Update app.py
Browse files
app.py
CHANGED
@@ -1,10 +1,11 @@
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from fastapi import FastAPI, HTTPException
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from huggingface_hub import
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import os
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import shutil
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import asyncio
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from concurrent.futures import ThreadPoolExecutor
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from dotenv import load_dotenv
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# Load environment variables from .env file
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load_dotenv()
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@@ -14,38 +15,71 @@ app = FastAPI(title="Hugging Face Model Transfer Service", version="1.0.0")
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# Thread pool for running blocking operations
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executor = ThreadPoolExecutor(max_workers=2)
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#
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os.makedirs(DOWNLOAD_DIR, exist_ok=True)
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# Hardcoded model repository ID
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HARDCODED_MODEL_REPO_ID = "
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# Hardcoded dataset repository ID
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HARDCODED_DATASET_REPO_ID = "
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# Hardcoded path in repository
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HARDCODED_PATH_IN_REPO = "
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"
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try:
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token=HF_TOKEN
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)
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except Exception as e:
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print(f"Download failed: {str(e)}")
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raise
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@@ -59,46 +93,55 @@ def upload_folder_to_dataset(folder_path: str):
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path_in_repo=HARDCODED_PATH_IN_REPO,
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repo_id=HARDCODED_DATASET_REPO_ID,
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repo_type="dataset",
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)
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print("Upload complete!")
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except Exception as e:
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print(f"Upload failed: {str(e)}")
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raise
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def cleanup_download(
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"""Clean up downloaded files."""
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try:
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if os.path.exists(
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shutil.rmtree(
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print(f"Cleaned up: {
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except Exception as e:
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print(f"Cleanup failed: {str(e)}")
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async def transfer_model():
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"""Download the hardcoded model and upload it to the hardcoded dataset repository."""
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try:
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# Download the model
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loop = asyncio.get_event_loop()
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executor,
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)
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# Upload to dataset
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await loop.run_in_executor(
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executor,
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upload_folder_to_dataset,
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)
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# Clean up downloaded files
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cleanup_download(local_dir)
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print(f"Model {HARDCODED_MODEL_REPO_ID} transferred successfully to {HARDCODED_DATASET_REPO_ID}")
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except Exception as e:
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print(f"Transfer failed: {str(e)}")
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raise
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@app.get("/")
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async def root():
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@@ -117,19 +160,13 @@ async def startup_event():
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@app.get("/status")
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async def get_status():
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"""Get server status
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try:
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disk_usage = shutil.disk_usage(DOWNLOAD_DIR)
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return {
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"status": "healthy",
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"download_dir": DOWNLOAD_DIR,
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"disk_space": {
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"total": disk_usage.total,
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"used": disk_usage.used,
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"free": disk_usage.free
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},
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"model": HARDCODED_MODEL_REPO_ID,
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"dataset": HARDCODED_DATASET_REPO_ID
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}
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except Exception as e:
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raise HTTPException(status_code=500, detail=f"Status check failed: {str(e)}")
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from fastapi import FastAPI, HTTPException
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from huggingface_hub import HfApi, hf_hub_download, list_repo_files
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import os
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import shutil
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import asyncio
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from concurrent.futures import ThreadPoolExecutor
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from dotenv import load_dotenv
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import tempfile
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# Load environment variables from .env file
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load_dotenv()
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# Thread pool for running blocking operations
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executor = ThreadPoolExecutor(max_workers=2)
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# Get Hugging Face token from environment variable
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HF_TOKEN = os.getenv("HUGGINGFACE_HUB_TOKEN")
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if not HF_TOKEN:
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raise ValueError("HUGGINGFACE_HUB_TOKEN environment variable is not set")
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# Hardcoded model repository ID
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HARDCODED_MODEL_REPO_ID = "bert-base-uncased" # Change this to your desired model
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# Hardcoded dataset repository ID
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HARDCODED_DATASET_REPO_ID = "your-username/your-dataset-name" # Change this to your dataset
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# Hardcoded path in repository
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HARDCODED_PATH_IN_REPO = "model_data/"
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def download_model_files() -> str:
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"""Download all files from a model repository to a temporary directory."""
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print(f"Downloading all files from model {HARDCODED_MODEL_REPO_ID}...")
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# Create a temporary directory for the downloaded files
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temp_dir = tempfile.mkdtemp(prefix="hf_model_")
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print(f"Created temporary directory: {temp_dir}")
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try:
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# Get list of all files in the repository
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api = HfApi(token=HF_TOKEN)
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files = list_repo_files(
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repo_id=HARDCODED_MODEL_REPO_ID,
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repo_type="model",
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token=HF_TOKEN
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)
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print(f"Found {len(files)} files to download")
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# Download each file
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for file_path in files:
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if file_path.endswith('/'): # Skip directories
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continue
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print(f"Downloading: {file_path}")
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# Create subdirectories if needed
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file_dir = os.path.join(temp_dir, os.path.dirname(file_path))
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os.makedirs(file_dir, exist_ok=True)
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# Download the file
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local_path = hf_hub_download(
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repo_id=HARDCODED_MODEL_REPO_ID,
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filename=file_path,
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cache_dir=temp_dir,
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force_download=True,
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resume_download=False,
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token=HF_TOKEN
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)
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# Move from cache to the desired location
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final_path = os.path.join(temp_dir, file_path)
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if local_path != final_path:
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shutil.move(local_path, final_path)
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print(f"All files downloaded to: {temp_dir}")
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return temp_dir
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except Exception as e:
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# Clean up on error
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shutil.rmtree(temp_dir, ignore_errors=True)
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print(f"Download failed: {str(e)}")
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raise
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path_in_repo=HARDCODED_PATH_IN_REPO,
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repo_id=HARDCODED_DATASET_REPO_ID,
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repo_type="dataset",
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token=HF_TOKEN
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)
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print("Upload complete!")
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except Exception as e:
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print(f"Upload failed: {str(e)}")
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raise
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def cleanup_download(temp_dir: str):
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"""Clean up downloaded files."""
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try:
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if os.path.exists(temp_dir):
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shutil.rmtree(temp_dir)
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print(f"Cleaned up temporary directory: {temp_dir}")
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except Exception as e:
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print(f"Cleanup failed: {str(e)}")
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async def transfer_model():
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"""Download the hardcoded model and upload it to the hardcoded dataset repository."""
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temp_dir = None
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try:
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# Download the model files
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loop = asyncio.get_event_loop()
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temp_dir = await loop.run_in_executor(
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executor,
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download_model_files
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)
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# Verify files were downloaded
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if not os.listdir(temp_dir):
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raise Exception("No files were downloaded")
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print(f"Downloaded files: {os.listdir(temp_dir)}")
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# Upload to dataset
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await loop.run_in_executor(
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executor,
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upload_folder_to_dataset,
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temp_dir
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)
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print(f"Model {HARDCODED_MODEL_REPO_ID} transferred successfully to {HARDCODED_DATASET_REPO_ID}")
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except Exception as e:
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print(f"Transfer failed: {str(e)}")
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raise
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finally:
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# Clean up downloaded files
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if temp_dir:
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cleanup_download(temp_dir)
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@app.get("/")
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async def root():
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@app.get("/status")
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async def get_status():
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"""Get server status."""
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try:
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return {
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"status": "healthy",
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"model": HARDCODED_MODEL_REPO_ID,
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"dataset": HARDCODED_DATASET_REPO_ID,
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"path_in_repo": HARDCODED_PATH_IN_REPO
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}
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except Exception as e:
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raise HTTPException(status_code=500, detail=f"Status check failed: {str(e)}")
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