diff --git a/package.json b/package.json index 78ed24227..e06b04a18 100644 --- a/package.json +++ b/package.json @@ -57,6 +57,8 @@ }, "dependencies": { "@anthropic-ai/sdk": "^0.53.0", + "@aws-sdk/client-bedrock": "^3.840.0", + "@aws-sdk/client-bedrock-runtime": "^3.842.0", "@duckdb/node-api": "1.3.2-alpha.25", "@e2b/code-interpreter": "^1.5.1", "@electron-toolkit/preload": "^3.0.1", diff --git a/src/main/presenter/configPresenter/providers.ts b/src/main/presenter/configPresenter/providers.ts index 688c06cf1..cc87c9d63 100644 --- a/src/main/presenter/configPresenter/providers.ts +++ b/src/main/presenter/configPresenter/providers.ts @@ -592,5 +592,20 @@ export const DEFAULT_PROVIDERS: LLM_PROVIDER_BASE[] = [ models: 'https://modelscope.cn/models', defaultBaseUrl: 'https://api-inference.modelscope.cn/v1/' } + }, + { + id: 'aws-bedrock', + name: 'AWS Bedrock', + apiType: 'aws-bedrock', + apiKey: '', + baseUrl: '', + enable: false, + websites: { + official: 'https://aws.amazon.com/bedrock/', + apiKey: 'https://console.aws.amazon.com/iam/', + docs: 'https://docs.aws.amazon.com/bedrock/latest/userguide/what-is-bedrock.html', + models: 'https://docs.aws.amazon.com/bedrock/latest/userguide/models-supported.html', + defaultBaseUrl: '' + } } ] diff --git a/src/main/presenter/llmProviderPresenter/index.ts b/src/main/presenter/llmProviderPresenter/index.ts index 4228aa160..a7bc97248 100644 --- a/src/main/presenter/llmProviderPresenter/index.ts +++ b/src/main/presenter/llmProviderPresenter/index.ts @@ -26,6 +26,7 @@ import { GithubProvider } from './providers/githubProvider' import { GithubCopilotProvider } from './providers/githubCopilotProvider' import { OllamaProvider } from './providers/ollamaProvider' import { AnthropicProvider } from './providers/anthropicProvider' +import { AwsBedrockProvider } from './providers/awsBedrockProvider' import { DoubaoProvider } from './providers/doubaoProvider' import { ShowResponse } from 'ollama' import { CONFIG_EVENTS, RATE_LIMIT_EVENTS } from '@/events' @@ -212,6 +213,8 @@ export class LLMProviderPresenter implements ILlmProviderPresenter { return new GroqProvider(provider, this.configPresenter) case 'vercel-ai-gateway': return new VercelAIGatewayProvider(provider, this.configPresenter) + case 'aws-bedrock': + return new AwsBedrockProvider(provider, this.configPresenter) default: console.warn(`Unknown provider type: ${provider.apiType}`) return undefined diff --git a/src/main/presenter/llmProviderPresenter/providers/awsBedrockProvider.ts b/src/main/presenter/llmProviderPresenter/providers/awsBedrockProvider.ts new file mode 100644 index 000000000..72c500728 --- /dev/null +++ b/src/main/presenter/llmProviderPresenter/providers/awsBedrockProvider.ts @@ -0,0 +1,918 @@ +import { + LLMResponse, + MODEL_META, + LLMCoreStreamEvent, + ModelConfig, + MCPToolDefinition, + ChatMessage, + AWS_BEDROCK_PROVIDER +} from '@shared/presenter' +import { BaseLLMProvider, SUMMARY_TITLES_PROMPT } from '../baseProvider' +import { ConfigPresenter } from '../../configPresenter' +import { presenter } from '@/presenter' +import { BedrockClient, ListFoundationModelsCommand } from '@aws-sdk/client-bedrock' +import { + BedrockRuntimeClient, + InvokeModelCommand, + InvokeModelCommandOutput, + InvokeModelWithResponseStreamCommand +} from '@aws-sdk/client-bedrock-runtime' +import Anthropic from '@anthropic-ai/sdk' +import { Usage } from '@anthropic-ai/sdk/resources/messages' + +export class AwsBedrockProvider extends BaseLLMProvider { + private bedrock!: BedrockClient + private bedrockRuntime!: BedrockRuntimeClient + private defaultModel = 'claude-3-7-sonnet-20250219' + + constructor(provider: AWS_BEDROCK_PROVIDER, configPresenter: ConfigPresenter) { + super(provider, configPresenter) + this.init() + } + + public