binapp.py

import gradio as gr
import requests
import json
import os
from typing import List, Dict, Optional

class BinericAPI:
    def __init__(self):
        self.api_key = os.environ.get("Key")
        if not self.api_key or self.api_key == "YOUR_API_KEY":
            raise ValueError("API Key not found. Please add your API key in the 'Secrets' tab (Key = 'YOUR_API_KEY')")
        
        self.base_url = "https://api.bineric.com/api/v1"
        self.headers = {'api-key': self.api_key}
    
    def get_balance(self):
        """Fetch balance from Bineric API"""
        try:
            response = requests.get(
                f'{self.base_url}/monitoring/balance',
                headers=self.headers
            )
            response.raise_for_status()
            return response.json()
        except requests.exceptions.RequestException as e:
            return {"error": f"API request failed: {str(e)}"}
    
    def chat_completion(self, model: str, messages: List[Dict], 
                       stream: bool = False, temperature: float = 0.7,
                       max_response_length: Optional[int] = None,
                       top_p: float = 0.95):
        """Get chat completion from various AI models"""
        try:
            # Prepare request payload
            payload = {
                "model": model,
                "messages": messages,
                "options": {
                    "stream": stream,
                    "temperature": temperature,
                    "top_p": top_p
                }
            }
            
            # Add max_response_length if provided
            if max_response_length:
                payload["options"]["max_response_length"] = max_response_length
            
            # Make API request
            response = requests.post(
                f'{self.base_url}/ai/chat/completions',
                headers=self.headers,
                json=payload
            )
            response.raise_for_status()
            
            return response.json()
        except requests.exceptions.RequestException as e:
            return {"error": f"Chat completion failed: {str(e)}"}

# Initialize API client
try:
    api_client = BinericAPI()
except ValueError as e:
    api_client = None

# Available models organized by provider
MODELS = {
    "OpenAI": [
        "gpt-5",
        "gpt-5-nano", 
        "gpt-4",
        "o1",
        "o3-mini",
        "gpt-oss-120b",
        "gpt-oss-20b"
    ],
    "Google": [
        "gemini-2.0-flash",
        "gemini-2.5-flash",
        "gemini-2.5-pro",
        "gemini-3-pro-preview"
    ],
    "Anthropic": [
        "claude-3.7-sonnet",
        "claude-sonnet-4",
        "claude-haiku-4-5"
    ],
    "DeepSeek": [
        "deepseek-v3.1-terminus",
        "deepseek-r1-0528"
    ],
    "Meta": [
        "meta-llama-3.1-8b",
        "meta-llama-3.1-405b",
        "meta-llama-3.3-70b"
    ],
    "Other": [
        "norskgpt",
        "qwen-3-coder-480b",
        "qwen-3-235b",
        "mistral_large_24_02",
        "llama4-maverick",
        "llama4-scout"
    ]
}

def get_balance():
    """Fetch and display balance"""
    if not api_client:
        return "❌ API Key not found. Please add your API key in the 'Secrets' tab (Key = 'YOUR_API_KEY')"
    
    balance_data = api_client.get_balance()
    
    if "error" in balance_data:
        return f"❌ Error: {balance_data['error']}"
    
    # Format the JSON response for better readability
    formatted_response = json.dumps(balance_data, indent=2)
    return f"✅ Balance retrieved successfully:\n\n{formatted_response}"

def chat_complete(model, system_prompt, user_message, temperature, max_tokens, top_p, history=None):
    """Generate chat completion"""
    if not api_client:
        return "", history, "❌ API Key not found. Please add your API key in the 'Secrets' tab"
    
    # Prepare messages
    messages = []
    
    # Add system prompt if provided
    if system_prompt.strip():
        messages.append({"role": "system", "content": system_prompt})
    
    # Add conversation history
    if history:
        for entry in history:
            messages.append({"role": "user", "content": entry["user"]})
            if entry["assistant"]:
                messages.append({"role": "assistant", "content": entry["assistant"]})
    
    # Add current user message
    messages.append({"role": "user", "content": user_message})
    
    # Get completion
    result = api_client.chat_completion(
        model=model,
        messages=messages,
        temperature=temperature,
        max_response_length=max_tokens if max_tokens > 0 else None,
        top_p=top_p
    )
    
    if "error" in result:
        return "", history, f"❌ Error: {result['error']}"
    
    # Extract response text
    if "choices" in result and len(result["choices"]) > 0:
        response_text = result["choices"][0].get("message", {}).get("content", "No response generated")
        
        # Update history
        if history is None:
            history = []
        
        history.append({
            "user": user_message,
            "assistant": response_text
        })
        
        # Format usage info if available
        usage_info = ""
        if "usage" in result:
            usage = result["usage"]
            usage_info = f"\n\n**Usage:**\n- Prompt tokens: {usage.get('prompt_tokens', 'N/A')}\n- Completion tokens: {usage.get('completion_tokens', 'N/A')}\n- Total tokens: {usage.get('total_tokens', 'N/A')}"
        
        return "", history, response_text + usage_info
    else:
        return "", history, "❌ No response generated from the model"

def clear_chat():
    """Clear chat history"""
    return [], "", ""

# Create Gradio interface
with gr.Blocks(title="Bineric AI Dashboard") as demo:
    gr.Markdown("# 🤖 Bineric AI Dashboard")
    gr.Markdown("Balance checking and AI chat completion using Bineric API")
    
    # Tabs for different functionalities
    with gr.Tabs():
        # Tab 1: Balance Checker
        with gr.Tab("💰 Balance"):
            gr.Markdown("### Check your API balance")
            with gr.Accordion("ℹ️ Setup Instructions", open=False):
                gr.Markdown("""
                1. **Add your API key in Gradio Secrets:**
                   - Go to the "Secrets" tab
                   - Add a new secret with:
                     - Key: `Key`
                     - Value: `YOUR_API_KEY_HERE`
                
                2. **Click the button below to fetch balance**
                """)
            
            balance_output = gr.Textbox(
                label="Balance Information",
                placeholder="Click 'Get Balance' to see your balance...",
                lines=15
            )
            
            with gr.Row():
                get_balance_btn = gr.Button("🔄 Get Balance", variant="primary")
                clear_balance_btn = gr.Button("🗑️ Clear")
            
            get_balance_btn.click(get_balance, outputs=balance_output)
            clear_balance_btn.click(lambda: "", outputs=balance_output)
        
        # Tab 2: Chat Completion
        with gr.Tab("💬 AI Chat"):
            gr.Markdown("### Chat with various AI models")
            
            with gr.Row():
                # Left column: Settings and input
                with gr.Column(scale=1):
                    # Model selection with groups
                    model_selector = gr.Dropdown(
                        label="Select AI Model",
                        choices=[model for models in MODELS.values() for model in models],
                        value="gpt-5",
                        interactive=True
                    )
                    
                    # Add model provider filter
                    provider_filter = gr.Dropdown(
                        label="Filter by Provider",
                        choices=list(MODELS.keys()),
                        value="OpenAI",
                        interactive=True
                    )
                    
                    # System prompt
                    system_prompt = gr.Textbox(
                        label="System Prompt (optional)",
                        placeholder="You are a helpful assistant...",
                        lines=3
                    )
                    
                    # Generation parameters
                    with gr.Accordion("⚙️ Advanced Parameters", open=False):
                        temperature = gr.Slider(
                            label="Temperature",
                            minimum=0.0,
                            maximum=2.0,
                            value=0.7,
                            step=0.1
                        )
                        
                        max_tokens = gr.Slider(
                            label="Max Tokens (0 = unlimited)",
                            minimum=0,
                            maximum=10000,
                            value=0,
                            step=100
                        )
                        
                        top_p = gr.Slider(
                            label="Top-p",
                            minimum=0.0,
                            maximum=1.0,
                            value=0.95,
                            step=0.05
                        )
                
                # Right column: Chat interface
                with gr.Column(scale=2):
                    # Chat history
                    chatbot = gr.Chatbot(
                        label="Conversation",
                        height=400
                    )
                    
                    # Hidden state for chat history
                    chat_state = gr.State([])
                    
                    # User input
                    user_input = gr.Textbox(
                        label="Your Message",
                        placeholder="Type your message here...",
                        lines=3
                    )
                    
                    # Response info
                    response_info = gr.Markdown("")
                    
                    # Buttons
                    with gr.Row():
                        send_btn = gr.Button("📤 Send", variant="primary")
                        clear_chat_btn = gr.Button("🗑️ Clear Chat")
                    
                    with gr.Row():
                        gr.Markdown("**Tip:** Press Shift+Enter for new line, Enter to send")
            
            # Update model list based on provider filter
            def update_model_list(provider):
                return gr.Dropdown(choices=MODELS[provider], value=MODELS[provider][0])
            
            provider_filter.change(
                update_model_list,
                inputs=provider_filter,
                outputs=model_selector
            )
            
            # Chat functions
            def send_message(model, system, message, temp, tokens, top, history):
                return chat_complete(model, system, message, temp, tokens, top, history)
            
            # Connect send button
            send_btn.click(
                send_message,
                inputs=[model_selector, system_prompt, user_input, temperature, max_tokens, top_p, chat_state],
                outputs=[user_input, chat_state, response_info]
            )
            
            # Allow Enter to send
            user_input.submit(
                send_message,
                inputs=[model_selector, system_prompt, user_input, temperature, max_tokens, top_p, chat_state],
                outputs=[user_input, chat_state, response_info]
            )
            
            # Clear chat
            clear_chat_btn.click(
                clear_chat,
                outputs=[chat_state, user_input, response_info]
            )
        
        # Tab 3: Model Information
        with gr.Tab("📚 Model Info"):
            gr.Markdown("### Available AI Models")
            
            for provider, models in MODELS.items():
                with gr.Accordion(f"🔹 {provider}", open=False):
                    model_table = []
                    for model in models:
                        model_table.append(f"- **{model}**")
                    
                    gr.Markdown("\n".join(model_table))
            
            gr.Markdown("""
            ---
            **API Documentation:**
            - All models use the same chat completion endpoint
            - Request format: JSON with messages array
            - Support for system prompts and conversation history
            - Token usage tracking available in responses
            """)
    
    # Footer
    gr.Markdown("""
    ---
    **Note:** This dashboard uses the Bineric API. Make sure your API key has access to the models you want to use.
    Balance information is fetched from the monitoring endpoint.
    """)

# Launch the app
if __name__ == "__main__":
    demo.launch(
        theme=gr.themes.Soft(),
        share=True
    )