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Update README.md #135
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Update README.md #135
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Touched up some of the new wording
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@gibbs-cullen please see one small conflict with changes I've already made.
Other than that looks really good!
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| * **ChatEngine** (_`/chat/completions`_) implements the full RAG workflow. It rewrites and transforms your queries into query embeddings before generating augmented search results (via the Context Engine) before returning them back to the end user. | ||
| * **ContextEngine** performs the “retrieval” part of RAG. The `ContextEngine` utilizes the underlying `KnowledgeBase` to retrieve the most relevant document chunks, then formulates a coherent textual context to augment the prompt for the LLM (via an OpenAI API endpoint). | ||
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| * **KnowledgeBase** _`/context/{upsert, delete}` - prepares your data for the RAG workflow. It automatically chunks and transforms your text data into text embeddings before upserting them into the Pinecone vector database. It also handles Delete operations. | ||
| * **KnowledgeBase** (_`/context/{upsert, delete}`) prepares your data for the RAG workflow. It automatically chunks and transforms your text data into text embeddings before upserting them into the Pinecone vector database. It also handles Delete operations. |
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@gibbs-cullen I've actually already changed these descriptions yesterday, in my own PR.
Can you take a look please? I the new phrasing is more accurate, conveying the actual responsibilities of each of these components.
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Ah ok, didn't see that. Feel free to move forward with this.
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ie. your other PR
miararoy
approved these changes
Nov 2, 2023
| **Canopy** is an open-source Retrieval Augmented Generation (RAG) framework built on top of the Pinecone vector database. Canopy enables developers to quickly and easily experiment with and build applications using Retrieval Augmented Generation (RAG). | ||
| Canopy provides a configurable built-in server that allows users to effortlessly deploy a RAG-infused Chatbot web app using their own documents as a knowledge base. | ||
| For advanced use cases, the canopy core library enables building your own custom retrieval-powered AI applications. | ||
| **Canopy** is an open-source Retrieval Augmented Generation (RAG) framework and context engine built on top of the Pinecone vector database. Canopy enables you to quickly and easily experiment with and build applications using RAG. Start chatting with your documents or text data with a few simple commands. |
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Start chatting with your documents or text data with a few simple commands.
Sounds like shoppingTV
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Touched up some of the new wording
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