feat: add weave to wandbot to track all intermediate steps and calls #76
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👍 Dependency issues cleared. Learn more about Socket for GitHub ↗︎ This PR previously contained dependency changes with security issues that have been resolved, removed, or ignored. |
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Hey @parambharat did you run eval on it? Do you want me to do it? |
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@ayulockin , there are no functional changes other than adding weave ops and changing a few langchain imports to work with the new langchain version. I don't think a eval re-run might be necessary here. |
| if chat_history is None: | ||
| chat_history = [] | ||
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| with get_openai_callback() as query_enhancer_cb, Timer() as query_enhancer_tb: | ||
| enhanced_query = self.query_enhancer.chain.invoke( | ||
| enhanced_query = self.query_enhancer( |
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is the requirement of not doing .chain.invoke a new thing in LECL?
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I see you have added __call__ methods.
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haha, yes, this allows the use of a weave.op decorator, making the weave integration easier.
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Hey @parambharat, reviewed and it looks good. I asked a few questions out of curiosity. But going ahead and merging it. Thanks for the weave integration. |
The PR adds weave integration to wandbot to track RAG pipeline calls for query enhancements, retrieval, and response synthesis.