typegpt-moderation 1.0.1

A client library for the TypeGPT Multimodal Moderation API.

TypeGPT Moderation Client

A simple and powerful Python client for the TypeGPT Multimodal Moderation API.

This library provides an easy-to-use interface to moderate various types of content—text, images, videos, and voice—by communicating with the deployed API at http://mono.typegpt.net.

Key Features

• Truly Multimodal: Moderate text, images, videos, and voice audio in a single API call.
• Flexible Inputs: Provide content via local file paths, public URLs, or raw in-memory bytes.
• Simple Interface: A clean and intuitive client that can be used as a context manager.
• Typed Responses: API responses are parsed into Pydantic models for easy and reliable access to data.
• Robust Error Handling: Catches API and network errors, raising a custom ModerationAPIError with details.

Installation

Install the library directly from PyPI using pip:

pip install typegpt-moderation

This will also install the required dependencies: httpx and pydantic.

Quickstart

Get started in just a few lines of code. The primary interface is the ModerationClient.

from typegpt_moderation import ModerationClient, ModerationAPIError

# It is recommended to use the client as a context manager
try:
    with ModerationClient() as client:
        # 1. Send content for moderation
        response = client.moderate(text="This is a test to see if the content is safe.")
        
        # 2. The API returns a response object containing a list of results
        result = response.results[0]
        
        # 3. Check the results
        if result.flagged:
            print("❌ Content was flagged as unsafe.")
            print(f"   Reason: {result.reason}")
            
            # See which specific categories were violated
            violated_categories = [cat for cat, flagged in result.categories.items() if flagged]
            print(f"   Categories: {violated_categories}")
        else:
            print("✅ Content is safe.")

except ModerationAPIError as e:
    print(f"An API error occurred: Status {e.status_code} - {e.detail}")
except Exception as e:
    print(f"An unexpected error occurred: {e}")

Usage Examples

The moderate() method can handle any combination of text, image, video, or voice.

1. Moderating Text

You can provide a single string or a list of strings.

with ModerationClient() as client:
    response = client.moderate(text="This is a simple text moderation request.")
    print(f"Flagged: {response.results[0].flagged}")

2. Moderating an Image

Provide a local file path or a public URL. The library handles the encoding.

with ModerationClient() as client:
    # From a local file
    response_from_file = client.moderate(image="/path/to/your/image.jpg")
    print(f"Image file flagged: {response_from_file.results[0].flagged}")

    # From a URL
    response_from_url = client.moderate(image="https://www.example.com/some-image.png")
    print(f"Image URL flagged: {response_from_url.results[0].flagged}")

3. Moderating a Video

Just like images, you can use a local file path or a public URL for videos.

with ModerationClient() as client:
    # From a local file
    response = client.moderate(video="/path/to/local/video.mp4")
    print(f"Video flagged: {response.results[0].flagged}")

4. Moderating Voice Audio

The API will transcribe the audio and moderate the resulting text.

with ModerationClient() as client:
    response = client.moderate(voice="/path/to/audio/note.mp3")
    result = response.results[0]
    
    print(f"Voice note flagged: {result.flagged}")
    
    # You can access the transcribed text from the result
    if result.transcribed_text:
        print(f"Transcribed Text: '{result.transcribed_text}'")

5. Multimodal Moderation (Combined Inputs)

The true power of the library is combining inputs. The API analyzes all provided content together for a single, holistic moderation result.

with ModerationClient() as client:
    response = client.moderate(
        text="Please review the attached media and voice note from the user.",
        image="/path/to/user_avatar.png",
        video="/path/to/user_post.mp4",
        voice="/path/to/user_voice_message.wav"
    )
    
    result = response.results[0]
    print(f"Overall content flagged: {result.flagged}")
    if result.flagged:
        print(f"Reason: {result.reason}")

API Reference

ModerationClient

The main class for interacting with the API.

• __init__(self, base_url="http://mono.typegpt.net", timeout=180)
  • base_url: The base URL of the moderation service.
  • timeout: Request timeout in seconds.

moderate() method

• moderate(self, text=None, image=None, video=None, voice=None, ...)
  • text (Optional[Union[str, List[str]]]): A string or list of strings to moderate.
  • image (Optional[Union[str, bytes]]): A URL, local file path, or raw bytes for an image.
  • video (Optional[Union[str, bytes]]): A URL, local file path, or raw bytes for a video.
  • voice (Optional[Union[str, bytes]]): A URL, local file path, or raw bytes for an audio file.
  • Returns: A ModerationResponse object.

Response Objects

Your results are returned as Pydantic models.

• ModerationResponse: The top-level response object.

  • id (str): A unique ID for the moderation request.
  • model (str): The model used for moderation.
  • results (List[ModerationResultItem]): A list containing the moderation result.

• ModerationResultItem: Contains the detailed moderation verdict.

  • flagged (bool): True if the content is unsafe, otherwise False.
  • moderation_type (str): Indicates which modalities were moderated (e.g., text_and_image).
  • categories (Dict[str, bool]): A dictionary of safety categories and whether they were violated.
  • category_scores (Dict[str, float]): A dictionary of scores for each category.
  • reason (Optional[str]): A human-readable explanation if the content was flagged.
  • transcribed_text (Optional[str]): The text transcribed from a provided voice file.

License

This project is licensed under the MIT License.