Delete app.py

app.py

@@ -1,637 +0,0 @@
-import os
-import gradio as gr
-from groq import Groq
-import json
-from datetime import datetime
-import time
-
-class RealTimeFactChecker:
-    def __init__(self):
-        self.client = None
-        self.model_options = ["compound-beta", "compound-beta-mini"]
-        
-    def initialize_client(self, api_key):
-        """Initialize Groq client with API key"""
-        try:
-            self.client = Groq(api_key=api_key)
-            return True, "✅ API Key validated successfully!"
-        except Exception as e:
-            return False, f"❌ Error initializing client: {str(e)}"
-    
-    def get_system_prompt(self):
-        """Get the system prompt for consistent behavior"""
-        return """You are a Real-time Fact Checker and News Agent. Your primary role is to provide accurate, up-to-date information by leveraging web search when needed.
-CORE RESPONSIBILITIES:
-1. **Fact Verification**: Always verify claims with current, reliable sources
-2. **Real-time Information**: Use web search for any information that changes frequently (news, stocks, weather, current events)
-3. **Source Transparency**: When using web search, mention the sources or indicate that you've searched for current information
-4. **Accuracy First**: If information is uncertain or conflicting, acknowledge this clearly
-RESPONSE GUIDELINES:
-- **Structure**: Start with a clear, direct answer, then provide supporting details
-- **Recency**: Always prioritize the most recent, reliable information
-- **Clarity**: Use clear, professional language while remaining accessible
-- **Completeness**: Provide comprehensive answers but stay focused on the query
-- **Source Awareness**: When you've searched for information, briefly indicate this (e.g., "Based on current reports..." or "Recent data shows...")
-WHEN TO SEARCH:
-- Breaking news or current events
-- Stock prices, market data, or financial information
-- Weather conditions or forecasts
-- Recent scientific discoveries or research
-- Current political developments
-- Real-time statistics or data
-- Verification of recent claims or rumors
-RESPONSE FORMAT:
-- Lead with key facts
-- Include relevant context
-- Mention timeframe when relevant (e.g., "as of today", "this week")
-- If multiple sources conflict, acknowledge this
-- End with a clear summary for complex topics
-Remember: Your goal is to be the most reliable, up-to-date source of information possible."""
-
-    def query_compound_model(self, query, model, temperature=0.7, custom_system_prompt=None):
-        """Query the compound model and return response with tool execution info"""
-        if not self.client:
-            return "❌ Please set a valid API key first.", None, None
-        
-        try:
-            start_time = time.time()
-            
-            # Use custom system prompt if provided
-            system_prompt = custom_system_prompt if custom_system_prompt else self.get_system_prompt()
-            
-            chat_completion = self.client.chat.completions.create(
-                messages=[
-                    {
-                        "role": "system",
-                        "content": system_prompt
-                    },
-                    {
-                        "role": "user",
-                        "content": query,
-                    }
-                ],
-                model=model,
-                temperature=temperature,
-                max_tokens=1500
-            )
-            
-            end_time = time.time()
-            response_time = round(end_time - start_time, 2)
-            
-            # Extract response
-            response_content = chat_completion.choices[0].message.content
-            
-            # Check for executed tools - Fixed the error here
-            executed_tools = getattr(chat_completion.choices[0].message, 'executed_tools', None)
-            
-            # Format tool execution info
-            tool_info = self.format_tool_info(executed_tools)
-            
-            return response_content, tool_info, response_time
-            
-        except Exception as e:
-            return f"❌ Error querying model: {str(e)}", None, None
-    
-    def format_tool_info(self, executed_tools):
-        """Format executed tools information for display - FIXED"""
-        if not executed_tools:
-            return "🔍 **Tools Used:** None (Used existing knowledge)"
-        
-        tool_info = "🔍 **Tools Used:**\n"
-        for i, tool in enumerate(executed_tools, 1):
-            try:
-                # Handle different tool object types
-                if hasattr(tool, 'name'):
-                    tool_name = tool.name
-                elif hasattr(tool, 'tool_name'):
-                    tool_name = tool.tool_name
-                elif isinstance(tool, dict):
-                    tool_name = tool.get('name', 'Unknown')
-                else:
-                    tool_name = str(tool)
-                
-                tool_info += f"{i}. **{tool_name}**\n"
-                
-                # Add tool parameters if available
-                if hasattr(tool, 'parameters'):
-                    params = tool.parameters
-                    if isinstance(params, dict):
-                        for key, value in params.items():
-                            tool_info += f"   - {key}: {value}\n"
-                elif hasattr(tool, 'input'):
-                    tool_info += f"   - Input: {tool.input}\n"
-                    
-            except Exception as e:
-                tool_info += f"{i}. **Tool {i}** (Error parsing details)\n"
-        
-        return tool_info
-    
-    def get_example_queries(self):
-        """Return categorized example queries"""
-        return {
-            "📰 Latest News": [
-                "What are the top 3 news stories today?",
-                "Latest developments in AI technology this week",
-                "Recent political events in the United States",
-                "Breaking news about climate change",
-                "What happened in the stock market today?"
