import os
import requests
import gradio as gr

# Set your API keys
os.environ['XAI_API_KEY'] = 'xai-Gxw7oW4yR6Q6oTd0v9lDRLotXZQYJNz9YKlH7R6eMyTmqIV9h6uustEGZAaJEvGmewlwbUnM1jTX4chj'  # Replace with your actual xAI API key
os.environ['SPORTS_API_KEY'] = '21253d4ad8mshc858b5f3ba04919p1b5a03jsna381170f15fe'  # Replace with your sports data API key

# Initialize conversation history
conversation_history = []

def fetch_sports_scores(sport):
    """Fetches real-time sports scores for the specified sport."""
    url = f"https://api.sportsdata.io/v4/{sport}/scores"
    headers = {
        "User-Agent": "YourAppName",
        "Authorization": f"Bearer {os.environ['SPORTS_API_KEY']}"
    }
    
    response = requests.get(url, headers=headers)
    
    if response.status_code == 200:
        return response.json()  # Return JSON data
    else:
        return f"Error fetching sports data: {response.text}"

def browse_web_page(url):
    """Simulated function to browse a web page."""
    return f"Browsing to {url}..."

def chat_with_bot(user_input):
    # Append user input to conversation history
    conversation_history.append({"role": "user", "content": user_input})

    url = "https://api.x.ai/v1/chat/completions"
    headers = {
        "Content-Type": "application/json",
        "Authorization": f"Bearer {os.environ['XAI_API_KEY']}"
    }
    
    messages = [{"role": "system", "content": "You are a helpful assistant."}] + \
               [{"role": msg["role"], "content": msg["content"]} for msg in conversation_history]

    data = {
        "messages": messages,
        "model": "grok-beta",
        "functions": [
            {
                "name": "fetch_sports_scores",
                "description": "Fetch real-time scores for a specific sport.",
                "parameters": {
                    "type": "object",
                    "properties": {
                        "sport": {
                            "type": "string",
                            "description": "The sport you want scores for.",
                            "example_value": "football",
                        },
                    },
                    "required": ["sport"],
                },
            },
            {
                "name": "browse_web_page",
                "description": "Browse a web page.",
                "parameters": {
                    "type": "object",
                    "properties": {
                        "url": {
                            "type": "string",
                            "description": "The URL of the web page to browse.",
                            "example_value": "https://example.com",
                        },
                    },
                    "required": ["url"],
                },
            },
        ],
        "stream": False,
        "temperature": 0.7
    }
    
    response = requests.post(url, headers=headers, json=data)
    
    if response.status_code == 200:
        bot_response = response.json()['choices'][0]['message']
        
        # Check if there's a function call request
        if 'function_call' in bot_response:
            function_name = bot_response['function_call']['name']
            args = bot_response['function_call']['arguments']
            
            if function_name == 'fetch_sports_scores':
                sport = args.get('sport')
                result = fetch_sports_scores(sport)
                bot_response_content = str(result)
            elif function_name == 'browse_web_page':
                url = args.get('url')
                bot_response_content = browse_web_page(url)
            else:
                bot_response_content = bot_response['content']
        else:
            bot_response_content = bot_response['content']
        
        # Append bot response to conversation history
        conversation_history.append({"role": "assistant", "content": bot_response_content})
        
        # Format the chat history for display
        chat_display = "\n".join([f"{msg['role'].capitalize()}: {msg['content']}" for msg in conversation_history])
        
        return chat_display
    else:
        return f"Error: {response.text}"

# Create Gradio interface
iface = gr.Interface(
    fn=chat_with_bot,
    inputs="text",
    outputs="text",
    title="xAI Chatbot with Function Calling",
    description="Chat with Grok! Type your message below.",
)

# Launch the interface
if __name__ == "__main__":
    iface.launch()