File size: 1,007 Bytes
df4be7c
 
0d4e1bb
df4be7c
0d4e1bb
 
df4be7c
 
0d4e1bb
 
 
d0ff32a
540f212
0d4e1bb
 
d0ff32a
0d4e1bb
d0ff32a
 
0d4e1bb
 
 
 
d0ff32a
0d4e1bb
df4be7c
0d4e1bb
df4be7c
 
0d4e1bb
d0ff32a
df4be7c
d0ff32a
df4be7c
 
d0ff32a
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
import gradio as gr
import requests
import os

# 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(
            "https://router.huggingface.co/hf-inference/mistralai/Mistral-7B-Instruct-v0.2",
        headers=headers,
        json=data
    )

    if response.status_code == 200:
        result = response.json()
        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}"

# Gradio arayüzü
iface = gr.Interface(
    fn=ask_model,
    inputs="text",
    outputs="text",
    title="Flutter AI Proxy",
    description="Flutter uygulaman buraya istek atacak, model yanıt dönecek."
)

iface.launch()