vector-stores

Building blocks for rapid development of GenAI applications

Explore LangChain and build powerful chatbots that interact with your own data. Gain insights into document loading, splitting, retrieval, question answering, and more.

Course LangChain Chat with Your Data

A Python package to access different LLMs, embeddings, vector stores etc.

Developed A LLM Powered Recommendation System, Based on Instructor-XL, Google Flan / GPT3.5 and FAISS. Conducted a consumer survey to understand the problems of a consumer, created the problem statement from the insights derived from the survey.

A proof of concept for Question-Answering API on a specific topic using RAG from pre-defined document(s) on the topic

Demonstrate two types of chat interactions with a Mattermost instance leveraging Mattermost OpenAPI v3 spec and Spring AI.

A simple demo of a Flutter application that implements Retrieval-Augmented Generation (RAG) using OpenAI's APIs.

This repository showcases Python scripts demonstrating interactions with various models using the LangChain library. From fine-tuning to custom runnables, explore examples with Gemini, Hugging Face, and Mistral AI models.