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main.py

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+"""
+Devrayog AI - Main API Server
+FastAPI-based API for Devrayog AI models
+"""
+
+from fastapi import FastAPI, HTTPException
+from fastapi.middleware.cors import CORSMiddleware
+from pydantic import BaseModel
+from typing import Optional
+import time
+import os
+
+app = FastAPI(
+    title="Devrayog AI API",
+    description="India's First Solo-Built AI - API Server",
+    version="0.1.0"
+)
+
+# CORS
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["*"],
+    allow_credentials=True,
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+
+# Request/Response models
+class ChatRequest(BaseModel):
+    message: str
+    model: str = "devrayog-agni"
+    max_tokens: int = 512
+    temperature: float = 0.7
+    system_prompt: Optional[str] = None
+
+class ChatResponse(BaseModel):
+    response: str
+    model: str
+    tokens_used: int
+    time_taken: float
+
+class ModelInfo(BaseModel):
+    name: str
+    description: str
+    parameters: str
+    status: str
+
+# Routes
+@app.get("/")
+async def root():
+    return {
+        "name": "Devrayog AI",
+        "version": "0.1.0",
+        "status": "running",
+        "message": "Welcome to Devrayog AI - India's First Solo-Built AI",
+        "endpoints": {
+            "chat": "/api/v1/chat",
+            "models": "/api/v1/models",
+            "health": "/health"
+        }
+    }
+
+@app.get("/health")
+async def health():
+    return {"status": "healthy", "timestamp": time.time()}
+
+@app.get("/api/v1/models")
+async def list_models():
+    return {
+        "models": [
+            {
+                "id": "devrayog-agni",
+                "name": "Devrayog Agni",
+                "description": "Fast and sharp - optimized for quick responses",
+                "parameters": "3.8B",
+                "status": "coming_soon"
+            },
+            {
+                "id": "devrayog-vayu",
+                "name": "Devrayog Vayu",
+                "description": "Creative and flowing - optimized for storytelling",
+                "parameters": "9B",
+                "status": "coming_soon"
+            },
+            {
+                "id": "devrayog-akash",
+                "name": "Devrayog Akash",
+                "description": "Most powerful - optimized for complex reasoning",
+                "parameters": "8B",
+                "status": "coming_soon"
+            }
+        ]
+    }
+
+@app.post("/api/v1/chat", response_model=ChatResponse)
+async def chat(request: ChatRequest):
+    start_time = time.time()
+    
+    # For now, return a placeholder response
+    # Once models are deployed, this will call the actual model
+    response = f"[Devrayog AI - {request.model}] Thank you for your message: '{request.message}'. This is a placeholder response. The actual model will be deployed soon on Hugging Face."
+    
+    time_taken = time.time() - start_time
+    
+    return ChatResponse(
+        response=response,
+        model=request.model,
+        tokens_used=len(response.split()),
+        time_taken=round(time_taken, 3)
+    )
+
+if __name__ == "__main__":
+    import uvicorn
+    port = int(os.environ.get("PORT", 8000))
+    uvicorn.run(app, host="0.0.0.0", port=port)