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ChatGPTService.swift
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677 lines (607 loc) · 25.7 KB
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import AIModel
import AsyncAlgorithms
import ChatBasic
import Dependencies
import Foundation
import IdentifiedCollections
import Logger
import Preferences
public enum ChatGPTServiceError: Error, LocalizedError {
case chatModelNotAvailable
case embeddingModelNotAvailable
case endpointIncorrect
case responseInvalid
case unauthorized(String)
case otherError(String)
public var errorDescription: String? {
switch self {
case .chatModelNotAvailable:
return "Chat model is not available, please add a model in the settings."
case .embeddingModelNotAvailable:
return "Embedding model is not available, please add a model in the settings."
case .endpointIncorrect:
return "ChatGPT endpoint is incorrect"
case .responseInvalid:
return "Response is invalid"
case let .unauthorized(reason):
return "Unauthorized: \(reason)"
case let .otherError(content):
return content
}
}
}
public struct ChatGPTError: Error, Codable, LocalizedError {
public var error: ErrorContent
public init(error: ErrorContent) {
self.error = error
}
public struct ErrorContent: Codable {
public var message: String
public var type: String?
public var param: String?
public var code: String?
public init(
message: String,
type: String? = nil,
param: String? = nil,
code: String? = nil
) {
self.message = message
self.type = type
self.param = param
self.code = code
}
}
public var errorDescription: String? {
error.message
}
}
public enum ChatGPTResponse: Equatable {
case status([String])
case partialText(String)
case partialReasoning(String)
case toolCalls([ChatMessage.ToolCall])
case usage(
promptTokens: Int,
completionTokens: Int,
cachedTokens: Int,
otherUsage: [String: Int]
)
}
public typealias ChatGPTResponseStream = AsyncThrowingStream<ChatGPTResponse, any Error>
public extension ChatGPTResponseStream {
func asText() async throws -> String {
var text = ""
for try await case let .partialText(response) in self {
text += response
}
return text
}
func asToolCalls() async throws -> [ChatMessage.ToolCall] {
var toolCalls = [ChatMessage.ToolCall]()
for try await case let .toolCalls(calls) in self {
toolCalls.append(contentsOf: calls)
}
return toolCalls
}
func asArray() async throws -> [ChatGPTResponse] {
var responses = [ChatGPTResponse]()
for try await response in self {
responses.append(response)
}
return responses
}
}
public protocol ChatGPTServiceType {
typealias Response = ChatGPTResponse
var configuration: ChatGPTConfiguration { get set }
func send(_ memory: ChatGPTMemory) -> ChatGPTResponseStream
}
public class ChatGPTService: ChatGPTServiceType {
public var configuration: ChatGPTConfiguration
public var utilityConfiguration: ChatGPTConfiguration
public var functionProvider: ChatGPTFunctionProvider
public init(
configuration: ChatGPTConfiguration = UserPreferenceChatGPTConfiguration(),
utilityConfiguration: ChatGPTConfiguration =
UserPreferenceChatGPTConfiguration(chatModelKey: \.preferredChatModelIdForUtilities),
functionProvider: ChatGPTFunctionProvider = NoChatGPTFunctionProvider()
) {
self.configuration = configuration
self.utilityConfiguration = utilityConfiguration
self.functionProvider = functionProvider
}
@Dependency(\.uuid) var uuid
@Dependency(\.date) var date
@Dependency(\.chatCompletionsAPIBuilder) var chatCompletionsAPIBuilder
/// Send the memory and stream the reply. While it's returning the results in a
/// ``ChatGPTResponseStream``, it's also streaming the results to the memory.
