app.py

import os
import json
import time
import gradio as gr
from datetime import datetime
from typing import List, Dict, Any, Optional, Union
import threading
import re
import aiohttp
import asyncio

# Import Groq
from groq import Groq

class CreativeAgenticAI:
    """
    Creative Agentic AI Chat Tool using multiple providers (Groq and Chutes)
    """
    
    def __init__(self, groq_api_key: str = None, chutes_api_key: str = None, provider: str = "groq", model: str = None):
        """
        Initialize the Creative Agentic AI system.
        
        Args:
            groq_api_key: Groq API key
            chutes_api_key: Chutes API key
            provider: Which provider to use ('groq' or 'chutes')
            model: Which model to use
        """
        self.groq_api_key = groq_api_key
        self.chutes_api_key = chutes_api_key
        self.provider = provider
        self.conversation_history = []
        
        # Initialize clients based on provider
        if provider == "groq" and groq_api_key:
            if not groq_api_key:
                raise ValueError("No Groq API key provided")
            self.groq_client = Groq(api_key=groq_api_key)
            self.model = model or "compound-beta"
        elif provider == "chutes" and chutes_api_key:
            if not chutes_api_key:
                raise ValueError("No Chutes API key provided")
            self.model = model or "openai/gpt-oss-20b"
        else:
            raise ValueError(f"Invalid provider or missing API key for {provider}")
        
    async def _chutes_chat_async(self, messages: List[Dict], temperature: float = 0.7, max_tokens: int = 1024) -> str:
        """
        Async method for Chutes API chat
        """
        headers = {
            "Authorization": f"Bearer {self.chutes_api_key}",
            "Content-Type": "application/json"
        }
        
        body = {
            "model": self.model,
            "messages": messages,
            "stream": False,  # Set to False for simpler handling
            "max_tokens": max_tokens,
            "temperature": temperature
        }
        
        async with aiohttp.ClientSession() as session:
            async with session.post(
                "https://llm.chutes.ai/v1/chat/completions", 
                headers=headers,
                json=body
            ) as response:
                if response.status == 200:
                    result = await response.json()
                    return result['choices'][0]['message']['content']
                else:
                    error_text = await response.text()
                    raise Exception(f"Chutes API error: {response.status} - {error_text}")

    def _chutes_chat_sync(self, messages: List[Dict], temperature: float = 0.7, max_tokens: int = 1024) -> str:
        """
        Synchronous wrapper for Chutes API chat
        """
        try:
            loop = asyncio.get_event_loop()
        except RuntimeError:
            loop = asyncio.new_event_loop()
            asyncio.set_event_loop(loop)
        
        return loop.run_until_complete(
            self._chutes_chat_async(messages, temperature, max_tokens)
        )
        
    def chat(self, message: str, 
             include_domains: List[str] = None,
             exclude_domains: List[str] = None,
             system_prompt: str = None,
             temperature: float = 0.7,
             max_tokens: int = 1024) -> Dict:
        """
        Send a message to the AI and get a response
        
        Args:
            message: User's message
            include_domains: List of domains to include for web search (Groq only)
            exclude_domains: List of domains to exclude from web search (Groq only)
            system_prompt: Custom system prompt
            temperature: Model temperature (0.0-2.0)
            max_tokens: Maximum tokens in response
            
        Returns:
            AI response with metadata
        """
        # Enhanced system prompt for better citation behavior
        if not system_prompt:
            if self.provider == "groq":
                citation_instruction = """
IMPORTANT: When you search the web and find information, you MUST:
1. Always cite your sources with clickable links in this format: [Source Title](URL)
2. Include multiple diverse sources when possible
3. Show which specific websites you used for each claim
4. At the end of your response, provide a "Sources Used" section with all the links
5. Be transparent about which information comes from which source
"""
                
                domain_context = ""
                if include_domains:
                    domain_context = f"\nYou are restricted to searching ONLY these domains: {', '.join(include_domains)}. Make sure to find and cite sources specifically from these domains."
                elif exclude_domains:
                    domain_context = f"\nAvoid searching these domains: {', '.join(exclude_domains)}. Search everywhere else on the web."
                
                system_prompt = f"""You are a creative and intelligent AI assistant with agentic capabilities. 
                You can search the web, analyze information, and provide comprehensive responses. 
                Be helpful, creative, and engaging while maintaining accuracy.
                
                {citation_instruction}
                {domain_context}
                
                Your responses should be well-structured, informative, and properly cited with working links."""
            else:
                # Simpler system prompt for Chutes (no web search capabilities)
                system_prompt = """You are a creative and intelligent AI assistant. 
                Be helpful, creative, and engaging while maintaining accuracy.
                Your responses should be well-structured, informative, and comprehensive."""
        
