Create app.py

app.py

@@ -0,0 +1,74 @@
+import os
+import sys
+import time
+import threading
+from datetime import datetime
+from fastapi import FastAPI
+from pydantic import BaseModel
+from transformers import pipeline
+from unsloth import FastLanguageModel
+
+# === Ortam değişkenleri
+os.environ.setdefault("HF_HOME", "/app/.cache")
+os.environ.setdefault("HF_HUB_CACHE", "/app/.cache")
+os.environ.setdefault("BITSANDBYTES_NOWELCOME", "1")
+
+# === Basit log
+def log(message):
+    timestamp = datetime.now().strftime("%H:%M:%S")
+    print(f"[{timestamp}] {message}", flush=True)
+
+# === FastAPI başlat
+app = FastAPI()
+pipe = None
+
+@app.on_event("startup")
+def load_model():
+    global pipe
+    model_name = "atasoglu/Turkish-Llama-3-8B-function-calling"
+    log(f"⬇️ Model yükleniyor: {model_name}")
+    model, tokenizer = FastLanguageModel.from_pretrained(
+        model_name=model_name,
+        load_in_4bit=True,
+        device_map="auto"
+    )
+    FastLanguageModel.for_inference(model)
+    pipe = pipeline(
+        "text-generation",
+        model=model,
+        tokenizer=tokenizer,
+        device_map="auto"
+    )
+    log("✅ Model yüklendi, test etmeye hazır.")
+
+class TestRequest(BaseModel):
+    user_input: str
+
+@app.post("/test")
+def test(req: TestRequest):
+    prompt = f"Kullanıcı: {req.user_input}\nAsistan:"
+    log(f"💬 Prompt alındı: {req.user_input}")
+    outputs = pipe(
+        prompt,
+        max_new_tokens=256,
+        temperature=0.2,
+        top_p=0.95,
+        repetition_penalty=1.1
+    )
+    answer = outputs[0]["generated_text"].replace(prompt, "").strip()
+    log("✅ Cevap üretildi.")
+    return {"response": answer}
+
+@app.get("/")
+def health():
+    return {"status": "ok"}
+
+def run_health_server():
+    import uvicorn
+    uvicorn.run(app, host="0.0.0.0", port=7860)
+
+threading.Thread(target=run_health_server, daemon=True).start()
+
+log("⏸️ Uygulama bekleme modunda...")
+while True:
+    time.sleep(60)