Practical step-by-step LangChain guides
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Updated
Apr 9, 2024 - Jupyter Notebook
Practical step-by-step LangChain guides
Explores the implementation of a LangChain Agent using Azure Cosmos DB for MongoDB vCore to handle traveler inquiries and bookings. The project provides detailed instructions for setting up the environment and loading travel data, aiming to empower developers to integrate similar agents into their solutions.
It automatically describes images in PDF files and generates questions from these descriptions. With its advanced RAG structure, it directs these questions directly to PDF text content, providing comprehensive information extraction and analysis.
The personal assistance chatbot integrates appointment creation, Google Calendar event scheduling with Google Meet, and email notifications using the Langchain and Zapier NLA integration.
Agentic RAG with LangChain and Pinecone
This repository hosts a Jupyter notebook that demonstrates the seamless integration of the Bard API with the LangChain library. By leveraging the capabilities of both platforms, we've crafted a custom Language Learning Model (LLM) that allows users to harness the power of Bard within the LangChain ecosystem.
FastAPI application with streaming Langchain agents and Tavily search tool
A Multi-modal chatbot with LangChain, that supports RAG, Paperswithcode, and Image generation using Dall-E-3
Welcome to our new Custom WebSearch Agent, now as an easy-to-use Streamlit app! No more sifting through loads of generic results. With this app, you get a search experience that's all about you. It's like having your own personal search assistant right at your fingertips.
Use a RAG Langchain agent that connects to your supermarket's inventory database and get information about product stocks and locations.
LanchainLLM
FullStack LangChain application using SpringBoot, LangChain4J and React - integrate with internal data and api and upload internal documents for RAG
A simple application to query and interact with multiple CSVs.
Generative AI demos, an example of a langchain based application that implements Retrieval-Augmented-Generation for an enhanced generation. It uses OpenAI model and OpenAI function tool agent. Able to run Ollama Mistral local LLM too.
A repository for final project of NLP Bootcamp at Indonesia AI
This tutorial is designed to make working with LangChain.js as easy and approachable as possible.
This project focuses on building a system of autonomous agents powered by Large Language Models (LLMs) and LangChain. Each agent is designed to complete specific tasks using various tools, and the agents are decoupled from each other. The architecture follows an event-driven design.
This project is a search-powered AI chatbot built with Streamlit and LangChain, designed to retrieve information from multiple sources like Wikipedia, Arxiv, and DuckDuckGo. It leverages LangChain's agent framework and Groq API for real-time, intelligent responses.
A social monitor and trading assistant agent. Powered by Langchain 🦜.
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