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from __future__ import annotations
import contextlib
import csv
import datetime
from datetime import datetime
import os
import re
import boto3
import botocore
import uuid
import time
from collections.abc import Sequence
from multiprocessing import Lock
from pathlib import Path
from typing import TYPE_CHECKING, Any
from gradio_client import utils as client_utils
import gradio as gr
from gradio import utils, wasm_utils
from tools.config import AWS_REGION, AWS_ACCESS_KEY, AWS_SECRET_KEY, RUN_AWS_FUNCTIONS
from botocore.exceptions import NoCredentialsError, TokenRetrievalError
if TYPE_CHECKING:
from gradio.components import Component
from gradio.flagging import FlaggingCallback
from threading import Lock
class CSVLogger_custom(FlaggingCallback):
"""
The default implementation of the FlaggingCallback abstract class in gradio>=5.0. Each flagged
sample (both the input and output data) is logged to a CSV file with headers on the machine running
the gradio app. Unlike ClassicCSVLogger, this implementation is concurrent-safe and it creates a new
dataset file every time the headers of the CSV (derived from the labels of the components) change. It also
only creates columns for "username" and "flag" if the flag_option and username are provided, respectively.
Example:
import gradio as gr
def image_classifier(inp):
return {'cat': 0.3, 'dog': 0.7}
demo = gr.Interface(fn=image_classifier, inputs="image", outputs="label",
flagging_callback=CSVLogger())
Guides: using-flagging
"""
def __init__(
self,
simplify_file_data: bool = True,
verbose: bool = True,
dataset_file_name: str | None = None,
):
"""
Parameters:
simplify_file_data: If True, the file data will be simplified before being written to the CSV file. If CSVLogger is being used to cache examples, this is set to False to preserve the original FileData class
verbose: If True, prints messages to the console about the dataset file creation
dataset_file_name: The name of the dataset file to be created (should end in ".csv"). If None, the dataset file will be named "dataset1.csv" or the next available number.
"""
self.simplify_file_data = simplify_file_data
self.verbose = verbose
self.dataset_file_name = dataset_file_name
self.lock = (
Lock() if not wasm_utils.IS_WASM else contextlib.nullcontext()
) # The multiprocessing module doesn't work on Lite.
def setup(
self,
components: Sequence[Component],
flagging_dir: str | Path,
):
self.components = components
self.flagging_dir = Path(flagging_dir)
self.first_time = True
def _create_dataset_file(
self,
additional_headers: list[str] | None = None,
replacement_headers: list[str] | None = None
):
os.makedirs(self.flagging_dir, exist_ok=True)
if replacement_headers:
if len(replacement_headers) != len(self.components):
raise ValueError(
f"replacement_headers must have the same length as components "
f"({len(replacement_headers)} provided, {len(self.components)} expected)"
)
headers = replacement_headers + ["timestamp"]
else:
if additional_headers is None:
additional_headers = []
headers = [
getattr(component, "label", None) or f"component {idx}"
for idx, component in enumerate(self.components)
] + additional_headers + ["timestamp"]
headers = utils.sanitize_list_for_csv(headers)
dataset_files = list(Path(self.flagging_dir).glob("dataset*.csv"))
if self.dataset_file_name:
self.dataset_filepath = self.flagging_dir / self.dataset_file_name
elif dataset_files:
try:
latest_file = max(
dataset_files, key=lambda f: int(re.findall(r"\d+", f.stem)[0])
)
latest_num = int(re.findall(r"\d+", latest_file.stem)[0])
with open(latest_file, newline="", encoding="utf-8") as csvfile:
reader = csv.reader(csvfile)
existing_headers = next(reader, None)
if existing_headers != headers:
new_num = latest_num + 1
self.dataset_filepath = self.flagging_dir / f"dataset{new_num}.csv"
else:
self.dataset_filepath = latest_file
except Exception:
self.dataset_filepath = self.flagging_dir / "dataset1.csv"
else:
self.dataset_filepath = self.flagging_dir / "dataset1.csv"
if not Path(self.dataset_filepath).exists():
with open(
self.dataset_filepath, "w", newline="", encoding="utf-8"
) as csvfile:
writer = csv.writer(csvfile)
writer.writerow(utils.sanitize_list_for_csv(headers))
if self.verbose:
print("Created dataset file at:", self.dataset_filepath)
elif self.verbose:
print("Using existing dataset file at:", self.dataset_filepath)
def flag(
self,
flag_data: list[Any],
flag_option: str | None = None,
username: str | None = None,
save_to_csv: bool = True,
save_to_dynamodb: bool = False,
dynamodb_table_name: str | None = None,
dynamodb_headers: list[str] | None = None, # New: specify headers for DynamoDB
replacement_headers: list[str] | None = None
) -> int:
if self.first_time:
additional_headers = []
if flag_option is not None:
additional_headers.append("flag")
if username is not None:
additional_headers.append("username")
additional_headers.append("id")
self._create_dataset_file(additional_headers=additional_headers, replacement_headers=replacement_headers)
self.first_time = False
csv_data = []
for idx, (component, sample) in enumerate(
zip(self.components, flag_data, strict=False)
):
save_dir = (
self.flagging_dir
/ client_utils.strip_invalid_filename_characters(
getattr(component, "label", None) or f"component {idx}"
)
)
if utils.is_prop_update(sample):
csv_data.append(str(sample))
else:
data = (
component.flag(sample, flag_dir=save_dir)
if sample is not None
else ""
)
if self.simplify_file_data:
data = utils.simplify_file_data_in_str(data)
csv_data.append(data)
if flag_option is not None:
csv_data.append(flag_option)
if username is not None:
csv_data.append(username)
timestamp = datetime.now().strftime('%Y-%m-%d %H:%M:%S.%f')[:-3] # Correct format for Amazon Athena
csv_data.append(timestamp)
generated_id = str(uuid.uuid4())
csv_data.append(generated_id)
# Build the headers
headers = (
[getattr(component, "label", None) or f"component {idx}" for idx, component in enumerate(self.components)]
)
if flag_option is not None:
headers.append("flag")
if username is not None:
headers.append("username")
headers.append("timestamp")
headers.append("id")
line_count = -1
if save_to_csv:
with self.lock:
with open(self.dataset_filepath, "a", newline="", encoding="utf-8") as csvfile:
writer = csv.writer(csvfile)
writer.writerow(utils.sanitize_list_for_csv(csv_data))
with open(self.dataset_filepath, encoding="utf-8") as csvfile:
line_count = len(list(csv.reader(csvfile))) - 1
if save_to_dynamodb == True:
if RUN_AWS_FUNCTIONS == "1":
try:
print("Connecting to DynamoDB via existing SSO connection")
dynamodb = boto3.resource('dynamodb', region_name=AWS_REGION)
#client = boto3.client('dynamodb')
test_connection = dynamodb.meta.client.list_tables()
except Exception as e:
print("No SSO credentials found:", e)
if AWS_ACCESS_KEY and AWS_SECRET_KEY:
print("Trying DynamoDB credentials from environment variables")
dynamodb = boto3.resource('dynamodb',aws_access_key_id=AWS_ACCESS_KEY,
aws_secret_access_key=AWS_SECRET_KEY, region_name=AWS_REGION)
# client = boto3.client('dynamodb',aws_access_key_id=AWS_ACCESS_KEY,
# aws_secret_access_key=AWS_SECRET_KEY, region_name=AWS_REGION)
else:
raise Exception("AWS credentials for DynamoDB logging not found")
else:
raise Exception("AWS credentials for DynamoDB logging not found")
if dynamodb_table_name is None:
raise ValueError("You must provide a dynamodb_table_name if save_to_dynamodb is True")
if dynamodb_headers:
dynamodb_headers = dynamodb_headers
if not dynamodb_headers and replacement_headers:
dynamodb_headers = replacement_headers
elif headers:
dynamodb_headers = headers
elif not dynamodb_headers:
raise ValueError("Headers not found. You must provide dynamodb_headers or replacement_headers to create a new table.")
if flag_option is not None:
if "flag" not in dynamodb_headers:
dynamodb_headers.append("flag")
if username is not None:
if "username" not in dynamodb_headers:
dynamodb_headers.append("username")
if "timestamp" not in dynamodb_headers:
dynamodb_headers.append("timestamp")
if "id" not in dynamodb_headers:
dynamodb_headers.append("id")
# Table doesn't exist — create it
try:
table = dynamodb.Table(dynamodb_table_name)
table.load()
except botocore.exceptions.ClientError as e:
if e.response['Error']['Code'] == 'ResourceNotFoundException':
#print(f"Creating DynamoDB table '{dynamodb_table_name}'...")
#print("dynamodb_headers:", dynamodb_headers)
attribute_definitions = [
{'AttributeName': 'id', 'AttributeType': 'S'} # Only define key attributes here
]
table = dynamodb.create_table(
TableName=dynamodb_table_name,
KeySchema=[
{'AttributeName': 'id', 'KeyType': 'HASH'} # Partition key
],
AttributeDefinitions=attribute_definitions,
BillingMode='PAY_PER_REQUEST'
)
# Wait until the table exists
table.meta.client.get_waiter('table_exists').wait(TableName=dynamodb_table_name)
time.sleep(5)
print(f"Table '{dynamodb_table_name}' created successfully.")
else:
raise
# Prepare the DynamoDB item to upload
try:
item = {
'id': str(generated_id), # UUID primary key
#'created_by': username if username else "unknown",
'timestamp': timestamp,
}
#print("dynamodb_headers:", dynamodb_headers)
#print("csv_data:", csv_data)
# Map the headers to values
item.update({header: str(value) for header, value in zip(dynamodb_headers, csv_data)})
#print("item:", item)
table.put_item(Item=item)
print("Successfully uploaded log to DynamoDB")
except Exception as e:
print("Could not upload log to DynamobDB due to", e)
return line_count |