        # Build messages
        messages = [{"role": "system", "content": system_prompt}]
        
        # Add conversation history (last 10 exchanges)
        messages.extend(self.conversation_history[-20:])  # Last 10 user-assistant pairs
        
        # Add current message with domain filtering context (Groq only)
        enhanced_message = message
        if self.provider == "groq" and (include_domains or exclude_domains):
            filter_context = []
            if include_domains:
                filter_context.append(f"ONLY search these domains: {', '.join(include_domains)}")
            if exclude_domains:
                filter_context.append(f"EXCLUDE these domains: {', '.join(exclude_domains)}")
            enhanced_message += f"\n\n[Domain Filtering: {' | '.join(filter_context)}]"
        
        messages.append({"role": "user", "content": enhanced_message})
        
        try:
            if self.provider == "groq":
                return self._handle_groq_chat(messages, include_domains, exclude_domains, temperature, max_tokens, message)
            elif self.provider == "chutes":
                return self._handle_chutes_chat(messages, temperature, max_tokens, message)
            else:
                raise ValueError(f"Unknown provider: {self.provider}")
                
        except Exception as e:
            error_msg = f"Error: {str(e)}"
            self.conversation_history.append({"role": "user", "content": message})
            self.conversation_history.append({"role": "assistant", "content": error_msg})
            
            return {
                "content": error_msg,
                "timestamp": datetime.now().isoformat(),
                "model": self.model,
                "provider": self.provider,
                "tool_usage": None,
                "error": str(e)
            }

    def _handle_groq_chat(self, messages: List[Dict], include_domains: List[str], exclude_domains: List[str], 
                         temperature: float, max_tokens: int, original_message: str) -> Dict:
        """Handle Groq API chat"""
        # Set up API parameters
        params = {
            "messages": messages,
            "model": self.model,
            "temperature": temperature,
            "max_tokens": max_tokens
        }
        
        # Add domain filtering if specified
        if include_domains and include_domains[0].strip():
            params["include_domains"] = [domain.strip() for domain in include_domains if domain.strip()]
        if exclude_domains and exclude_domains[0].strip():
            params["exclude_domains"] = [domain.strip() for domain in exclude_domains if domain.strip()]
        
        # Make the API call
        response = self.groq_client.chat.completions.create(**params)
        content = response.choices[0].message.content
        
        # Extract tool usage information and enhance it
        tool_info = self._extract_tool_info(response)
        
        # Process content to enhance citations
        processed_content = self._enhance_citations(content, tool_info)
        
        # Add to conversation history
        self.conversation_history.append({"role": "user", "content": original_message})
        self.conversation_history.append({"role": "assistant", "content": processed_content})
        
        # Create response object
        return {
            "content": processed_content,
            "timestamp": datetime.now().isoformat(),
            "model": self.model,
            "provider": "groq",
            "tool_usage": tool_info,
            "parameters": {
                "temperature": temperature,
                "max_tokens": max_tokens,
                "include_domains": include_domains,
                "exclude_domains": exclude_domains
            }
        }

    def _handle_chutes_chat(self, messages: List[Dict], temperature: float, max_tokens: int, original_message: str) -> Dict:
        """Handle Chutes API chat"""
        content = self._chutes_chat_sync(messages, temperature, max_tokens)
        
        # Add to conversation history
        self.conversation_history.append({"role": "user", "content": original_message})
        self.conversation_history.append({"role": "assistant", "content": content})
        
        # Create response object
        return {
            "content": content,
            "timestamp": datetime.now().isoformat(),
            "model": self.model,
            "provider": "chutes",
            "tool_usage": None,  # Chutes doesn't have tool usage info
            "parameters": {
                "temperature": temperature,
                "max_tokens": max_tokens
            }
        }
    
    def _extract_tool_info(self, response) -> Dict:
        """Extract tool usage information in a JSON serializable format (Groq only)"""
        tool_info = {
            "tools_used": [],
            "search_queries": [],
            "sources_found": []
        }
        
        if hasattr(response.choices[0].message, 'executed_tools'):
            tools = response.choices[0].message.executed_tools
            if tools:
                for tool in tools:
                    tool_dict = {
                        "tool_type": getattr(tool, "type", "unknown"),
                        "tool_name": getattr(tool, "name", "unknown"),
                    }
                    
                    # Extract search queries and results
                    if hasattr(tool, "input"):
                        tool_input = str(tool.input)
                        tool_dict["input"] = tool_input
                        # Try to extract search query
                        if "search" in tool_dict["tool_name"].lower():
                            tool_info["search_queries"].append(tool_input)
                    
                    if hasattr(tool, "output"):
                        tool_output = str(tool.output)
                        tool_dict["output"] = tool_output
                        # Try to extract URLs from output
                        urls = self._extract_urls(tool_output)
                        tool_info["sources_found"].extend(urls)
                    
                    tool_info["tools_used"].append(tool_dict)
        
        return tool_info
    
    def _extract_urls(self, text: str) -> List[str]:
        """Extract URLs from text"""
        url_pattern = r'https?://[^\s<>"]{2,}'
        urls = re.findall(url_pattern, text)
        return list(set(urls))  # Remove duplicates
    
    def _enhance_citations(self, content: str, tool_info: Dict) -> str:
        """Enhance content with better citation formatting (Groq only)"""
        if not tool_info or not tool_info.get("sources_found"):
            return content
        
