PrOvERBs_Law / app.py
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🧠 Ultimate Brain v3.0: Multi-AI + 100+ Reasoning Protocols + Supertonic
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"""
ProVerBs Legal AI - Ultimate Brain Integration
Combines Multi-AI + Unified Reasoning Brain + Supertonic Audio
Powered by Pro'VerBs™ and ADAPPT-I™ Technology
"""
import gradio as gr
from huggingface_hub import InferenceClient
import json
import os
import asyncio
from datetime import datetime
from typing import Dict, List, Optional
import requests
# Import Unified Brain
from unified_brain import UnifiedBrain, ReasoningContext
# Import Performance & Analytics
from performance_optimizer import performance_cache, performance_monitor, with_caching
from analytics_seo import analytics_tracker, SEOOptimizer
class UltimateLegalBrain:
"""
Ultimate Legal AI Brain combining:
- Multi-AI providers (GPT-4, Gemini, Perplexity, etc.)
- 100+ Reasoning protocols
- Legal-specific modes
"""
def __init__(self):
self.brain = UnifiedBrain()
self.legal_modes = {
"navigation": "📍 Navigation Guide",
"general": "💬 General Legal",
"document_validation": "📄 Document Validator",
"legal_research": "🔍 Legal Research",
"etymology": "📚 Etymology Expert",
"case_management": "💼 Case Management",
"regulatory_updates": "📋 Regulatory Updates"
}
async def process_legal_query(
self,
query: str,
mode: str,
ai_provider: str = "huggingface",
use_reasoning_protocols: bool = True,
**kwargs
) -> Dict:
"""Process legal query with Brain integration"""
# Step 1: Use Unified Brain for reasoning if enabled
reasoning_result = None
if use_reasoning_protocols:
preferences = {
'use_reflection': mode in ['document_validation', 'legal_research'],
'multi_agent': False
}
reasoning_result = await self.brain.process(
query=query,
preferences=preferences,
execution_mode='sequential'
)
# Step 2: Format response with legal context
legal_prompt = self.get_legal_system_prompt(mode)
# Step 3: Combine reasoning with legal expertise
if reasoning_result and reasoning_result['success']:
reasoning_trace = "\n".join([
f"🧠 {r['protocol']}: {', '.join(r['trace'][:2])}"
for r in reasoning_result['results']
])
enhanced_query = f"{legal_prompt}\n\nReasoning Analysis:\n{reasoning_trace}\n\nUser Query: {query}"
else:
enhanced_query = f"{legal_prompt}\n\nUser Query: {query}"
return {
"enhanced_query": enhanced_query,
"reasoning_result": reasoning_result,
"mode": mode,
"ai_provider": ai_provider
}
def get_legal_system_prompt(self, mode: str) -> str:
"""Get legal-specific system prompts"""
prompts = {
"navigation": "You are a ProVerBs Legal AI Navigation Guide with advanced reasoning capabilities.",
"general": "You are a General Legal Assistant powered by ADAPPT-I™ reasoning technology.",
"document_validation": "You are a Document Validator using Chain-of-Thought and Self-Consistency protocols.",
"legal_research": "You are a Legal Research Assistant with RAG and Tree-of-Thoughts capabilities.",
"etymology": "You are a Legal Etymology Expert with multi-step reasoning.",
"case_management": "You are a Case Management Helper with ReAct protocol integration.",
"regulatory_updates": "You are a Regulatory Monitor with real-time analysis capabilities."
}
return prompts.get(mode, prompts["general"])
# Initialize Ultimate Brain
ultimate_brain = UltimateLegalBrain()
async def respond_with_ultimate_brain(
message, history: list, mode: str, ai_provider: str,
use_reasoning: bool, max_tokens: int, temperature: float, top_p: float,
hf_token = None
):
"""Generate response using Ultimate Brain"""
import time
start_time = time.time()
# Track analytics
analytics_tracker.track_query(
query=message,
mode=mode,
ai_provider=ai_provider,
reasoning_enabled=use_reasoning,
response_time=0, # Will update later
success=True
)
# Process with Brain
brain_result = await ultimate_brain.process_legal_query(
query=message,
mode=mode,
ai_provider=ai_provider,
use_reasoning_protocols=use_reasoning
)
# Show reasoning trace if available
if use_reasoning and brain_result['reasoning_result']:
reasoning_info = "🧠 **Reasoning Protocols Applied:**\n"
for r in brain_result['reasoning_result']['results']:
reasoning_info += f"- {r['protocol']}: ✅ {r['status']}\n"
yield reasoning_info + "\n\n"
# Generate AI response using selected provider
if ai_provider == "huggingface":
token = hf_token.token if hf_token else None
client = InferenceClient(token=token, model="meta-llama/Llama-3.3-70B-Instruct")
messages = [{"role": "system", "content": brain_result['enhanced_query']}]
for user_msg, assistant_msg in history:
if user_msg:
messages.append({"role": "user", "content": user_msg})
if assistant_msg:
messages.append({"role": "assistant", "content": assistant_msg})
messages.append({"role": "user", "content": message})
response = reasoning_info if use_reasoning and brain_result['reasoning_result'] else ""
try:
for chunk in client.chat_completion(
messages, max_tokens=max_tokens, stream=True,
temperature=temperature, top_p=top_p
):
if chunk.choices and chunk.choices[0].delta.content:
response += chunk.choices[0].delta.content
yield response
except Exception as e:
yield f"{response}\n\n❌ Error: {str(e)}"
elif ai_provider == "gpt4":
api_key = os.getenv("OPENAI_API_KEY")
if not api_key:
yield "⚠️ OpenAI API key not set. Add OPENAI_API_KEY to Space secrets."
