Document Review AI

A proof-of-concept system that automates document review workflows using LLMs (OpenAI, Claude, Gemini). Accepts text input, summarizes content, classifies into categories, and generates actionable next steps with structured output validation.

Features

• Summarization — extracts key points from documents
• Classification — categorizes by type (email, contract, invoice, report, etc.)
• Next Steps — generates structured action items
• Guardrails — validated, constrained outputs with confidence scoring
• Multi-Provider — supports OpenAI, Anthropic Claude, and Google Gemini
• Batch Processing — analyze multiple documents at once

Architecture

frontend/         Next.js UI (Tailwind, ReactDropzone, ReactMarkdown)
backend/          FastAPI (Python 3.11)
  app/
    api/          REST endpoints
    core/         config, settings
    services/     AI logic, guardrails, prompt building
    schemas/      Pydantic models
docker-compose.yml

Quick Start

# 1. Set your API key
export OPENAI_API_KEY="sk-..."

# 2. Start both services
docker compose up -d

# 3. Open the app
open http://localhost:3000

API Usage

curl -X POST http://localhost:8000/api/v1/analyze \
  -H "Content-Type: application/json" \
  -d '{"text": "Your document text here"}'

Response includes summary, classification, next_steps, confidence_score, and timestamp.

Configuration

Set via environment variables or backend/.env:

Variable	Default	Description
OPENAI_API_KEY	—	OpenAI API key
ANTHROPIC_API_KEY	—	Anthropic API key
GEMINI_API_KEY	—	Google Gemini API key
LLM_PROVIDER	openai	Provider: openai, claude, or gemini
LLM_MODEL	gpt-4	Model name

Tech Stack

• Backend: Python, FastAPI, Pydantic, Uvicorn
• Frontend: Next.js 14, TypeScript, Tailwind CSS
• Infrastructure: Docker, Docker Compose

document-review-ai