RAGXLangchainJS

RAGxLangChainJS

This project is a JavaScript-based implementation using the innovative Retrieval-Augmented Generation (RAG) architecture through LangChainJS. This system effectively combines a document retriever and a response generator to handle complex queries with high accuracy. The "Retriever" component acts like a precision search tool within a document corpus, extracting the most relevant information based on user queries. Following retrieval, the "Generator" synthesizes this information into coherent and contextually relevant responses. This dual-component approach is ideal for tasks that require deep content synthesis and understanding, such as generating detailed summaries or answering multifaceted questions from a broad array of document sources. This application handles numerous documents and complex queries with ease, making it a valuable tool for researchers, content creators, and data analysts.

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Features

• Dynamic Text Retrieval: Efficiently retrieves text data from a pool of documents based on query relevance.
• Advanced Text Processing: Utilizes advanced NLP techniques for text parsing, segmentation, and embedding.
• Contextual Response Generation: Generates responses that are context-aware, ensuring high relevance and accuracy.

Pre-requisites

• The project uses Ollama with LangChainJS, so make sure you have Ollama installed. After installing, run

  $ ollama pull gemma:2b-instruct-q5_0
  $ ollama pull nomic-embed-text
  

  in powershell.

• The project also uses ChromaDB as the database for vector storage, so download and install Docker from https://www.docker.com/ and run

  $ docker pull chromadb/chroma
  $ docker run -p 8000:8000 chromadb/chroma
  

  in powershell to pull a chromaDB image and initiate a chromaDB container. The embeddings will be created and stored inside the chromaDB container that is created in docker.

Installation

• Clone the repository using git clone.

• After cloning, go the root directory and run npm install in the terminal for installing the packages.

• After the packages are successfully installed, run npm start in the terminal. You'll get an error the first time, then run npm start again for the code to work.

Contributing

Contributions to the project are welcome! Please create Pull Requests, or submit issues to suggest changes to the repository, or report bugs.

License

This project is licensed under the MIT License - see the LICENSE file for details.