Woody f5cfe44183 feat(backend): add LLM monitoring with step names, timing, and prompt logging ... - 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>		2026-04-23 14:51:57 +08:00
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__init__.py	feat: Phase 1.1 project setup with config, database, and models	2026-04-22 16:13:52 +08:00
embedding_client.py	feat(backend): add embedding client and update LLM client	2026-04-23 13:26:43 +08:00
llm_client.py	feat(backend): add LLM monitoring with step names, timing, and prompt logging	2026-04-23 14:51:57 +08:00
query_decomposer.py	feat(backend): add LLM monitoring with step names, timing, and prompt logging	2026-04-23 14:51:57 +08:00
rag.py	feat(backend): add LLM monitoring with step names, timing, and prompt logging	2026-04-23 14:51:57 +08:00
relevance_filter.py	feat(backend): add LLM monitoring with step names, timing, and prompt logging	2026-04-23 14:51:57 +08:00