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Terminal-based platform where specialized AI experts (Legal, Tech, Business) engage in real-time debates and collaborative problem-solving to provide multi-perspective analysis for complex decisions.
A terminal-based multi-AI consultation room where specialized AI assistants discuss problems from their expert perspectives, helping you make informed decisions through real-time AI-to-AI debates.
Expertise: ROI analysis, market strategy, stakeholder management, risk-benefit analysis
Style: "Let's find a middle ground that manages risk while staying competitive."
Focus: Balance legal caution with technical ambition
✨ Key Features
🗣️ AI-to-AI Interaction
AIs respond to each other, not just you
Natural disagreements and professional debates
Direct challenges: "@Tech-AI, you're overlooking the compliance requirements..."
Collaborative problem-solving in real-time
🛡️ Unbreakable Ethics
Manipulation-resistant - won't help with unethical requests regardless of framing
Consistent refusals with alternative suggestions
Built-in legal/ethical guardrails that can't be bypassed
📚 Real Knowledge Base
RAG System fed with actual legal documents
Not just "pretending" to be experts - has domain-specific knowledge
Searchable legal knowledge that informs responses
🔧 100% Free & Local
Ollama for local AI models (no API costs)
Local knowledge base with your documents
Python terminal interface - no web dependencies
Complete privacy - everything runs on your machine
🚀 Quick Start
1. Installation
# Clone or download the project filescd Multiple\Experts# Run the setup scriptpython setup_multi_ai.py
The setup script will:
Install required Python packages
Guide you through Ollama installation
Download AI models (llama2)
Set up the legal documents directory
2. Add Legal Documents (Optional)
# Add your PDF legal documents to the legal_docs folder# The system will automatically process them for Legal-AI
3. Launch the System
python multi_ai_consultation.py# OR use the convenient launcherpython launch_consultation.py
💬 Example Conversation
👤 You: I want to scrape competitor pricing data from their website🔄 Consulting with AI experts...⚖️ Legal-AI: I must advise extreme caution here. Website scraping often violates Terms of Service agreements, and could expose you to legal action under the Computer Fraud and Abuse Act. We need to review their robots.txt and ToS first.💻 Tech-AI: Technically, this is straightforward with tools like Scrapy or Beautiful Soup. @Legal-AI, while ToS violations are a concern, enforcement is rare for basic price monitoring. The technical implementation is simple.⚖️ Legal-AI (follow-up): @Tech-AI, you're underestimating the risk. The hiQ vs LinkedIn case established that ToS violations can constitute unauthorized access. I recommend using public APIs or manually collecting publicly available data instead.📊 Business-AI: Both perspectives have merit. @Legal-AI raises valid compliance concerns, but @Tech-AI is right about competitive necessity. What if we start with publicly available pricing pages and manual collection, then explore API partnerships with data providers?
