import gradio as gr
import os
from exa_py import Exa
import traceback

# Get API key from environment variable
EXA_API_KEY = os.getenv("EXA_API_KEY")
print(f"=== DEBUG INFO ===")
print(f"API Key status: {'Set' if EXA_API_KEY else 'Not set'}")
if EXA_API_KEY:
    print(f"API Key length: {len(EXA_API_KEY)}")
    print(f"API Key starts with: {EXA_API_KEY[:8]}...")

if not EXA_API_KEY:
    raise ValueError("EXA_API_KEY environment variable is required")

try:
    exa = Exa(EXA_API_KEY)
    print("Exa client initialized successfully")
except Exception as e:
    print(f"Error initializing Exa client: {e}")
    raise

def search_trainers(requirements, num_results=5):
    """Search for LinkedIn profiles matching the requirements"""
    try:
        print(f"\n=== SEARCH DEBUG ===")
        print(f"Query: {requirements}")
        print(f"Num results: {num_results}")
        print("Making API call...")
        
        response = exa.search_and_contents(
            query=requirements,
            type="auto",
            category="linkedin profile",
            num_results=num_results,
            text={"max_characters": 2000},
            summary=True
        )
        
        print(f"API call successful!")
        print(f"Number of results: {len(response.results)}")
        
        # Print first result for debugging
        if response.results:
            first_result = response.results[0]
            print(f"First result title: {first_result.title}")
            print(f"First result URL: {first_result.url}")
        
        return response.results
        
    except Exception as e:
        print(f"=== SEARCH ERROR ===")
        print(f"Error: {e}")
        print(f"Error type: {type(e).__name__}")
        print(f"Traceback: {traceback.format_exc()}")
        return []

def find_trainers(requirements, num_trainers):
    """Main function to find trainers and format results for Gradio"""
    try:
        # Validate input
        if not requirements.strip():
            return "Please enter your trainer requirements."
        
        # Ensure num_trainers is within reasonable bounds
        num_trainers = max(1, min(int(num_trainers), 20))
        
        print(f"\n=== FIND TRAINERS ===")
        print(f"Requirements: {requirements}")
        print(f"Number: {num_trainers}")
        
        # Search for trainers
        trainers = search_trainers(requirements, num_trainers)
        
        if not trainers:
            return f"""
## No Results Found

**Search Details:**
- Query: "{requirements}"
- Number requested: {num_trainers}
- API Status: ✅ Connected

**Try these suggestions:**
1. **Simplify your search**: Try just "trainer" or "coach"
2. **Remove location**: Try without city/country restrictions
3. **Use different keywords**: "leadership trainer", "business coach", "corporate trainer"

**Example working queries:**
- "leadership trainer"
- "sales coach" 
- "business trainer"
- "corporate training expert"

Check the logs tab for detailed error information.
            """
        
        # Format results
        results = f"## ✅ Found {len(trainers)} Matching Trainers\n\n"
        
        for i, trainer in enumerate(trainers, 1):
            results += f"### {i}. {trainer.title}\n"
            results += f"**LinkedIn:** [View Profile]({trainer.url})\n\n"
            
            if trainer.summary:
                results += f"**Summary:**\n{trainer.summary}\n\n"
            
            if trainer.text:
                # Limit text preview to 300 characters for better readability
                text_preview = trainer.text[:300] + "..." if len(trainer.text) > 300 else trainer.text
                results += f"**Profile Details:**\n{text_preview}\n\n"
            
            results += "---\n\n"
        
        return results
        
    except Exception as e:
        error_msg = f"""
## ❌ Error Occurred

**Error:** {str(e)}

**Type:** {type(e).__name__}

**Troubleshooting:**
1. Check the Logs tab for detailed error information
2. Try a simpler search query
3. Verify your API key is working

Please check the application logs for more details.
        """
        print(f"FIND_TRAINERS ERROR: {e}")
        print(f"Full traceback: {traceback.format_exc()}")
        return error_msg

# Test the API connection on startup
def test_api_connection():
    try:
        print("\n=== TESTING API CONNECTION ===")
        test_response = exa.search(
            query="test",
            num_results=1
        )
        print("✅ API connection test successful!")
        return True
    except Exception as e:
        print(f"❌ API connection test failed: {e}")
        return False

# Test on startup
api_working = test_api_connection()

# Create Gradio interface
def create_trainer_finder_app():
    with gr.Blocks(title="Trainer Finder", theme=gr.themes.Soft()) as app:
        gr.Markdown("# 🎯 Trainer Finder")
        gr.Markdown("Find specialized trainers based on your requirements using Exa API")
        
        # Add status indicators
        api_status = "✅ API Connected" if api_working else "❌ API Connection Failed"
        env_status = "✅ Environment Variable Set" if EXA_API_KEY else "❌ Environment Variable Missing"
        
        gr.Markdown(f"""
**System Status:**
- {env_status}
- {api_status}
        """)
        
        with gr.Row():
            with gr.Column(scale=2):
                requirements_input = gr.Textbox(
                    label="Training Requirements",
                    placeholder="Start simple: try 'leadership trainer' or 'sales coach'",
                    lines=3,
                    value="leadership trainer"  # Default value for testing
                )
                
                num_trainers_input = gr.Slider(
                    minimum=1,
                    maximum=10,  # Reduced for faster testing
                    value=3,     # Reduced default
                    step=1,
                    label="Number of trainers to find"
                )
                
                search_button = gr.Button("🔍 Find Trainers", variant="primary")
        
        with gr.Row():
            results_output = gr.Markdown(label="Results")
        
        # Connect the button to the function
        search_button.click(
            fn=find_trainers,
            inputs=[requirements_input, num_trainers_input],
            outputs=results_output
        )
        
        # Simplified examples for better success rate
        gr.Examples(
            examples=[
                ["leadership trainer", 3],
                ["sales coach", 3], 
                ["business trainer", 3],
                ["executive coach", 3]
            ],
            inputs=[requirements_input, num_trainers_input]
        )
    
    return app

# Create and launch the app
if __name__ == "__main__":
    app = create_trainer_finder_app()
    app.launch()