🌌 Q&A Planet

Added loader for enhancing user experience

Q&A Planet is a AI platform where you can upload any document and ask question related to it

🛠 Technologies used

Frontend Framework

• ReactJs: For building the user interface.
• VueJs: For additional components and interactivity.

Backend Framework

• FastAPI: For building the API efficiently.
• Python: The programming language used for the backend.

Data Validation and Parsing

• Pydantic: For validating request and response data.

CORS Handling

• CORS Middleware from FastAPI: To enable cross-origin resource sharing.

File Handling

• PyMuPDF: For processing PDF files.

Text Processing

• LangChain: For text splitting and handling large documents.
• Hugging Face Transformers: For natural language processing tasks.
• Sentence Transformers: For embedding sentences and retrieving contextual information.

Database Management

• SQLAlchemy ORM: For database interactions and object-relational mapping.

📥 Installation

Use the package manager pip to install foobar. Copy the proejct url

Frontend

cd ./frontend

npm install

and the frontend server will start

Backend Server

cd ./backend

To install all the dependencies

pip install fastapi uvicorn sqlalchemy pymupdf langchain transformers sentence-transformers fastapi[all]

To run the backend server

uvicorn main:app --reload

the server will run at port

http://127.0.0.1:8000/docs#/

📡 API Documentation

BASE URL

http://localhost:8000

🚀 Endpoints

1. Upload PDF Document

• Endpoint: /upload_pdf
• Method: POST
• Description: Upload a PDF file to the server for processing.

Request

• Headers:

  • Content-Type: multipart/form-data

• Body:

  • file: The PDF file to be uploaded (required).

Response

• Status Code: 200 OK
• Response Body:

  {
    "document_id": "string" // The ID of the uploaded document.
  }
  
  

2. Ask a Question

• Endpoint: /ask_question
• Method: POST
• Description: Submit a question related to the uploaded document and receive an answer.

Request

• Headers:

  • Content-Type: application/json

• Body:

  • document_id: The ID of the document to ask questions about.
  • question: The question to be asked.

  Response

• Status Code: 200 OK

• Response Body:

  {
    "answer": "string" // The answer to the asked question.
  }
  

3. Get Document Questions

• Endpoint: /document/{document_id}/questions
• Method: GET
• Description: Retrieve a list of questions and answers associated with a specific document.

Request

• Path Parameters:

  • document_id: The ID of the document for which questions are retrieved (required).

  Response

• Status Code: 200 OK

• Response Body:

  [
    {
      "question": "string", // The question asked.
       "answer": "string"     // The answer provided.
     }
  ]