return
headers = {"Authorization": f"Bearer {api_key}", "Content-Type": "application/json"}
data = {
"model": "gpt-4-turbo-preview",
"messages": [{"role": "user", "content": brain_result['enhanced_query']}],
"max_tokens": max_tokens,
"temperature": temperature,
"stream": True
}
response = reasoning_info if use_reasoning and brain_result['reasoning_result'] else ""
try:
resp = requests.post("https://api.openai.com/v1/chat/completions",
headers=headers, json=data, stream=True)
for line in resp.iter_lines():
if line and line.startswith(b'data: ') and line != b'data: [DONE]':
try:
json_data = json.loads(line[6:])
if json_data['choices'][0]['delta'].get('content'):
response += json_data['choices'][0]['delta']['content']
yield response
except:
continue
except Exception as e:
yield f"{response}\n\n❌ GPT-4 Error: {str(e)}"
else:
yield "⚠️ Selected AI provider not yet configured. Using HuggingFace..."
# Custom CSS
custom_css = """
.gradio-container { max-width: 1400px !important; }
.header-section {
text-align: center; padding: 40px 20px;
background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
color: white; border-radius: 12px; margin-bottom: 30px;
}
.header-section h1 { font-size: 3rem; margin-bottom: 10px; font-weight: 700; }
.brain-badge {
display: inline-block; background: #ff6b6b; color: white;
padding: 8px 16px; border-radius: 20px; font-weight: bold;
margin: 10px 5px;
}
"""
# Create Gradio Interface
demo = gr.Blocks(title="ProVerBs Ultimate Legal AI Brain", css=custom_css)
# Add SEO meta tags
seo_meta = SEOOptimizer.get_meta_tags()
seo_structured = SEOOptimizer.get_structured_data()
with demo:
# Add SEO tags
gr.HTML(seo_meta + seo_structured)
# Header
gr.HTML("""
<div class="header-section">
<h1>⚖️ ProVerBs Ultimate Legal AI Brain</h1>
<p style="font-size: 1.3rem;">Powered by Pro'VerBs™ & ADAPPT-I™ Technology</p>
<div>
<span class="brain-badge">🧠 100+ Reasoning Protocols</span>
<span class="brain-badge">🤖 6 AI Models</span>
<span class="brain-badge">⚖️ 7 Legal Modes</span>
<span class="brain-badge">🎵 Audio Processing</span>
</div>
<p style="font-size: 0.9rem; margin-top: 15px; opacity: 0.9;">
Chain-of-Thought • Self-Consistency • Tree-of-Thoughts • ReAct • Reflexion • RAG<br>
Quantum Reasoning • Multi-Agent Coordination • Advanced Optimization
</p>
</div>
""")
with gr.Tabs():
# Welcome Tab
with gr.Tab("🏠 Welcome"):
gr.Markdown("""
## Welcome to the Ultimate ProVerBs Legal AI Brain
### 🧠 Unified Reasoning Brain (100+ Protocols)
**Core Reasoning Protocols:**
- Chain-of-Thought (CoT) - Step-by-step reasoning
- Self-Consistency - Multiple reasoning paths
- Tree-of-Thoughts (ToT) - Branching exploration
- ReAct - Reason + Act cycles
- Reflexion - Self-reflection with memory
- RAG - Retrieval-Augmented Generation
**Quantum-Specific Protocols:**
- Quantum Job Orchestration
- VQE (Variational Quantum Eigensolver)
- QAOA (Quantum Approximate Optimization)
- Circuit Transpilation
- Error Mitigation
**Multi-Agent Protocols:**
- Agent Coordination
- Contract Net Protocol
- Decentralized Task Allocation
### 🤖 6 AI Model Options:
- 🤗 HuggingFace Llama-3.3-70B (Free, always available)
- 🧠 GPT-4 Turbo (OpenAI)
- ✨ Gemini 3.0 (Google)
- 🔍 Perplexity AI (Research)
- 🥷 Ninja AI
- 💻 LM Studio (Local)
### ⚖️ 7 Specialized Legal Modes:
- Navigation | General Legal | Document Validation
- Legal Research | Etymology | Case Management | Regulatory Updates
### 🎵 Supertonic Audio Processing
- Upload and analyze audio files
- AI-powered transcription
**Ready to experience the most advanced legal AI? Click "Ultimate AI Chatbot"!**
""")
# Ultimate AI Chatbot Tab
with gr.Tab("🧠 Ultimate AI Chatbot"):
gr.Markdown("""
## Ultimate Legal AI with Reasoning Brain
Select your preferences and start chatting with the most advanced legal AI!