///
/// If ``ChatGPTConfiguration/runFunctionsAutomatically`` is enabled, the service will handle
/// the tool calls inside the function. Otherwise, it will return the tool calls to the caller.
public func send(_ memory: ChatGPTMemory) -> ChatGPTResponseStream {
return Debugger.$id.withValue(.init()) {
ChatGPTResponseStream { continuation in
let task = Task(priority: .userInitiated) {
do {
var pendingToolCalls = [ChatMessage.ToolCall]()
var sourceMessageId = ""
var isInitialCall = true
loop: while !pendingToolCalls.isEmpty || isInitialCall {
try Task.checkCancellation()
isInitialCall = false
var functionCallResponses = [ChatCompletionsRequestBody.Message]()
if !pendingToolCalls.isEmpty {
if configuration.runFunctionsAutomatically {
var toolCallStatuses = [String: String]() {
didSet {
if toolCallStatuses != oldValue {
continuation.yield(.status(
Array(toolCallStatuses.values).sorted()
))
}
}
}
for toolCall in pendingToolCalls {
let id = toolCall.id
for await response in await runFunctionCall(
toolCall,
memory: memory,
sourceMessageId: sourceMessageId
) {
switch response {
case let .output(output):
functionCallResponses.append(.init(
role: .tool,
content: output,
toolCallId: id
))
case let .status(status):
toolCallStatuses[id] = status
}
}
toolCallStatuses[id] = nil
}
toolCallStatuses = [:]
} else {
if !configuration.runFunctionsAutomatically {
continuation.yield(.toolCalls(pendingToolCalls))
continuation.finish()
return
}
}
}
sourceMessageId = uuid().uuidString
let stream = try await sendRequest(
memory: memory,
proposedMessageId: sourceMessageId
)
for try await content in stream {
try Task.checkCancellation()
switch content {
case let .partialText(text):
continuation.yield(ChatGPTResponse.partialText(text))
case let .partialReasoning(text):
continuation.yield(ChatGPTResponse.partialReasoning(text))
case let .partialToolCalls(toolCalls):
guard configuration.runFunctionsAutomatically else { break }
var toolCallStatuses = [String: String]() {
didSet {
if toolCallStatuses != oldValue {
continuation.yield(.status(
Array(toolCallStatuses.values).sorted()
))
}
}
}
for toolCall in toolCalls.keys.sorted() {
if let toolCallValue = toolCalls[toolCall] {
for await status in await prepareFunctionCall(
toolCallValue,
memory: memory,
sourceMessageId: sourceMessageId
) {
toolCallStatuses[toolCallValue.id] = status
}
}
}
case let .usage(
promptTokens,
completionTokens,
cachedTokens,
otherUsage
):
continuation.yield(
.usage(
promptTokens: promptTokens,
completionTokens: completionTokens,
cachedTokens: cachedTokens,
otherUsage: otherUsage
)
)
}
}
let replyMessage = await memory.history
.last { $0.id == sourceMessageId }
pendingToolCalls = replyMessage?.toolCalls ?? []
#if DEBUG
Debugger.didReceiveResponse(content: replyMessage?.content ?? "")
#endif
}
#if DEBUG
Debugger.didFinish()
#endif
continuation.finish()
} catch {
continuation.finish(throwing: error)
}
}
continuation.onTermination = { _ in
task.cancel()
}
}
}
}
}
// - MARK: Internal
extension ChatGPTService {
enum StreamContent {
case partialReasoning(String)
case partialText(String)
case partialToolCalls([Int: ChatMessage.ToolCall])
case usage(
promptTokens: Int,
completionTokens: Int,
cachedTokens: Int,
otherUsage: [String: Int]
)
}
enum FunctionCallResult {
case status(String)
case output(String)
}
/// Send the memory as prompt to ChatGPT, with stream enabled.
func sendRequest(
memory: ChatGPTMemory,
proposedMessageId: String
) async throws -> AsyncThrowingStream<StreamContent, Error> {
let prompt = await memory.generatePrompt()
guard let model = configuration.model else {
throw ChatGPTServiceError.chatModelNotAvailable
}
guard let url = URL(string: configuration.endpoint) else {
throw ChatGPTServiceError.endpointIncorrect
}
let requestBody = createRequestBody(prompt: prompt, model: model, stream: true)
let api = chatCompletionsAPIBuilder.buildStreamAPI(
model: model,
endpoint: url,
apiKey: configuration.apiKey,
requestBody: requestBody
)
#if DEBUG
Debugger.didSendRequestBody(body: requestBody)
#endif
return AsyncThrowingStream<StreamContent, Error> { continuation in
let task = Task {
do {
await memory.streamMessage(
id: proposedMessageId,
role: .assistant,
references: prompt.references
)
let chunks = try await api()
var usage: ChatCompletionResponseBody.Usage = .init(
promptTokens: 0,
completionTokens: 0,
cachedTokens: 0,
otherUsage: [:]
)
for try await chunk in chunks {
try Task.checkCancellation()
if let newUsage = chunk.usage {
usage.merge(with: newUsage)
}
guard let delta = chunk.message else { continue }
// The api will always return a function call with JSON object.
