/rag_langchain_gradio

A basic "retrieval augmented generation" (RAG) app with Langchain and OpenAI in Python + Pinecone + Gradio app.

Primary LanguagePython

Smart Q&A Application with OpenAI and Pinecone Integration

A "retrieval augmented generation" (RAG) app with Langchain and OpenAI in Python + Gradio interface + Pinecone vector database.

The "Smart Q&A Application with OpenAI and Pinecone Integration" is a simple Python application designed for question-answering tasks. Leveraging powerful technologies such as OpenAI for natural language understanding and Pinecone for efficient similarity search, this application offers a range of features to enhance the user's experience:

  1. Document Processing:

    • The app allows users to input a directory of documents for analysis.
    • Documents are efficiently processed and broken down into smaller, manageable chunks.

  2. Embeddings Generation with OpenAI:

    • Utilizes the OpenAI API to generate embeddings from LLMs for the processed document chunks.
    • Embeddings capture semantic information, enabling better understanding of the content.
    • Leverage "retrieval augmented generation" (RAG) from Langchain.

  3. Efficient Search with Pinecone:

    • Establishes a connection to the Pinecone service for efficient similarity search.
    • Creates an index to store and retrieve document embeddings.

  4. OpenAI Language Model Integration:

    • Incorporates OpenAI's powerful language model for advanced natural language processing.
    • Fine-tuned parameters, such as temperature, enhance the quality of responses.

  5. Question-Answer Chain:

    • Implements a question-answer chain from the OpenAI language model, enabling a dynamic and contextualized Q&A experience.

  6. User-Friendly Gradio Interface:

    • The application features an interactive user interface created with Gradio.
    • Users can input their queries using a textbox, enhancing user interaction and accessibility.

  7. Real-Time Results Display:

    • Results are displayed in real-time in another textbox, providing users with quick and relevant answers to their queries.

  8. Extensibility and Customization:

    • The application can be easily extended and customized to fit different use cases, making it a versatile tool for various domains.
    • Easily extendable to display source urls.

  9. Smart Search Inside PDFs:

    • The app includes an informative user prompt, encouraging users to search inside PDFs, suggesting its capability to handle PDF documents.

Overall, this application amalgamates cutting-edge technologies to create an intelligent Q&A system, making it a valuable tool for tasks that require natural language understanding and efficient document retrieval.

How to use:

  1. Install requirements:
pip install -r requirements.txt
  1. Place your Environment variables in the .env file.
  2. Run the app:
python app.py
  1. Visit http://127.0.0.1:7860/ on your browser.

Preview:

Links: