mirror of
https://github.com/jie65535/JChatGPT.git
synced 2025-07-28 18:59:20 +08:00
Update to streaming processing response
Update regex
This commit is contained in:
parent
d1ee8f9fcf
commit
c479282fe4
@ -1,12 +1,17 @@
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package top.jie65535.mirai
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import com.aallam.openai.api.chat.ChatCompletionChunk
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import com.aallam.openai.api.chat.ChatCompletionRequest
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import com.aallam.openai.api.chat.ChatMessage
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import com.aallam.openai.api.chat.ChatRole
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import com.aallam.openai.api.chat.ToolCall
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import com.aallam.openai.api.model.ModelId
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import io.ktor.util.collections.*
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import kotlinx.coroutines.Deferred
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import kotlinx.coroutines.async
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import kotlinx.coroutines.awaitAll
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import kotlinx.coroutines.delay
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import kotlinx.coroutines.flow.Flow
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import kotlinx.coroutines.launch
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import kotlinx.coroutines.runBlocking
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import net.mamoe.mirai.console.command.CommandManager.INSTANCE.register
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@ -334,35 +339,103 @@ object JChatGPT : KotlinPlugin(
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do {
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try {
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val startedAt = OffsetDateTime.now().toEpochSecond().toInt()
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val response = chatCompletion(history)
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// 移除思考内容
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val responseContent = response.content?.replace(thinkRegex, "")?.trim()
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history.add(ChatMessage.Assistant(
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content = responseContent,
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name = response.name,
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toolCalls = response.toolCalls
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))
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val responseFlow = chatCompletions(history)
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var responseMessageBuilder: StringBuilder? = null
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val responseToolCalls = mutableListOf<ToolCall.Function>()
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val toolCallTasks = mutableListOf<Deferred<ChatMessage>>()
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// 处理聊天流式响应
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responseFlow.collect { chunk ->
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val delta = chunk.choices[0].delta
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if (delta == null) return@collect
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if (response.toolCalls.isNullOrEmpty()) {
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done = true
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} else {
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done = false
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// 处理函数调用
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for (toolCall in response.toolCalls) {
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require(toolCall is ToolCall.Function) { "Tool call is not a function" }
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val functionResponse = toolCall.execute(event)
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history.add(
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ChatMessage(
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role = ChatRole.Tool,
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toolCallId = toolCall.id,
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name = toolCall.function.name,
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content = functionResponse
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)
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)
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if (toolCall.function.name == "endConversation") {
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done = true
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// 处理内容更新
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if (delta.content != null) {
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if (responseMessageBuilder == null) {
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responseMessageBuilder = StringBuilder(delta.content)
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} else {
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responseMessageBuilder.append(delta.content)
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}
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}
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// 处理工具调用更新
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val toolCalls = delta.toolCalls
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if (toolCalls != null) {
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for (toolCallChunk in toolCalls) {
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val index = toolCallChunk.index
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val toolId = toolCallChunk.id
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val function = toolCallChunk.function
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// 新的请求
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if (index >= responseToolCalls.size) {
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// 处理已完成的工具调用
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responseToolCalls.lastOrNull()?.let { toolCall ->
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toolCallTasks.add(async {
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val functionResponse = toolCall.execute(event)
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ChatMessage(
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role = ChatRole.Tool,
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toolCallId = toolCall.id,
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name = toolCall.function.name,
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content = functionResponse
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)
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})
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}
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// 加入新的工具调用
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if (toolId != null && function != null) {
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responseToolCalls.add(ToolCall.Function(toolId, function))
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}
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} else if (function != null) {
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// 拼接函数名字
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if (function.nameOrNull != null) {
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val currentTool = responseToolCalls[index]
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responseToolCalls[index] = currentTool.copy(
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function = currentTool.function.copy(
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nameOrNull = currentTool.function.nameOrNull.orEmpty() + function.name
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)
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)
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}
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// 拼接函数参数
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if (function.argumentsOrNull != null) {
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val currentTool = responseToolCalls[index]
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responseToolCalls[index] = currentTool.copy(
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function = currentTool.function.copy(
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argumentsOrNull = currentTool.function.argumentsOrNull.orEmpty() + function.arguments
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)
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)
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}
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}
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}
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}
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}
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// 移除思考内容
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val responseContent = responseMessageBuilder?.replace(thinkRegex, "")?.trim()
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// 记录AI回答
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history.add(ChatMessage.Assistant(
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content = responseContent,
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toolCalls = responseToolCalls
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))
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// 处理最后一个工具调用
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if (responseToolCalls.size > toolCallTasks.size) {
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val toolCallMessage = responseToolCalls.last().let { toolCall ->
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val functionResponse = toolCall.execute(event)
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ChatMessage(
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role = ChatRole.Tool,
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toolCallId = toolCall.id,
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name = toolCall.function.name,
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content = functionResponse
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)
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}
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if (toolCallTasks.isNotEmpty()) {
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// 等待之前的所有工具完成
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history.addAll(toolCallTasks.awaitAll())
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}
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// 将最后一个也加入对话历史中
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history.add(toolCallMessage)
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// 如果调用中包含结束对话工具则表示完成，反之则继续循环
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done = history.any { it.name == "endConversation" }
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} else {
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done = true
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}
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if (!done) {
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@ -370,11 +443,6 @@ object JChatGPT : KotlinPlugin(
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buildString {
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append("系统提示：本次运行还剩${retry-1}轮")
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// if (response.toolCalls.isNullOrEmpty()) {
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// append("\n在上一轮对话中未检测到调用任何工具，请检查工具调用语法是否正确？")
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// append("\n如果你确实不需要调用其它工具比如发送消息，请调用`endConversation`来结束对话。")
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// }
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val newMessages = getAfterHistory(startedAt, event)
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if (newMessages.isNotEmpty()) {
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append("\n以下是上次运行至今的新消息\n\n$newMessages")
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@ -404,206 +472,12 @@ object JChatGPT : KotlinPlugin(
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}
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}
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// private suspend fun startChat(event: MessageEvent) {
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// if (!requestMap.add(event.sender.id)) {
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// // CD中不再引用消息，否则可能导致和机器人无限循环对话
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// event.subject.sendMessage("再等等...")
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// return
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// }
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//
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// val history = mutableListOf<ChatMessage>()
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// if (PluginConfig.prompt.isNotEmpty()) {
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// val prompt = getSystemPrompt(event)
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// if (PluginConfig.logPrompt) {
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// logger.info("Prompt: $prompt")
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// }
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// history.add(ChatMessage(ChatRole.System, prompt))
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// }
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// val historyText = getHistory(event)
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// logger.info("History: $historyText")
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// history.add(ChatMessage.User(historyText))
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//
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// try {
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// var done = true
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// // 至少重试两次
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// var retry = max(PluginConfig.retryMax, 3)
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// val finalToolCalls = mutableMapOf<Int, ToolCall.Function>()
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// val contentBuilder = StringBuilder()
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// do {
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// finalToolCalls.clear()
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// contentBuilder.setLength(0)
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//
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// try {
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// var sent = false
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// // 流式处理响应
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// withTimeout(PluginConfig.timeout) {
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// chatCompletions(history, retry > 1).collect { chunk ->
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// val delta = chunk.choices[0].delta
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// if (delta == null) return@collect
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//
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// // 处理工具调用
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// val toolCalls = delta.toolCalls
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// if (toolCalls != null) {
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// for (toolCall in toolCalls) {
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// val index = toolCall.index
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// val toolId = toolCall.id
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// val function = toolCall.function
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// // 取出未完成的函数调用
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// val incompleteCall = finalToolCalls[index]
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// // 如果是新的函数调用，保存起来
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// if (incompleteCall == null && toolId != null && function != null) {