        # Add sources section if not already present
        if "Sources Used:" not in content and "sources:" not in content.lower():
            sources_section = "\n\n---\n\n### 📚 Sources Used:\n"
            for i, url in enumerate(tool_info["sources_found"][:10], 1):  # Limit to 10 sources
                # Try to extract domain name for better formatting
                domain = self._extract_domain(url)
                sources_section += f"{i}. [{domain}]({url})\n"
            
            content += sources_section
        
        return content
    
    def _extract_domain(self, url: str) -> str:
        """Extract domain name from URL for display"""
        try:
            if url.startswith(('http://', 'https://')):
                domain = url.split('/')[2]
                # Remove www. prefix if present
                if domain.startswith('www.'):
                    domain = domain[4:]
                return domain
            return url
        except:
            return url
    
    def clear_history(self):
        """Clear conversation history"""
        self.conversation_history = []
    
    def get_history_summary(self) -> str:
        """Get a summary of conversation history"""
        if not self.conversation_history:
            return "No conversation history"
        
        user_messages = [msg for msg in self.conversation_history if msg["role"] == "user"]
        assistant_messages = [msg for msg in self.conversation_history if msg["role"] == "assistant"]
        
        return f"Conversation: {len(user_messages)} user messages, {len(assistant_messages)} assistant responses"

# Global variables
ai_instance = None
current_provider = "groq"
api_key_status = {"groq": "Not Set", "chutes": "Not Set"}

def validate_api_keys(groq_api_key: str, chutes_api_key: str, provider: str, model: str) -> str:
    """Validate API keys and initialize AI instance"""
    global ai_instance, current_provider, api_key_status
    
    current_provider = provider
    
    if provider == "groq":
        if not groq_api_key or len(groq_api_key.strip()) < 10:
            api_key_status["groq"] = "Invalid ❌"
            return "❌ Please enter a valid Groq API key (should be longer than 10 characters)"
        
        try:
            # Test the Groq API key
            client = Groq(api_key=groq_api_key)
            test_response = client.chat.completions.create(
                messages=[{"role": "user", "content": "Hello"}],
                model=model,
                max_tokens=10
            )
            
            # Create AI instance
            ai_instance = CreativeAgenticAI(groq_api_key=groq_api_key, provider="groq", model=model)
            api_key_status["groq"] = "Valid ✅"
            
            return f"✅ Groq API Key Valid! Creative Agentic AI is ready.\n\n**Provider:** Groq\n**Model:** {model}\n**Status:** Connected with web search capabilities!"
            
        except Exception as e:
            api_key_status["groq"] = "Invalid ❌"
            ai_instance = None
            return f"❌ Error validating Groq API key: {str(e)}\n\nPlease check your API key and try again."
    
    elif provider == "chutes":
        if not chutes_api_key or len(chutes_api_key.strip()) < 10:
            api_key_status["chutes"] = "Invalid ❌"
            return "❌ Please enter a valid Chutes API key (should be longer than 10 characters)"
        
        try:
            # Test the Chutes API key with a simple request
            test_ai = CreativeAgenticAI(chutes_api_key=chutes_api_key, provider="chutes", model=model)
            test_response = test_ai._chutes_chat_sync(
                [{"role": "user", "content": "Hello"}], 
                temperature=0.7, 
                max_tokens=10
            )
            
            # Create AI instance
            ai_instance = CreativeAgenticAI(chutes_api_key=chutes_api_key, provider="chutes", model=model)
            api_key_status["chutes"] = "Valid ✅"
            
            return f"✅ Chutes API Key Valid! Creative AI is ready.\n\n**Provider:** Chutes\n**Model:** {model}\n**Status:** Connected (text generation focused)!"
            
        except Exception as e:
            api_key_status["chutes"] = "Invalid ❌"
            ai_instance = None
            return f"❌ Error validating Chutes API key: {str(e)}\n\nPlease check your API key and try again."

def get_available_models(provider: str) -> List[str]:
    """Get available models for the selected provider"""
    if provider == "groq":
        return ["compound-beta", "compound-beta-mini"]
    elif provider == "chutes":
        return ["openai/gpt-oss-20b", "meta-llama/llama-3.1-8b-instruct", "anthropic/claude-3-sonnet"]
    return []

def update_model_choices(provider: str):
    """Update model choices based on provider selection"""
    models = get_available_models(provider)
    return gr.Radio(choices=models, value=models[0] if models else None, label=f"🧠 {provider.title()} Models")

def chat_with_ai(message: str, 
                include_domains: str, 
                exclude_domains: str,
                system_prompt: str,
                temperature: float,
                max_tokens: int,
                history: List) -> tuple:
    """Main chat function"""
    global ai_instance, current_provider
    
    if not ai_instance:
        error_msg = f"⚠️ Please set your {current_provider.title()} API key first!"
        history.append([message, error_msg])
        return history, ""
    
    if not message.strip():
        return history, ""
    