-            ],
-            "💰 Financial Data": [
-                "Current price of Bitcoin",
-                "Tesla stock price today",
-                "How is the S&P 500 performing today?",
-                "Latest cryptocurrency market trends",
-                "What's the current inflation rate?"
-            ],
-            "🌤️ Weather Updates": [
-                "Current weather in New York City",
-                "Weather forecast for London this week",
-                "Is it going to rain in San Francisco today?",
-                "Temperature in Tokyo right now",
-                "Weather conditions in Sydney"
-            ],
-            "🔬 Science & Technology": [
-                "Latest breakthroughs in fusion energy",
-                "Recent discoveries in space exploration",
-                "New developments in quantum computing",
-                "Latest medical research findings",
-                "Recent advances in renewable energy"
-            ],
-            "🏆 Sports & Entertainment": [
-                "Latest football match results",
-                "Who won the recent tennis tournament?",
-                "Box office numbers for this weekend",
-                "Latest movie releases this month",
-                "Recent celebrity news"
-            ],
-            "🔍 Fact Checking": [
-                "Is it true that the Earth's population reached 8 billion?",
-                "Verify: Did company X announce layoffs recently?",
-                "Check if the recent earthquake in Turkey was magnitude 7+",
-                "Confirm the latest unemployment rate statistics",
-                "Verify recent claims about electric vehicle sales"
-            ]
-        }
-    
-    def get_custom_prompt_examples(self):
-        """Return custom system prompt examples"""
-        return {
-            "🎯 Fact-Checker": "You are a fact-checker. Always verify claims with multiple sources and clearly indicate confidence levels in your assessments. Use phrases like 'highly confident', 'moderately confident', or 'requires verification' when presenting information.",
-            
-            "📊 News Analyst": "You are a news analyst. Focus on providing balanced, unbiased reporting with multiple perspectives on current events. Always present different viewpoints and avoid partisan language.",
-            
-            "💼 Financial Advisor": "You are a financial advisor. Provide accurate market data with context about trends and implications for investors. Always include disclaimers about market risks and the importance of professional financial advice.",
-            
-            "🔬 Research Assistant": "You are a research assistant specializing in scientific and technical information. Provide detailed, evidence-based responses with proper context about methodology and limitations of studies.",
-            
-            "🌍 Global News Correspondent": "You are a global news correspondent. Focus on international events and their interconnections. Provide cultural context and explain how events in one region might affect others.",
-            
-            "📈 Market Analyst": "You are a market analyst. Provide detailed financial analysis including technical indicators, market sentiment, and economic factors affecting price movements."
-        }
-
-def create_interface():
-    fact_checker = RealTimeFactChecker()
-    
-    # Custom CSS for beautiful styling
-    custom_css = """
-    <style>
-    .gradio-container {
-        max-width: 1400px !important;
-        margin: 0 auto;
-        background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
-        min-height: 100vh;
-        font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif;
-    }
-    
-    .main-header {
-        background: linear-gradient(135deg, #1e3c72 0%, #2a5298 100%);
-        color: white;
-        padding: 30px;
-        border-radius: 20px;
-        margin-bottom: 30px;
-        text-align: center;
-        box-shadow: 0 10px 30px rgba(0,0,0,0.3);
-    }
-    
-    .main-header h1 {
-        font-size: 2.5rem;
-        margin: 0;
-        text-shadow: 2px 2px 4px rgba(0,0,0,0.3);
-    }
-    
-    .main-header p {
-        font-size: 1.2rem;
-        margin: 10px 0 0 0;
-        opacity: 0.9;
-    }
-    
-    .feature-card {
-        background: white;
-        border-radius: 15px;
-        padding: 25px;
-        margin: 20px 0;
-        box-shadow: 0 8px 25px rgba(0,0,0,0.1);
-        border: 1px solid #e1e8ed;
-        transition: transform 0.3s ease, box-shadow 0.3s ease;
-    }
-    
-    .feature-card:hover {
-        transform: translateY(-5px);
-        box-shadow: 0 15px 40px rgba(0,0,0,0.2);
-    }
-    
-    .example-grid {
-        display: grid;
-        grid-template-columns: repeat(auto-fit, minmax(300px, 1fr));
-        gap: 15px;
-        margin-top: 20px;
-    }
-    
-    .example-category {
-        background: #f8f9fa;
-        border-radius: 10px;
-        padding: 15px;
-        border-left: 4px solid #667eea;
-    }
-    
-    .example-category h4 {
-        margin: 0 0 10px 0;
-        color: #2d3748;
-        font-weight: 600;