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// // 添加函数调用
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// finalToolCalls[index] = ToolCall.Function(toolId, function)
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// } else if (incompleteCall != null && function != null && function.argumentsOrNull != null) {
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// // 更新参数内容
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// finalToolCalls[index] = incompleteCall.copy(
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// function = incompleteCall.function.copy(
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// argumentsOrNull = incompleteCall.function.arguments + function.arguments
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// )
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// )
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// }
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// }
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// }
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//
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// // 处理响应内容
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// val contentChunk = delta.content
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// // 避免连续发送多次，只拆分第一次进行发送
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// if (contentChunk != null && !sent) {
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// // 填入内容
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// contentBuilder.append(contentChunk)
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// sent = parseStreamingContent(contentBuilder, event)
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// }
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// }
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// }
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//
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// val lastBlock = contentBuilder.toString().trim()
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// if (lastBlock.isNotEmpty()) {
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// event.subject.sendMessage(
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// if (lastBlock.length > PluginConfig.messageMergeThreshold) {
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// event.buildForwardMessage {
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// event.bot says toMessage(event.subject, lastBlock)
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// }
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// } else {
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// toMessage(event.subject, lastBlock)
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// }
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// )
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// }
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//
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// if (finalToolCalls.isNotEmpty()) {
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// val toolCalls = finalToolCalls.values.toList()
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// history.add(ChatMessage.Assistant(toolCalls = toolCalls))
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// for (toolCall in toolCalls) {
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// val functionResponse = toolCall.execute(event)
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// history.add(
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// ChatMessage(
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// role = ChatRole.Tool,
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// toolCallId = toolCall.id,
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// name = toolCall.function.name,
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// content = functionResponse
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// )
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// )
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// done = false
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// }
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// } else {
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// done = true
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// }
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// } catch (e: Exception) {
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// if (retry <= 1) {
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// throw e
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// } else {
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// done = false
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// logger.warning("调用llm时发生异常，重试中", e)
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// event.subject.sendMessage(event.message.quote() + "出错了...正在重试...")
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// }
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// }
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// } while (!done && 0 < --retry)
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// } catch (ex: Throwable) {
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// logger.warning(ex)
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// event.subject.sendMessage(event.message.quote() + "很抱歉，发生异常，请稍后重试")
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// } finally {
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// // 一段时间后才允许再次提问，防止高频对话
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// launch {
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// delay(10.seconds)
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// requestMap.remove(event.sender.id)
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// }
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// }
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// }
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// /**
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// * 解析流消息
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// */
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// private fun parseStreamingContent(contentBuilder: StringBuilder, event: MessageEvent): Boolean {
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// // 处理推理内容
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// val thinkBeginAt = contentBuilder.indexOf("<think")
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// if (thinkBeginAt >= 0) {
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// val thinkEndAt = contentBuilder.indexOf("</think>")
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// if (thinkEndAt > 0) {
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// // 去除思考内容
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// contentBuilder.delete(thinkBeginAt, thinkEndAt + "</think>".length)
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// }
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// // 跳过本轮处理
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// return false
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// }
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//
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// // 处理代码块
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// val codeBlockBeginAt = contentBuilder.indexOf("```")
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// if (codeBlockBeginAt >= 0) {
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// val codeBlockEndAt = contentBuilder.indexOf("```", codeBlockBeginAt + 3)
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// if (codeBlockEndAt >= 0) {
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// val codeBlockContentBegin = contentBuilder.indexOf("\n", codeBlockBeginAt + 3)
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// if (codeBlockContentBegin in codeBlockBeginAt..codeBlockEndAt) {
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// val codeBlockContent = contentBuilder.substring(codeBlockContentBegin, codeBlockEndAt).trim()
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// contentBuilder.delete(codeBlockBeginAt, codeBlockEndAt + 3)
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// launch {
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// // 发送代码块内容
