LLMChatAnthropic

以一种简单优雅的方式与 Anthropic 和 Anthropic 兼容的聊天完成 API 进行交互。

概述

LLMChatAnthropic 是一个简单而强大的 Swift 包，它优雅地封装了与 Anthropic 和 Anthropic 兼容的聊天完成 API 交互的复杂性。它提供了一套完整的 Swift 风格的方法，用于发送聊天完成请求和流式传输响应。

安装

您可以使用 Swift Package Manager 将 LLMChatAnthropic 添加为项目的依赖项，方法是将其添加到 Package.swift 的 dependencies 值中。

dependencies: [
    .package(url: "https://github.com/kevinhermawan/swift-llm-chat-anthropic.git", .upToNextMajor(from: "1.0.0"))
],
targets: [
    .target(
        /// ...
        dependencies: [.product(name: "LLMChatAnthropic", package: "swift-llm-chat-anthropic")])
]

或者，在 Xcode 中

在 Xcode 中打开您的项目。
点击 File -> Swift Packages -> Add Package Dependency...
输入仓库 URL：https://github.com/kevinhermawan/swift-llm-chat-anthropic.git
选择您要添加的版本。您可能想要添加最新版本。
点击 Add Package。

文档

您可以在这里找到文档：https://kevinhermawan.github.io/swift-llm-chat-anthropic/documentation/llmchatanthropic

用法

初始化

import LLMChatAnthropic

// Basic initialization
let chat = LLMChatAnthropic(apiKey: "<YOUR_ANTHROPIC_API_KEY>")

// Initialize with custom endpoint and headers
let chat = LLMChatAnthropic(
    apiKey: "<YOUR_API_KEY>",
    endpoint: URL(string: "https://custom-api.example.com/v1/messages")!,
    headers: ["Custom-Header": "Value"]
)

发送聊天完成请求

let messages = [
    ChatMessage(role: .system, content: "You are a helpful assistant."),
    ChatMessage(role: .user, content: "What is the capital of Indonesia?")
]

let task = Task {
    do {
        let completion = try await chat.send(model: "claude-3-5-sonnet", messages: messages)

        print(completion.content.first?.text ?? "No response")
    } catch {
        print(String(describing: error))
    }
}

// To cancel completion
task.cancel()

流式传输聊天完成响应

let messages = [
    ChatMessage(role: .system, content: "You are a helpful assistant."),
    ChatMessage(role: .user, content: "What is the capital of Indonesia?")
]

let task = Task {
    do {
        for try await chunk in chat.stream(model: "claude-3-5-sonnet", messages: messages) {
            if let text = chunk.delta?.text {
                print(text, terminator: "")
            }
        }
    } catch {
        print(String(describing: error))
    }
}

// To cancel completion
task.cancel()

高级用法

视觉

let messages = [
    ChatMessage(
        role: .user,
        content: [
            .image("https://images.pexels.com/photos/45201/kitty-cat-kitten-pet-45201.jpeg"), // Also supports base64 strings
            .text("What is in this image?")
        ]
    )
]

Task {
    do {
        let completion = try await chat.send(model: "claude-3-5-sonnet", messages: messages)

        print(completion.content.first?.text ?? "")
    } catch {
        print(String(describing: error))
    }
}

要了解有关视觉的更多信息，请查看 Anthropic 文档。

工具使用

let messages = [
    ChatMessage(role: .user, content: "Recommend a book similar to '1984'")
]

let recommendBookTool = ChatOptions.Tool(
    name: "recommend_book",
    description: "Recommend a book based on a given book and genre",
    parameters: .object(
        properties: [
            "reference_book": .string(description: "The name of a book the user likes"),
            "genre": .enum(
                description: "The preferred genre for the book recommendation",
                values: [.string("fiction"), .string("non-fiction")]
            )
        ],
        required: ["reference_book", "genre"],
        additionalProperties: .boolean(false)
    )
)

let options = ChatOptions(tools: [recommendBookTool])

Task {
    do {
        let completion = try await chat.send(model: "claude-3-5-sonnet", messages: messages, options: options)

        if let toolInput = completion.content.first(where: { $0.type == "tool_use" })?.toolInput {
            print(toolInput)
       }
    } catch {
        print(String(describing: error))
    }
}

要了解有关工具使用的更多信息，请查看 Anthropic 文档。

提示缓存（Beta 版）

let chat = LLMChatAnthropic(
    apiKey: "<YOUR_ANTHROPIC_API_KEY>",
    headers: ["anthropic-beta": "prompt-caching-2024-07-31"] // Required
)

let messages = [
    ChatMessage(role: .system, content: "<YOUR_LONG_PROMPT>", cacheControl: .init(type: .ephemeral)),
    ChatMessage(role: .user, content: "What is the capital of Indonesia?")
]

let task = Task {
    do {
        let completion = try await chat.send(model: "claude-3-5-sonnet", messages: messages)

        print(completion.content.first?.text ?? "No response")
    } catch {
        print(String(describing: error))
    }
}

要了解有关提示缓存的更多信息，请查看 Anthropic 文档。

PDF 支持（Beta 版）

let chat = LLMChatAnthropic(
    apiKey: "<YOUR_ANTHROPIC_API_KEY>",
    headers: ["anthropic-beta": "pdfs-2024-09-25"] // Required
)

let messages = [
    ChatMessage(role: .user, content: [.text("Explain this document"), .document(document)])
]

let task = Task {
    do {
        let completion = try await chat.send(model: "claude-3-5-sonnet", messages: messages)

        print(completion.content.first?.text ?? "No response")
    } catch {
        print(String(describing: error))
    }
}

要了解有关 PDF 支持的更多信息，请查看 Anthropic 文档。

错误处理

LLMChatAnthropic 通过 LLMChatAnthropicError 枚举提供结构化的错误处理。此枚举包含三种情况，代表您可能遇到的不同类型的错误

let messages = [
    ChatMessage(role: .system, content: "You are a helpful assistant."),
    ChatMessage(role: .user, content: "What is the capital of Indonesia?")
]

do {
    let completion = try await chat.send(model: "claude-3-5-sonnet", messages: messages)

    print(completion.content.first?.text ?? "No response")
} catch let error as LLMChatAnthropicError {
    switch error {
    case .serverError(let statusCode, let message):
        // Handle server-side errors (e.g., invalid API key, rate limits)
        print("Server Error [\(statusCode)]: \(message)")
    case .networkError(let error):
        // Handle network-related errors (e.g., no internet connection)
        print("Network Error: \(error.localizedDescription)")
    case .decodingError(let error):
        // Handle errors that occur when the response cannot be decoded
        print("Decoding Error: \(error.localizedDescription)")
    case .streamError:
        // Handle errors that occur when streaming responses
        print("Stream Error")
    case .cancelled:
        // Handle requests that are cancelled
        print("Request was cancelled")
    }
} catch {
    // Handle any other errors
    print("An unexpected error occurred: \(error)")
}

支持

如果您觉得 LLMChatAnthropic 有用并希望支持其开发，请考虑捐款。您的贡献有助于维护项目和开发新功能。

非常感谢您的支持！❤️

贡献

欢迎贡献！如果您有任何建议或改进，请打开一个问题或提交一个拉取请求。

许可

本仓库根据 Apache License 2.0 许可发布。