app.py

import os
from groq import Groq
import gradio as gr
from datetime import datetime
import time


class RTFC:
    def __init__(self):
        self.client = None
        self.model_options = ["groq/compound", "groq/compound-mini"]

    # Validate API Key
    def server(self, api_key):
        try:
            self.client = Groq(api_key=api_key)
            return True, "✅ API Key validated successfully"
        except Exception as e:
            return False, f"❌ Error: {str(e)}"

    # System prompt (instructions for LLM)
    def system_prompt(self):
        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."""

    # Query the Grok model
    def query_compound_model(self, query, model, temperature=0.7):
        if not self.client:
            return "Please set a valid API Key", None, None

        try:
            start_time = time.time()
            system_prompt = self.system_prompt()

            response = self.client.chat.completions.create(
                model=model,
                messages=[
                    {"role": "system", "content": system_prompt},
                    {"role": "user", "content": query},
                ],
                temperature=temperature,
                max_tokens=1000,
            )

            end_time = time.time()
            response_time = round(end_time - start_time, 2)

            final_response = response.choices[0].message.content
            executed_tools = getattr(response.choices[0].message, "executed_tools", None)
            tool_info = self.format_tool_info(executed_tools)

            return final_response, tool_info, response_time

        except Exception as e:
            return f"Error: {str(e)}", None, None

    # Tool info formatter
    def format_tool_info(self, executed_tools):
        if not executed_tools:
            return "Tools Used: Existing Knowledge Only"

        tool_info = "Tools Used:\n"
        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_info += f"{i}. {tool_name}\n"

                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:
                tool_info += f"{i}. Tool {i} (Error parsing details)\n"

        return tool_info


# ============== GRADIO INTERFACE ==============
def create_interface():
    fact_checker = RTFC()

    # Validate API key
    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.server(api_key.strip())
        return message, success

    # Process query
    def process_query(query, model, temperature, api_key):
        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", "", ""

        if not fact_checker.client:
            success, message = fact_checker.server(api_key.strip())
            if not success:
                return message, "", ""

        response, tool_info, response_time = fact_checker.query_compound_model(
            query.strip(), model, temperature
        )

        timestamp = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
        formatted_response = (
            f"**Query:** {query}\n\n**Response:**\n{response}\n\n---\n"
            f"*Generated at {timestamp} in {response_time}s*"
        )

        return formatted_response, tool_info or "", f"Response time: {response_time}s"

    # Gradio UI
    with gr.Blocks(title="Real-Time Fact Checker", theme=gr.themes.Soft(primary_hue="blue")) as demo:
        gr.Markdown("## 🧠 Real-time Fact Checker & News Agent")

        with gr.Row():
            with gr.Column(scale=1):
                api_key_input = gr.Textbox(
                    label="Enter your GROK API Key",
                    placeholder="Enter your GROK API key here...",
                    type="password",
                )

                label_status = gr.Textbox(
                    label="Status",
                    value="Please enter your API key",
                    interactive=False,
                )

                validate_btn = gr.Button("Validate API Key")

                query_input = gr.Textbox(
                    label="Query",
                    placeholder="e.g., What are the latest AI developments today?",
                    lines=4,
                )

                model_choice = gr.Dropdown(
                    choices=fact_checker.model_options,
                    value="groq/compound",
                    label="Model",
                    info="compound: More capable | compound-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",
                )

                with gr.Row():
                    submit_btn = gr.Button("🔎 Get Real-time Information")
                    clear_btn = gr.Button("🧹 Clear")

            with gr.Column(scale=2):
                response_output = gr.Markdown(
                    label="Response",
                    value="*Your response will appear here...*",
                )

                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,
                )

        # Button interactions
        validate_btn.click(
            fn=validate_api_key,
            inputs=[api_key_input],
            outputs=[label_status, gr.State()],
        )

        submit_btn.click(
            fn=process_query,
            inputs=[query_input, model_choice, temperature, api_key_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],
        )

    return demo


# ============== MAIN ENTRY POINT ==============
if __name__ == "__main__":
    demo = create_interface()
    demo.launch()