Autonomous Multi-Agent Enterprise Procurement Document Reviewer
Agents League Hackathon Submission

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What It Does

ProcureShield AI reviews inbound vendor contracts using a 3-agent LangGraph pipeline:

Agent	Role
Agent 1 — Data Extractor	Pulls payment terms, liability caps, SLA clauses, and 7+ other fields from raw contract text
Agent 2 — Compliance Auditor	Cross-references extracted items against company procurement standards and produces a prioritised risk report (HIGH / MEDIUM / LOW)
Agent 3 — Reply Automator	Drafts a professional negotiation email requesting amendments to all flagged clauses

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Project Structure

procureshield_ai/
├── app.py                    ← Streamlit UI (entry point)
├── pipeline.py               ← LangGraph orchestration
├── config.py                 ← Credential loader
├── requirements.txt          ← Python dependencies
├── .env.example              ← Copy to .env and add your API key
│
├── agents/
│   ├── state.py              ← Shared AgentState TypedDict
│   ├── data_extractor.py     ← Agent 1
│   ├── compliance_auditor.py ← Agent 2
│   └── reply_automator.py    ← Agent 3
│
├── utils/
│   └── document_parser.py    ← PDF / DOCX text extraction
│
└── sample_data/
    └── sample_contract.txt   ← Demo contract with intentional violations

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Quick Start

🚀 Setup Instructions for Judges

To run and evaluate the live agent swarm, please configure your own OpenAI API key. The project is designed to automatically read your local environment variables.

⚙️ Quick Start Installation

1. Clone this repository to your local workspace.
2. Create a .env file in the root directory and add your key:

   OPENAI_API_KEY=your_actual_openai_key_here

3. Run the installation and start the backend:

   pip install -r requirements.txt
   uvicorn main:app --reload

Note: If no API key is provided, the system will automatically fall back to a high-fidelity Offline Demo Mode so you can still experience the multi-agent UI pipeline workflow without any API errors!

1. Install dependencies

cd procureshield_ai
pip install -r requirements.txt

2. Add your API key

cp .env.example .env
# Open .env and replace "your-openai-api-key-here" with your real key

Or enter the key directly in the sidebar when the app is running.

3. Launch the app

streamlit run app.py

Then open http://localhost:8501 in your browser.

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Using Azure OpenAI Instead

Edit .env and fill in the Azure section:

AZURE_OPENAI_API_KEY=your-azure-key
AZURE_OPENAI_ENDPOINT=https://your-resource.openai.azure.com/
AZURE_OPENAI_DEPLOYMENT=your-deployment-name
AZURE_OPENAI_API_VERSION=2024-02-01

Comment out OPENAI_API_KEY — the app auto-detects which provider to use.

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Supported Input Formats

Format	Notes
Paste text	Any contract clauses pasted directly
PDF	Text-based PDFs (not scanned images)
DOCX / DOC	Microsoft Word documents
TXT	Plain text files

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Company Procurement Standards (built-in)

The Compliance Auditor uses these rules (edit in agents/compliance_auditor.py):

Area	Acceptable	HIGH Risk
Payment Terms	Net-30 or better	Net-90 or longer
Liability Cap	≥ $1,000,000	< $500,000
Data Security	SOC2 / ISO27001 / GDPR DPA	None specified
Auto-Renewal Notice	≥ 30 days	< 30 days
SLA Uptime	≥ 99.5%	< 99%
Termination Lock-in	≤ 12 months	> 12 months

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Tech Stack

• LangGraph — Multi-agent state graph orchestration
• LangChain OpenAI — LLM client (OpenAI or Azure OpenAI)
• Streamlit — Interactive web UI
• PyPDF2 — PDF text extraction
• python-docx — DOCX text extraction
• python-dotenv — Environment variable management

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License

MIT — free to use, modify, and extend.