Update app.py

app.py

@@ -1,16 +1,8 @@
-import os
-import time
-from typing import List, Dict, Any
-
 import gradio as gr
-from fastapi import FastAPI
-from fastapi.middleware.cors import CORSMiddleware
-from pydantic import BaseModel
 from huggingface_hub import InferenceClient
+import os
 
-# =============================
-# MODEL
-# =============================
+# HF model
 REPO_ID = "Qwen/Qwen2.5-7B-Instruct"
 HF_TOKEN = os.getenv("HF_TOKEN")
 
@@ -19,78 +11,36 @@ client = InferenceClient(
     token=HF_TOKEN
 )
 
-# =============================
-# FASTAPI
-# =============================
-app = FastAPI()
-
-app.add_middleware(
-    CORSMiddleware,
-    allow_origins=["*"],
-    allow_methods=["*"],
-    allow_headers=["*"],
-)
-
-# =============================
-# REQUEST MODEL
-# =============================
-class ChatRequest(BaseModel):
-    message: str
-    history: List[Any] | None = []
+def chat_fn(message, history):
+    if not message:
+        return "Bir şey yazmadın."
 
-# =============================
-# API ENDPOINT
-# =============================
-@app.post("/api/chat")
-async def chat(req: ChatRequest):
-    messages = [
-        {
-            "role": "system",
-            "content": "Sen ZenkaMind isimli bir yapay zekasın. Sadece Türkçe konuş."
-        }
-    ]
+    try:
+        messages = [
+            {"role": "system", "content": "Sen ZenkaMind isimli, sadece Türkçe konuşan bir asistansın."}
+        ]
 
-    for h in req.history or []:
-        if isinstance(h, list) and len(h) == 2:
-            messages.append({"role": "user", "content": h[0]})
-            messages.append({"role": "assistant", "content": h[1]})
+        for u, a in history:
+            messages.append({"role": "user", "content": u})
+            messages.append({"role": "assistant", "content": a})
 
-    messages.append({"role": "user", "content": req.message})
+        messages.append({"role": "user", "content": message})
 
-    try:
-        out = client.chat_completion(
+        output = client.chat_completion(
             messages=messages,
             max_tokens=300,
-            temperature=0.7,
+            temperature=0.7
         )
 
-        reply = out.choices[0].message.content
-        return {"response": reply}
+        return output.choices[0].message.content
 
     except Exception as e:
-        return {"response": f"Model hatası: {str(e)}"}
+        return f"Hata oluştu: {str(e)}"
 
-# =============================
-# GRADIO UI (HF İÇİN ŞART)
-# =============================
-def demo_chat(msg, history):
-    history = history or []
-    r = client.chat_completion(
-        messages=[
-            {"role": "system", "content": "Türkçe konuş."},
-            {"role": "user", "content": msg},
-        ],
-        max_tokens=200,
-    )
-    answer = r.choices[0].message.content
-    history.append((msg, answer))
-    return history, history
-
-with gr.Blocks() as demo:
-    gr.Markdown("# 🤖 ZenkaMind – Test Sunucusu")
-    chatbot = gr.Chatbot()
-    inp = gr.Textbox(placeholder="Mesaj yaz...")
-    inp.submit(demo_chat, [inp, chatbot], [chatbot, chatbot])
+demo = gr.ChatInterface(
+    fn=chat_fn,
+    title="ZenkaMind API Test",
+    description="Bu ekran sadece backend test içindir."
+)
 
-# ⚠️ HF BURAYI ÇALIŞTIRIR
-app = gr.mount_gradio_app(app, demo, path="/")
+demo.launch()