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Chatwithpdf

Chatwithpdf is a Python and Streamlit application for conversational question answering over uploaded PDF documents. It extracts and chunks PDF text, indexes the chunks in FAISS, and uses LangChain with Anthropic Claude 3 Sonnet to answer questions using retrieved content.

Explore the practical guide ↓

Independent OpenViST project profile, based on linked sources.

Chatwithpdf — 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 Chatwithpdf when you want to query information across uploaded PDFs through conversational questions, or when you want to set up its documented local RAG workflow.

Who it is for

  • People who need to ask questions about information in one or more PDF documents.
  • Developers seeking a documented Python and Streamlit example of retrieval-augmented PDF question answering.

Documented uses

  • Upload PDF files and process their text for retrieval.
  • Ask questions about the documents and receive conversational responses based on retrieved content.
  • Run the documented application locally with an Anthropic API key.
Before you choose

Requirements & limits

The repository is public and MIT-licensed. Local use requires an Anthropic API key. The repository also lists a hosted Streamlit homepage.

  • The local workflow depends on an Anthropic API key and the project's Python dependencies.
  • The documented stack is Streamlit, PyPDF2, LangChain, FAISS, and Anthropic Claude 3 Sonnet.
  • The README describes retrieval and conversational answers but does not specify document-size limits or citation behavior.

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

Set up Chatwithpdf locally

Prepare the documented local Streamlit application to accept PDF questions.

Before you start

  • Python and the repository's listed dependencies
  • An Anthropic API key set as ANTHROPIC_API_KEY
  • A .env file containing environment variables

Steps

  1. Clone the ChatwithPDF repository.

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

  3. Set the Anthropic API key in the environment and create a .env file containing the environment variables.

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

Expected outcome

The local Streamlit application is started and ready for the documented PDF question-answering workflow.

Guide limitations

  • The setup requires an Anthropic API key.
  • The README does not specify document-size limits or answer citation behavior.
Documentation 1 ↗
Source-based practical guide

Ask questions about uploaded PDFs

Process PDF files and submit a question about their contents.

Before you start

  • Access to the running Chatwithpdf application
  • One or more PDF files containing the information to query

Steps

  1. Upload the PDF files.

  2. Select “Submit & Process” to process them.

  3. Enter a question related to the uploaded documents.

Expected outcome

The application returns a conversational response using retrieved document content.

Guide limitations

  • The README does not specify document-size limits or explain whether responses include citations.
Documentation 1 ↗
Evidence and transparency

Sources & review

Official repository ↗
Source record details
Source availability
Active
Sources checked
17 October 2026
Original website title
sagnik-datta-02/ChatwithPDF · Official homepage title · retained in its source language
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