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# OpenAI Embeddings Example
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A Hybrid Search and Augmented Generation prompting solution using Python [OpenAI](https://openai.com/) API embeddings sourced from [Pinecone](https://docs.pinecone.io/docs/python-client) vector database indexes and managed by [LangChain](https://www.langchain.com/). Implements the following:
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A Hybrid Search and Augmented Generation prompting solution using Python [OpenAI API Embeddings](https://platform.openai.com/docs/guides/embeddings) persisted to a [Pinecone](https://docs.pinecone.io/docs/python-client) vector database index and managed by [LangChain](https://www.langchain.com/). Implements the following:
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-**PDF Loader**. a command-line pdf loader program that extracts text, vectorizes, and
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loads into a Pinecone dot product vector database that is dimensioned to match OpenAI embeddings.
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### Retrieval Augmented Generation
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For the question, _"What analytics and accounting courses does Wharton offer?"_, an
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For the question, _"What analytics and accounting courses does Wharton offer?"_, an
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embedding can potentially dramatically alter the response generated by chatGPT. To illustrate, I uploaded a batch of 21 sets of lecture notes in PDF format for an online analytics course taught by Wharton professor [Brian Bushee](https://accounting.wharton.upenn.edu/profile/bushee/). You can download these from https://cdn.lawrencemcdaniel.com/fswl/openai-embeddings-data.zip to test whether your results are consistent.
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