Moncey10/homework_validation_system

<<<<<<< HEAD --- title: Homework Validation System sdk: docker appport: 7860 --- hello ======= --- title: Homework Validation System sdk: docker appport: 7860 ---

Homework Validation System (FastAPI)

A backend API that validates student homework by extracting text from teacher and student files, comparing answers, and generating remarks using rule-based logic and optional AI.

Features

• —Upload teacher and student homework files
• —OCR support for images and scanned PDFs
• —Text extraction from PDF and DOCX
• —Similarity matching using TF-IDF + cosine similarity
• —Optional AI-generated remarks (OpenAI / Gemini)
• —FastAPI Swagger documentation

Tech Stack

• —FastAPI
• —Python
• —pytesseract
• —Pillow
• —pypdf / pdf2image
• —python-docx
• —scikit-learn
• —OpenAI / Gemini (optional)

Project Structure

homeworkvalidationsystem/ │ ├── app.py ├── requirements.txt ├── artifacts/ ├── uploads/ ├── src/ │ ├── extractors.py │ ├── similarity.py │ ├── llm_client.py │ └── utils.py └── README.md

Installation

1. Create Virtual Environment

python -m venv myenv

2. Install Requirements

pip install -r requirements.txt

OCR Setup (Required)

Install Tesseract OCR

This project uses Tesseract OCR for extracting text from images and scanned PDFs.

Windows

1. 1.Download and install Tesseract OCR.
2. 2.Default installation path:
3. 3.Add this path in your code:

pytesseract.pytesseract.tesseract_cmd = r"C:\Program Files\Tesseract-OCR\tesseract.exe"

Run API

uvicorn app:app --reload --host 0.0.0.0 --port 8000

Swagger UI:

http://localhost:8000/docs

Example API Response

{ "studentid": 1, "homeworkid": 10, "status": "Needs Review", "matchpercentage": 72, "teacherextractedtext": "...", "studentextractedtext": "...", "aigeneratedremark": "Good attempt but missing key points.", "llmused": true }

>>>>>> cdb5b148e5facdea1aec264a5b4d0b6293132b6e