-    }
-    
-    .status-success {
-        background: linear-gradient(135deg, #48bb78 0%, #38a169 100%);
-        color: white;
-        padding: 10px 15px;
-        border-radius: 8px;
-        font-weight: 500;
-    }
-    
-    .status-warning {
-        background: linear-gradient(135deg, #ed8936 0%, #dd6b20 100%);
-        color: white;
-        padding: 10px 15px;
-        border-radius: 8px;
-        font-weight: 500;
-    }
-    
-    .status-error {
-        background: linear-gradient(135deg, #f56565 0%, #e53e3e 100%);
-        color: white;
-        padding: 10px 15px;
-        border-radius: 8px;
-        font-weight: 500;
-    }
-    
-    .results-section {
-        background: white;
-        border-radius: 15px;
-        padding: 30px;
-        margin: 30px 0;
-        box-shadow: 0 8px 25px rgba(0,0,0,0.1);
-    }
-    
-    .tool-info {
-        background: #f7fafc;
-        border-left: 4px solid #4299e1;
-        padding: 15px;
-        border-radius: 8px;
-        margin: 15px 0;
-    }
-    
-    .performance-badge {
-        background: linear-gradient(135deg, #38b2ac 0%, #319795 100%);
-        color: white;
-        padding: 8px 15px;
-        border-radius: 20px;
-        font-weight: 500;
-        display: inline-block;
-        margin: 10px 0;
-    }
-    
-    .footer-section {
-        background: #2d3748;
-        color: white;
-        padding: 30px;
-        border-radius: 15px;
-        margin-top: 30px;
-        text-align: center;
-    }
-    
-    .footer-section a {
-        color: #63b3ed;
-        text-decoration: none;
-        font-weight: 500;
-    }
-    
-    .footer-section a:hover {
-        color: #90cdf4;
-        text-decoration: underline;
-    }
-    
-    .prompt-example {
-        background: #ebf8ff;
-        border: 1px solid #bee3f8;
-        border-radius: 8px;
-        padding: 12px;
-        margin: 8px 0;
-        cursor: pointer;
-        transition: all 0.3s ease;
-    }
-    
-    .prompt-example:hover {
-        background: #bee3f8;
-        transform: translateX(5px);
-    }
-    
-    .prompt-example-title {
-        font-weight: 600;
-        color: #2b6cb0;
-        margin-bottom: 5px;
-    }
-    
-    .prompt-example-text {
-        font-size: 0.9rem;
-        color: #4a5568;
-        line-height: 1.4;
-    }
-    </style>
-    """
-    
-    def validate_api_key(api_key):
-        if not api_key or api_key.strip() == "":
-            return "❌ Please enter a valid API key", False
-        
-        success, message = fact_checker.initialize_client(api_key.strip())
-        return message, success
-    
-    def process_query(query, model, temperature, api_key, system_prompt):
-        if not api_key or api_key.strip() == "":
-            return "❌ Please set your API key first", "", ""
-        
-        if not query or query.strip() == "":
-            return "❌ Please enter a query", "", ""
-        
-        # Initialize client if not already done
-        if not fact_checker.client:
-            success, message = fact_checker.initialize_client(api_key.strip())
-            if not success:
-                return message, "", ""
-        
-        response, tool_info, response_time = fact_checker.query_compound_model(
-            query.strip(), model, temperature, system_prompt.strip() if system_prompt else None
-        )
-        
-        # Format response with timestamp
-        timestamp = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
-        formatted_response = f"**Query:** {query}\n\n**Response:**\n{response}\n\n---\n*Generated at {timestamp} in {response_time}s*"
-        
-        return formatted_response, tool_info or "", f"⚡ Response time: {response_time}s"
-    
-    def reset_system_prompt():
-        return fact_checker.get_system_prompt()
-    
-    def load_example(example_text):
-        return example_text
-    
-    def load_custom_prompt(prompt_text):
-        return prompt_text
-    
-    # Create the Gradio interface
-    with gr.Blocks(title="Real-time Fact Checker & News Agent", css=custom_css) as demo:
-        
-        # Header
-        gr.HTML("""
-        <div class="main-header">
-            <h1>🔍 Real-time Fact Checker & News Agent</h1>
-            <p>Powered by Groq's Compound Models with Built-in Web Search</p>
-        </div>
-        """)
-        
-        with gr.Row():
-            with gr.Column(scale=2):
-                # API Key section
-                with gr.Group():
-                    gr.HTML('<div class="feature-card">API Key Section</div>')
-                    gr.Markdown("### 🔑 API Configuration")
-                    api_key_input = gr.Textbox(
-                        label="Groq API Key",
-                        placeholder="Enter your Groq API key here...",
-                        type="password",
-                        info="Get your free API key from https://console.groq.com/"
-                    )
-                    api_status = gr.Textbox(
-                        label="Status",
-                        value="⚠️ Please enter your API key",
-                        interactive=False