// The first round will contain the function name and an empty argument.
// e.g. {"name":"weather","arguments":""}
// The other rounds will contain part of the arguments.
let toolCalls = delta.toolCalls?
.reduce(into: [Int: ChatMessage.ToolCall]()) {
$0[$1.index ?? 0] = ChatMessage.ToolCall(
id: $1.id ?? "",
type: $1.type ?? "",
function: .init(
name: $1.function?.name ?? "",
arguments: $1.function?.arguments ?? ""
)
)
}
await memory.streamMessage(
id: proposedMessageId,
role: delta.role?.asChatMessageRole,
content: delta.content,
toolCalls: toolCalls
)
if let toolCalls {
continuation.yield(.partialToolCalls(toolCalls))
}
if let content = delta.content {
continuation.yield(.partialText(content))
}
if let reasoning = delta.reasoningContent {
continuation.yield(.partialReasoning(reasoning))
}
}
Logger.service.info("ChatGPT usage: \(usage)")
continuation.yield(.usage(
promptTokens: usage.promptTokens,
completionTokens: usage.completionTokens,
cachedTokens: usage.cachedTokens,
otherUsage: usage.otherUsage
))
continuation.finish()
} catch let error as CancellationError {
continuation.finish(throwing: error)
} catch let error as NSError where error.code == NSURLErrorCancelled {
continuation.finish(throwing: error)
} catch {
await memory.appendMessage(.init(
id: uuid().uuidString,
role: .assistant,
content: error.localizedDescription
))
continuation.finish(throwing: error)
}
}
continuation.onTermination = { _ in
task.cancel()
}
}
}
/// When a function call is detected, but arguments are not yet ready, we can call this
/// to report the status.
func prepareFunctionCall(
_ call: ChatMessage.ToolCall,
memory: ChatGPTMemory,
sourceMessageId: String
) async -> AsyncStream<String> {
return .init { continuation in
guard let function = functionProvider.function(named: call.function.name) else {
continuation.finish()
return
}
let task = Task {
await memory.streamToolCallResponse(
id: sourceMessageId,
toolCallId: call.id
)
await function.prepare { summary in
continuation.yield(summary)
await memory.streamToolCallResponse(
id: sourceMessageId,
toolCallId: call.id,
summary: summary
)
}
continuation.finish()
}
continuation.onTermination = { _ in
task.cancel()
}
}
}
/// Run a function call from the bot.
@discardableResult
func runFunctionCall(
_ call: ChatMessage.ToolCall,
memory: ChatGPTMemory,
sourceMessageId: String
) async -> AsyncStream<FunctionCallResult> {
#if DEBUG
Debugger.didReceiveFunction(name: call.function.name, arguments: call.function.arguments)
#endif
return .init { continuation in
let task = Task {
guard let function = functionProvider.function(named: call.function.name) else {
let response = await fallbackFunctionCall(
call,
memory: memory,
sourceMessageId: sourceMessageId
)
continuation.yield(.output(response))
continuation.finish()
return
}
await memory.streamToolCallResponse(
id: sourceMessageId,
toolCallId: call.id
)
do {
// Run the function
let result = try await function
.call(argumentsJsonString: call.function.arguments) { summary in
continuation.yield(.status(summary))
await memory.streamToolCallResponse(
id: sourceMessageId,
toolCallId: call.id,
summary: summary
)
}
#if DEBUG
Debugger.didReceiveFunctionResult(result: result.botReadableContent)
#endif
await memory.streamToolCallResponse(
id: sourceMessageId,
toolCallId: call.id,
content: result.botReadableContent
)
continuation.yield(.output(result.botReadableContent))
continuation.finish()
} catch {
// For errors, use the error message as the result.
