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Gemini + LangChain PDF QA Utility

This project shows how to use Google Gemini and LangChain to answer questions about a PDF file.

What it does

  • Loads a PDF from a web link.
  • Splits the PDF into chunks and creates a searchable index.
  • Lets you ask questions about the PDF using Gemini.
  • Shows how to generate general content and keep chat history.

Requirements

  • Python 3.8 or newer
  • google-generativeai
  • langchain
  • langchain-google-genai
  • chromadb
  • python-dotenv
  • ipython

Install everything with:

pip install google-generativeai langchain langchain-google-genai chromadb python-dotenv ipython

or

pip install -r requirements.txt

Setup

  1. Get a Gemini API key from Google AI Studio.
  2. Make a .env file in this folder with:
    GEMINI_API_KEY=your_api_key_here
    

Usage

Run the script:

python gemini-utilize.py

Customization

You can change the PDF link, chunk size, or prompts in the script.

  • temperature : Influences the randomness in token selection.
  • top_k : Measure of how many of the most probable tokens are considered at each step.
  • max_output_tokens : Upper limit of tokens generated in a response.
  • top_p : Controls how the AI model chooses words when generating text.

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Simple LLM using Gemini Pro Model and LangChain

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