onProxyResolved(): void { + this.init() + } + + protected async init() { + if (this.provider.enable) { + try { + const provider = this.provider as AWS_BEDROCK_PROVIDER + const accessKeyId = provider.credential?.accessKeyId || process.env.BEDROCK_ACCESS_KEY_ID + const secretAccessKey = + provider.credential?.secretAccessKey || process.env.BEDROCK_SECRET_ACCESS_KEY + const region = provider.credential?.region || process.env.BEDROCK_REGION + + if (!accessKeyId || !secretAccessKey) { + throw new Error( + 'apiKey must be provided as "${ACCESS_KEY_ID}:${SECRET_ACCESS_KEY}" format.' + ) + } + + this.bedrock = new BedrockClient({ + credentials: { accessKeyId, secretAccessKey }, + region + }) + + this.bedrockRuntime = new BedrockRuntimeClient({ + credentials: { accessKeyId, secretAccessKey }, + region + }) + + await super.init() + } catch (error) { + console.error('Failed to initialize AWS Bedrock provider:', error) + } + } + } + + protected async fetchProviderModels(): Promise { + try { + const command = new ListFoundationModelsCommand({}) + const response = await this.bedrock.send(command) + const models = response.modelSummaries + + return ( + models + ?.filter((m) => m.modelId?.includes('anthropic.claude')) + ?.filter((m) => m.modelLifecycle?.status === 'ACTIVE') + .map((m) => ({ + // id: m.modelId!, + // id: m.modelArn!, + id: `${m.inferenceTypesSupported?.includes('ON_DEMAND') ? m.modelId! : `us.${m.modelId}`}`, + // name: `${m.modelName} (${m.modelId})`, + name: m.modelId?.replace('anthropic.', '') || '', + providerId: this.provider.id, + maxTokens: 64_000, + group: `AWS Bedrock Claude - ${m.modelId?.includes('opus') ? 'opus' : m.modelId?.includes('sonnet') ? 'sonnet' : m.modelId?.includes('haiku') ? 'haiku' : 'other'}`, + isCustom: false, + contextLength: 200_000, + vision: false, + functionCall: false, + reasoning: false + })) || [] + ) + } catch (error) { + console.error('获取AWS Bedrock Anthropic模型列表出错:', error) + } + + // 如果API请求失败或返回数据解析失败，返回默认模型列表 + console.log('从API获取模型列表失败，使用默认模型配置') + return [ + { + id: 'anthropic.claude-sonnet-4-20250514-v1:0', + name: 'AWS Bedrock Claude Sonnet 4', + providerId: this.provider.id, + maxTokens: 64_000, + group: 'Bedrock Claude 4', + isCustom: false, + contextLength: 200000, + vision: true, + functionCall: true, + reasoning: true + }, + { + id: 'anthropic.claude-3-7-sonnet-20250219-v1:0', + name: 'AWS Bedrock Claude 3.7 Sonnet', + providerId: this.provider.id, + maxTokens: 64_000, + group: 'Bedrock Claude 3.7', + isCustom: false, + contextLength: 200000, + vision: true, + functionCall: true, + reasoning: true + }, + { + id: 'anthropic.claude-3-5-sonnet-20241022-v2:0', + name: 'AWS Bedrock Claude 3.5 Sonnet', + providerId: this.provider.id, + maxTokens: 8192, + group: 'Bedrock Claude 3.5', + isCustom: false, + contextLength: 200000, + vision: true, + functionCall: true, + reasoning: false + }, + { + id: 'anthropic.claude-3-5-sonnet-20240620-v1:0', + name: 'AWS Bedrock Claude 3.5 Sonnet (Legacy)', + providerId: this.provider.id, + maxTokens: 8192, + group: 'Bedrock Claude 3.5', + isCustom: false, + contextLength: 200000, + vision: true, + functionCall: true, + reasoning: false + }, + { + id: 'anthropic.claude-3-haiku-20240307-v1:0', + name: 'AWS Bedrock Claude 3 Haiku', + providerId: this.provider.id, + maxTokens: 8192, + group: 'Bedrock Claude 3', + isCustom: false, + contextLength: 200000, + vision: true, + functionCall: true, + reasoning: false + } + ] + } + + public async check(): Promise<{ isOk: boolean; errorMsg: string | null }> { + try { + if (!this.bedrockRuntime) { + return { isOk: false, errorMsg: '未初始化 AWS Bedrock SDK' } + } + + // 发送一个简单请求来检查 API 连接状态 + // Prepare the payload for the Messages API request. + const payload = { + anthropic_version: 'bedrock-2023-05-31', + max_tokens: 