🪄 PDFQuest: PDF Question-Answer tool

PDFQuest is an AI-powered PDF QA tool that enables you to easily upload and analyze PDF documents with advanced question-answering capabilities. PDFQuest goes beyond traditional keyword-based search and utilizes vector embeddings and semantic search to deliver precise and efficient results from your PDFs to improve your workflow efficiency.

Installation

1. Clone the repository using git clone https://github.com/ayush-vibrant/PDFQuest.git
2. Navigate to the project directory by running cd PDFQuest
3. Install the required packages using pip install -r requirements.txt

Usage

To use PDFQuest, simply run python -m streamlit run folder-location/PDFQuest/streamlit/main.py in your terminal. This will start a local server that you can access through your web browser. In the command, replace folder-location/ with the actual path to the PDFQuest directory on your machine.

Environment Variables

Before running the app, make sure to create a .env file in your local system and add the following environment variables:

OPENAI_API_KEY=<your openai api key>
PINECONE_API_KEY=<your pinecone api key>
PINECONE_API_ENV=<your pinecone api env>
USE_PINECONE=false
PINECONE_INDEX_NAME=<test>
TEMPERATURE=0
QA_WITH_SOURCE=false

For streamlit applications. Secrets management happens from a different file. See this for more information.

Add a file called secrets.toml in a folder called .streamlit at the root of your app repo, and copy/paste your secrets into that file.

OPENAI_API_KEY="your openai api key"
PINECONE_API_KEY="your pinecone api key"
PINECONE_API_ENV="your pinecone api env"
USE_PINECONE="false"
PINECONE_INDEX_NAME="test"
TEMPERATURE="0"
QA_WITH_SOURCE="false"

Architecture