"""
REST API Endpoints Page for Vietnamese Sentiment Analysis
"""

import gradio as gr
import os

def get_api_base_url():
    """Get the correct API base URL based on environment"""
    # Check if we're on Hugging Face Spaces
    space_id = os.getenv('SPACE_ID')

    if space_id:
        # We're on Hugging Face Spaces
        space_name = os.getenv('SPACE_NAME', 'your-space-name')
        return f"https://{space_name}.hf.space:7861"
    else:
        # We're running locally
        return "http://localhost:7861"

def create_api_endpoints_page():
    """Create the REST API endpoints tab"""

    # Get the correct base URL
    api_base_url = get_api_base_url()
    is_hf_spaces = os.getenv('SPACE_ID') is not None

    # REST API Endpoints Tab
    with gr.Tab("🌐 REST API Endpoints"):
        # Create dynamic content based on environment
        if is_hf_spaces:
            environment_info = f"""
            ## 🌐 REST API Endpoints

            Your sentiment analysis model is now available via REST API!

            **📍 Environment:** Hugging Face Spaces
            **🔗 Base URL:** `{api_base_url}`
            **📚 Interactive Docs:** {api_base_url}/docs
            """
        else:
            environment_info = f"""
            ## 🌐 REST API Endpoints

            Your sentiment analysis model is now available via REST API!

            **📍 Environment:** Local Development
            **🔗 Base URL:** `{api_base_url}`
            **📚 Interactive Docs:** {api_base_url}/docs
            """

        gr.Markdown(environment_info)

        # Static content
        gr.Markdown(f"""
        ### Available Endpoints:

        #### 📝 Single Text Analysis
        **POST** `/analyze`
        ```json
        {{
            "text": "Giảng viên dạy rất hay và tâm huyết.",
            "language": "vi"
        }}
        ```

        #### 📊 Batch Analysis
        **POST** `/analyze/batch`
        ```json
        {{
            "texts": [
                "Text 1",
                "Text 2",
                "Text 3"
            ],
            "language": "vi"
        }}
        ```

        #### ❤️ Health Check
        **GET** `/health`

        #### ℹ️ Model Information
        **GET** `/model/info`

        #### 🧹 Memory Cleanup
        **POST** `/memory/cleanup`

        ### 📚 Interactive API Documentation
        Visit **{api_base_url}/docs** for interactive API documentation with Swagger UI.

        ### 🚀 Usage Examples

        **cURL Example:**
        ```bash
        curl -X POST "{api_base_url}/analyze" \\
             -H "Content-Type: application/json" \\
             -d '{{"text": "Giảng viên dạy rất hay và tâm huyết."}}'
        ```

        **Python Example:**
        ```python
        import requests

        response = requests.post(
            "{api_base_url}/analyze",
            json={{"text": "Giảng viên dạy rất hay và tâm huyết."}}
        )
        result = response.json()
        print(f"Sentiment: {{result['sentiment']}}")
        print(f"Confidence: {{result['confidence']:.2%}}")
        ```

        **JavaScript Example:**
        ```javascript
        const response = await fetch('{api_base_url}/analyze', {{
            method: 'POST',
            headers: {{ 'Content-Type': 'application/json' }},
            body: JSON.stringify({{
                text: 'Giảng viên dạy rất hay và tâm huyết.'
            }})
        }});
        const result = await response.json();
        console.log('Sentiment:', result.sentiment);
        console.log('Confidence:', (result.confidence * 100).toFixed(2) + '%');
        ```

        ### 📝 Response Format
        ```json
        {{
            "sentiment": "Positive",
            "confidence": 0.89,
            "probabilities": {{
                "positive": 0.89,
                "neutral": 0.08,
                "negative": 0.03
            }},
            "processing_time": 0.123,
            "text": "Giảng viên dạy rất hay và tâm huyết."
        }}
        ```

        ### ⚠️ Rate Limiting & Performance
        - **Maximum batch size:** 10 texts per request
        - **Memory management:** Automatic cleanup after each request
        - **Processing time:** ~100ms per text
        - **CORS enabled:** Cross-origin requests supported

        ---
        *API server runs alongside the Gradio interface for maximum flexibility!*
        """)