-                    )
-                    validate_btn = gr.Button("Validate API Key", variant="secondary")
-                    gr.HTML('</div>')
-                
-                # Advanced options
-                with gr.Group():
-                    gr.HTML('<div class="feature-card">⚙️ Advanced Options</div>')
-                    gr.Markdown("### ⚙️ Advanced Options")
-                    
-                    # Custom System Prompt Examples
-                    with gr.Accordion("📝 System Prompt Examples (Click to view)", open=False):
-                        gr.Markdown("**Click any example to load it as your system prompt:**")
-                        
-                        custom_prompts = fact_checker.get_custom_prompt_examples()
-                        for title, prompt in custom_prompts.items():
-                            with gr.Row():
-                                gr.HTML(f"""
-                                <div class="prompt-example" onclick="document.getElementById('system_prompt_input').value = '{prompt}'">
-                                    <div class="prompt-example-title">{title}</div>
-                                    <div class="prompt-example-text">{prompt[:100]}...</div>
-                                </div>
-                                """)
-                    
-                    with gr.Accordion("🔧 System Prompt (Click to customize)", open=False):
-                        system_prompt_input = gr.Textbox(
-                            label="System Prompt",
-                            value=fact_checker.get_system_prompt(),
-                            lines=8,
-                            info="Customize how the AI behaves and responds",
-                            elem_id="system_prompt_input"
-                        )
-                        reset_prompt_btn = gr.Button("Reset to Default", variant="secondary", size="sm")
-                        
-                        # Add buttons for each custom prompt
-                        gr.Markdown("**Quick Load Custom Prompts:**")
-                        custom_prompts = fact_checker.get_custom_prompt_examples()
-                        for title, prompt in custom_prompts.items():
-                            prompt_btn = gr.Button(title, variant="secondary", size="sm")
-                            prompt_btn.click(
-                                fn=lambda p=prompt: p,
-                                outputs=[system_prompt_input]
-                            )
-                    
-                    gr.HTML('</div>')
-
-                # Query section
-                with gr.Group():
-                    gr.HTML('<div class="feature-card">Query section</div>')
-                    gr.Markdown("### 💭 Your Query")
-                    query_input = gr.Textbox(
-                        label="Ask anything that requires real-time information",
-                        placeholder="e.g., What are the latest AI developments today?",
-                        lines=4
-                    )
-                    
-                    with gr.Row():
-                        model_choice = gr.Dropdown(
-                            choices=fact_checker.model_options,
-                            value="compound-beta",
-                            label="Model",
-                            info="compound-beta: More capable | compound-beta-mini: Faster"
-                        )
-                        temperature = gr.Slider(
-                            minimum=0.0,
-                            maximum=1.0,
-                            value=0.7,
-                            step=0.1,
-                            label="Temperature",
-                            info="Higher = more creative, Lower = more focused"
-                        )
-                    
-                    submit_btn = gr.Button("🔍 Get Real-time Information", variant="primary", size="lg")
-                    clear_btn = gr.Button("Clear", variant="secondary")
-                    gr.HTML('</div>')
-            
-            with gr.Column(scale=1):
-                # Example queries with tabs
-                with gr.Group():
-                    gr.HTML('<div class="feature-card">Example queries with tabs</div>')
-                    gr.Markdown("### 📝 Example Queries")
-                    gr.Markdown("Click any example to load it:")
-                    
-                    examples = fact_checker.get_example_queries()
-                    
-                    with gr.Accordion("📰 Latest News", open=True):
-                        for query in examples["📰 Latest News"]:
-                            example_btn = gr.Button(query, variant="secondary", size="sm")
-                            example_btn.click(
-                                fn=lambda q=query: q,
-                                outputs=[query_input]
-                            )
-                    
-                    with gr.Accordion("💰 Financial Data", open=False):
-                        for query in examples["💰 Financial Data"]:
-                            example_btn = gr.Button(query, variant="secondary", size="sm")