10, + messages: [ + { + role: 'user', + content: [{ type: 'text', text: 'Hi' }] + } + ] + } + const command = new InvokeModelCommand({ + contentType: 'application/json', + body: JSON.stringify(payload), + modelId: this.defaultModel + }) + const apiResponse = await this.bedrockRuntime.send(command) + + // Decode and return the response(s) + const decodedResponseBody = new TextDecoder().decode(apiResponse.body) + /** @type {MessagesResponseBody} */ + const responseBody = JSON.parse(decodedResponseBody) + const responseText = responseBody.content[0].text + + return { isOk: responseText.length > 0, errorMsg: null } + } catch (error: unknown) { + console.error('AWS Bedrock Claude API check failed:', error) + const errorMessage = error instanceof Error ? error.message : String(error) + return { isOk: false, errorMsg: `API 检查失败: ${errorMessage}` } + } + } + + // 依赖 generateText + public async summaryTitles(messages: ChatMessage[], modelId: string): Promise { + const prompt = `${SUMMARY_TITLES_PROMPT}\n\n${messages.map((m) => `${m.role}: ${m.content}`).join('\n')}` + const response = await this.generateText(prompt, modelId, 0.3, 50) + + return response.content.trim() + } + + // 依赖 generateText + async summaries( + text: string, + modelId: string, + temperature?: number, + maxTokens?: number, + systemPrompt?: string + ): Promise { + const prompt = `请对以下内容进行摘要: + +${text} + +请提供一个简洁明了的摘要。` + + return this.generateText(prompt, modelId, temperature, maxTokens, systemPrompt) + } + + async generateText( + prompt: string, + modelId: string, + temperature?: number, + maxTokens?: number, + systemPrompt?: string + ): Promise { + try { + const payload = { + anthropic_version: 'bedrock-2023-05-31', + max_tokens: maxTokens, + temperature, + system: systemPrompt, + messages: [ + { + role: 'user', + content: [{ type: 'text', text: prompt }] + } + ] + } + const command = new InvokeModelCommand({ + contentType: 'application/json', + body: JSON.stringify(payload), + modelId + }) + + const response = await this.bedrockRuntime.send(command) + + // Decode and return the response(s) + const decodedResponseBody = new TextDecoder().decode(response.body) + /** @type {MessagesResponseBody} */ + const responseBody = JSON.parse(decodedResponseBody) + return { content: responseBody.content[0].text, reasoning_content: undefined } + } catch (error) { + console.error('AWS Bedrock generate text error:', error) + throw error + } + } + + private formatMessages(messages: ChatMessage[]): { + system?: string + messages: Anthropic.MessageParam[] + } { + // console.log('开始格式化消息，总消息数:', messages.length) + + // 提取系统消息 + let systemContent = '' + for (const msg of messages) { + if (msg.role === 'system') { + systemContent += + (typeof msg.content === 'string' + ? msg.content + : msg.content && Array.isArray(msg.content) + ? msg.content + .filter((c) => c.type === 'text') + .map((c) => c.text || '') + .join('\n') + : '') + '\n' + } + } + + // 定义消息组和内容块的类型 + type ContentBlock = Anthropic.ContentBlockParam + type ToolCall = { id: string; function: { name: string; arguments?: string } } + type MessageGroup = { + role: string + contents: ContentBlock[] + toolCalls?: string[] + hasToolUse?: boolean + } + + // 预处理：对消息进行分组 + // 新的逻辑：每个assistant消息如果包含tool_calls，就单独成组 + const messageGroups: MessageGroup[] = [] + let currentGroup: MessageGroup | null = null + + // 用于跟踪tool_calls和tool响应的匹配 + const toolResponseMap = new Map() + + // 第一阶段：建立初始分组和收集工具响应 + for (let i = 0; i < messages.length; i++) { + const msg = messages[i] + if (msg.role === 'system') continue // 系统消息已处理 + + // console.log( + // `处理第${i + 1}条消息, 角色:${msg.role}`, + // msg.content + // ? typeof msg.content === 'string' + // ? '内容长度:' + msg.content.length + // : '数组内容长度:' + (Array.isArray(msg.content) ? msg.content.length : 0) + // : '无内容' + // ) + + // 处理工具响应，将其与对应的工具调用关联 + if (msg.role === 'tool' && 'tool_call_id' in msg) { + const toolCallId = msg.tool_call_id as string + const responseContent = + typeof msg.content === 'string' + ? msg.content + : Array.isArray(msg.content) + ? JSON.stringify(msg.content) + : '' + + toolResponseMap.set(toolCallId, { + type: 'tool_result', + tool_use_id: toolCallId, + content: responseContent + } as ContentBlock) + + // console.log('记录tool响应，tool_call_id:', toolCallId) + continue + } + + // 处理用户消息 - 开始新组 + if (msg.role === 'user') { + if (currentGroup) { + messageGroups.push(currentGroup) + } + + let formattedContent: ContentBlock[] = [] + if (typeof msg.content === 'string') { + formattedContent = [{ type: 'text', text: msg.content }] + } else if (msg.content && Array.isArray(msg.content)) { + formattedContent = msg.content.map((c) => { + if (c.type === 'image_url' && c.image_url) { + return { + type: 'image', + source: c.image_url.url.startsWith('data:image') + ? { + type: 'base64', + data: c.image_url.url.split(',')[1], + media_type: c.image_url.url.split(';')[0].split(':')[1] as + | 'image/jpeg' + | 'image/png' + | 'image/gif' + | 'image/webp' + } + : { type: 'url', url: c.image_url.url } + } as ContentBlock + } else { + return { type: 'text', text: c.text || '' } as ContentBlock + } + }) + } + + currentGroup = { + role: 'user', + contents: formattedContent + } + + // console.log('开始新的用户消息组') + continue + } + + // 处理assistant消息 - 添加到当前组或开始新组 + if (msg.role === 'assistant') { + // 检查是否需要新建一个组： + // 1. 当前还没有组 + // 2. 当前组不是assistant + // 3. 当前组是assistant但包含了工具调用 + const shouldCreateNewGroup = + !currentGroup || currentGroup.role !== 'assistant' || currentGroup.hasToolUse === true + + if (shouldCreateNewGroup) { + if (currentGroup) { + messageGroups.push(currentGroup) + } + + currentGroup = { + role: 'assistant', + contents: [], + toolCalls: [], + hasToolUse: false + } + } + + // 确保currentGroup已初始化 + if (!currentGroup) { + currentGroup = { + role: 'assistant', + contents: [], + toolCalls: [], + hasToolUse: false + } + } + + // 处理常规内容 + if (msg.content) { + let assistantContent: ContentBlock[] = [] + if (typeof msg.content === 'string') { + if (msg.content.trim()) { + assistantContent = [{ type: 'text', text: msg.content }] + } + } else if (Array.isArray(msg.content)) { + // 处理各种内容类型 + for (const content of msg.content) { + if (content.type === 'text') { + currentGroup.contents.push({ + type: 'text', + text: content.text || '' + } as ContentBlock) + } else if (content.type === 'image_url' && content.image_url) { + currentGroup.contents.push({ + type: 'image', + source: content.image_url.url.startsWith('data:image') + ? { + type: 'base64', + data: content.image_url.url.split(',')[1], + media_type: content.image_url.url.split(';')[0].split(':')[1] as + | 'image/jpeg' + | 'image/png' + | 'image/gif' + | 'image/webp' + } + : { type: 'url', url: content.image_url.url } + } as ContentBlock) + } + } + + continue + } + + currentGroup.contents.push(...assistantContent) + // console.log('添加文本内容到当前assistant组, 项数:', assistantContent.length) + } + + // 处理tool_calls + if ('tool_calls' in msg && Array.isArray(msg.tool_calls)) { + // console.log('处理assistant消息中的tool_calls', msg.tool_calls.length) + + // 标记当前组包含工具调用 + if (currentGroup) { + currentGroup.hasToolUse = true + } + + for (const toolCall of msg.tool_calls as ToolCall[]) { + try { + // @ts-ignore - 转换为Anthropic格式 + currentGroup.contents.push({ + type: 'tool_use', + id: toolCall.id, + name: toolCall.function.name, + input: JSON.parse(toolCall.function.arguments || '{}') + } as ContentBlock) + + // console.log('添加tool_call到当前assistant组:', toolCall.function.name) + + // 记录工具调用，稍后查找响应 + if (!currentGroup.toolCalls) currentGroup.toolCalls = [] + currentGroup.toolCalls.push(toolCall.id) + } catch (e) { + console.error('Error processing tool_call:', e) + } + } + } + } + } + + // 添加最后一个组 + if (currentGroup) { + messageGroups.push(currentGroup) + } + + // console.log('预处理完成，消息组数量:', messageGroups.length) + + // 第二阶段：生成最终的格式化消息 + const formattedMessages: Anthropic.MessageParam[] = [] + + for (const group of messageGroups) { + if (group.contents.length === 0) continue + + // 添加组的主要内容 + formattedMessages.push({ + role: group.role as 'user' | 'assistant', + content: group.contents as Anthropic.ContentBlockParam[] + }) + + // console.log(`添加${group.role}组，内容项数:${group.contents.length}`) + + // 如果是assistant组且有工具调用，添加对应的工具响应 + if (group.role === 'assistant' && group.toolCalls && group.toolCalls.length > 0) { + for (const toolCallId of group.toolCalls) { + const toolResponse = toolResponseMap.get(toolCallId) + if (toolResponse) { + formattedMessages.push({ + role: 'user', + content: [toolResponse] + }) + + // console.log('添加工具响应，tool_call_id:', toolCallId) + } + } + } + } + + // console.log('格式化完成, 最终消息数:', formattedMessages.length) + // 为调试目的，打印前3条消息的结构 + // formattedMessages.slice(0, Math.min(3, formattedMessages.length)).forEach((msg, i) => { + // console.log(`最终消息#${i + 1}:`, { + // role: msg.role, + // contentLength: Array.isArray(msg.content) ? msg.content.length : 0, + // contentTypes: Array.isArray(msg.content) + // ? msg.content.map((c) => c.type).join(',') + // : typeof msg.content + // }) + // }) + + return { + system: systemContent || undefined, + messages: formattedMessages + } + } + + // 依赖 formatMessages + async completions( + messages: ChatMessage[], + modelId: string, + temperature?: number, + maxTokens?: number + ): Promise { + try { + if (!this.bedrockRuntime) { + throw new Error('AWS Bedrock client is not initialized') + } + + const formattedMessages = this.formatMessages(messages) + + // 创建基本请求参数 + const payload = { + anthropic_version: 'bedrock-2023-05-31', + max_tokens: maxTokens, + temperature, + system: formattedMessages.system, + messages + } + + const command = new InvokeModelCommand({ + contentType: 'application/json', + body: JSON.stringify(payload), + modelId + }) + + // 执行请求 + const response = (await this.bedrockRuntime.send(command)) as InvokeModelCommandOutput & { + usage?: any + } + + const resultResp: LLMResponse = { + content: '' + } + + // 添加usage信息 + if (response.usage) { + resultResp.totalUsage = { + prompt_tokens: response.usage.input_tokens, + completion_tokens: response.usage.output_tokens, + total_tokens: response.usage.input_tokens + response.usage.output_tokens + } + } + + // 获取文本内容 + // const content = response.content + // .filter((block) => block.type === 'text') + // .map((block) => (block.type === 'text' ? block.text : '')) + // .join('') + const decodedResponseBody = new TextDecoder().decode(response.body) + /** @type {MessagesResponseBody} */ + const responseBody = JSON.parse(decodedResponseBody) + const content = responseBody.content[0].text + + // 处理标签 + if (content.includes('')) { + const thinkStart = content.indexOf('') + const thinkEnd = content.indexOf('') + + if (thinkEnd > thinkStart) { + // 提取reasoning_content + resultResp.reasoning_content = content.substring(thinkStart + 7, thinkEnd).trim() + + // 合并前后的普通内容 + const beforeThink = content.substring(0, thinkStart).trim() + const afterThink = content.substring(thinkEnd + 8).trim() + resultResp.content = [beforeThink, afterThink].filter(Boolean).join('\n') + } else { + // 如果没有找到配对的结束标签，将所有内容作为普通内容 + resultResp.content = content + } + } else { + // 没有think标签，所有内容作为普通内容 + resultResp.content = content + } + + return resultResp + } catch (error) { + console.error('AWS Bedrock Claude completions error:', error) + throw error + } + } + + // 依赖 formatMessages + // 