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PDF-Insight(Gen-1)

PDF Insight: RAG-Based Gen-AI Application

Demo

demo.mp4

Tech Stack

Client: HTML, CSS, JS

Server: Flask

Database: Mongo-db, astra-db

Features

  • Adding PDFs seamlessly: Effortlessly incorporate PDF files into sessions.
  • Smooth session switching: Easily transition between sessions with minimal hassle.
  • Streamlined for faster inference: Designed for optimal performance, ensuring swift response times and minimal latency during inference.

Environment Variables

  • LANGCHAIN_API_KEY: Required for integrating with Langsmith (optional).

  • LANGCHAIN_PROJECT: Specifies the name of the Langsmith project (optional).

    • Example: LANGCHAIN_PROJECT="MY_PROJECT_NAME"
  • GROQ_API_KEY: Required for interacting with the Groq inference engine.

  • ASTRA_DB_APPLICATION_TOKEN: Token used to connect with Astra DB.

  • ASTRA_DB_ID: Identifier for connecting with Astra Vector DB.

  • MONGO_CONNECTION_STRING: Connection string for MongoDB cluster.

    • Example: MONGO_CONNECTION_STRING = "mongodb+srv://{username}:{password}@<cluster_name>.<value>.mongodb.net"
  • MONGO_CLUSTER_USERNAME: Username for accessing the MongoDB cluster.

  • MONGO_CLUSTER_PASSWORD: Password for accessing the MongoDB cluster.

  • APP_SECRET_KEY: Secret key for the Flask application.

Run Locally

Clone the project

  git clone https://github.com/nis12ram/PDF-Insight.git

Create python virual environment

  python -m venv <path>/venv

Install requirements & Add .env file

  pip install -r requirements.txt

Change static path

approach2flaskServer.py

app.config['STATIC_FOLDER'] = <path_to_your_static_folder>

run

approach2flaskServer.py

python approach2flaskServer.py

RAG Architecture

llmarch

APP Architecture

systemArch

Acknowledgements

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get insights of your pdf easily.

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