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@@ -2065,33 +2065,33 @@ async def process_chat_response(
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for tool_call in response_tool_calls:
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tool_call_id = tool_call.get("id", "")
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tool_name = tool_call.get("function", {}).get("name", "")
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- tool_call_args = tool_call.get("function", {}).get("arguments", "{}")
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+ tool_args = tool_call.get("function", {}).get("arguments", "{}")
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tool_function_params = {}
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try:
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# json.loads cannot be used because some models do not produce valid JSON
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- tool_function_params = ast.literal_eval(
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- tool_call_args
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- )
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+ tool_function_params = ast.literal_eval(tool_args)
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except Exception as e:
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log.debug(e)
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# Fallback to JSON parsing
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try:
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- tool_function_params = json.loads(
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- tool_call_args
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- )
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+ tool_function_params = json.loads(tool_args)
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except Exception as e:
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log.error(
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- f"Error parsing tool call arguments: {tool_call_args}"
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+ f"Error parsing tool call arguments: {tool_args}"
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)
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# Mutate the original tool call response params as they are passed back to the passed
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- # back to the LLM via the content blocks. If they are in a json block and are invalid json,
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+ # back to the LLM via the content blocks. If they are in a json block and are invalid json,
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# this can cause downstream LLM integrations to fail (e.g. bedrock gateway) where response
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# params are not valid json.
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# Main case so far is no args = "" = invalid json.
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- log.debug(f"Parsed args from {tool_call_args} to {tool_function_params}")
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- tool_call.setdefault("function", {})["arguments"] = json.dumps(tool_function_params)
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+ log.debug(
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+ f"Parsed args from {tool_args} to {tool_function_params}"
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+ )
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+ tool_call.setdefault("function", {})["arguments"] = json.dumps(
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+ tool_function_params
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+ )
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tool_result = None
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Timothy Jaeryang Baek