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debug: enhance diagnostic logging to detect args field in tool_calls

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Added more detailed logging to identify if DeepSeek responses include
both 'function.arguments' and 'args' fields, or if tool_calls are
objects vs dicts, to understand why parse_tool_call isn't converting
string args to dict as expected.
This commit is contained in:
Bill Ballou
2025-11-06 12:00:08 -05:00
parent 2e0cf4d507
commit e8939be04e
1 changed files with 20 additions and 10 deletions
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30
agent/chat_model_wrapper.py
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@@ -51,16 +51,26 @@ class ToolCallArgsParsingWrapper:
message = choice['message']
print(f" Message keys: {list(message.keys())}")
if 'tool_calls' in message and message['tool_calls']:
print(f" tool_calls count: {len(message['tool_calls'])}")
for i, tc in enumerate(message['tool_calls'][:2]): # Show first 2
print(f" tool_calls[{i}] keys: {list(tc.keys())}")
if 'function' in tc:
print(f" function keys: {list(tc['function'].keys())}")
if 'arguments' in tc['function']:
args = tc['function']['arguments']
print(f" arguments type: {type(args).__name__}")
print(f" arguments value (first 100 chars): {str(args)[:100]}")
# Check for raw tool_calls in message (before parse_tool_call processing)
if 'tool_calls' in message:
tool_calls_value = message['tool_calls']
print(f" message['tool_calls'] type: {type(tool_calls_value)}")
if tool_calls_value:
print(f" tool_calls count: {len(tool_calls_value)}")
for i, tc in enumerate(tool_calls_value): # Show ALL
print(f" tool_calls[{i}] type: {type(tc)}")
print(f" tool_calls[{i}] keys: {list(tc.keys()) if isinstance(tc, dict) else 'N/A'}")
if isinstance(tc, dict):
if 'function' in tc:
print(f" function keys: {list(tc['function'].keys())}")
if 'arguments' in tc['function']:
args = tc['function']['arguments']
print(f" function.arguments type: {type(args).__name__}")
print(f" function.arguments value: {str(args)[:100]}")
if 'args' in tc:
print(f" ALSO HAS 'args' KEY: type={type(tc['args']).__name__}")
print(f" args value: {str(tc['args'])[:100]}")
# Fix tool_calls: Normalize to OpenAI format if needed
if 'choices' in response_dict: