client_example.py

"""
Example client for the AI Model Runner API
"""

import json
import requests
from typing import List, Dict, Any

class AIModelRunnerClient:
    def __init__(self, base_url: str = "http://localhost:8000"):
        self.base_url = base_url.rstrip("/")
    
    def get_api_info(self) -> Dict[str, Any]:
        """Get API information"""
        response = requests.get(f"{self.base_url}/")
        return response.json()
    
    def health_check(self) -> Dict[str, Any]:
        """Check API health"""
        response = requests.get(f"{self.base_url}/health")
        return response.json()
    
    def list_models(self) -> Dict[str, Any]:
        """List available models"""
        response = requests.get(f"{self.base_url}/models")
        return response.json()
    
    def chat(self, messages: List[Dict[str, str]], **kwargs) -> Dict[str, Any]:
        """Send chat message"""
        data = {
            "messages": messages,
            "model": kwargs.get("model", "microsoft/DialoGPT-medium"),
            "max_length": kwargs.get("max_length", 100),
            "temperature": kwargs.get("temperature", 0.7)
        }
        response = requests.post(f"{self.base_url}/chat", json=data)
        return response.json()
    
    def analyze_code(self, code: str, task: str, language: str = "python") -> Dict[str, Any]:
        """Analyze code"""
        data = {
            "code": code,
            "task": task,
            "language": language
        }
        response = requests.post(f"{self.base_url}/code", json=data)
        return response.json()
    
    def reasoning(self, problem: str, context: str = "", steps: int = 5) -> Dict[str, Any]:
        """Perform reasoning"""
        data = {
            "problem": problem,
            "context": context,
            "steps": steps
        }
        response = requests.post(f"{self.base_url}/reasoning", json=data)
        return response.json()
    
    def analyze_sentiment(self, text: str) -> Dict[str, Any]:
        """Analyze sentiment"""
        data = {"text": text}
        response = requests.post(f"{self.base_url}/analyze-sentiment", json=data)
        return response.json()

def demo():
    """Demonstrate API usage"""
    client = AIModelRunnerClient()
    
    print("=== AI Model Runner API Demo ===\n")
    
    # Check API status
    print("1. API Status:")
    status = client.health_check()
    print(f"   Status: {status}")
    print()
    
    # List models
    print("2. Available Models:")
    models = client.list_models()
    for model in models["models"]:
        print(f"   - {model['name']} ({model['type']}): {'✓' if model['loaded'] else '✗'}")
    print()
    
    # Chat example
    print("3. Chat Example:")
    chat_response = client.chat([
        {"role": "user", "content": "Hello! How can you help me today?"}
    ])
    print(f"   User: Hello! How can you help me today?")
    print(f"   AI: {chat_response['response']}")
    print()
    
    # Code analysis example
    print("4. Code Analysis Example:")
    code = """
def fibonacci(n):
    if n <= 1:
        return n
    return fibonacci(n-1) + fibonacci(n-2)
"""
    code_response = client.analyze_code(code, "explain", "python")
    print("   Original Code:")
    print(code)
    print("   Analysis:")
    print(code_response["result"])
    print()
    
    # Reasoning example
    print("5. Reasoning Example:")
    reasoning_response = client.reasoning(
        problem="How to implement an efficient sorting algorithm?",
        context="Working with large datasets",
        steps=3
    )
    print(f"   Problem: How to implement an efficient sorting algorithm?")
    print("   Reasoning:")
    print(reasoning_response["reasoning"])
    print()
    
    # Sentiment analysis example
    print("6. Sentiment Analysis Example:")
    sentiment = client.analyze_sentiment("I love using this AI API! It's fantastic and very helpful.")
    print(f"   Text: I love using this AI API! It's fantastic and very helpful.")
    print(f"   Sentiment: {sentiment['sentiment']}")
    print(f"   Confidence: {sentiment['confidence']:.2%}")
    print()

if __name__ == "__main__":
    try:
        demo()
    except requests.exceptions.ConnectionError:
        print("Error: Cannot connect to the API. Make sure the server is running on http://localhost:8000")
    except Exception as e:
        print(f"Error: {e}")