feat(llm): 大模型双协议(OpenAI+Anthropic)接入 + SSH凭证修复 + 容量预测AI解读
后端双协议: 新增 anthropic.go(Complete/Stream/工具转换) + client.go 工厂按 Protocol 路由; llm.Client 加 Stream; llm_chat 三方法收敛复用 llm.Client; resolveProtocol 按 provider 路由; Agent CLI 注入协议。编码套餐(GLM-5.2/Kimi/MiMo/Anthropic)走 Anthropic /v1/messages。 SSH凭证修复: applyCredential 正确解析凭证 JSON 的 private_key(旧实现把整个 JSON 当私钥 → ssh.ParsePrivateKey 失败 → ssh-key 登录不通); AssignCredential/批量导入/单台 CRUD 三处统一; 单台补齐 credential_id 字段(原被忽略)。 容量预测: 新增 AI 深度解读(buildCapacityInsightPrompt + PredictiveCapacityTab 按钮, 复用 aiApi.chat)。 其他: DeepSeek 模型名更新为 deepseek-v4-flash/pro; 智能助手去掉重复模型配置按钮; LLMConfig 精简生成参数(Claude Code 式)。 Co-Authored-By: Claude <noreply@anthropic.com>
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// anthropic.go - Anthropic Messages 协议 LLM 客户端实现 // Logan.Li
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// 支持官方 Claude（api.anthropic.com）及智谱 GLM 编码套餐（open.bigmodel.cn/api/anthropic）等
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// 所有 Anthropic /v1/messages 兼容端点。与 openai.go 实现同一 Client 接口，由 client.go 按 Protocol 路由。
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// 鉴权统一用 Authorization: Bearer（智谱编码套餐实测通过；官方 Claude 较新版本亦支持）+ anthropic-version。
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package llm
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import (
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"bufio"
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"bytes"
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"context"
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"encoding/json"
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"fmt"
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"io"
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"net/http"
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"strings"
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"time"
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)
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// AnthropicClient Anthropic Messages 协议客户端 // Logan.Li
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type AnthropicClient struct {
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cfg Config
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client *http.Client
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}
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// NewAnthropicClient 创建 Anthropic 兼容客户端 // Logan.Li
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func NewAnthropicClient(cfg Config) Client {
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timeout := cfg.Timeout
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if timeout <= 0 {
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timeout = 180 * time.Second
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}
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return &AnthropicClient{cfg: cfg, client: &http.Client{Timeout: timeout}}
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}
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// Name 返回客户端名称 // Logan.Li
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func (c *AnthropicClient) Name() string { return "anthropic(" + c.cfg.Model + ")" }
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// ---- 请求体结构（Anthropic Messages 格式） // Logan.Li ----
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// anthropicMessage Anthropic 消息：content 可为字符串或 block 数组，用 RawMessage 原样嵌入。
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type anthropicMessage struct {
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Role string `json:"role"`
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Content json.RawMessage `json:"content"`
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}
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// anthropicRequest Anthropic /v1/messages 请求体 // Logan.Li
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type anthropicRequest struct {
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Model string `json:"model"`
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MaxTokens int `json:"max_tokens"`
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System string `json:"system,omitempty"` // system 抽到顶层（不在 messages 内）
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Messages []anthropicMessage `json:"messages"`
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Tools []anthropicTool `json:"tools,omitempty"`
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Temperature float64 `json:"temperature,omitempty"`
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Stream bool `json:"stream,omitempty"`
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}
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// anthropicTool Anthropic 工具定义（input_schema，对应 OpenAI 的 parameters） // Logan.Li
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type anthropicTool struct {
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Name string `json:"name"`
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Description string `json:"description"`
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InputSchema map[string]interface{} `json:"input_schema"`
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}
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// 响应 content block：text 或 tool_use（互斥字段） // Logan.Li
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type anthropicBlock struct {
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Type string `json:"type"` // text | tool_use
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Text string `json:"text,omitempty"`
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ID string `json:"id,omitempty"` // tool_use
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Name string `json:"name,omitempty"` // tool_use
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Input json.RawMessage `json:"input,omitempty"` // tool_use
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}
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// 请求侧 content block（assistant 输出 tool_use / user 输出 tool_result） // Logan.Li
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type textBlock struct {
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Type string `json:"type"` // 固定 "text"
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Text string `json:"text"`
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}
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type toolUseBlock struct {
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Type string `json:"type"` // 固定 "tool_use"
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ID string `json:"id"`
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Name string `json:"name"`
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Input json.RawMessage `json:"input"`
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}
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type toolResultBlock struct {
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Type string `json:"type"` // 固定 "tool_result"
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ToolUseID string `json:"tool_use_id"`
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Content string `json:"content"`
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}
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// anthropicResponse Anthropic /v1/messages 响应体 // Logan.Li
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type anthropicResponse struct {
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ID string `json:"id"`
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Model string `json:"model"`
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Content []anthropicBlock `json:"content"`
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Usage struct {
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InputTokens int `json:"input_tokens"`
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OutputTokens int `json:"output_tokens"`
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} `json:"usage"`
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Error *struct {
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Type string `json:"type"`
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Message string `json:"message"`
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} `json:"error,omitempty"`
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}
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// buildMessages 把 OpenAI 风格 Message[] 转成 Anthropic messages + 顶层 system // Logan.Li
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// - system role 抽到顶层 system 字段
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// - tool role（工具结果）→ user 消息的 tool_result 块
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// - assistant 带 tool_calls → content 含 tool_use 块
