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| 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, "<div class='status-success'>✅ API Key validated successfully!</div>" | |
| except Exception as e: | |
| return False, f"<div class='status-error'>❌ Error initializing client: {str(e)}</div>" | |
| 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 "<div class='status-error'>❌ Please set a valid API key first.</div>", None, None | |
| try: | |
| start_time = time.time() | |
| 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) | |
| response_content = chat_completion.choices[0].message.content | |
| executed_tools = getattr(chat_completion.choices[0].message, 'executed_tools', None) | |
| tool_info = self.format_tool_info(executed_tools) | |
| return response_content, tool_info, response_time | |
| except Exception as e: | |
| return f"<div class='status-error'>❌ Error querying model: {str(e)}</div>", None, None | |
| def format_tool_info(self, executed_tools): | |
| """Format executed tools information as HTML""" | |
| if not executed_tools: | |
| return "<div class='tool-info'>🔍 <strong>Tools Used:</strong> None (Used existing knowledge)</div>" | |
| tool_html = "<div class='tool-info'>🔍 <strong>Tools Used:</strong><ul>" | |
| for i, tool in enumerate(executed_tools, 1): | |
| try: | |
| 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_html += f"<li>{i}. <strong>{tool_name}</strong>" | |
| if hasattr(tool, 'parameters'): | |
| params = tool.parameters | |
| if isinstance(params, dict): | |
| tool_html += "<ul>" | |
| for key, value in params.items(): | |
| tool_html += f"<li>{key}: {value}</li>" | |
| tool_html += "</ul>" | |
| elif hasattr(tool, 'input'): | |
| tool_html += f"<ul><li>Input: {tool.input}</li></ul>" | |
| tool_html += "</li>" | |
| except Exception: | |
| tool_html += f"<li>{i}. <strong>Tool {i}</strong> (Error parsing details)</li>" | |
| tool_html += "</ul></div>" | |
| return tool_html | |
| 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.", | |
| "📊 News Analyst": "You are a news analyst. Focus on providing balanced, unbiased reporting with multiple perspectives on current events.", | |
| "💼 Financial Advisor": "You are a financial advisor. Provide accurate market data with context about trends and implications for investors.", | |
| "🔬 Research Assistant": "You are a research assistant specializing in scientific and technical information. Provide detailed, evidence-based responses.", | |
| "🌍 Global News Correspondent": "You are a global news correspondent. Focus on international events and their interconnections.", | |
| "📈 Market Analyst": "You are a market analyst. Provide detailed financial analysis including technical indicators and market sentiment." | |
| } | |
| def create_interface(): | |
| fact_checker = RealTimeFactChecker() | |
| custom_css = """ | |
| <style> | |
| .gradio-container { | |
| background: linear-gradient(135deg, #667eea 0%, #764ba2 100%); | |
| padding: 20px; | |
| min-height: 100vh; | |
| font-family: 'Segoe UI', sans-serif; | |
| color: #333; | |
| } | |
| h1, h2, h3, h4 { | |
| color: white; | |
| text-shadow: 1px 1px 2px rgba(0,0,0,0.1); | |
| } | |
| .feature-card { | |
| background: white; | |
| border-radius: 10px; | |
| padding: 20px; | |
| margin-bottom: 20px; | |
| box-shadow: 0 4px 6px rgba(0,0,0,0.1); | |
| transition: transform 0.3s ease; | |
| } | |
| .feature-card:hover { | |
| transform: translateY(-5px); | |
| } | |
| .example-grid { | |
| display: grid; | |
| grid-template-columns: repeat(auto-fit, minmax(200px, 1fr)); | |
| gap: 10px; | |
| } | |
| .status-success { | |
| background: #48bb78; | |
| color: white; | |
| padding: 10px; | |
| border-radius: 5px; | |
| } | |
| .status-warning { | |
| background: #ed8936; | |
| color: white; | |
| padding: 10px; | |
| border-radius: 5px; | |
| } | |
| .status-error { | |
| background: #f56565; | |
| color: white; | |
| padding: 10px; | |
| border-radius: 5px; | |
| } | |
| .results-section { | |
| background: white; | |
| border-radius: 10px; | |
| padding: 20px; | |
| margin-top: 20px; | |
| box-shadow: 0 4px 6px rgba(0,0,0,0.1); | |
| } | |
| .response-content { | |
| background: #f8f9fa; | |
| padding: 15px; | |
| border-radius: 8px; | |
| margin-bottom: 15px; | |
| } | |
| .response-content h3 { | |
| color: #2d3748; | |
| margin-bottom: 10px; | |
| } | |
| .response-content p { | |
| line-height: 1.6; | |
| color: #4a5568; | |
| } | |
| .timestamp { | |
| font-size: 0.9rem; | |
| color: #718096; | |
| margin-top: 10px; | |
| } | |
| .tool-info { | |
| background: #edf2f7; | |
| padding: 15px; | |
| border-radius: 8px; | |
| color: #2d3748; | |
| } | |
| .tool-info ul { | |
| list-style-type: none; | |
| padding-left: 0; | |
| } | |
| .tool-info li { | |
| margin-bottom: 8px; | |
| } | |
| .performance-badge { | |
| background: #48bb78; | |
| color: white; | |
| padding: 5px 10px; | |
| border-radius: 15px; | |
| font-weight: bold; | |
| display: inline-block; | |
| } | |
| .footer-section { | |
