwargs.get("tool_calls", [])
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]
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chunk_ = ChatGenerationChunk(
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message=AIMessageChunk(
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