Method Signature
client.files.delete(
file_id: str
) -> FileDeleted
Parameters
The ID of the file to delete.
Response
Returns a FileDeleted object:
class FileDeleted(BaseModel):
id: str # The ID of the deleted file
deleted: bool # Whether the file was successfully deleted
object: Literal["file"] # Always "file"
Examples
Delete a File
from openai import OpenAI
client = OpenAI()
response = client.files.delete("file-abc123")
if response.deleted:
print(f"File {response.id} deleted successfully")
else:
print("File deletion failed")
Delete and Verify
from openai import NotFoundError
file_id = "file-abc123"
# Delete the file
response = client.files.delete(file_id)
print(f"Deleted: {response.deleted}")
# Verify deletion
try:
client.files.retrieve(file_id)
print("File still exists!")
except NotFoundError:
print("File successfully removed")
Delete Multiple Files
file_ids = ["file-abc123", "file-def456", "file-ghi789"]
for file_id in file_ids:
try:
response = client.files.delete(file_id)
if response.deleted:
print(f"✓ Deleted {file_id}")
else:
print(f"✗ Failed to delete {file_id}")
except Exception as e:
print(f"✗ Error deleting {file_id}: {e}")
Delete Old Files
from datetime import datetime, timedelta
# Get all files
files = client.files.list()
# Delete files older than 30 days
thirty_days_ago = datetime.now() - timedelta(days=30)
for file in files:
file_date = datetime.fromtimestamp(file.created_at)
if file_date < thirty_days_ago:
response = client.files.delete(file.id)
print(f"Deleted old file: {file.filename}")
Delete Files by Purpose
# Delete all batch files
batch_files = client.files.list(purpose="batch")
for file in batch_files:
response = client.files.delete(file.id)
print(f"Deleted batch file: {file.filename}")
Async Usage
from openai import AsyncOpenAI
client = AsyncOpenAI()
response = await client.files.delete("file-abc123")
print(f"Deleted: {response.deleted}")
Delete Multiple Files Concurrently
import asyncio
from openai import AsyncOpenAI
client = AsyncOpenAI()
async def delete_files(file_ids):
tasks = [client.files.delete(fid) for fid in file_ids]
results = await asyncio.gather(*tasks, return_exceptions=True)
for file_id, result in zip(file_ids, results):
if isinstance(result, Exception):
print(f"Error deleting {file_id}: {result}")
elif result.deleted:
print(f"Deleted {file_id}")
file_ids = ["file-abc123", "file-def456", "file-ghi789"]
await delete_files(file_ids)
Error Handling
from openai import OpenAI, NotFoundError, APIError
client = OpenAI()
try:
response = client.files.delete("file-abc123")
print(f"File deleted: {response.deleted}")
except NotFoundError:
print("File not found or already deleted")
except APIError as e:
print(f"API error: {e}")
except Exception as e:
print(f"Unexpected error: {e}")
Important Notes
- Vector Store Removal: Deleting a file removes it from all vector stores where it’s being used
- Irreversible: File deletion cannot be undone
- Fine-tuning Jobs: Deleting a training file does not affect fine-tuning jobs that have already completed
- Active Jobs: Be cautious when deleting files that may be in use by active jobs
- Batch Files: Files with
purpose=batch may auto-expire, so manual deletion might not be necessary
Best Practices
-
Check before deleting: Always verify the file details before deletion
file = client.files.retrieve("file-abc123")
print(f"About to delete: {file.filename} ({file.purpose})")
# Confirm before proceeding
response = client.files.delete(file.id)
-
Clean up expired files: Delete expired batch files to free up storage
from datetime import datetime
files = client.files.list()
now = datetime.now().timestamp()
for file in files:
if file.expires_at and file.expires_at < now:
client.files.delete(file.id)
-
Log deletions: Keep track of deleted files for audit purposes
import logging
logger = logging.getLogger(__name__)
response = client.files.delete(file_id)
logger.info(f"Deleted file {file_id}: {response.deleted}")