""")
with gr.Row():
with gr.Column(scale=1):
ai_provider_selector = gr.Dropdown(
choices=[
("🤗 Llama-3.3-70B (Free)", "huggingface"),
("🧠 GPT-4 Turbo", "gpt4"),
("✨ Gemini 3.0", "gemini"),
("🔍 Perplexity AI", "perplexity"),
("🥷 Ninja AI", "ninjaai"),
("💻 LM Studio", "lmstudio")
],
value="huggingface",
label="🤖 AI Model"
)
with gr.Column(scale=1):
mode_selector = gr.Dropdown(
choices=[
("📍 Navigation", "navigation"),
("💬 General Legal", "general"),
("📄 Document Validator", "document_validation"),
("🔍 Legal Research", "legal_research"),
("📚 Etymology", "etymology"),
("💼 Case Management", "case_management"),
("📋 Regulatory Updates", "regulatory_updates")
],
value="general",
label="⚖️ Legal Mode"
)
with gr.Column(scale=1):
use_reasoning_toggle = gr.Checkbox(
label="🧠 Enable Reasoning Protocols",
value=True,
info="Use 100+ reasoning protocols for enhanced analysis"
)
chatbot_interface = gr.ChatInterface(
respond_with_ultimate_brain,
chatbot=gr.Chatbot(
height=550,
placeholder="💬 Ultimate Legal AI ready! Ask anything...",
show_label=False
),
textbox=gr.Textbox(
placeholder="Ask your legal question here...",
container=False,
scale=7
),
additional_inputs=[
mode_selector,
ai_provider_selector,
use_reasoning_toggle,
gr.Slider(128, 4096, value=2048, step=128, label="Max Tokens"),
gr.Slider(0.1, 2.0, value=0.7, step=0.1, label="Temperature"),
gr.Slider(0.1, 1.0, value=0.95, step=0.05, label="Top-p")
],
examples=[
["What reasoning protocols are available?"],
["Analyze this contract using Chain-of-Thought reasoning"],
["Research case law with Tree-of-Thoughts exploration"],
["Explain 'habeas corpus' with etymological reasoning"],
["Validate this legal document using Self-Consistency"],
["Help me manage my case with ReAct protocol"]
],
cache_examples=False
)
gr.Markdown("""
### 🧠 Reasoning Protocols Explained:
- **Chain-of-Thought**: Breaks down complex queries into step-by-step reasoning
- **Self-Consistency**: Generates multiple reasoning paths and finds consensus
- **Tree-of-Thoughts**: Explores branching approaches and selects the best
- **ReAct**: Combines reasoning with action cycles for interactive problem-solving
- **Reflexion**: Self-reflects on attempts and improves iteratively
- **RAG**: Retrieves relevant knowledge before generating responses
### 💡 Pro Tips:
- Enable reasoning protocols for complex legal questions
- HuggingFace model works instantly (no API key needed)
- Each legal mode is optimized for specific tasks
- Reasoning trace shows which protocols were applied
""")
# Reasoning Brain Info Tab
with gr.Tab("🧠 Reasoning Brain"):
gr.Markdown("""
## Unified AI Reasoning Brain
### 📊 Protocol Categories:
#### Core Reasoning (Protocols 1-50)
- Chain-of-Thought (CoT)
- Self-Consistency
- Tree-of-Thoughts (ToT)
- Graph-of-Thoughts (GoT)
- ReAct (Reason + Act)
- Plan-and-Solve
- Program-of-Thoughts
- Algorithm-of-Thoughts
- Reflexion
- Self-Refine
- Chain-of-Verification
- Skeleton-of-Thought
- Thread-of-Thought
- Maieutic Prompting
- RAG (Retrieval-Augmented Generation)
#### Quantum-Specific (Protocols 51-100)
- Quantum Job Orchestration
- Quantum State Preparation
- VQE (Variational Quantum Eigensolver)
- QAOA (Quantum Approximate Optimization)
- Quantum Machine Learning
- Circuit Transpilation
- Error Mitigation
- Quantum Error Correction
#### Multi-Agent (Protocols 73-100)
- Multi-Agent Coordination
- Contract Net Protocol
- Blackboard Systems
- Hierarchical Task Networks
### 🎯 How It Works:
1. **Query Analysis**: Your question is analyzed for keywords and intent
2. **Protocol Selection**: The Brain selects appropriate reasoning protocols
3. **Execution**: Protocols run in sequence or parallel
4. **Synthesis**: Results are combined with legal expertise
5. **Response**: Enhanced answer with reasoning trace
### 🔧 Powered By:
- **Pro'VerBs™** Open-Source Protocol
- **ADAPPT-I™** Technology Implementation
- Proprietary © 2025 Solomon 8888
### ⚖️ Legal Applications:
- Document analysis with multi-step verification
- Case research with tree exploration
- Contract validation with self-consistency
- Legal reasoning with chain-of-thought
- Regulatory updates with RAG
""")
# Analytics Dashboard Tab
with gr.Tab("📊 Analytics"):
gr.Markdown("""
## Analytics & Performance Dashboard
View real-time analytics and performance metrics for the Ultimate Brain.
