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"""
ProVerBs Ultimate Brain with Complete Voice Cloning
Integrates Supertonic voice cloning with all controls
"""
# Import everything from app_ultimate_brain
import sys
import os
sys.path.append(os.path.dirname(__file__))
import gradio as gr
from huggingface_hub import InferenceClient
import json
import os
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
# Import Voice Cloning
from supertonic_voice_module import create_supertonic_interface
# Define class FIRST
class UltimateLegalBrain:
def __init__(self):
self.brain = UnifiedBrain()
self.legal_modes = {
"navigation": "π Navigation Guide",
"general": "π¬ General Legal",
"document_validation": "π Document Validator",
"legal_research": "π Legal Research",
"etymology": "π Etymology Expert",
"case_management": "πΌ Case Management",
"regulatory_updates": "π Regulatory Updates"
}
async def process_legal_query(self, query: str, mode: str, ai_provider: str = "huggingface", use_reasoning_protocols: bool = True, **kwargs) -> Dict:
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')
legal_prompt = self.get_legal_system_prompt(mode)
if reasoning_result and reasoning_result['success']:
reasoning_trace = "\n".join([f"π§ {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:
prompts = {
"navigation": "You are a ProVerBs Legal AI Navigation Guide with advanced reasoning capabilities.",
"general": "You are a General Legal Assistant powered by ADAPPT-Iβ’ 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"])
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):
import time
start_time = time.time()
brain_result = await ultimate_brain.process_legal_query(query=message, mode=mode, ai_provider=ai_provider, use_reasoning_protocols=use_reasoning)
if use_reasoning and brain_result['reasoning_result']:
reasoning_info = "π§ **Reasoning Protocols Applied:**\n"
for r in brain_result['reasoning_result']['results']:
reasoning_info += f"- {r['protocol']}: β
{r['status']}\n"
yield reasoning_info + "\n\n"
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\nβ Error: {str(e)}"
# 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;
}
"""
# SEO
seo_meta = SEOOptimizer.get_meta_tags()
seo_structured = SEOOptimizer.get_structured_data()
# Initialize AFTER class definition
ultimate_brain = UltimateLegalBrain()
# Override the demo with voice cloning integrated
demo_with_voice = gr.Blocks(title="ProVerBs Ultimate Legal AI Brain", css=custom_css)
with demo_with_voice:
# Add SEO tags
gr.HTML(seo_meta + seo_structured)
# Header
gr.HTML("""
<div class="header-section">
<h1>βοΈ ProVerBs Ultimate Legal AI Brain</h1>
<p style="font-size: 1.3rem;">Powered by Pro'VerBsβ’ & ADAPPT-Iβ’ Technology</p>
<div>
<span class="brain-badge">π§ 100+ Reasoning Protocols</span>
<span class="brain-badge">π€ 6 AI Models</span>
<span class="brain-badge">βοΈ 7 Legal Modes</span>
<span class="brain-badge">ποΈ Voice Cloning</span>
</div>
<p style="font-size: 0.9rem; margin-top: 15px; opacity: 0.9;">
Chain-of-Thought β’ Self-Consistency β’ Tree-of-Thoughts β’ ReAct β’ Reflexion β’ RAG<br>
Quantum Reasoning β’ Multi-Agent β’ Voice Cloning β’ Audio Processing
</p>
</div>
""")
with gr.Tabs():
# Welcome Tab
with gr.Tab("π Welcome"):
gr.Markdown("""
## Welcome to the Ultimate ProVerBs Legal AI Brain
### π§ 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
### π€ 6 AI Model Options:
- π€ HuggingFace Llama-3.3-70B (Free, always available)
- π§ GPT-4 Turbo (OpenAI)
- β¨ Gemini 3.0 (Google)
- π Perplexity AI (Research)
- π₯· Ninja AI
- π» LM Studio (Local)
### βοΈ 7 Specialized Legal Modes:
- Navigation | General Legal | Document Validation
- Legal Research | Etymology | Case Management | Regulatory Updates
### ποΈ **NEW! Supertonic Voice Cloning:**
- Record voice samples
- Clone voices with text-to-speech
- Professional audio processing
- Voice profile management
- **Full controls**: Play, Record, Pause, Rewind, etc.
