Embeds text files into vectors, stores them on Pinecone, and enables semantic search using GPT3 and Langchain in a Next.js UI

This Flask backend API takes a document in multiple formats and allows you to perform semantic search using Langchain, Cohere and Qdrant.

Tutorial and template for a semantic search app powered by the Atlas Embedding Database, Langchain, OpenAI and FastAPI

This repository is a sample application and guided walkthrough for a semantic search question-and-answer style interaction with custom user-uploaded documents. Typescript, NextJS, OpenAI, Langchain, Pinecone

Search and indexing your own Google Drive Files using GPT3, LangChain, and Python

Uses Langchain to semantic search over a chat conversation

AI-powered YouTube search. Index any channel, playlist, or video and search through transcripts with natural language. Uses Gemini embeddings + ChromaDB for semantic search. Click any result to jump to the exact timestamp. React + FastAPI + LangChain. Self-hosted, BYOK (bring your own key).

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TypeScript SDK for building RAG applications with Supabase and pgvector. Features semantic search, OpenAI embeddings, LangChain support, and comprehensive type definitions.

This code example shows how to make a chatbot for semantic search over documents using Streamlit, LangChain, and various vector databases. The chatbot lets users ask questions and get answers from a document collection. The code is in Python and can be customized for different scenarios and data.

Developing a RAG-powered chatbot for CreditTrust Financial that analyzes customer complaints across five financial products. The AI tool retrieves relevant complaint narratives using semantic search and generates actionable insights, helping product managers identify trends faster. Built with Python, LangChain, FAISS/ChromaDB, and Gradio/Streamlit.

This Python project demonstrates semantic search using MongoDB and two different LLM frameworks: LangChain and LlamaIndex. The goal is to load documents from MongoDB, generate embeddings for the text data, and perform semantic searches using both LangChain and LlamaIndex frameworks.

A Python application that leverages Langchain to integrate with Anthropic's Claude AI for processing and analyzing PDF research papers. The tool extracts text, identifies key terms, and performs semantic searches across academic databases.

Golang RAG chatbot for university admissions. Built with LangChain, pgvector, Neo4j & Gemini AI. Features semantic search, knowledge graphs, async processing & hexagonal architecture. Demonstrates high-performance AI in Go as alternative to Python RAG systems.

A context-aware legal chatbot built with LangChain that blends BM25 keyword search with semantic retrieval, applies multi-hop and multi-query strategies with reciprocal rank fusion for highly relevant, grounded responses, and includes a custom ConversationSummaryMemory implementation for stable, reliable conversational context management.

Building a semantic search engine using LangChain and OpenAI

An intelligent audio analysis tool that automatically transcribes and enables semantic search of audio recordings using Whisper and LangChain.

🤖 Agentic RAG - An intelligent document assistant with semantic chunking, hybrid search (vector + BM25), multi-format support (PDF, Word, CSV, Excel), and multi-channel bots (Telegram, WhatsApp). Built with FastAPI, React, PostgreSQL/pgvector, and LangChain.

Creating a RAG-powered assistant for CreditTrust Financial that examines client complaints across five financial services. The AI solution fetches relevant complaint records using semantic search and delivers practical insights, helping product teams detect patterns faster. Built with Python, LangChain, FAISS/ChromaDB, and Gradio/Streamlit.

Full-stack LLM Engineering Lab. Features: Autonomous Agents (ReAct/AutoGPT) | Fine-Tuning Llama/Mistral (SFT/DPO) | Large Model Deployment (DeepSeek 671B / 2.5-bit) | Advanced RAG (Hybrid Search) | Function Calling (Stream/Text-to-SQL/External APIs) | Frameworks (LangChain, Semantic Kernel, OpenAI) | Daily SOTA Paper Tracking. From theory to 0-to-1

Langchain implementation for semantic search in nodejs

DocuMind – An AI-powered PDF chatbot that allows users to upload documents and ask questions, with memory support and semantic search using LangChain, FastAPI, and Hugging Face embeddings.

A complex pharmaceutical recommendation system that makes use of cutting-edge technologies like LangChain for dynamic information retrieval, Neo4j for effective data storage, and SBERT for semantic embedding.

Semantic Search on Langchain Github Issues with Weaviate

An interactive CLI-based Smart FAQ system powered by LangChain and FAISS that retrieves accurate answers using semantic search and HuggingFace embeddings.

A lightweight and extensible pipeline for loading PDF documents, generating text embeddings using OpenAI, and storing them in a Chroma vector database for semantic search and retrieval-augmented generation (RAG) with Langchain.

An advanced PDF-to-knowledge chatbot built with LangChain + LangGraph, featuring hybrid semantic/keyword search (OpenSearch) and web-augmented answers via Serper API, supporting multimodal extraction of text, tables, and images through a modern React + FastAPI interface.

Cold Email Generator is a FastAPI-based app that automates personalized cold emails for job applications. It uses RAG, semantic search, and AI-powered analysis to extract job details, match them with your portfolio, and generate professional emails. Featuring FastAPI, Groq LLM, and LangChain for intelligent automation. 🚀

Use semantic search to browse similar and related cards in Magic: The Gathering. Powered by Langchain.

An open-source, plug-and-play LangChain-based RAG system that enables businesses to build domain-specific LLM apps using their internal documents with semantic search and natural language querying.