    # Process domain lists (only for Groq)
    include_list = None
    exclude_list = None
    if current_provider == "groq":
        include_list = [d.strip() for d in include_domains.split(",")] if include_domains.strip() else []
        exclude_list = [d.strip() for d in exclude_domains.split(",")] if exclude_domains.strip() else []
    
    try:
        # Get AI response
        response = ai_instance.chat(
            message=message,
            include_domains=include_list if include_list else None,
            exclude_domains=exclude_list if exclude_list else None,
            system_prompt=system_prompt if system_prompt.strip() else None,
            temperature=temperature,
            max_tokens=int(max_tokens)
        )
        
        # Format response
        ai_response = response["content"]
        
        # Add enhanced tool usage info (Groq only)
        if response.get("tool_usage") and current_provider == "groq":
            tool_info = response["tool_usage"]
            tool_summary = []
            
            if tool_info.get("search_queries"):
                tool_summary.append(f"🔍 Search queries: {len(tool_info['search_queries'])}")
            
            if tool_info.get("sources_found"):
                tool_summary.append(f"📄 Sources found: {len(tool_info['sources_found'])}")
            
            if tool_info.get("tools_used"):
                tool_summary.append(f"🔧 Tools used: {len(tool_info['tools_used'])}")
            
            if tool_summary:
                ai_response += f"\n\n*{' | '.join(tool_summary)}*"
        
        # Add domain filtering info (Groq only)
        if current_provider == "groq" and (include_list or exclude_list):
            filter_info = []
            if include_list:
                filter_info.append(f"✅ Included domains: {', '.join(include_list)}")
            if exclude_list:
                filter_info.append(f"❌ Excluded domains: {', '.join(exclude_list)}")
            
            ai_response += f"\n\n*🌐 Domain filtering applied: {' | '.join(filter_info)}*"
        
        # Add provider info
        ai_response += f"\n\n*🤖 Powered by: {current_provider.title()} ({response.get('model', 'unknown')})*"
        
        # Add to history
        history.append([message, ai_response])
        
        return history, ""
        
    except Exception as e:
        error_msg = f"❌ Error: {str(e)}"
        history.append([message, error_msg])
        return history, ""

def clear_chat_history():
    """Clear the chat history"""
    global ai_instance
    if ai_instance:
        ai_instance.clear_history()
    return []

def create_gradio_app():
    """Create the main Gradio application"""
    
    # Custom CSS for better styling
    css = """
    .container {
        max-width: 1200px;
        margin: 0 auto;
    }
    .header {
        text-align: center;
        background: linear-gradient(to right, #00ff94, #00b4db);
        color: white;
        padding: 20px;
        border-radius: 10px;
        margin-bottom: 20px;
    }
    .status-box {
        background-color: #f8f9fa;
        border: 1px solid #dee2e6;
        border-radius: 8px;
        padding: 15px;
        margin: 10px 0;
    }
    .example-box {
        background-color: #e8f4fd;
        border-left: 4px solid #007bff;
        padding: 15px;
        margin: 10px 0;
        border-radius: 0 8px 8px 0;
    }
    .domain-info {
        background-color: #fff3cd;
        border: 1px solid #ffeaa7;
        border-radius: 8px;
        padding: 15px;
        margin: 10px 0;
    }
    .citation-info {
        background-color: #d1ecf1;
        border: 1px solid #bee5eb;
        border-radius: 8px;
        padding: 15px;
        margin: 10px 0;
    }
    .provider-info {
        background-color: #f8d7da;
        border: 1px solid #f5c6cb;
        border-radius: 8px;
        padding: 15px;
        margin: 10px 0;
    }
    #neuroscope-accordion {
        background: linear-gradient(to right, #00ff94, #00b4db); 
        border-radius: 8px;
    }
    """
    
    with gr.Blocks(css=css, title="🤖 Multi-Provider Creative Agentic AI Chat", theme=gr.themes.Ocean()) as app:
        
        # Header
        gr.HTML("""
        <div class="header">
            <h1>🤖 NeuroScope-AI Enhanced</h1>
            <p>Multi-Provider AI Chat Tool - Powered by Groq's Compound Models & Chutes API</p>
        </div>
        """)