添加coreStream方法 + async *coreStream( + messages: ChatMessage[], + modelId: string, + modelConfig: ModelConfig, + temperature: number, + maxTokens: number, + mcpTools: MCPToolDefinition[] + ): AsyncGenerator { + if (!this.bedrockRuntime) throw new Error('AWS Bedrock client is not initialized') + if (!modelId) throw new Error('Model ID is required') + console.log('modelConfig', modelConfig, modelId) + try { + // 格式化消息 + const formattedMessagesObject = this.formatMessages(messages) + console.log('formattedMessagesObject', JSON.stringify(formattedMessagesObject)) + + // 将MCP工具转换为Anthropic工具格式 + const anthropicTools = + mcpTools.length > 0 + ? await presenter.mcpPresenter.mcpToolsToAnthropicTools(mcpTools, this.provider.id) + : undefined + + // 创建基本请求参数 + // const streamParams = { + // model: modelId, + // max_tokens: maxTokens || 1024, + // temperature: temperature || 0.7, + // messages: formattedMessagesObject.messages, + // stream: true + // } as Anthropic.Messages.MessageCreateParamsStreaming + const payload = { + anthropic_version: 'bedrock-2023-05-31', + max_tokens: maxTokens || 1024, + temperature: temperature || 0.7, + // system: formattedMessagesObject.system, + messages: formattedMessagesObject.messages, + thinking: undefined as any, + tools: undefined as any + } + const command = new InvokeModelWithResponseStreamCommand({ + contentType: 'application/json', + body: JSON.stringify(payload), + modelId + }) + + // 启用Claude 3.7模型的思考功能 + if (modelId.includes('claude-3-7')) { + payload.thinking = { budget_tokens: 1024, type: 'enabled' } + } + + // // 如果有系统消息，添加到请求参数中 + // if (formattedMessagesObject.system) { + // // @ts-ignore - system属性在类型定义中可能不存在，但API已支持 + // streamParams.system = formattedMessagesObject.system + // } + + // 添加工具参数 + if (anthropicTools && anthropicTools.length > 0) { + // @ts-ignore - 类型不匹配，但格式是正确的 + payload.tools = anthropicTools + } + // 创建Anthropic流 + const response = await this.bedrockRuntime.send(command) + const body = await response.body + if (!body) { + throw new Error('No response body from AWS Bedrock') + } + + // 状态变量 + let accumulatedJson = '' + let toolUseDetected = false + let currentToolId = '' + let currentToolName = '' + let currentToolInputs: Record = {} + let usageMetadata: Usage | undefined + // 处理流中的各种事件 + for await (const item of body) { + if (!item.chunk) continue + + const chunk = JSON.parse(new TextDecoder().decode(item.chunk.bytes)) + // 处理使用统计 + if (chunk.type === 'message_start' && chunk.message.usage) { + usageMetadata = chunk.message.usage + } + + // 处理工具调用开始 + // @ts-ignore - Anthropic SDK类型定义不完整 + if (chunk.type === 'content_block_start' && chunk.content_block?.type === 'tool_use') { + toolUseDetected = true + // @ts-ignore - content_block不在类型定义中 + currentToolId = chunk.content_block.id || `anthropic-tool-${Date.now()}` + // @ts-ignore - content_block不在类型定义中 + currentToolName = chunk.content_block.name || '' + currentToolInputs = {} + accumulatedJson = '' + + // 发送工具调用开始事件 + if (currentToolName) { + yield { + type: 'tool_call_start', + tool_call_id: currentToolId, + tool_call_name: currentToolName + } + } + continue + } + + // 处理工具调用参数更新 - input_json_delta + // @ts-ignore - 类型定义中没有工具相关字段 + if (chunk.type === 'content_block_delta' && chunk.delta?.type === 'input_json_delta') { + // @ts-ignore - partial_json不在类型定义中 + const partialJson = chunk.delta.partial_json + if (partialJson) { + accumulatedJson += partialJson + + // 发送工具调用参数块事件 + yield { + type: 'tool_call_chunk', + tool_call_id: currentToolId, + tool_call_arguments_chunk: partialJson + } + } + continue + } + + // 处理工具使用更新 - tool_use_delta + // @ts-ignore - 类型定义中没有工具相关字段 + if (chunk.type === 'content_block_delta' && chunk.delta?.type === 'tool_use_delta') { + // @ts-ignore - delta.name不在类型定义中 + if (chunk.delta.name && !currentToolName) { + // @ts-ignore - 访问delta.name + currentToolName = chunk.delta.name + yield { + type: 'tool_call_start', + tool_call_id: currentToolId, + tool_call_name: currentToolName + } + } + + // @ts-ignore - delta.input不在类型定义中 + if (chunk.delta.input) { + currentToolInputs = { + ...currentToolInputs, + // @ts-ignore - 访问delta.input + ...chunk.delta.input + } + } + continue + } + + // 处理内容块结束 + if (chunk.type === 'content_block_stop') { + // 处理工具调用完成 + if (toolUseDetected && currentToolName && accumulatedJson) { + try { + // 尝试解析完整的JSON + const jsonStr = accumulatedJson.trim() + if (jsonStr && (jsonStr.startsWith('{') || jsonStr.startsWith('['))) { + try { + const jsonObject = JSON.parse(jsonStr) + if (jsonObject && typeof jsonObject === 'object') { + currentToolInputs = { ...currentToolInputs, ...jsonObject } + } + } catch (e) { + console.error('解析完整JSON失败:', e) + } + } + } catch (e) { + console.error('处理累积JSON失败:', e) + } + + // 发送工具调用结束事件 + const argsString = JSON.stringify(currentToolInputs) + yield { + type: 'tool_call_end', + tool_call_id: currentToolId, + tool_call_arguments_complete: argsString + } + + // 重置工具调用状态 + accumulatedJson = '' + } + continue + } + + // 检查消息是否因为工具调用而停止 + if (chunk.type === 'message_delta' && chunk.delta?.stop_reason === 'tool_use') { + // 设置为工具使用停止，主循环会处理工具调用 + continue + } + + // 处理思考内容（如果有） + // @ts-ignore - 类型定义中没有thinking相关字段 + if (chunk.type === 'content_block_delta' && chunk.delta?.type === 'thinking_delta') { + // @ts-ignore - delta.thinking不在类型定义中 + const thinkingText = chunk.delta.thinking + if (thinkingText) { + yield { + type: 'reasoning', + reasoning_content: thinkingText + } + } + continue + } + + // 处理常规文本内容 + if (chunk.type === 'content_block_delta' && chunk.delta.type === 'text_delta') { + const text = chunk.delta.text + if (text) { + // 处理标签 + if (text.includes('')) { + const parts = text.split('') + if (parts[0]) { + yield { + type: 'text', + content: parts[0] + } + } + + if (parts[1]) { + // 检查是否包含 + const thinkParts = parts[1].split('') + if (thinkParts.length > 1) { + yield { + type: 'reasoning', + reasoning_content: thinkParts[0] + } + + if (thinkParts[1]) { + yield { + type: 'text', + content: thinkParts[1] + } + } + } else { + yield { + type: 'reasoning', + reasoning_content: parts[1] + } + } + } + } else if (text.includes('')) { + const parts = text.split('') + yield { + type: 'reasoning', + reasoning_content: parts[0] + } + + if (parts[1]) { + yield { + type: 'text', + content: parts[1] + } + } + } else { + yield { + type: 'text', + content: text + } + } + } + continue + } + } + if (usageMetadata) { + yield { + type: 'usage', + usage: { + prompt_tokens: usageMetadata.input_tokens, + completion_tokens: usageMetadata.output_tokens, + total_tokens: usageMetadata.input_tokens + usageMetadata.output_tokens + } + } + } + // 发送停止事件 + yield { + type: 'stop', + stop_reason: toolUseDetected ? 'tool_use' : 'complete' + } + } catch (error) { + console.error('AWS Bedrock Claude coreStream error:', error) + yield { + type: 'error', + error_message: error instanceof Error ? error.message : '未知错误' + } + yield { type: 'stop', stop_reason: 'error' } + } + } +} diff --git a/src/renderer/src/assets/llm-icons/aws-bedrock.svg b/src/renderer/src/assets/llm-icons/aws-bedrock.svg new file mode 100644 index 000000000..e05aa0f1b --- /dev/null +++ b/src/renderer/src/assets/llm-icons/aws-bedrock.svg @@ -0,0 +1,5 @@ + + + Icon-Architecture/64/Arch_Amazon-Bedrock_64 + + diff --git a/src/renderer/src/components/icons/ModelIcon.vue b/src/renderer/src/components/icons/ModelIcon.vue index 2ef7c4db1..27cd1c744 100644 --- a/src/renderer/src/components/icons/ModelIcon.vue +++ b/src/renderer/src/components/icons/ModelIcon.vue @@ -58,6 +58,7 @@ import metaColorIcon from '@/assets/llm-icons/meta.svg?url' import lmstudioColorIcon from '@/assets/llm-icons/lmstudio.svg?url' import _302aiIcon from '@/assets/llm-icons/302ai.svg?url' import modelscopeColorIcon from '@/assets/llm-icons/modelscope-color.svg?url' +import awsBedrockIcon from '@/assets/llm-icons/aws-bedrock.svg?url' // 导入所有图标 const icons = { modelscope: modelscopeColorIcon, @@ -124,6 +125,7 @@ const icons = { o4: openaiColorIcon, glm: zhipuColorIcon, meta: metaColorIcon, + 'aws-bedrock': awsBedrockIcon, default: defaultIcon } @@ -162,7 +164,8 @@ const invert = computed(() => { props.modelId.toLowerCase().includes('groq') || props.modelId.toLowerCase().includes('github') || props.modelId.toLowerCase().includes('moonshot') || - props.modelId.toLowerCase().includes('lmstudio') + props.modelId.toLowerCase().includes('lmstudio') || + props.modelId.toLowerCase().includes('aws-bedrock') ) { return true } diff --git a/src/renderer/src/components/settings/BedrockProviderSettingsDetail.vue b/src/renderer/src/components/settings/BedrockProviderSettingsDetail.vue new file mode 100644 index 000000000..79f785c72 --- /dev/null +++ b/src/renderer/src/components/settings/BedrockProviderSettingsDetail.vue @@ -0,0 +1,285 @@ + + + + + diff --git a/src/renderer/src/components/settings/ModelProviderSettings.vue b/src/renderer/src/components/settings/ModelProviderSettings.vue index ac006f292..b76c84225 100644 --- a/src/renderer/src/components/settings/ModelProviderSettings.vue +++ b/src/renderer/src/components/settings/ModelProviderSettings.vue @@ -137,6 +137,12 @@ @auth-success="handleAnthropicAuthSuccess" @auth-error="handleAnthropicAuthError" /> + { } } + // 更新 AWS Bedrock Provider 的配置 + const updateAwsBedrockProviderConfig = async ( + providerId: string, + updates: Partial + ): Promise => { + await updateProviderConfig(providerId, updates) + const currentProvider = providers.value.find((p) => p.id === providerId)! + + // 只在特定条件下刷新模型列表 + const needRefreshModels = ['accessKeyId', 'secretAccessKey', 'region'].some( + (key) => key in updates + ) + if (needRefreshModels && currentProvider.enable) { + await refreshAllModels() + } + } + // 更新provider的API配置 const updateProviderApi = async ( providerId: string, @@ -1537,6 +1554,15 @@ export const useSettingsStore = defineStore('settings', () => { ) } + // AWS Bedrock + const setAwsBedrockCredential = async (credential: AwsBedrockCredential) => { + await configP.setSetting('awsBedrockCredential', JSON.stringify({ credential })) + } + + const getAwsBedrockCredential = async (): Promise => { + return await configP.getSetting('awsBedrockCredential') + } + // 默认系统提示词相关方法 const getDefaultSystemPrompt = async (): Promise => { return await configP.getDefaultSystemPrompt() @@ -1596,6 +1622,7 @@ export const useSettingsStore = defineStore('settings', () => { updateProviderApi, updateProviderAuth, updateProviderStatus, + updateAwsBedrockProviderConfig, refreshProviderModels, setSearchEngine, addCustomProvider, @@ -1642,6 +1669,8 @@ export const useSettingsStore = defineStore('settings', () => { getAzureApiVersion, setGeminiSafety, getGeminiSafety, + setAwsBedrockCredential, + getAwsBedrockCredential, getDefaultSystemPrompt, setDefaultSystemPrompt, setupProviderListener, diff --git a/src/shared/presenter.d.ts b/src/shared/presenter.d.ts index 9dc55b247..186e95f44 100644 --- a/src/shared/presenter.d.ts +++ b/src/shared/presenter.d.ts @@ -541,6 +541,16 @@ export interface ModelScopeMcpSyncResult { errors: string[] } +export type AWS_BEDROCK_PROVIDER = LLM_PROVIDER & { + credential?: AwsBedrockCredential +} + +export interface AwsBedrockCredential { + accessKeyId: string + secretAccessKey: string + region?: string +} + export interface ILlmProviderPresenter { setProviders(provider: LLM_PROVIDER[]): void getProviders(): LLM_PROVIDER[]