let content = "Error: \(error.localizedDescription)"
#if DEBUG
Debugger.didReceiveFunctionResult(result: content)
#endif
await memory.streamToolCallResponse(
id: sourceMessageId,
toolCallId: call.id,
content: content,
summary: content
)
continuation.yield(.output(content))
continuation.finish()
}
}
continuation.onTermination = { _ in
task.cancel()
}
}
}
/// Mock a function call result when the bot is calling a function that is not implemented.
func fallbackFunctionCall(
_ call: ChatMessage.ToolCall,
memory: ChatGPTMemory,
sourceMessageId: String
) async -> String {
let temporaryMemory = ConversationChatGPTMemory(systemPrompt: {
if call.function.name == "python" {
return """
Act like a Python interpreter.
I will give you Python code and you will execute it.
Reply with output of the code and tell me it's an answer generated by LLM.
"""
} else {
return """
You are a function simulator. Your name is \(call.function.name).
Act like a function.
I will send you the arguments.
Reply with output of the function and tell me it's an answer generated by LLM.
"""
}
}())
let service = ChatGPTService(
configuration: OverridingChatGPTConfiguration(
overriding: utilityConfiguration,
with: .init(temperature: 0)
),
functionProvider: NoChatGPTFunctionProvider()
)
let stream = service.send(temporaryMemory)
do {
let result = try await stream.asText()
await memory.streamToolCallResponse(
id: sourceMessageId,
toolCallId: call.id,
content: result,
summary: "Finished running function."
)
return result
} catch {
return error.localizedDescription
}
}
func createRequestBody(
prompt: ChatGPTPrompt,
model: ChatModel,
stream: Bool
) -> ChatCompletionsRequestBody {
let serviceSupportsFunctionCalling = switch model.format {
case .openAI, .openAICompatible, .azureOpenAI, .gitHubCopilot:
model.info.supportsFunctionCalling
case .ollama, .googleAI, .claude:
false
}
let messages = prompt.history.flatMap { chatMessage in
let images = chatMessage.images.map { image in
ChatCompletionsRequestBody.Message.Image(
base64EncodeData: image.base64EncodedData,
format: {
switch image.format {
case .png: .png
case .jpeg: .jpeg
case .gif: .gif
}
}()
)
}
var all = [ChatCompletionsRequestBody.Message]()
all.append(ChatCompletionsRequestBody.Message(
role: {
switch chatMessage.role {
case .system: .system
case .user: .user
case .assistant: .assistant
}
}(),
content: chatMessage.content ?? "",
name: chatMessage.name,
toolCalls: {
if serviceSupportsFunctionCalling {
chatMessage.toolCalls?.map {
.init(
id: $0.id,
type: $0.type,
function: .init(
name: $0.function.name,
arguments: $0.function.arguments
)
)
}
} else {
nil
}
}(),
images: images,
audios: [],
cacheIfPossible: chatMessage.cacheIfPossible
))
for call in chatMessage.toolCalls ?? [] {
if serviceSupportsFunctionCalling {
all.append(ChatCompletionsRequestBody.Message(
role: .tool,
content: call.response.content,
toolCallId: call.id
))
} else {
all.append(ChatCompletionsRequestBody.Message(
role: .user,
content: call.response.content
))
}
}
return all
}
let remainingTokens = prompt.remainingTokenCount
let requestBody = ChatCompletionsRequestBody(
model: model.info.modelName,
messages: messages,
temperature: configuration.temperature,
stream: stream,
stop: configuration.stop.isEmpty ? nil : configuration.stop,
maxTokens: maxTokenForReply(
maxToken: model.info.maxTokens,
remainingTokens: remainingTokens
),
toolChoice: serviceSupportsFunctionCalling
? functionProvider.functionCallStrategy
: nil,
tools: serviceSupportsFunctionCalling
? functionProvider.functions.map {
.init(function: ChatGPTFunctionSchema(
name: $0.name,
description: $0.description,
parameters: $0.argumentSchema
))
}
: []
)
return requestBody
}
func maxTokenForReply(maxToken: Int, remainingTokens: Int?) -> Int? {
guard let remainingTokens else { return nil }
return min(maxToken / 2, remainingTokens)
}
}