AI Legal Team Agents

An interactive Streamlit app that analyzes uploaded legal documents using a team of specialized AI agents (LegalAdvisor, ContractAnalyst, LegalStrategist, and Team Lead). It searches an embedded knowledge base (ChromaDB) built from your PDF and produces concise, actionable insights.

Key Features

• Document ingestion: Upload a PDF; content is chunked and embedded into ChromaDB.
• Multi‑agent analysis: Research, contract review, risk assessment, compliance checks.
• Concise Custom Query: In the “Custom Query” mode, the agent answers strictly and concisely (3–5 sentences) without long analysis.
• Structured results: Executive summary, critical clauses by risk level, strengths, weaknesses, and actionable recommendations.

Requirements

• Python 3.10+
• A Google Gemini API key (set as GOOGLE_API_KEY)

Setup (Windows PowerShell)

1) Create and activate a virtual environment
python -m venv legal-venv
./legal-venv/Scripts/Activate.ps1

2) Install dependencies
pip install -r requirements.txt

3) Use the Google Gemini API key once localhost is live

4) Run the app
streamlit run legal_team.py

If PowerShell blocks script execution, run PowerShell as Administrator and temporarily enable scripts:

Set-ExecutionPolicy -Scope Process -ExecutionPolicy Bypass

Usage

1. Start the app: streamlit run legal_team.py.
2. Enter your API key in the sidebar when prompted.
3. Upload a legal PDF.
4. Pick an analysis type:
   • Contract Review / Legal Research / Risk Assessment / Compliance Check: Click “Analyze” to generate the multi‑agent report with tabs.
   • Custom Query: Ask a question about the uploaded document. The agent replies directly and briefly, avoiding long legal analysis.

Output Overview

• Analysis tab: Executive summary; critical clauses highlighted by risk.
• Key Points tab: Strengths and weaknesses listed without colored backgrounds.
• Recommendations tab: Actionable items listed plainly (no colored backgrounds).

Project Structure

legal-assistant-final/
  ├─ legal_team.py           # Streamlit app
  ├─ requirements.txt        # Python dependencies
  └─ tmp/                    # Local ChromaDB and contents DB storage

Troubleshooting

• Missing agno.* imports: Ensure you installed from requirements.txt inside the active virtual environment.
• No results after upload: Verify the PDF is text‑extractable (not image‑only) and try again.

Notes

• The app uses Google Gemini for both embeddings and generation.
• Data is stored locally in tmp/ for persistence across runs.

Live link: https://sprnjt-legal-ai-assistant-legal-team-ltme7x.streamlit.app

Project Screenshots:

Main Page:

After upload of Google Gemini API key and Legal Doc:

Contract Analysis of Receiving Party(Client):

Contract Analysis of Issuing Party:

Key Points:

Actionable Recommendations:

Custom Query Chat: