---
title: drewster99/swift-llm-kit
framework: Swift Package Catalog
role: article
path: packages/drewster99/swift-llm-kit
---

# drewster99/swift-llm-kit

A Swift package for talking to many LLM providers through one interface. It

## Supported providers

Each provider below ships as a built-in preset with a stable ID and a fixed endpoint. Any other OpenAI-compatible backend can be added as a custom provider.

| Provider | Built-in ID | Notes | |---|---|---| | Anthropic (Claude) | `builtin.anthropic` | Native Messages API, prompt caching, adaptive and extended thinking | | OpenAI | `builtin.openai` | | | ChatGPT subscription (Codex) | `builtin.codex-chatgpt` | Signs in with the Codex CLI's `~/.codex/auth.json`, not an API key | | Google Gemini | `builtin.gemini` | Native `generateContent` API | | xAI (Grok) | `builtin.xai` | | | DeepSeek | `builtin.deepseek` | | | Moonshot AI (Kimi) | `builtin.moonshot` | | | z.ai | `builtin.zai`, `builtin.zai-coding` | General and coding endpoints | | Meta Model API | `builtin.meta-model-api` | | | Mistral | `builtin.mistral` | | | Alibaba Cloud (DashScope) | `builtin.alibabacloud`, `-beijing`, `-singapore` | US, Beijing, Singapore regions | | Hugging Face | `builtin.huggingface` | Inference router | | OpenRouter | `builtin.openrouter` | | | Ollama | `builtin.ollama`, `builtin.ollama-cloud` | Local or cloud | | LM Studio | `builtin.lmstudio` | Local |

## Features

- **One `LLMProvider` interface.** Every backend implements `send(messages:tools:)`, so your app doesn't need to know which vendor is answering. - **Tool calling.** Tools, tool calls, and tool results work the same way on every provider, with per-call `LLMToolChoice` (`auto`, `required`, `textOnly`, or one specific tool) and optional `strict` schemas. - **Reasoning and effort, modeled correctly.** Anthropic's general `effort` and OpenAI's `reasoning_effort` are kept as separate settings, and so are thinking budgets and on/off switches. Each is sent only to models known to accept it, so an unsupported parameter never causes an HTTP 400. - **Structured output.** `LLMResponseFormat` covers JSON-object and JSON-schema modes. - **Multimodal input.** Images and PDF documents are attached to messages. - **A model catalog that knows capabilities.** It combines each provider's `/models` listing, bundled metadata, [LiteLLM](https://github.com/BerriAI/litellm) data, and your own overrides, in a fixed priority order. - **Capability probing.** `ModelProber` measures what an endpoint really accepts (thinking-budget ranges, effort levels, tool choice, structured output) instead of trusting documentation. - **Keychain-backed API keys.** Keys never live in UserDefaults or plain files. - **SwiftUI-ready settings.** `LLMKitManager` is `@Observable @MainActor`, so providers, models, and configurations bind directly to views. - **Prompt caching.** Supports Anthropic's ephemeral cache (5 min or 1 h) and reports cached-input tokens from OpenAI and xAI. Request bodies are serialized deterministically, so provider-side caches keep hitting.

## Requirements

- macOS 15 or newer - Swift 6.1 or newer (Xcode 16.4+)

iOS and visionOS support is [on the wish list](https://github.com/drewster99/swift-llm-kit/issues?q=is%3Aissue+is%3Aopen+iOS), and contributions are welcome.

## Installation

```swift .package(url: "https://github.com/drewster99/swift-llm-kit", from: "0.0.210") ```

Then add the product to your target:

```swift .product(name: "SwiftLLMKit", package: "swift-llm-kit") ```

## Quick start

```swift import SwiftLLMKit

@MainActor func hello(apiKey: String) async throws {     let kit = LLMKitManager(         appIdentifier: "com.example.MyApp",         keychainServicePrefix: "com.example.MyApp"     )     kit.load()

// Stored in the Keychain — never in UserDefaults or a plain file.     try kit.setBuiltInProviderAPIKey(id: BuiltInProviders.ID.anthropic, apiKey: apiKey)

await kit.refreshIfNeeded()   // fetches each provider's current model list

let configuration = ModelConfiguration(         name: "Claude Sonnet",         providerID: BuiltInProviders.ID.anthropic,         modelID: "claude-sonnet-5"     )     kit.addConfiguration(configuration)

let provider = try kit.makeProvider(for: configuration.id)     let response = try await provider.send(messages: [.user("Hello!")], tools: [])     print(response.text ?? "") } ```

### Tool calling

```swift let weather = LLMToolDefinition(     name: "get_weather",     description: "Current weather for a city",     parameters: [         "type": .string("object"),         "properties": .dictionary([             "city": .dictionary(["type": .string("string")])         ]),         "required": .array([.string("city")])     ] )

var messages: [LLMMessage] = [.user("What's the weather in Oslo?")] let response = try await provider.send(messages: messages, tools: [weather]) messages.append(.assistant(from: response))

for call in response.toolCalls {     // call.arguments is the model's JSON argument string, e.g. {"city":"Oslo"}     messages.append(.toolResult("12°C, light rain", callID: call.id)) } let answer = try await provider.send(messages: messages, tools: [weather]) print(answer.text ?? "") ```

`.assistant(from:)` carries the provider's reasoning continuation (Anthropic thinking blocks, Gemini thought signatures, Codex reasoning items), so multi-turn tool use keeps working on reasoning models.

## How it fits together

- **`LLMKitManager`** is the central coordinator. It owns providers, model configurations, and the model catalog, and it saves them under Application Support. - **`LLMProvider`** is the per-request protocol, implemented by `AnthropicProvider`, `OpenAICompatibleProvider`, `GeminiProvider`, and `OllamaProvider`, plus an internal Codex Responses adapter that `makeProvider(for:)` returns for the ChatGPT-subscription provider. - **`ModelInfo` / `ModelCapabilities`** record what a model can do. The providers read them to decide which request fields to send. - **`ModelProber`** measures capabilities that no vendor publishes.

[`CLAUDE.md`](CLAUDE.md) explains the design decisions in depth: why effort is two settings, why some knobs fail open and others fail closed, and how probe records are versioned.

## Contributing

Contributions are very welcome. Good places to start:

- [Good first issues](https://github.com/drewster99/swift-llm-kit/issues?q=is%3Aissue+is%3Aopen+label%3A%22good+first+issue%22) are small and self-contained, with pointers to the exact files involved. - [Help wanted](https://github.com/drewster99/swift-llm-kit/issues?q=is%3Aissue+is%3Aopen+label%3A%22help+wanted%22) issues are larger features and improvements. - [ROADMAP.md](ROADMAP.md) has the longer-term plans and the reasoning behind them.

See [CONTRIBUTING.md](CONTRIBUTING.md) for how to build, test, and submit a change.

## Changelog

See [GitHub Releases](https://github.com/drewster99/swift-llm-kit/releases), plus [CHANGELOG.md](CHANGELOG.md) for the historical notes.

## License

MIT. See [LICENSE](LICENSE).

## Package Metadata

Repository: drewster99/swift-llm-kit

Default branch: main

README: README.md