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func (c *AnthropicClient) buildMessages(req *CompletionRequest) (string, []anthropicMessage) {
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var system string
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var msgs []anthropicMessage
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for _, m := range req.Messages {
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switch m.Role {
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case "system":
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if system == "" {
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system = m.Content
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} else {
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system += "\n" + m.Content
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}
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case "tool":
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raw, _ := json.Marshal([]toolResultBlock{{
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Type: "tool_result", ToolUseID: m.ToolCallID, Content: m.Content,
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}})
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msgs = append(msgs, anthropicMessage{Role: "user", Content: raw})
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case "assistant":
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// assistant 消息可能含文本 + tool_use 计划，组装成 content block 数组
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blocks := make([]interface{}, 0, 1+len(m.ToolCalls))
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if m.Content != "" {
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blocks = append(blocks, textBlock{Type: "text", Text: m.Content})
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}
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for _, tc := range m.ToolCalls {
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args := json.RawMessage("{}")
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if strings.TrimSpace(tc.Function.Arguments) != "" {
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args = json.RawMessage(tc.Function.Arguments)
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}
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blocks = append(blocks, toolUseBlock{
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Type: "tool_use", ID: tc.ID, Name: tc.Function.Name, Input: args,
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})
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}
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raw, _ := json.Marshal(blocks)
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msgs = append(msgs, anthropicMessage{Role: "assistant", Content: raw})
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default: // user
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raw, _ := json.Marshal(m.Content)
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msgs = append(msgs, anthropicMessage{Role: "user", Content: raw})
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}
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}
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return system, msgs
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}
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// buildTools OpenAI Tool[](parameters) → Anthropic [](input_schema) // Logan.Li
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func buildTools(tools []Tool) []anthropicTool {
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out := make([]anthropicTool, 0, len(tools))
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for _, t := range tools {
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out = append(out, anthropicTool{
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Name: t.Function.Name, Description: t.Function.Description, InputSchema: t.Function.Parameters,
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})
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}
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return out
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}
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// buildRequest 构造 Anthropic 请求体（Complete 与 Stream 共用） // Logan.Li
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func (c *AnthropicClient) buildRequest(req *CompletionRequest, stream bool) ([]byte, error) {
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system, msgs := c.buildMessages(req)
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payload := anthropicRequest{
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Model: c.cfg.Model, MaxTokens: c.cfg.MaxTokens, System: system,
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Messages: msgs, Tools: buildTools(req.Tools),
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Temperature: c.cfg.Temperature, Stream: stream,
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}
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if payload.MaxTokens <= 0 {
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payload.MaxTokens = 4096
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}
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body, err := json.Marshal(payload)
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if err != nil {
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return nil, fmt.Errorf("序列化请求失败: %w", err)
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}
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return body, nil
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}
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// newHTTPRequest 构造 POST /v1/messages 请求（Bearer + anthropic-version） // Logan.Li
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func (c *AnthropicClient) newHTTPRequest(ctx context.Context, body []byte) (*http.Request, error) {
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httpReq, err := http.NewRequestWithContext(ctx, http.MethodPost, c.cfg.Endpoint+"/v1/messages", bytes.NewReader(body))
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if err != nil {
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return nil, fmt.Errorf("构造请求失败: %w", err)
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}
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httpReq.Header.Set("Content-Type", "application/json")
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httpReq.Header.Set("Authorization", "Bearer "+c.cfg.APIKey)
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httpReq.Header.Set("anthropic-version", "2023-06-01")
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return httpReq, nil
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}
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// Complete 一次性补全（Anthropic /v1/messages） // Logan.Li
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// 响应 content blocks：text 拼为 Content，tool_use 转为 ToolCalls；usage 映射。
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func (c *AnthropicClient) Complete(ctx context.Context, req *CompletionRequest) (*CompletionResponse, error) {
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body, err := c.buildRequest(req, false)
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if err != nil {
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return nil, err
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}
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httpReq, err := c.newHTTPRequest(ctx, body)
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if err != nil {
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return nil, err
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}
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resp, err := c.client.Do(httpReq)
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if err != nil {
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return nil, fmt.Errorf("LLM 连接失败: %w", err)
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}
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defer resp.Body.Close()
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raw, _ := io.ReadAll(resp.Body)
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if resp.StatusCode != http.StatusOK {
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return nil, fmt.Errorf("LLM 返回错误 (HTTP %d): %s", resp.StatusCode, extractErrorMessage(raw))
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}
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var parsed anthropicResponse
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if err := json.Unmarshal(raw, &parsed); err != nil {
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return nil, fmt.Errorf("解析 LLM 响应失败: %w", err)
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}