        # Provider Selection
        with gr.Group():
            with gr.Accordion("🤖 Multi-Provider NeuroScope AI", open=False, elem_id="neuroscope-accordion"):
                gr.Markdown("""
                    **Enhanced with Multiple AI Providers:**
                    - 🧠 Intelligence (Neuro) - Now supports Groq & Chutes
                    - 🔍 Advanced capabilities (Scope) - Web search with Groq, powerful text generation with Chutes
                    - 🤖 AI capabilities (AI) - Multiple model options
                    - ⚡ Precision & Speed (Scope) - Choose the best provider for your needs
                """)

        # Provider and API Key Section
        with gr.Row():
            with gr.Column():
                provider_selection = gr.Radio(
                    choices=["groq", "chutes"],
                    label="🏢 AI Provider",
                    value="groq",
                    info="Choose your AI provider"
                )
                
                # API Key inputs
                groq_api_key = gr.Textbox(
                    label="🔑 Groq API Key",
                    placeholder="Enter your Groq API key here...",
                    type="password",
                    info="Get your API key from: https://console.groq.com/",
                    visible=True
                )
                
                chutes_api_key = gr.Textbox(
                    label="🔑 Chutes API Key",
                    placeholder="Enter your Chutes API key here...",
                    type="password",
                    info="Get your API key from: https://chutes.ai/",
                    visible=False
                )
            
            with gr.Column():
                model_selection = gr.Radio(
                    choices=get_available_models("groq"),
                    label="🧠 Groq Models",
                    value="compound-beta",
                    info="compound-beta: More powerful | compound-beta-mini: Faster"
                )
                
                connect_btn = gr.Button("🔗 Connect", variant="primary", size="lg")
        
        # Status display
        status_display = gr.Markdown("### 📊 Status: Not connected", elem_classes=["status-box"])

        # Provider Information
        with gr.Group():
            with gr.Accordion("🏢 Provider Comparison", open=False, elem_id="neuroscope-accordion"):
                gr.Markdown("""
                <div class="provider-info">
                <h3>🆚 Groq vs Chutes Comparison</h3>
                
                **🚀 Groq (Compound Models)**
                - ✅ **Web Search Capabilities** - Can search the internet and cite sources
                - ✅ **Agentic Tools** - Advanced tool usage and autonomous web browsing
                - ✅ **Domain Filtering** - Control which websites to search
                - ✅ **Citation System** - Automatic source linking and references
                - ⚡ **Ultra-fast inference** - Groq's hardware acceleration
                - 🧠 **Models**: compound-beta, compound-beta-mini
                
                **🎯 Chutes**
                - ✅ **Multiple Model Access** - Various open-source and commercial models
                - ✅ **Cost-effective** - Competitive pricing
                - ✅ **High-quality text generation** - Excellent for creative writing and analysis
                - ⚡ **Good performance** - Reliable and fast responses
                - 🧠 **Models**: GPT-OSS-20B, Llama 3.1, Claude 3 Sonnet, and more
                - ❌ **No web search** - Relies on training data only
                
                **💡 Use Groq when you need:**
                - Real-time information and web search
                - Research with source citations
                - Domain-specific searches
                - Agentic AI capabilities
                
                **💡 Use Chutes when you need:**
                - Pure text generation and analysis
                - Creative writing tasks
                - Cost-effective AI access
                - Variety of model options
                </div>
                """)
        
        # Update UI based on provider selection
        def update_provider_ui(provider):
            groq_visible = provider == "groq"
            chutes_visible = provider == "chutes"
            models = get_available_models(provider)
            
            return (
                gr.update(visible=groq_visible),  # groq_api_key
                gr.update(visible=chutes_visible),  # chutes_api_key
                gr.update(choices=models, value=models[0] if models else None, 
                         label=f"🧠 {provider.title()} Models"),  # model_selection
                gr.update(visible=groq_visible),  # domain filtering sections
                gr.update(visible=groq_visible),  # include domains
                gr.update(visible=groq_visible)   # exclude domains
            )
        
        provider_selection.change(
            fn=update_provider_ui,
            inputs=[provider_selection],
            outputs=[groq_api_key, chutes_api_key, model_selection]  # We'll add domain filtering updates later
        )
        
        # Connect button functionality
        connect_btn.click(
            fn=validate_api_keys,
            inputs=[groq_api_key, chutes_api_key, provider_selection, model_selection],
            outputs=[status_display]
        )
        
        # Main Chat Interface
        with gr.Tab("💬 Chat"):
            chatbot = gr.Chatbot(
                label="Multi-Provider Creative AI Assistant",
                height=500,
                show_label=True,
                bubble_full_width=False,
                show_copy_button=True
            )
            
            with gr.Row():
                msg = gr.Textbox(
                    label="Your Message",
                    placeholder="Type your message here...",
                    lines=3
                )
                with gr.Column():
                    send_btn = gr.Button("📤 Send", variant="primary")
                    clear_btn = gr.Button("🗑️ Clear", variant="secondary")
            