| background: #2d3748; | |
| color: white; | |
| padding: 20px; | |
| border-radius: 10px; | |
| margin-top: 20px; | |
| text-align: center; | |
| } | |
| .footer-section a { | |
| color: #63b3ed; | |
| text-decoration: none; | |
| } | |
| .footer-section a:hover { | |
| text-decoration: underline; | |
| } | |
| @media (max-width: 768px) { | |
| .gradio-row { | |
| flex-direction: column; | |
| } | |
| } | |
| </style> | |
| """ | |
| def validate_api_key(api_key): | |
| if not api_key or api_key.strip() == "": | |
| return "<div class='status-error'>❌ Please enter a valid API key</div>", 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 "<div class='status-error'>❌ Please set your API key first</div>", "", "" | |
| if not query or query.strip() == "": | |
| return "<div class='status-error'>❌ Please enter a query</div>", "", "" | |
| 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 | |
| ) | |
| timestamp = datetime.now().strftime("%Y-%m-%d %H:%M:%S") | |
| formatted_response = f""" | |
| <div class='response-content'> | |
| <h3>Query: {query}</h3> | |
| <p>{response}</p> | |
| <p class='timestamp'>Generated at {timestamp} in {response_time}s</p> | |
| </div> | |
| """ | |
| performance_html = f"<span class='performance-badge'>⚡ Response time: {response_time}s</span>" | |
| return formatted_response, tool_info or "", performance_html | |
| 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 | |
| with gr.Blocks(title="Real-time Fact Checker & News Agent", css=custom_css) as demo: | |
| gr.HTML(""" | |
| <div style='text-align: center; padding: 20px;'> | |
| <h1>🔍 Real-time Fact Checker & News Agent</h1> | |
| <p style='color: white;'>Powered by Groq's Compound Models with Built-in Web Search</p> | |
| </div> | |
| """) | |
| with gr.Row(elem_classes="gradio-row"): | |
| with gr.Column(scale=2): | |
| with gr.Group(): | |
| gr.HTML('<div class="feature-card">') | |
| gr.Markdown("### 🔑 API Configuration") | |
| api_key_input = gr.Textbox( | |
| label="Groq API Key", | |
| placeholder="Enter your Groq API key here...", | |
| type="password" | |
| ) | |
| api_status = gr.HTML( | |
| label="Status", | |
| value="<div class='status-warning'>⚠️ Please enter your API key</div>" | |
| ) | |
| validate_btn = gr.Button("Validate API Key", variant="secondary") | |
| gr.HTML('</div>') | |
| with gr.Group(): | |
| gr.HTML('<div class="feature-card">') | |
| 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" | |
| ) | |
| temperature = gr.Slider( | |
| minimum=0.0, | |
| maximum=1.0, | |
| value=0.7, | |
| step=0.1, | |
| label="Temperature" | |
| ) | |
| submit_btn = gr.Button("🔍 Get Real-time Information", variant="primary") | |
| clear_btn = gr.Button("Clear", variant="secondary") | |
| gr.HTML('</div>') | |
| with gr.Column(scale=1): | |
| with gr.Group(): | |
| gr.HTML('<div class="feature-card">') | |
| gr.Markdown("### 📝 Example Queries") | |
| examples = fact_checker.get_example_queries() | |
| for category, queries in examples.items(): | |
| with gr.Accordion(category, open=False): | |
| for query in queries: | |
| gr.Button(query, variant="secondary").click( | |
| fn=lambda q=query: q, | |
| outputs=[query_input] | |
| ) | |
| gr.HTML('</div>') | |
| gr.HTML('<div class="results-section">') | |
| gr.Markdown("### 📊 Results") | |
| with gr.Row(): | |
| with gr.Column(scale=2): | |
| response_output = gr.HTML( | |
| label="Response", | |
| value="<div class='response-content'><p>Your response will appear here...</p></div>" | |
| ) | |
| with gr.Column(scale=1): | |
| tool_info_output = gr.HTML( | |
| label="Tool Execution Info", | |
| value="<div class='tool-info'>Tool execution details will appear here...</div>" | |
| ) | |
| performance_output = gr.HTML( | |
| label="Performance", | |
| value="" | |
| ) | |
| gr.HTML('</div>') | |
| gr.HTML(""" | |
| <div class="footer-section"> | |
| <h3>🔗 Useful Links</h3> | |
| <p> | |
| <a href="https://console.groq.com/" target="_blank">Groq Console</a> | | |
| <a href="https://console.groq.com/docs/quickstart" target="_blank">Docs</a> | | |
| <a href="https://console.groq.com/docs/models" target="_blank">Models</a> | |
| </p> | |
| <h3>💡 Tips</h3> | |
| <p>Use custom prompts to specialize the AI. Check tool info for web search usage.</p> | |
| </div> | |
| """) | |
| validate_btn.click( | |
| fn=validate_api_key, | |
| inputs=[api_key_input], | |
| outputs=[api_status, gr.State()] | |
| ) | |
| submit_btn.click( | |
| fn=process_query, | |
| inputs=[query_input, model_choice, temperature, api_key_input, gr.State()], | |
| outputs=[response_output, tool_info_output, performance_output] | |
| ) | |
| clear_btn.click( | |
| fn=lambda: ("", "<div class='response-content'><p>Your response will appear here...</p></div>", | |
| "<div class='tool-info'>Tool execution details will appear here...</div>", ""), | |
| outputs=[query_input, response_output, tool_info_output, performance_output] | |
| ) | |
| return demo | |
| if __name__ == "__main__": | |
| demo = create_interface() | |
| demo.launch(share=True) |