ai-agents-tool-calling-workaro-when-using-langchain-with-vllm-s-openai-compatible-7275fe35

THEN Implement a custom parser that strips the '<|python_tag|>' prefix from the AIMessage content and attempts to parse the remaining JSON into a ToolCall object with name and parameters.

from langchain.schema import AIMessage
from langchain_core.runnables import RunnableLambda
import json

def parse_tool_call(x):
    if isinstance(x, AIMessage):
        if x.content.startswith('<|python_tag|>'):
            x.content = x.content.replace('<|python_tag|>', '')
        try:
            parsed = json.loads(x.content)
            if parsed.get('name') and parsed.get('parameters'):
                from langchain_core.messages import ToolCall
                x.tool_calls = [ToolCall(name=parsed['name'], args=parsed['parameters'], id=x.id)]
        except json.JSONDecodeError:
            pass
    return x

chain = llm_with_tools | RunnableLambda(parse_tool_call)