Create main.py

main.py

@@ -0,0 +1,55 @@
+import os
+import tempfile
+from fastapi import FastAPI, File, UploadFile, Form
+from fastapi.responses import JSONResponse
+from gradio_client import Client, handle_file
+from deep_translator import GoogleTranslator
+
+app = FastAPI()
+
+HF_TOKEN = os.getenv("HF_TOKEN")
+if not HF_TOKEN:
+    raise ValueError("HF_TOKEN environment variable is not set.")
+
+try:
+    client = Client("Luisgust/moondream1", hf_token=HF_TOKEN)
+except Exception as e:
+    print(f"Failed to initialize Gradio client: {e}")
+    raise
+
+@app.post("/get_caption")
+async def get_caption(image: UploadFile = File(...), context: str = Form(...)):
+    try:
+        # Create a temporary file
+        with tempfile.NamedTemporaryFile(delete=False) as temp_file:
+            # Write the uploaded file contents to the temp file
+            contents = await image.read()
+            temp_file.write(contents)
+            temp_file_path = temp_file.name
+
+        # Use the temporary file path with handle_file or any other processing
+        image_data = handle_file(temp_file_path)
+
+        # Call the Gradio API to get the description
+        description = client.predict(
+            image=image_data,
+            question=context,
+            api_name="/answer_question"
+        )
+
+        # Translate the description to Arabic
+        translator = GoogleTranslator(source='auto', target='ar')
+        translated_description = translator.translate(description)
+
+        # Return the translated result as a JSON response
+        return JSONResponse(content={"caption": translated_description})
+
+    except Exception as e:
+        print(f"Error during prediction: {e}")
+        return JSONResponse(content={"error": str(e)}, status_code=500)
+
+    finally:
+        # Remove the temporary file
+        if os.path.exists(temp_file_path):
+            os.remove(temp_file_path)
+