fc7a91d991
<!-- .github/pull_request_template.md --> ## Description <!-- Provide a clear description of the changes in this PR --> This PR implements the 'FEELING_LUCKY' search type, which intelligently routes user queries to the most appropriate search retriever, addressing [#1162](https://github.com/topoteretes/cognee/issues/1162). - implement new search type FEELING_LUCKY - Add the select_search_type function to analyze queries and choose the proper search type - Integrate with an LLM for intelligent search type determination - Add logging for the search type selection process - Support fallback to RAG_COMPLETION when the LLM selection fails - Add tests for the new search type ## How it works When a user selects the 'FEELING_LUCKY' search type, the system first sends their natural language query to an LLM-based classifier. This classifier analyzes the query's intent (e.g., is it asking for a relationship, a summary, or a factual answer?) and selects the optimal SearchType, such as 'INSIGHTS' or 'GRAPH_COMPLETION'. The main search function then proceeds using this dynamically selected type. If the classification process fails, it gracefully falls back to the default 'RAG_COMPLETION' type. ## Testing Tests can be run with: ```bash python -m pytest cognee/tests/unit/modules/search/search_methods_test.py -k "feeling_lucky" -v ``` ## DCO Affirmation I affirm that all code in every commit of this pull request conforms to the terms of the Topoteretes Developer Certificate of Origin. Signed-off-by: EricXiao <taoiaox@gmail.com> |
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