README.md

metadata

title: Contract Red Team
emoji: 🔍
colorFrom: yellow
colorTo: blue
sdk: gradio
app_file: app.py
pinned: false
license: mit

Contract Red Team

Question

How can an AI assistant review a contract while keeping evidence visible?

System Boundary

This Space is a contract-risk triage tool. It is not legal advice. It is designed to surface clauses worth human review.

Method

The app extracts text from a PDF, chunks the contract into clauses, searches for risk patterns, and uses model-assisted explanation to describe potential issues such as termination, non-compete, IP assignment, liability, and arbitration.

Technique

This is evidence-first document triage. The system combines deterministic risk patterns with model explanation.

The design goal is to keep the clause visible. The model should not be a magic summarizer; it should point to text that a human can inspect.

Output

The app returns a risk report with clause evidence, category labels, and suggested review questions.

Why It Matters

High-stakes document AI must be evidence-first. The user should see why a clause was flagged, not merely receive a summary.

What To Notice

The strongest outputs are tied to exact clauses. If the evidence is vague, the finding should be treated as weak.

Effect In Practice

This workflow can help users prioritize review time by surfacing clauses that deserve attention before a detailed legal review.

Hugging Face Extension

The Space can be expanded with a clause-risk dataset, model explanations, and evaluation on category precision and evidence quality.

Limitations

Contracts are jurisdiction-specific and context-dependent. This tool should be used for education and triage only, followed by professional legal review.

Run Locally

pip install -r requirements.txt
python app.py