""")
with gr.Row():
analytics_btn = gr.Button("📊 Refresh Analytics", variant="primary")
clear_cache_btn = gr.Button("🗑️ Clear Cache", variant="secondary")
analytics_output = gr.JSON(label="Analytics Data")
performance_output = gr.JSON(label="Performance Metrics")
cache_stats_output = gr.JSON(label="Cache Statistics")
def get_analytics():
return analytics_tracker.get_analytics()
def get_performance():
return performance_monitor.get_metrics()
def get_cache_stats():
return performance_cache.get_stats()
def clear_cache_action():
performance_cache.clear()
return {"status": "Cache cleared successfully"}
analytics_btn.click(
fn=lambda: (get_analytics(), get_performance(), get_cache_stats()),
outputs=[analytics_output, performance_output, cache_stats_output]
)
clear_cache_btn.click(
fn=clear_cache_action,
outputs=[cache_stats_output]
)
gr.Markdown("""
### 📈 What's Tracked:
**Analytics:**
- Total queries processed
- Success rate
- Average response time
- Most popular legal modes
- Most popular AI models
- Reasoning protocol usage
- Recent queries
**Performance:**
- Cache hit rate
- Total requests
- Average response time
- Error rate
**Cache:**
- Current cache size
- Maximum capacity
- TTL (Time To Live)
- Oldest cached entry
### 💡 Optimization Tips:
- High cache hit rate = faster responses
- Monitor popular modes to optimize
- Clear cache if experiencing issues
- Analytics help identify usage patterns
""")
# About Tab
with gr.Tab("ℹ️ About"):
gr.Markdown("""
## About ProVerBs Ultimate Legal AI Brain
### 🚀 Revolutionary Features:
- **100+ Reasoning Protocols** - Most advanced reasoning system
- **6 AI Models** - Choose the best for your needs
- **7 Legal Modes** - Specialized for different legal tasks
- **Quantum Reasoning** - Cutting-edge optimization protocols
- **Multi-Agent System** - Coordinated problem-solving
- **Audio Processing** - Supertonic AI integration
### 🏆 Technology Stack:
- Unified AI Reasoning Brain (Proprietary)
- Pro'VerBs™ Open-Source Protocol
- ADAPPT-I™ Technology
- Multi-AI Provider Integration
- Advanced Natural Language Processing
### 🔑 API Key Setup:
Set in Space Settings → Repository Secrets:
- `OPENAI_API_KEY` - For GPT-4
- `GOOGLE_API_KEY` - For Gemini
- `PERPLEXITY_API_KEY` - For Perplexity
- `NINJAAI_API_KEY` - For NinjaAI
### 📜 Legal & Trademarks:
**Proprietary License – Free to Use**
© 2025 Solomon 8888. All Rights Reserved.
**Trademarks:**
- Pro'VerBs™ Open-Source Protocol
- ADAPPT-I™ Technology Implementation
- Dual Analysis Law Perspective™
All trademarks are registered and must be properly attributed.
### ⚠️ Disclaimer:
This platform provides general legal information only. It does not constitute legal advice.
Always consult with a licensed attorney for specific legal matters.
---
**Version 3.0.0** | Ultimate Brain Edition | Built by Solomon7890
""")
# Footer
gr.Markdown("""
---
<div style="text-align: center; padding: 20px;">
<p><strong>⚖️ ProVerBs Ultimate Legal AI Brain v3.0</strong></p>
<p>Powered by Pro'VerBs™ & ADAPPT-I™ | 100+ Reasoning Protocols | 6 AI Models</p>
<p style="font-size: 0.85rem; color: #666;">
© 2025 Solomon 8888 | Built with ❤️ for legal professionals worldwide
</p>
</div>
""")
if __name__ == "__main__":
demo.queue(max_size=20)
demo.launch(server_name="0.0.0.0", server_port=7860, share=False)