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@markbackman markbackman commented Sep 6, 2024

RAG demo that uses Stratechery articles as a data source. Some highlights about the implementation:

  • Articles are chunked using a semantic chunking strategy. This allows for content in the articles to be arranged into similar themes.
  • OpenAI text-embedding-3-small is used for embeddings
  • Pinecone is the vector database
  • Langchain is used to query the vector database and construct prompts

The demo indexes the title and published date and the system prompt gets the current date at run time, which allows you to ask questions like: "what was your last article?" or "tell me about what Apple has been up to this year".

The UI contains a drawer that shows you the RAG performance (query time, response time, total RAG time), token utilization (current RAG query and cumulative), and links to the source articles.

Lastly, I've updated the waveform to provide a little more friendly animation during the wait time.

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@markbackman markbackman force-pushed the mb/rag-function-calling branch from f1404b3 to 1cb49b9 Compare September 12, 2024 23:21
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