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@@ -4163,25 +4163,26 @@ async def streaming_chat_response_handler(response, ctx):
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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(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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if tool_args and tool_args.strip():
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try:
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tool_function_params = json.loads(tool_args)
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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(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_args}"
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)
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results.append(
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{
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"tool_call_id": tool_call_id,
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"content": f"Error: Tool call arguments could not be parsed. The model generated malformed or incomplete JSON for `{tool_function_name}`. Please try again.",
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}
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)
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continue
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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(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_args}"
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)
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results.append(
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{
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"tool_call_id": tool_call_id,
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"content": f"Error: Tool call arguments could not be parsed. The model generated malformed or incomplete JSON for `{tool_function_name}`. Please try again.",
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}
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)
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continue
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# Ensure arguments are valid JSON for downstream LLM integrations
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log.debug(
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