This project shows how to use Google Gemini and LangChain to answer questions about a PDF file.
- 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.
- 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 ipythonor
pip install -r requirements.txt- Get a Gemini API key from Google AI Studio.
- Make a
.envfile in this folder with:GEMINI_API_KEY=your_api_key_here
Run the script:
python gemini-utilize.pyYou 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.