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🧩 Interfacing with different LLMs-chains, vectorstore databases, and autonomous agents.

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🧩 GPT Vector Agent

WIP

This is an experimental playground for interfacing with different LLMs-chains (via LangChain), vectorstores (via Pinecone.io), and autonomous/chained agents.

πŸ₯… Goals:

  1. To ideate, and experiment potential use cases for generative AI
  2. Provide public documention current understanding and lessons learned

πŸ“ Prompt Design (Great resources)

  1. Prompt Engineering by learnprompting.org - an open source introductory course on prompt engineering
  2. ChatGPT Prompt Engineering for Developers - Prompt engineering basics straight from OpenAI

🦜 πŸ”— LangChain

  1. Welcome to LangChain - LangChain is a framework for developing applications powered by language models.
  • Be data-aware: connect a language model to other sources of data
  • Be agentic: Allow a language model to interact with its environment
  1. Six Main Components of LangChain:
  • πŸ—ƒοΈ Schema (4 items)
  • πŸ—ƒοΈ Models (3 items)
  • πŸ—ƒοΈ Prompts (4 items)
  • πŸ—ƒοΈ Indexes (4 items)
  • πŸ—ƒοΈ Memory (1 items)
  • πŸ—ƒοΈ Chains (4 items)
  • πŸ—ƒοΈ Agents (4 items)

πŸ”’ Vectorstore Databases

Guides

πŸ§ͺ Experimental Projects

Difficulty Description
🍼 Beginner Entry level projects to practice using OpenAI + LangChain
πŸ§‘πŸΎβ€πŸ’» Intermediate Mid-level projects to practice using OpenAI + LangChain + Custom Knowledge base
πŸ§‘πŸΎβ€πŸ’» Advanced Advanced-level projects and custom implementations of OpenAI + LangChain + Embeddings + Vectorstore Databases

HuxleyPDF - PDF Chat bot

  • Upload PDF docs, ask questions, receive conversational responses about your data
  • Difficulty: Beginner
  • Repo: Repo
  • Stack: Built in Python, Streamlit (front end), OpenAI (LLM) + Pinecone (vector database)
  • Todo: Add connectiom to S3 bucket

🌟 Contributing

As an open-source project in a rapidly developing field, I welcome any contributions, whether it be in the form of updating code, better documentation, or projec to feature.

This repo and series is run by Fred Siika