APIs

API reference: pe.api package

pe.api.API is responsible for implementing the foundation model APIs. It has the following key methods:

• pe.api.API.random_api(): Randomly generates the synthetic samples for the initial samples of the Private Evolution algorithm.

• pe.api.API.variation_api(): Generates the variations of the given synthetic samples for the initial or the next Private Evolution iteration.

Available APIs

Currently, the following APIs are implemented:

• Images

  • pe.api.StableDiffusion: The APIs of Stable Diffusion (introduced in [1]).

  • pe.api.ImprovedDiffusion: The APIs of the improved diffusion model (introduced in [1]).

  • pe.api.DrawText: The APIs that render text on images (introduced in [3]).

  • pe.api.Avatar: The APIs that generate avatars using the Python Avatars library (introduced in [3]).

  • pe.api.NearestImage: The APIs that utilize a static image dataset (introduced in [3]).

• Text

  • pe.api.LLMAugPE: The APIs for text generation using LLMs (introduced in [2]). When constructing the instance of this API, an LLM instance is required. The LLM instances follow the interface of pe.llm.LLM. Currently, the following LLMs are implemented:

    • pe.llm.OpenAILLM: The LLMs from OpenAI APIs.

    • pe.llm.AzureOpenAILLM: The LLMs from Azure OpenAI APIs.

    • pe.llm.HuggingfaceLLM: The open-source LLMs from Huggingface.

Adding Your Own APIs

To add your own APIs, you need to create a class that inherits from pe.api.API and implements the pe.api.API.random_api() and pe.api.API.variation_api() methods.

Citations

[1] (1,2)

Differentially Private Synthetic Data via Foundation Model APIs 1: Images (ICLR 2024).

[2]

Differentially Private Synthetic Data via Foundation Model APIs 2: Text (ICML 2024 Spotlight).

[3] (1,2,3)

Differentially Private Synthetic Data via APIs 3: Using Simulators Instead of Foundation Models.