Log the complete prompt, schema, extra_body content, full API response,
token counts, and full parsed JSON output. Add exc_info=True tracebacks
on all failure paths.
vLLM servers support JSON schema enforcement via extra_body (guided_json
or structured_outputs), not OpenAI's response_format protocol. LangChain's
with_structured_output(method='json_schema') sends response_format which
vLLM ignores, causing NoneType not iterable parsing errors.
- vLLM path: direct OpenAI SDK call with extra_body={guided_json|structured_outputs}
- OpenRouter path: unchanged with_structured_output(method='json_schema')
- Try new 'structured_outputs' format first, fall back to legacy 'guided_json'
- Update _SEED_DECOMPOSE with explicit JSON array instruction
- Add diagnostic logging: exc_info=True, schema preview, prompt template preview
- Add logging in _parse_legacy_json for fallback failure debugging
vLLM's chat_template_kwargs leaked into LangChain's AsyncCompletions.parse()
via _get_langchain_model's model_kwargs, causing structured decomposition
to fail on vLLM backends. Skip vLLM-specific params when building the
LangChain model — only provider-agnostic params (OpenAI reasoning) pass through.
- Log extra_body contents before sending to LLM
- Log full LLM response object for debugging
- Changed extra_body format to OpenRouter reasoning format
Ultraworked with [Sisyphus](https://github.com/code-yeongyu/oh-my-openagent)
Co-authored-by: Sisyphus \u003cclio-agent@sisyphuslabs.ai\u003e
- LLMClient.complete() now accepts step_name parameter to identify processing step
- Logs prompt preview (first 100 + last 100 chars) at INFO level
- Logs processing time in milliseconds with token usage stats
- Updated QueryDecomposer, RelevanceFilter, and RAGService to pass step names
Ultraworked with [Sisyphus](https://github.com/code-yeongyu/oh-my-openagent)
Co-authored-by: Sisyphus <clio-agent@sisyphuslabs.ai>
Woody