        # Advanced Settings
        with gr.Accordion("⚙️ Advanced Settings", open=False, elem_id="neuroscope-accordion"):
            with gr.Row():
                temperature = gr.Slider(
                    minimum=0.0,
                    maximum=2.0,
                    value=0.7,
                    step=0.1,
                    label="🌡️ Temperature",
                    info="Higher = more creative, Lower = more focused"
                )
                max_tokens = gr.Slider(
                    minimum=100,
                    maximum=4000,
                    value=1024,
                    step=100,
                    label="📝 Max Tokens",
                    info="Maximum length of response"
                )
                
            system_prompt = gr.Textbox(
                label="🎭 Custom System Prompt",
                placeholder="Override the default system prompt...",
                lines=2,
                info="Leave empty to use provider-optimized default prompt"
            )    
        
        # Domain Filtering Section (Groq only)
        with gr.Group() as domain_group:
            with gr.Accordion("🌐 Domain Filtering (Groq Web Search Only)", open=False, elem_id="neuroscope-accordion"):
                gr.Markdown("""
                <div class="domain-info">
                <h4>🔍 Domain Filtering Guide (Groq Only)</h4>
                <p><strong>Note:</strong> Domain filtering only works with Groq's compound models that have web search capabilities.</p>
                <p>Control which websites the AI can search when answering your questions:</p>
                <ul>
                    <li><strong>Include Domains:</strong> Only search these domains (comma-separated)</li>
                    <li><strong>Exclude Domains:</strong> Never search these domains (comma-separated)</li>
                    <li><strong>Examples:</strong> arxiv.org, *.edu, github.com, stackoverflow.com</li>
                    <li><strong>Wildcards:</strong> Use *.edu for all educational domains</li>
                </ul>
                <p><strong>New:</strong> Domain filtering status will be shown in responses!</p>
                </div>
                """)
                
                with gr.Row():
                    include_domains = gr.Textbox(
                        label="✅ Include Domains (comma-separated)",
                        placeholder="arxiv.org, *.edu, github.com, stackoverflow.com",
                        info="Only search these domains"
                    )
                    exclude_domains = gr.Textbox(
                        label="❌ Exclude Domains (comma-separated)", 
                        placeholder="wikipedia.org, reddit.com, twitter.com",
                        info="Never search these domains"
                    )
                    
            with gr.Accordion("🔗 Common Domain Examples", open=False, elem_id="neuroscope-accordion"):
                gr.Markdown("""
                **Academic & Research:**
                - `arxiv.org`, `*.edu`, `scholar.google.com`, `researchgate.net`
                
                **Technology & Programming:**
                - `github.com`, `stackoverflow.com`, `docs.python.org`, `developer.mozilla.org`
                
                **News & Media:**
                - `reuters.com`, `bbc.com`, `npr.org`, `apnews.com`
                
                **Business & Finance:**
                - `bloomberg.com`, `wsj.com`, `nasdaq.com`, `sec.gov`
                
                **Science & Medicine:**
                - `nature.com`, `science.org`, `pubmed.ncbi.nlm.nih.gov`, `who.int`
                """)

        # Update provider UI function with domain filtering
        def update_provider_ui_complete(provider):
            groq_visible = provider == "groq"
            chutes_visible = provider == "chutes"
            models = get_available_models(provider)
            
            return (
                gr.update(visible=groq_visible),  # groq_api_key
                gr.update(visible=chutes_visible),  # chutes_api_key
                gr.update(choices=models, value=models[0] if models else None, 
                         label=f"🧠 {provider.title()} Models"),  # model_selection
                gr.update(visible=groq_visible),  # domain_group
            )
        
        provider_selection.change(
            fn=update_provider_ui_complete,
            inputs=[provider_selection],
            outputs=[groq_api_key, chutes_api_key, model_selection, domain_group]
        )
        
        # IMPORTANT Section with Citation Info
        with gr.Group():
            with gr.Accordion("📚 IMPORTANT - Citations & Multi-Provider Features!", open=False, elem_id="neuroscope-accordion"):
                gr.Markdown("""
                <div class="citation-info">
                <h3>🆕 Multi-Provider Enhancement</h3>
                <p>This enhanced version now supports both Groq and Chutes AI providers:</p>
                <ul>
                    <li><strong>🚀 Groq Integration:</strong> Agentic AI with web search, citations, and tool usage</li>
                    <li><strong>🎯 Chutes Integration:</strong> Multiple AI models for text generation and analysis</li>
                    <li><strong>🔄 Easy Switching:</strong> Switch between providers based on your needs</li>
                    <li><strong>📊 Provider Comparison:</strong> Clear information about each provider's strengths</li>
                </ul>
                