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// event.subject.sendMessage(
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// if (codeBlockContent.length < PluginConfig.messageMergeThreshold) {
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// toMessage(event.subject, codeBlockContent)
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// } else {
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// // 消息内容太长则转为转发消息避免刷屏
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// event.buildForwardMessage {
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// event.bot says toMessage(event.subject, codeBlockContent)
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// }
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// }
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// )
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// }
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// }
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// }
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// // 跳过本轮处理
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// return true
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// }
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//
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// // 徒手trimStart
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// var contentBeginAt = 0
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// while (contentBeginAt < contentBuilder.length) {
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// if (contentBuilder[contentBeginAt].isWhitespace()) {
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// contentBeginAt++
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// } else {
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// break
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// }
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// }
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//
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// // 对空行进行分割输出
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// val emptyLineAt = contentBuilder.indexOf("\n\n", contentBeginAt)
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// if (emptyLineAt > 0) {
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// val lineContent = contentBuilder.substring(contentBeginAt, emptyLineAt)
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// contentBuilder.delete(0, emptyLineAt + 2)
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// launch {
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// // 发送消息内容
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// event.subject.sendMessage(toMessage(event.subject, lineContent))
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// }
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// return true
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// }
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// return false
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// }
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private val regexAtQq = Regex("@(\\d+)")
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private val regexAtQq = Regex("""@(\d{5,12})""")
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private val regexLaTeX = Regex(
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"\\\\\\((.+?)\\\\\\)|" + // 匹配行内公式 \(...\)
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"\\\\\\[(.+?)\\\\\\]|" + // 匹配独立公式 \[...\]
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"\\$\\s(.+?)\\s\\$|" // 匹配行内公式 $...$
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"""\\\((.+?)\\\)|""" + // 匹配行内公式 \(...\)
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"""\\\[(.+?)\\]|""" + // 匹配独立公式 \[...\]
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"""\$(.+?)\$""" // 匹配行内公式 $...$
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)
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private data class MessageChunk(val range: IntRange, val content: Message)
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@ -704,28 +578,31 @@ object JChatGPT : KotlinPlugin(
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GroupManageAgent(),
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)
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// private fun chatCompletions(
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// private suspend fun chatCompletion(
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// chatMessages: List<ChatMessage>,
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// hasTools: Boolean = true
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// ): Flow<ChatCompletionChunk> {
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// val llm = this.llm ?: throw NullPointerException("OpenAI Token 未设置，无法开始")
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// ): ChatMessage {
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// val llm = LargeLanguageModels.chat ?: throw NullPointerException("OpenAI Token 未设置，无法开始")
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// val availableTools = if (hasTools) {
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// myTools.filter { it.isEnabled }.map { it.tool }
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// } else null
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// val request = ChatCompletionRequest(
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// model = ModelId(PluginConfig.chatModel),
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// temperature = PluginConfig.chatTemperature,
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// messages = chatMessages,
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// tools = availableTools,
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// )
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// logger.info("API Requesting... Model=${PluginConfig.chatModel}")
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// return llm.chatCompletions(request)
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// val response = llm.chatCompletion(request)
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// val message = response.choices.first().message
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// logger.info("Response: $message ${response.usage}")
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// return message
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// }
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private suspend fun chatCompletion(
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private fun chatCompletions(
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chatMessages: List<ChatMessage>,
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hasTools: Boolean = true
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): ChatMessage {
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): Flow<ChatCompletionChunk> {
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val llm = LargeLanguageModels.chat ?: throw NullPointerException("OpenAI Token 未设置，无法开始")
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val availableTools = if (hasTools) {
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myTools.filter { it.isEnabled }.map { it.tool }
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@ -737,10 +614,7 @@ object JChatGPT : KotlinPlugin(
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tools = availableTools,
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)
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logger.info("API Requesting... Model=${PluginConfig.chatModel}")
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val response = llm.chatCompletion(request)
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val message = response.choices.first().message
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logger.info("Response: $message ${response.usage}")
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return message
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return llm.chatCompletions(request)
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}
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private fun getNameCard(member: Member): String {
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