updata2 app.py

app.py

@@ -1,29 +1,33 @@
 import gradio as gr
 import requests
+import os
 
-HF_API_URL = "https://router.huggingface.co/hf-inference"
-MODEL_ID = "meta-llama/Llama-3.2-1B-Instruct"
-HEADERS = {"Authorization": "Bearer HF_API_KEY"}
+# Token environment variable olarak alınır (Settings > Variables'da tanımlandı)
+HF_API_KEY = os.getenv("HF_API_KEY")
 
 def ask_model(prompt):
+    headers = {"Authorization": f"Bearer {HF_API_KEY}"}
+    data = {"inputs": prompt}
+
     response = requests.post(
-        HF_API_URL,
-        headers=HEADERS,
-        json={
-            "model": MODEL_ID,
-            "inputs": prompt,
-            "parameters": {"max_new_tokens": 200},
-        },
+        "https://router.huggingface.co/hf-inference/models/mistralai/Mistral-7B-Instruct-v0.2",
+        headers=headers,
+        json=data
     )
+
     if response.status_code == 200:
         result = response.json()
-        return result[0]["generated_text"]
+        if isinstance(result, list) and len(result) > 0 and "generated_text" in result[0]:
+            return result[0]["generated_text"]
+        else:
+            return str(result)
     else:
-        return f"Error {response.status_code}: {response.text}"
+        return f"Error: {response.status_code} - {response.text}"
 
+# Gradio arayüzü
 iface = gr.Interface(
     fn=ask_model,
-    inputs=gr.Textbox(label="prompt"),
+    inputs="text",
     outputs="text",
     title="Flutter AI Proxy",
     description="Flutter uygulaman buraya istek atacak, model yanıt dönecek."