                <h3>🔗 Groq Enhanced Citation System</h3>
                <p>When using Groq, you get:</p>
                <ul>
                    <li><strong>Automatic Source Citations:</strong> All responses include clickable links to sources</li>
                    <li><strong>Sources Used Section:</strong> Dedicated section showing all websites referenced</li>
                    <li><strong>Domain Filtering Verification:</strong> Clear indication when domain filtering is applied</li>
                    <li><strong>Search Query Tracking:</strong> Shows what queries were made to find information</li>
                </ul>
                
                <h3>🎯 Chutes Model Access</h3>
                <p>When using Chutes, you get access to:</p>
                <ul>
                    <li><strong>Multiple Models:</strong> GPT-OSS-20B, Llama 3.1, Claude 3 Sonnet</li>
                    <li><strong>Cost-Effective:</strong> Competitive pricing for high-quality AI</li>
                    <li><strong>Specialized Tasks:</strong> Optimized for creative writing and analysis</li>
                    <li><strong>Reliable Performance:</strong> Consistent and fast responses</li>
                </ul>
                </div>
                
                ### 🔍 **Web Search Behavior (Groq Only)**
                
                **No Domains Specified:**
                  - AI operates with **unrestricted web search capabilities**.
                  - Compound models autonomously search the **entire internet** for the most relevant and up-to-date information.
                  - AI has complete freedom to use its **agentic tools** and browse **any website** it finds useful.
                
                **Include Domains Specified (e.g., `arxiv.org`, `*.edu`):**
                  - AI is restricted to search **only the specified domains**.
                  - Acts as a **strict whitelist**, making the AI **laser-focused** on your chosen sources.
                  - Ensures information is sourced from **preferred or authoritative domains** (e.g., academic or research-focused).
                
                **Exclude Domains Specified (e.g., `wikipedia.org`, `reddit.com`):**
                  - AI searches the entire web **except the listed domains**.
                  - Useful for **filtering out unreliable or unwanted sources**.
                  - Allows broad search with **targeted exclusions**.
                
                **Both Include and Exclude Domains Specified:**
                  - **Only the include domains** are used for searching.
                  - **Exclude list is ignored** because the include list already restricts search scope.
                  - Guarantees AI pulls content **exclusively from whitelisted domains**, regardless of the excluded ones.
                
                ---
                
                ### 🎭 **Custom System Prompt Feature**
                
                Allows complete override of the AI's **default personality and behavior** for both providers.
                You can redefine the AI to act as:
                  - A **professional business consultant**
                  - A **coding mentor**
                  - A **creative writer**
                  - A **specific character or persona**
                - Provides full control to **reshape the AI's tone, expertise, and conversational style** with a single prompt.
                """)
        
        # How to Use Section
        with gr.Accordion("📖 How to Use This Enhanced Multi-Provider App", open=False, elem_id="neuroscope-accordion"):
            gr.Markdown("""
            ### 🚀 Getting Started
            1. **Choose your AI Provider** - Select between Groq (web search + agentic) or Chutes (text generation)
            2. **Enter your API Key** - 
               - Groq: Get one from [console.groq.com](https://console.groq.com/)
               - Chutes: Get one from [chutes.ai](https://chutes.ai/)
            3. **Select a model** - Choose from provider-specific model options
            4. **Click Connect** - Validate your key and connect to the AI
            5. **Start chatting!** - Type your message and get intelligent responses
            
            ### 🎯 Key Features
            **🚀 Groq Features:**
            - **Agentic AI**: The AI can use tools and search the web autonomously
            - **Smart Citations**: Automatic source linking and citation formatting
            - **Domain Filtering**: Control which websites the AI searches
            - **Ultra-fast**: Groq's hardware-accelerated inference
            
            **🎯 Chutes Features:**
            - **Multiple Models**: Access to various open-source and commercial models
            - **Cost-Effective**: Competitive pricing for AI access
            - **High Quality**: Excellent text generation and analysis
            - **Model Variety**: Choose the best model for your specific task
            
            **🔄 Universal Features:**
            - **Memory**: Maintains conversation context throughout the session
            - **Customizable**: Adjust temperature, tokens, and system prompts
            - **Provider Switching**: Easy switching between AI providers
            
            ### 💡 Tips for Best Results
            **For Groq:**
            - Be specific in your questions for better web search results
            - Use domain filtering for specialized research
            - Check the "Sources Used" section for all references
            - Try different domain combinations to see varied results
            
            **For Chutes:**
            - Experiment with different models for different tasks
            - Use higher temperatures for creative tasks
            - Leverage the variety of available models (GPT, Llama, Claude)
            - Perfect for tasks that don't require real-time information
            
            **General:**
            - Adjust temperature: higher for creativity, lower for precision
            - Try different system prompts for different conversation styles
            - Use the provider that best fits your current task
            """)
        
        # Sample Examples Section
        with gr.Accordion("🎯 Sample Examples to Test Both Providers", open=False, elem_id="neuroscope-accordion"):
            gr.Markdown("""
            <div class="example-box">
            <h4>🆚 Provider Comparison Examples</h4>
            <p>Try the same prompts with both providers to see the difference:</p>
            
