{"repo":"FullStackWithLawrence/openai-embeddings","free":true,"listed":false,"github":"https://github.com/FullStackWithLawrence/openai-embeddings","clone":"git clone https://github.com/FullStackWithLawrence/openai-embeddings.git","description":"OpenAI chatGPT hybrid search and retrieval augmented generation","language":"Python","stars":18,"topics":["ci","ci-cd","embeddings","github-actions","langchain","langchain-python","openai","openai-api","pre-commit","pre-commit-hooks"],"license":"AGPL-3.0","category":"ai-agents","readme_excerpt":"OpenAI Embeddings Example 🤖 Retrieval Augmented Generation and Hybrid Search 🤖 A Hybrid Search and Augmented Generation prompting solution using Python OpenAI API Embeddings persisted to a Pinecone vector database index and managed by LangChain. Demonstrates the following: - System Prompting . How do use the system prompt to modify LLM text completion behavior. - Templates . How to create templates in order keep your prompts DRY. - LangChain . How to setup a project using LangChain as an alternative to vendor specific LLM PyPi packages. - PDF Loader . a command-line pdf loader program that extracts text, vectorizes, and loads into a Pinecone dot product vector database that is dimensioned to match OpenAI embeddings. - Pinecone . How to create, load, and query a Pinecone vector database. - Retrieval Augmented Generation (RAG) . A chatGPT prompt based on a hybrid search retriever that locates relevant documents from the vector database and includes these in OpenAI prompts. Secondarily, I also use this repo for demonstrating how to setup Pydantic to manage your project settings and how to safely work with sensitive credentials data inside your project. Installation You'll also need to add your api keys to the .env file in the root of the repo. - Get your OpenAI API key - Get your Pinecone API Key Usage Retrieval Augmented Generation For the question, \"What analytics and accounting courses does Wharton offer?\" , an embedding can potentially dramatically alter the response gener","default_branch":null,"files":null,"tree":[],"storefront":"/r/FullStackWithLawrence","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/FullStackWithLawrence/openai-embeddings/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}