-                            example_btn.click(
-                                fn=lambda q=query: q,
-                                outputs=[query_input]
-                            )
-                    
-                    with gr.Accordion("🌤️ Weather Updates", open=False):
-                        for query in examples["🌤️ Weather Updates"]:
-                            example_btn = gr.Button(query, variant="secondary", size="sm")
-                            example_btn.click(
-                                fn=lambda q=query: q,
-                                outputs=[query_input]
-                            )
-                    
-                    with gr.Accordion("🔬 Science & Technology", open=False):
-                        for query in examples["🔬 Science & Technology"]:
-                            example_btn = gr.Button(query, variant="secondary", size="sm")
-                            example_btn.click(
-                                fn=lambda q=query: q,
-                                outputs=[query_input]
-                            )
-                    
-                    with gr.Accordion("🏆 Sports & Entertainment", open=False):
-                        for query in examples["🏆 Sports & Entertainment"]:
-                            example_btn = gr.Button(query, variant="secondary", size="sm")
-                            example_btn.click(
-                                fn=lambda q=query: q,
-                                outputs=[query_input]
-                            )
-                    
-                    with gr.Accordion("🔍 Fact Checking", open=False):
-                        for query in examples["🔍 Fact Checking"]:
-                            example_btn = gr.Button(query, variant="secondary", size="sm")
-                            example_btn.click(
-                                fn=lambda q=query: q,
-                                outputs=[query_input]
-                            )
-                    
-                    gr.HTML('</div>')
-        
-        # Results section
-        gr.HTML('<div class="results-section">')
-        gr.Markdown("### 📊 Results")
-        
-        with gr.Row():
-            with gr.Column(scale=2):
-                response_output = gr.Markdown(
-                    label="Response",
-                    value="*Your response will appear here...*"
-                )
-            
-            with gr.Column(scale=1):
-                tool_info_output = gr.Markdown(
-                    label="Tool Execution Info",
-                    value="*Tool execution details will appear here...*"
-                )
-                
-                performance_output = gr.Textbox(
-                    label="Performance",
-                    value="",
-                    interactive=False
-                )
-        gr.HTML('</div>')
-        
-        # Event handlers
-        validate_btn.click(
-            fn=validate_api_key,
-            inputs=[api_key_input],
-            outputs=[api_status, gr.State()]
-        )
-        
-        reset_prompt_btn.click(
-            fn=reset_system_prompt,
-            outputs=[system_prompt_input]
-        )
-        
-        submit_btn.click(
-            fn=process_query,
-            inputs=[query_input, model_choice, temperature, api_key_input, system_prompt_input],
-            outputs=[response_output, tool_info_output, performance_output]
-        )
-        
-        clear_btn.click(
-            fn=lambda: ("", "*Your response will appear here...*", "*Tool execution details will appear here...*", ""),
-            outputs=[query_input, response_output, tool_info_output, performance_output]
-        )
-        
-        # Footer
-        gr.HTML("""
-        <div class="footer-section">
-            <h3>🔗 Useful Links</h3>
-            <p>
-                <a href="https://console.groq.com/" target="_blank">Groq Console</a> - Get your free API key<br>
-                <a href="https://console.groq.com/docs/quickstart" target="_blank">Groq Documentation</a> - Learn more about Groq models<br>
-                <a href="https://console.groq.com/docs/models" target="_blank">Compound Models Info</a> - Details about compound models
-            </p>
-            
-            <h3>💡 Tips</h3>
-            <ul style="text-align: left; display: inline-block;">
-                <li>The compound models automatically use web search when real-time information is needed</li>
-                <li>Try different temperature settings: 0.1 for factual queries, 0.7-0.9 for creative questions</li>
-                <li>compound-beta is more capable but slower, compound-beta-mini is faster but less capable</li>
-                <li>Use custom system prompts to specialize the AI for different types of queries</li>
-                <li>Check the Tool Execution Info to see when web search was used</li>
-            </ul>
-        </div>
-        """)
-    
-    return demo
-
-# Launch the application
-if __name__ == "__main__":
-    demo = create_interface()
-    demo.launch(
-        share=True
-    )