MacPaw/OpenAI

Features

• OpenAI API Clients - Provides an asynchronous Swift client for calling OpenAI's API across Apple platforms.
• Streaming Chat Responses - Generates text responses from a language model with optional real-time token-by-token output.
• Assistant Management APIs - Creates and manages assistants, threads, messages, and runs in conversational workflows.
• Assistant Thread Runners - Starts a new thread and immediately processes it with an assistant.
• Chat Completion Services - Sends prompts and conversation history to language models and returns generated text responses.
• Conversational AI Assistants - Creates and manages AI assistants with threads, messages, and tool execution for conversational workflows.
• API Speech Synthesizers - Generates audible speech from a text string using a specified voice and audio format.
• Image Generation - Creates new images from text descriptions using a generative AI model.
• Conversation Threads - Manages assistant conversations as persistent threads with sequential message and run state tracking.
• Multimodal Content Generators - Creates images, synthesizes speech, and transcribes or translates audio using generative AI models.
• Prompt-Based Text Generation - Sends a text prompt to a language model and returns the generated text response.
• Image Description Generators - Creates new images based on textual descriptions using a DALL-E model.
• Unified Audio Transcription - Converts spoken audio into written text, supporting multiple languages and formats.
• Streaming Text Generation - Delivers generated text tokens incrementally as the model produces them for real-time display.
• Multimodal Clients - Generates images, synthesizes speech, transcribes audio, and computes text embeddings.
• API Speech Synthesizers - Converts a text string into spoken audio using a specified voice and format.
• LLM Schema Outputs - Specifies a JSON schema to constrain the format of a model's text response for reliable parsing.
• Schema-Constrained Outputs - Provides structured output generation by constraining model responses to a provided JSON schema.
• Schema-Constrained Sampling - Forces the model to return structured data that conforms to a provided JSON schema.
• Streaming Response Architectures - Delivers incremental tokens or audio chunks via an AsyncSequence for real-time consumption.
• Incremental Response Clients - Receives generated text tokens incrementally as the model produces them for real-time display.
• Model Context Protocol - Connects external tools and data sources through a standardized Model Context Protocol interface.
• Assistant Configuration Updates - Modifies the configuration of an existing AI assistant, such as its model or instructions.
• Assistant Creations - Configures new AI assistants with a model, instructions, and tools for conversational tasks.
• Assistant File Uploads - Uploads files, such as PDFs, to be used by an AI assistant as a knowledge source.
• MCP Protocol Integrations - Integrates external tools and data sources through the Model Context Protocol.
• Function Calling Interfaces - Invokes callable functions that a model can execute during a chat completion.
• Image Variation and Mixing - Generates new images as variations of a provided source image using a generative AI model.
• Message Management - Retrieves all messages belonging to a specific conversation thread for review or processing.
• Speech-to-Text Translation - Translates spoken audio from any language into English text.
• Structured Output Generators - Constrains model responses to conform to a provided JSON schema for reliable programmatic parsing.
• Text Embedding Generators - Converts a text input into a vector representation for use in machine learning tasks.
• Text Embeddings - Converts text into numerical vectors for semantic search, clustering, or similarity comparison tasks.
• Streaming Speech Outputs - Delivers synthesized speech audio data in chunks as it is generated.
• Vector Embeddings - Converts text into numerical vectors using an embedding model for similarity search and clustering.
• Tool Output Submissions - Provides the results of a tool call back to the assistant so it can continue processing.
• Image Editing - Modifies existing images by applying changes described in a text prompt.
• Run Status Inspections - Fetches the current state and details of a specific assistant run for monitoring progress.
• Mask-Guided Image Editors - Edits images by applying a prompt to areas specified by a mask.
• Message Appending APIs - Provides an API to add new messages to an existing conversation thread for assistant workflows.
• Remote Tool Integrations - Connects to external data sources and services via the Model Context Protocol to extend model capabilities.
• Content Moderation - Checks text against a content policy and returns category-specific violation scores.
• Content Moderation Policies - Classifies input text to determine if it violates a defined content policy.
• Response Structure Standardization - Creates AI-powered responses with configurable input and output schemas for programmatic use.
• AI and Machine Learning - Client library for interacting with public generative AI APIs.
• Development Packages - API client for AI services.

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