🤖 vs-code extension that suggest commit messages by AI & context
-
Updated
Jun 15, 2025 - TypeScript
🤖 vs-code extension that suggest commit messages by AI & context
A collection of LangChain pipelines using Groq API with LLaMA and DeepSeek models – featuring sequential, parallel, conditional, and simple chains.
A starter repo on how to create your first simple LLM application using LangChain
An intelligent chatbot that allows users to upload text-based Ayurveda PDFs and ask questions based on the content using RAG (Retrieval-Augmented Generation) combining semantic search and LLM-based responses.
FastMail is an AI-powered email management tool designed to streamline email responses
Click below to checkout the website
The application makes a processes a resume (from a PDF) and a job posting (scraped via WebBaseLoader) to extract structured JSON data using langchain-groq. It employs NLP techniques (nltk, scikit-learn) to preprocess text and calculate an ATS compatibility score (36.28%) via cosine similarity, indicating a moderate resume-job match.
Click below to checkout the website
App Builder is an AI-powered coding assistant built with LangGraph that works like a multi-agent developer team. It converts natural language requests into complete, functional projects — file by file. Using Planner, Architect, and Coder agents, it plans, designs, and writes code just like a real developer.
Local RAG Pipeline – "Where Did I Put That File?". This project is a local Retrieval-Augmented Generation (RAG) pipeline built to help users locate files and folders using natural language.
A Streamlit-based application that extracts key financial metrics — Revenue (actual & expected) and EPS (actual & expected) — from textual financial news or articles using LLM (LLaMA 3) powered by LangChain and GROQ API.
Welcome to the On-Device AI RAG project! This repository demonstrates how to utilize the ObjectBox Vector Database and LangChain to build a robust Retrieval-Augmented Generation (RAG) system directly on your device.
The Streamlit App for improving Google SEO ranking of Persian Contents with help of Groq Langchain
This project combines the power of vector databases, large language models, and chat history management to create an interactive PDF chatbot
The AI agents that execute different tasks with assistance of LangChain, CrewAI and AutoGen
This project implements a Retrieval-Augmented Generation (RAG) chatbot that can answer medical questions—especially focused on Anatomy and Forensics—based on uploaded PDF documents. It uses Hugging Face models for embedding and language generation, FAISS for vector storage, and a simple Streamlit frontend for an interactive chat interface.
AI-powered customer feedback analyzer that uses generative AI to transform customer reviews into actionable business insights. Upload review data, get instant summaries, satisfaction scores, detailed reports, and improvement suggestions—all in an easy-to-deploy Docker container.
Repository for "8x7B Nexus: Converging AI Reasoning, Prompt Engineering, and Human QA in Test Generation" reseach
Add a description, image, and links to the langchain-groq topic page so that developers can more easily learn about it.
To associate your repository with the langchain-groq topic, visit your repo's landing page and select "manage topics."