RAG-based question answering chatbot using Deep Lake, LangChain, and GPT-3.5. This project builds a chatbot that retrieves relevant information from text datasets using vector embeddings and generates context-aware answers via GPT-3.5 Turbo. Includes a Streamlit app for a user-friendly interface.

Unlock the potential of AI-driven solutions and delve into the world of Large Language Models. Explore cutting-edge concepts, real-world applications, and best practices to build powerful systems with these state-of-the-art models.

Examples for quickly getting started using Deep Lake! https://activeloop.ai/

Chatbot assistant enabling GitHub repository interaction using LLMs with Retrieval Augmented Generation

Artificial Intelligence LLM experiments and quick intros using Ollama, GPT4All, OpenAI and HuggingFace models with LangChain and DeepLake vector store

DrakeLLM is developed to help students to solve the issue of making notes from videos, books and others. Utilising RAG, Drake helps in making quick notes along with a Q&A bot. Books, YouTube tutorials or Videos, Drake supports all your means.

This Python script downloads a YouTube video, transcribes its audio content, and generates a summary of the transcription using language modeling techniques.

This Python code retrieves an article from a provided URL, extracts its title and text, and then utilizes the ChatOpenAI library (assuming access) to generate a bulleted summary using the GPT-4 model.

RAG project for QA retrieval using Llama Index

A Statistical Research GPT that integrates DeepLake and Eurostat API

🤖 Career Assistant | Gradio, Cohere , Faiss and Langchain

A list of examples for different use of LangChain

An example Airflow Pipeline with Deeplake for Machine Learning

This repository enables users to interact with their documents using a chat interface

LLMs are deep learning models with billions of parameters that excel at a wide range of natural language processing tasks. They can perform tasks like translation, sentiment analysis, and chatbot conversations without being specifically trained for them

Using langchain, deeplake and openai to create a Q&A on the Mojo lang programming manual

ActiveLoop's Course on LangChain and Vector Databases in Production

Intelligent sales assistant built using Deep Lake, Whisper, LangChain, and GPT 3.5/4

This is a CLI app using LangChain and Activeloop vector DB to index and chat with the Chainstack docs

Simple implementation of CBIR with a pretrained ViT model and local Deeplake DB