OpenViSTAI · Agents · Blockchain · Crypto
Submit a project
Menu
RAG & Knowledge Systems

Gemini PDF Chatbot

Gemini PDF Chatbot is a Python and Streamlit application that accepts multiple PDF files, extracts and processes their text, and uses a Gemini conversational model to answer questions based on the document context. It can be run locally or with Docker and uses a Google API key.

Explore the practical guide ↓

Independent OpenViST project profile, based on linked sources.

Gemini PDF Chatbot — OpenViST project profile in RAG & Knowledge Systems.
OpenViST project illustration. See the linked sources for product details.
Understand the project

Practical overview

When it fits

Use it when you have a collection of PDFs and want to ask questions about their contents through one conversational interface.

Who it is for

  • People who need to consult information across several PDF documents through a chat interface.
  • Developers seeking a self-hostable Python application for document-grounded Gemini question answering.

Documented uses

  • Upload multiple PDFs and extract their text for processing.
  • Ask conversational questions about information in the uploaded documents.
  • Run the application locally or start it with Docker Compose.
Before you choose

Requirements & limits

  • The Gemini-powered workflow requires a Google API key configured in a .env file.
  • The README documents Docker Compose and a local Python workflow; local development requires Python 3.10 or higher.
  • The app extracts PDF text and answers from document context; the available description does not specify file-size or document-count limits.
  • The repository is public and carries an MIT license.

Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.

Source-based practical guide

Run the app locally and start a PDF chat

Set up the documented local development workflow and reach the PDF chat interface.

Before you start

  • Python 3.10 or higher
  • A Google API key
  • The repository and its requirements.txt

Steps

  1. Clone the repository.

  2. Install dependencies with pip install -r requirements.txt.

  3. Put the Google API key in a .env file as GOOGLE_API_KEY=your_api_key_here.

  4. Start the app with streamlit run main.py.

  5. Upload PDFs in the sidebar and select “Submit & Process”; then use the chat interface.

Expected outcome

A local Streamlit interface for processing uploaded PDFs and asking questions about their contents.

Guide limitations

  • The workflow depends on a Google API key.
  • The README does not specify limits for file size, PDF count, or document formats beyond PDF.
Documentation 1 ↗
Source-based practical guide

Start the app with Docker Compose

Build and start the application locally using the documented Docker setup.

Before you start

  • Docker installed
  • A Google API key

Steps

  1. Set GOOGLE_API_KEY in a .env file.

  2. Run docker compose up --build.

  3. Open http://localhost:8501 when the application is available.

Expected outcome

The app is started locally through Docker Compose at the documented address.

Guide limitations

  • The guide does not document cloud deployment as part of this local startup sequence.
  • A Google API key is required.
Documentation 1 ↗
Evidence and transparency

Sources & review

Official repository ↗
Source record details
Source availability
Active
Sources checked
12 October 2026
Original website title
kaifcoder/gemini_multipdf_chat · Official homepage title · retained in its source language
How we review sourcesSuggest a correction