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app.py

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+from dotenv import load_dotenv
+load_dotenv()
+
+import gradio as gr
+import requests
+
+API_URL = "https://api-inference.huggingface.co/models/microsoft/conditional-image-captioning"
+import os
+HEADERS = {"Authorization": f"Bearer {os.getenv('HF_TOKEN')}"}
+
+
+def predict_caption(image):
+    try:
+        response = requests.post(
+            API_URL,
+            headers=HEADERS,
+            json={"inputs": image}
+        )
+        result = response.json()
+        return result[0]["generated_text"] if isinstance(result, list) else str(result)
+    except Exception as e:
+        return f"Hata oluştu: {str(e)}"
+
+demo = gr.Interface(
+    fn=predict_caption,
+    inputs=gr.Image(type="filepath"),
+    outputs="text",
+    title="Resim Açıklayıcı Proxy",
+    description="Bu Gradio arayüzü Hugging Face üzerinden resim açıklaması üretir."
+)
+
+demo.launch()
+

requirements.txt

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+gradio
+requests
+python-dotenv
+