final working version

app.py

@@ -2,7 +2,7 @@ import gradio as gr
 import requests
 import os
 
-# Hugging Face token (Settings → Variables → New Variable → Key: HF_API_KEY)
+# Hugging Face API anahtarını Settings → Variables → HF_API_KEY olarak eklemelisin.
 HF_API_KEY = os.getenv("HF_API_KEY")
 
 def ask_model(prompt):
@@ -12,26 +12,30 @@ def ask_model(prompt):
     }
     data = {"inputs": prompt}
 
-    # ✅ Yeni endpoint — artık sadece bu kullanılacak
+    # ✅ Yeni Hugging Face yönlendirme sistemi
     API_URL = "https://router.huggingface.co/hf-inference/models/mistralai/Mistral-7B-Instruct-v0.2"
 
-    response = requests.post(API_URL, headers=headers, json=data)
+    try:
+        response = requests.post(API_URL, headers=headers, json=data, timeout=60)
 
-    if response.status_code == 200:
-        output = response.json()
-        if isinstance(output, list) and "generated_text" in output[0]:
-            return output[0]["generated_text"]
+        if response.status_code == 200:
+            output = response.json()
+            # Bazı modeller farklı yapıda dönebilir
+            if isinstance(output, list) and "generated_text" in output[0]:
+                return output[0]["generated_text"]
+            else:
+                return str(output)
         else:
-            return str(output)
-    else:
-        return f"Error: {response.status_code} - {response.text}"
+            return f"Error: {response.status_code} - {response.text}"
+    except Exception as e:
+        return f"Hata oluştu: {str(e)}"
 
 iface = gr.Interface(
     fn=ask_model,
-    inputs="text",
-    outputs="text",
+    inputs=gr.Textbox(label="Prompt"),
+    outputs=gr.Textbox(label="Yanıt"),
     title="Flutter AI Proxy",
-    description="Flutter uygulaman buraya istek atacak, model yanıt dönecek."
+    description="Flutter uygulaman buraya istek atacak, model yanıt dönecek.",
 )
 
-iface.launch()
+iface.launch(share=True)