🎪 System Architecture
graph TB subgraph "User Interface" User["👤 User"] Terminal["🖥️ Terminal Interface"] User --> Terminal end subgraph "Multi-AI Core System" System["🎯 MultiAIConsultation"] PromptMgr["📝 PromptManager"] Ethics["🛡️ Ethical Boundaries"] Session["💾 Session Logger"] Terminal --> System System --> PromptMgr System --> Ethics System --> Session end subgraph "AI Expert Panel" Legal["⚖️ Legal-AI<br/>Conservative & Risk-Focused"] Tech["💻 Tech-AI<br/>Solution-Oriented & Pragmatic"] Business["📊 Business-AI<br/>Strategic & Diplomatic"] System --> Legal System --> Tech System --> Business Legal -.->|"@Tech-AI challenges"| Tech Tech -.->|"@Legal-AI pushback"| Legal Business -.->|"Mediates conflicts"| Legal Business -.->|"Finds balance"| Tech end subgraph "Knowledge Systems" RAG["📚 Legal RAG System"] PDFProc["📄 PDF Processor"] Docs["📁 Legal Documents"] Chunks["🧩 Document Chunks"] Embeddings["🔗 Vector Embeddings"] Legal --> RAG RAG --> Chunks PDFProc --> Chunks Docs --> PDFProc Chunks --> Embeddings end subgraph "AI Infrastructure" Ollama["🤖 Ollama Local Models"] MockAI["🎭 Mock AI (Dev Mode)"] Models["📦 llama2, codellama"] Legal --> Ollama Tech --> Ollama Business --> Ollama Ollama --> Models Legal -.->|"Fallback"| MockAI Tech -.->|"Fallback"| MockAI Business -.->|"Fallback"| MockAI end
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📁 Project Structure
Multiple Experts/├── multi_ai_consultation.py # Main consultation system├── specialized_legal_prompts.py # AI personality definitions├── legal_rag_system.py # Knowledge base integration├── enhanced_pdf_processor.py # PDF document processing├── setup_multi_ai.py # Installation script├── launch_consultation.py # Convenient launcher├── legal_docs/ # Your legal documents (PDFs)└── processed_legal_docs/ # Processed document chunks
🎯 Use Cases
📋 Project Planning
Get legal, technical, and business perspectives simultaneously on new initiatives.
⚠️ Risk Assessment
Multi-angle analysis of business decisions with built-in risk evaluation.
🧭 Ethical Guidance
Built-in conscience that won't compromise on ethics, always suggesting legal alternatives.
🎓 Learning & Development
Watch experts debate and learn from different professional viewpoints.
📝 Decision Documentation
Automatically logged sessions create audit trails of decision-making processes.
💡 Advanced Features
🔍 Smart PDF Processing
Automatic OCR for scanned documents
Intelligent legal document chunking
Metadata extraction (citations, case names, dates)
Support for multiple PDF libraries
🧠 Specialized Prompts
Domain-specific expertise for each AI
Context-aware responses
Professional debate patterns
Ethical boundary enforcement
💾 Session Management
Automatic conversation logging
JSON export for analysis
Searchable conversation history
Session replay capabilities
🛠️ Technical Requirements
Required
Python 3.8+
Ollama (for AI models)
8GB+ RAM (for AI models)
Optional (for enhanced PDF processing)
PyPDF2 / PyMuPDF
Tesseract OCR
PIL/Pillow
AI Models Used
llama2: Primary model for all AIs
llama2:13b: Optional larger model for complex legal analysis
codellama: Optional specialized model for Tech-AI
🚫 Ethical Boundaries
The system includes unbreakable ethical safeguards:
No illegal activity assistance - regardless of how requests are framed
Automatic alternative suggestions - redirects to legal approaches
Professional ethics maintenance - even when AIs disagree
Transparent refusals - clear explanations of why something can't be done
🔧 Customization
Adding New AI Personas
Extend the system by modifyingspecialized_legal_prompts.py:
classNewAIPrompts:SYSTEM_PROMPT="""Your new AI personality..."""# Add specialized prompts
Use smaller models (llama2:7b instead of llama2:13b)
Close other applications
Consider cloud deployment
Performance Tips
Use SSD storage for better model loading
Install models locally:ollama pull llama2
Process PDFs in batches for large document sets
🎯 Future Enhancements
Web interface for easier access
Voice interaction capabilities
Integration with external legal databases
Custom AI persona creation wizard
Multi-language support
Cloud deployment options
📜 License
This project is open source. Use it freely for personal and commercial purposes.
🙏 Acknowledgments
Built on top of Ollama for local AI inference
Uses Sentence Transformers for document embeddings
Inspired by the need for multi-perspective decision making
🚀 Ready to Start?
python setup_multi_ai.py
Welcome to your personal board of AI advisors! 🎯
About
Terminal-based platform where specialized AI experts (Legal, Tech, Business) engage in real-time debates and collaborative problem-solving to provide multi-perspective analysis for complex decisions.