            <h4>🔬 Research & Analysis</h4>
            <ul>
                <li><strong>Groq (with web search):</strong> "What are the latest breakthroughs in quantum computing in 2024?"</li>
                <li><strong>Chutes (knowledge-based):</strong> "Explain the fundamental principles of quantum computing"</li>
                <li><strong>Groq with domains:</strong> Same question with "arxiv.org, *.edu" in include domains</li>
            </ul>
            
            <h4>💻 Programming & Tech</h4>
            <ul>
                <li><strong>Groq:</strong> "What are the current best practices for React 18 in 2024?"</li>
                <li><strong>Chutes:</strong> "Write a comprehensive React component with hooks and best practices"</li>
                <li><strong>Groq filtered:</strong> Same with "github.com, stackoverflow.com" included</li>
            </ul>
            
            <h4>🎨 Creative Tasks (Great for Chutes)</h4>
            <ul>
                <li>"Write a short story about AI and humans working together"</li>
                <li>"Create a marketing plan for a sustainable fashion brand"</li>
                <li>"Generate ideas for a mobile app that helps with mental health"</li>
                <li>"Write a poem about the beauty of code"</li>
            </ul>
            
            <h4>📊 Business & Analysis</h4>
            <ul>
                <li><strong>Groq:</strong> "What are the current trends in cryptocurrency markets?"</li>
                <li><strong>Chutes:</strong> "Analyze the pros and cons of different investment strategies"</li>
                <li><strong>Groq filtered:</strong> Crypto question with "bloomberg.com, wsj.com" included</li>
            </ul>
            
            <h4>🧠 Model-Specific Testing (Chutes)</h4>
            <ul>
                <li><strong>GPT-OSS-20B:</strong> "Explain complex scientific concepts in simple terms"</li>
                <li><strong>Llama 3.1:</strong> "Help me debug this Python code and explain the solution"</li>
                <li><strong>Claude 3 Sonnet:</strong> "Analyze this business scenario and provide strategic recommendations"</li>
            </ul>
            </div>
            """)
        
        # Event handlers
        send_btn.click(
            fn=chat_with_ai,
            inputs=[msg, include_domains, exclude_domains, system_prompt, temperature, max_tokens, chatbot],
            outputs=[chatbot, msg]
        )
        
        msg.submit(
            fn=chat_with_ai,
            inputs=[msg, include_domains, exclude_domains, system_prompt, temperature, max_tokens, chatbot],
            outputs=[chatbot, msg]
        )
        
        clear_btn.click(
            fn=clear_chat_history,
            outputs=[chatbot]
        )
        
        # Footer
        with gr.Accordion("🚀 About This Enhanced Multi-Provider Tool", open=True, elem_id="neuroscope-accordion"):
            gr.Markdown("""
            **Enhanced Multi-Provider Creative Agentic AI Chat Tool** with dual API support:
            
            **🆕 New Multi-Provider Features:**
            - 🚀 **Groq Integration**: Agentic AI with web search, citations, and tool usage
            - 🎯 **Chutes Integration**: Multiple AI models for diverse text generation tasks
            - 🔄 **Provider Switching**: Easy switching between different AI providers
            - 📊 **Provider Comparison**: Clear information about each provider's strengths
            - 🧠 **Multiple Models**: Access to various AI models through both providers
            
            **🚀 Groq Features:**
            - 🔗 **Automatic Source Citations**: Every response includes clickable links to sources
            - 📚 **Sources Used Section**: Dedicated section showing all websites referenced  
            - 🌐 **Domain Filtering Verification**: Clear indication when filtering is applied
            - 🔍 **Search Query Tracking**: Shows what queries were made
            - ⚡ **Enhanced Tool Usage Display**: Better visibility into AI's research process
            - 🔍 Web search with domain filtering
            - 🧠 Advanced AI reasoning with tool usage
            
            **🎯 Chutes Features:**
            - 🤖 **Multiple AI Models**: GPT-OSS-20B, Llama 3.1, Claude 3 Sonnet
            - 💰 **Cost-Effective**: Competitive pricing for AI access
            - 🎨 **Creative Excellence**: Optimized for writing and analysis tasks
            - ⚡ **Reliable Performance**: Consistent and fast responses
            
            **🔄 Universal Features:**
            - 💬 Conversational memory and context
            - ⚙️ Customizable parameters and prompts
            - 🎨 Creative and analytical capabilities
            - 🌟 Enhanced user interface with provider-specific optimizations
            
            **💡 Choose Your Provider:**
            - **Use Groq** when you need real-time information, web search, and citations
            - **Use Chutes** when you need pure text generation, creative writing, or cost-effective AI access
            """)
    
    return app

# Main execution
if __name__ == "__main__":
    app = create_gradio_app()
    app.launch(
        share=True
    )