
Get your intelligent document assistant up and running in minutes. Connect APIs, index your PDFs, and start asking questions.
Follow the guided steps below to configure your environment, set up the Gemini API key, initialize the FAISS vector store, and verify your installation. Each step includes validation checks so you can confirm everything is working before moving on.
Follow the guided setup process to configure, install, and launch your PDF Chatbot.
Set up your Python virtual environment, API keys, and configuration variables following the quickstart guide.
Install all required packages including LangChain, FAISS, Google Generative AI, and Streamlit.
Launch the Streamlit server, upload your PDFs, and start chatting with your documents instantly.
Configure your Gemini API key and other service credentials.
Checking Python 3.11+ installation...
Verifying LangChain and Gemini API dependencies...
Python 3.11+ detected. All core dependencies satisfied.
Initializing FAISS vector store...
Environment file (.env) detected with Gemini API key configured.
FAISS index ready. Vector store initialized with dimension 768.
Building document chunker pipeline...
Port 8501 is already in use. Streamlit cannot bind to the default port.
Having trouble getting PDF Chatbot running? Browse these frequently asked questions or use the search to find solutions fast.
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