Create main.py

app/main.py

@@ -0,0 +1,42 @@
+import os
+import requests
+from fastapi import FastAPI
+from app.models import ChatRequest, ChatResponse
+
+app = FastAPI(title="AI Chat Service (Hugging Face Space)")
+
+# Hugging Face API ayarları
+HF_API_TOKEN = os.getenv("HF_API_TOKEN")
+MODEL_URL = os.getenv("MODEL_URL", "https://api-inference.huggingface.co/models/meta-llama/Llama-3-8B-Instruct")
+HEADERS = {"Authorization": f"Bearer {HF_API_TOKEN}"}
+
+
+def query_huggingface(prompt: str):
+    """Hugging Face modeline prompt gönderir ve cevabı döner."""
+    response = requests.post(MODEL_URL, headers=HEADERS, json={"inputs": prompt})
+    response.raise_for_status()
+    data = response.json()
+
+    if isinstance(data, list) and "generated_text" in data[0]:
+        return data[0]["generated_text"]
+    elif isinstance(data, dict) and "generated_text" in data:
+        return data["generated_text"]
+    else:
+        return str(data)
+
+
+@app.get("/")
+def home():
+    return {"message": "AI Chat Service is running 🚀"}
+
+
+@app.post("/chat", response_model=ChatResponse)
+def chat(request: ChatRequest):
+    """Sohbet endpoint'i"""
+    prompt = ""
+    for role, msg in request.history:
+        prompt += f"{role}: {msg}\n"
+    prompt += f"User: {request.message}\nAssistant:"
+
+    model_output = query_huggingface(prompt)
+    return ChatResponse(response=model_output)