feat: Implement LLM features using litellm#189
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feat: Implement LLM features using litellm#189google-labs-jules[bot] wants to merge 1 commit intomainfrom
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This commit implements the LLM features that were previously added as placeholders. The implementation uses the `litellm` library to provide a provider-agnostic interface to various Large Language Models. The `openodia.llm.LLM` class now provides the following methods: - `summarize`: For abstractive text summarization. - `named_entity_recognition`: For Named Entity Recognition. - `sentiment_analysis`: For sentiment analysis. The implementation is configurable via environment variables: - `OPENODIA_LLM_MODEL`: To specify the LLM model to use (e.g., `gemini/gemini-pro`, `openai/gpt-4`). Defaults to `gemini/gemini-pro`. - API keys for the respective services are read from standard environment variables (`GEMINI_API_KEY`, `OPENAI_API_KEY`, etc.). The documentation has been updated to reflect these changes and provide usage examples. Unit tests have been added for the new features, using `unittest.mock` to patch the `litellm.completion` function and avoid actual API calls. The `litellm` library has been added as a dependency in `pyproject.toml`.
Codecov Report✅ All modified and coverable lines are covered by tests. Additional details and impacted files@@ Coverage Diff @@
## main #189 +/- ##
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+ Coverage 99.49% 99.55% +0.06%
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Files 9 10 +1
Lines 199 227 +28
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+ Hits 198 226 +28
Misses 1 1
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This change implements the previously-defined placeholder methods for LLM features using the
litellmlibrary. This provides a provider-agnostic way to use different LLMs for summarization, NER, and sentiment analysis. The implementation is configurable via environment variables. Unit tests and documentation have been added.