Upload core/ai_gateway.py with huggingface_hub

core/ai_gateway.py

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+from abc import ABC, abstractmethod
+from typing import Dict, Any, Optional
+from enum import Enum
+import asyncio
+import logging
+import os
+import requests
+import json
+
+logger = logging.getLogger(__name__)
+
+class ModelType(Enum):
+    TEXT_GENERATION = "text_generation"
+    IMAGE_GENERATION = "image_generation"
+    EMBEDDING = "embedding"
+
+class ModelProvider(Enum):
+    LOCAL_LLAMA = "local_llama"
+    LOCAL_MISTRAL = "local_mistral"
+    API_OPENAI = "api_openai"
+    LOCAL_STABLE_DIFFUSION = "local_stable_diffusion"
+
+class BaseModel(ABC):
+    @abstractmethod
+    async def generate(self, prompt: str, **kwargs) -> str:
+        pass
+
+class MockLlamaModel(BaseModel):
+    def __init__(self, model_path: str):
+        self.model_path = model_path
+        logger.info(f"Initialized mock Llama model with path: {model_path}")
+
+    async def generate(self, prompt: str, max_length: int = 512, **kwargs) -> str:
+        # Simulate model response for demonstration
+        return f"Mock response to: {prompt[:50]}... [Truncated for demo]"
+
+class MockMistralModel(BaseModel):
+    def __init__(self, model_path: str):
+        self.model_path = model_path
+        logger.info(f"Initialized mock Mistral model with path: {model_path}")
+
+    async def generate(self, prompt: str, max_length: int = 512, **kwargs) -> str:
+        # Simulate model response for demonstration
+        return f"Mistral-style response to: {prompt[:50]}... [Truncated for demo]"
+
+class MockStableDiffusionModel(BaseModel):
+    def __init__(self):
+        logger.info("Initialized mock Stable Diffusion model")
+
+    async def generate(self, prompt: str, **kwargs) -> str:
+        # Simulate image generation for demonstration
+        return f"Mock image generated for prompt: {prompt[:50]}... [Truncated for demo]"
+
+class AIGateway:
+    def __init__(self):
+        self.models = {}
+        self._initialize_models()
+    
+    def _initialize_models(self):
+        """Initialize available models"""
+        try:
+            # In a real implementation, we would load actual models
+            # For this demo, we'll use mock implementations
+            self.models[ModelProvider.LOCAL_LLAMA] = MockLlamaModel("llama-model-path")
+            self.models[ModelProvider.LOCAL_MISTRAL] = MockMistralModel("mistral-model-path")
+            self.models[ModelProvider.LOCAL_STABLE_DIFFUSION] = MockStableDiffusionModel()
+            logger.info("AI Gateway initialized with mock models")
+        except Exception as e:
+            logger.error(f"Error initializing models: {e}")
+    
+    async def generate_text(
+        self, 
+        prompt: str, 
+        provider: ModelProvider = ModelProvider.LOCAL_LLAMA,
+        **kwargs
+    ) -> str:
+        """
+        Generate text using the specified provider
+        """
+        if provider not in self.models:
+            raise ValueError(f"Model provider {provider} not available")
+        
+        model = self.models[provider]
+        logger.info(f"Generating text using {provider.value}")
+        
+        try:
+            result = await model.generate(prompt, **kwargs)
+            logger.info(f"Generated {len(result)} characters")
+            return result
+        except Exception as e:
+            logger.error(f"Error generating text: {e}")
+            raise
+    
+    async def generate_image(
+        self,
+        prompt: str,
+        **kwargs
+    ) -> str:
+        """
+        Generate image using the image generation model
+        """
+        model = self.models[ModelProvider.LOCAL_STABLE_DIFFUSION]
+        logger.info("Generating image")
+        
+        try:
+            result = await model.generate(prompt, **kwargs)
+            logger.info("Image generated successfully")
+            return result
+        except Exception as e:
+            logger.error(f"Error generating image: {e}")
+            raise
+    
+    async def route_request(
+        self, 
+        prompt: str, 
+        preferred_provider: Optional[ModelProvider] = None,
+        fallback_providers: Optional[list] = None
+    ) -> str:
+        """
+        Route request with fallback mechanism
+        """
+        providers_to_try = []
+        
+        if preferred_provider:
+            providers_to_try.append(preferred_provider)
+        
+        if fallback_providers:
+            providers_to_try.extend(fallback_providers)
+        else:
+            # Default fallback order
+            providers_to_try.extend([
+                ModelProvider.LOCAL_LLAMA,
+                ModelProvider.LOCAL_MISTRAL
+            ])
+        
+        for provider in providers_to_try:
+            try:
+                return await self.generate_text(prompt, provider)
+            except Exception as e:
+                logger.warning(f"Provider {provider.value} failed: {e}")
+                continue
+        
+        raise RuntimeError("All providers failed")