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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)
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