AI-powered contract reviewer that ingests agreements, extracts key clauses, flags risks, drafts redlines, and generates plain-language summaries.

--> Repository Name - RedlineAI-backend --> Link : https://github.com/dev-philip/RedlineAI-backend --> Description - Redline AI – The Agentic Contract Reviewer & SLA Copilot backend service

Contracts hide critical risks in fine print. Busy professionals and non-lawyers often miss:

• Rent escalations
• Auto-renewals
• Uptime exceptions
• Restrictive jurisdictions
• Data-use loopholes
• Hidden fees

These oversights lead to costly mistakes, delays, and risky commitments.

Redline AI acts as your contract copilot:

• Ingest & Structure: Upload PDF/DOCX → OCR → extract clauses + labels
• Risk & Compare: Match clauses to policy/precedent with vector similarity search (TiDB Serverless)
• Decide & Act: Score risk, propose redlines, notify stakeholders, schedule obligations
• Explain: Generate clear rationales & summaries for business/ops/legal teams

• 📂 Contract ingestion (PDF/DOCX with OCR)
• 🏷️ Clause extraction & tagging (Uptime, Termination, Data Use, etc.)
• 🔍 Vector search against internal policy & past approved language
• 🚨 Risk scoring & redline suggestions
• 📅 Obligation reminders (renewal dates, reporting deadlines)
• 📊 Dashboard + audit log (planned)

• Backend: FastAPI
• Frontend: React + Tailwind (UI, clause viewer, dashboard)
• LLM/Embeddings: OpenAI + LangChain
• Vector DB: TiDB Serverless (VECTOR KNN search)
• Database: PostgreSQL
• Infra: Docker, Uvicorn/Gunicorn, Redis

Clone the repo and install dependencies:

git clone https://github.com/dev-philip/RedlineAI-backend cd RedlineAI-backend pip install -r requirements.txt

1. Clone repo : "https://github.com/dev-philip/RedlineAI-backend"

2. Create a New Conda Environment conda create -n redline-ai-env python=3.11

3. Create a New Conda Environment conda activate redline-ai-env

4. Install pip inside the conda environment (optional, but safe to check) conda install pip

5. Install your dependencies from requirements.txt pip install -r requirements.txt

6. Copy isrgrootx1.pem file from the root project and put it in this location in your local system C:\certs\isrgrootx1.pem. This applies to only windows user. For other operating system and For troubleshooting tip for TLS connection with TIDB use this link : https://docs.pingcap.com/tidbcloud/secure-connections-to-serverless-clusters/

7. Start Project Server : uvicorn app.main:app --reload

1. Create a New Conda Environment conda create -n redline-ai-env python=3.11

2. Create a New Conda Environment conda activate redline-ai-env

3. Install pip inside the conda environment (optional, but safe to check) conda install pip

4. Install your dependencies from requirements.txt pip install -r requirements.txt

5. Verify Installed Packages pip list

6. If you want to save the exact environment for others to use with Conda, you can later export: conda env export > environment.yml OR recreate it using:

7. conda env create -f environment.yml

8. Use pip install and add package to requirement.txt file pip install pydantic-settings echo pydantic-settings >> requirements.txt OR Option 2: Re-freeze your environment. After installing the package, run: pip freeze > requirements.txt Note : This overwrites requirements.txt with everything currently installed in your environment — good for syncing it all, but might include extras you don’t want.

9. Start Project Server : conda activate redline-ai-env uvicorn app.main:app --reload

http://127.0.0.1:8000 → Welcome message http://127.0.0.1:8000/docs → Swagger UI