**Get Started:** Click "π€ AI Legal Chatbot" or "ποΈ Voice Cloning" tab!
""")
# AI Chatbot Tab (copy from original)
with gr.Tab("π€ AI Legal Chatbot"):
gr.Markdown("""
## Multi-AI Legal Chatbot
Select your AI model and legal assistant mode below!
""")
with gr.Row():
ai_provider_selector = gr.Dropdown(
choices=[
("π€ Llama-3.3-70B (Free)", "huggingface"),
("π§ GPT-4 Turbo", "gpt4"),
("β¨ Gemini 3.0", "gemini"),
("π Perplexity AI", "perplexity"),
("π₯· Ninja AI", "ninjaai"),
("π» LM Studio", "lmstudio")
],
value="huggingface",
label="π€ AI Model"
)
mode_selector = gr.Dropdown(
choices=[
("π Navigation", "navigation"),
("π¬ General Legal", "general"),
("π Document Validator", "document_validation"),
("π Legal Research", "legal_research"),
("π Etymology", "etymology"),
("πΌ Case Management", "case_management"),
("π Regulatory Updates", "regulatory_updates")
],
value="general",
label="βοΈ Legal Mode"
)
use_reasoning_toggle = gr.Checkbox(
label="π§ 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="π¬ 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"]
],
cache_examples=False
)
# Voice Cloning Tab - FULL SUPERTONIC INTERFACE
with gr.Tab("ποΈ Voice Cloning"):
create_supertonic_interface()
# Analytics Tab
with gr.Tab("π Analytics"):
gr.Markdown("""
## Analytics & Performance Dashboard
View real-time analytics and performance metrics for the Ultimate Brain.
""")
with gr.Row():
analytics_btn = gr.Button("π Refresh Analytics", variant="primary")
clear_cache_btn = gr.Button("ποΈ 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]
)
# Reasoning Brain Tab
with gr.Tab("π§ Reasoning Brain"):
gr.Markdown("""
## Unified AI Reasoning Brain
### π Protocol Categories:
#### Core Reasoning (Protocols 1-50)
- Chain-of-Thought, Self-Consistency, Tree-of-Thoughts
- ReAct, Reflexion, RAG, and more
#### Quantum-Specific (Protocols 51-100)
- Quantum Job Orchestration, VQE, QAOA
- Circuit Transpilation, Error Mitigation
#### Multi-Agent (Protocols 73-100)
- Multi-Agent Coordination
- Contract Net Protocol
""")
# About Tab
with gr.Tab("βΉοΈ About"):
gr.Markdown("""
## About ProVerBs Ultimate Legal AI Brain
### π 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
- **Voice Cloning** - Professional Supertonic integration
- **Audio Processing** - Complete recording and playback controls
### ποΈ Voice Cloning Features:
- Record voice samples with full controls
- Clone any voice with text-to-speech
- Professional audio processing
- Export voice profiles
- Play, Pause, Record, Rewind, Stop controls
### π Resources:
- **Main Space**: https://huggingface.co/spaces/Solomon7890/ProVerbS_LaW_mAiN_PAgE
- **Supertonic**: https://github.com/supertone-inc/supertonic
- **Models**: https://huggingface.co/Supertone/supertonic
### β οΈ Disclaimer:
This platform provides general legal information only. Consult with a licensed attorney for specific legal matters.
---
**Version 3.0.0 + Voice Cloning** | Built by Solomon7890
""")
# Footer
gr.Markdown("""
---
<div style="text-align: center; padding: 20px;">
<p><strong>βοΈ ProVerBs Ultimate Legal AI Brain v3.0 + Voice Cloning</strong></p>
<p>Powered by Pro'VerBsβ’ & ADAPPT-Iβ’ | 100+ Protocols | 6 AI Models | Voice Cloning</p>
<p style="font-size: 0.85rem; color: #666;">
Β© 2025 Solomon 8888 | Built with β€οΈ for legal professionals worldwide
</p>
</div>
""")
# Use the new demo with voice cloning
demo = demo_with_voice
if __name__ == "__main__":
demo.queue(max_size=20)
demo.launch(server_name="0.0.0.0", server_port=7860, share=False)
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