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if parsed.Error != nil && parsed.Error.Message != "" {
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return nil, fmt.Errorf("LLM 错误: %s", parsed.Error.Message)
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}
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var textBuf strings.Builder
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var toolCalls []ToolCall
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for _, b := range parsed.Content {
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switch b.Type {
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case "text":
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textBuf.WriteString(b.Text)
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case "tool_use":
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args := string(b.Input)
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if strings.TrimSpace(args) == "" {
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args = "{}"
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}
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toolCalls = append(toolCalls, ToolCall{
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ID: b.ID, Type: "function",
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Function: FunctionCall{Name: b.Name, Arguments: args},
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})
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}
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}
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return &CompletionResponse{
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ID: parsed.ID,
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Model: parsed.Model,
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Message: Message{
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Role: "assistant",
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Content: textBuf.String(),
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ToolCalls: toolCalls,
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},
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Usage: Usage{
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PromptTokens: parsed.Usage.InputTokens,
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CompletionTokens: parsed.Usage.OutputTokens,
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TotalTokens: parsed.Usage.InputTokens + parsed.Usage.OutputTokens,
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},
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}, nil
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}
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// Stream 流式补全（Anthropic SSE） // Logan.Li
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// 逐 token 回调 text_delta；usage 从 message_start(input) + message_delta(output) 取。
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// 注：流式主要用于纯对话（智能助手），tool_use 流式增量在此不组装（Agent CLI 走 Complete）。
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func (c *AnthropicClient) Stream(ctx context.Context, req *CompletionRequest, onDelta func(string)) (*CompletionResponse, error) {
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body, err := c.buildRequest(req, true)
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if err != nil {
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return nil, err
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}
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httpReq, err := c.newHTTPRequest(ctx, body)
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if err != nil {
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return nil, err
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}
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httpReq.Header.Set("Accept", "text/event-stream")
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streamClient := &http.Client{Timeout: 0} // 流式由 ctx 控制超时
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resp, err := streamClient.Do(httpReq)
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if err != nil {
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return nil, fmt.Errorf("LLM 连接失败: %w", err)
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}
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defer resp.Body.Close()
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if resp.StatusCode != http.StatusOK {
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raw, _ := io.ReadAll(resp.Body)
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return nil, fmt.Errorf("LLM 返回错误 (HTTP %d): %s", resp.StatusCode, extractErrorMessage(raw))
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}
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var contentBuilder strings.Builder
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var usage Usage
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var eventType string
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reader := bufio.NewReader(resp.Body)
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for {
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line, readErr := reader.ReadString('\n')
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trimmed := strings.TrimSpace(line)
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switch {
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case strings.HasPrefix(trimmed, "event:"):
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eventType = strings.TrimSpace(strings.TrimPrefix(trimmed, "event:"))
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case strings.HasPrefix(trimmed, "data:"):
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data := strings.TrimSpace(strings.TrimPrefix(trimmed, "data:"))
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if data != "" && data != "[DONE]" {
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switch eventType {
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case "content_block_delta":
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var d struct {
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Delta struct {
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Type string `json:"type"`
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Text string `json:"text"`
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} `json:"delta"`
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}
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if json.Unmarshal([]byte(data), &d) == nil && d.Delta.Type == "text_delta" && d.Delta.Text != "" {
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contentBuilder.WriteString(d.Delta.Text)
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if onDelta != nil {
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onDelta(d.Delta.Text)
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}
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}
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case "message_start":
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var d struct {
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Message struct {
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Usage struct {
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InputTokens int `json:"input_tokens"`
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} `json:"usage"`
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} `json:"message"`
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}
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if json.Unmarshal([]byte(data), &d) == nil {
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usage.PromptTokens = d.Message.Usage.InputTokens
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}
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case "message_delta":
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var d struct {
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Usage struct {
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OutputTokens int `json:"output_tokens"`
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} `json:"usage"`
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}
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if json.Unmarshal([]byte(data), &d) == nil {
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usage.CompletionTokens = d.Usage.OutputTokens
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usage.TotalTokens = usage.PromptTokens + usage.CompletionTokens
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}
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}
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}
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eventType = "" // 消费完 data 重置，防默认事件串用
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}
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if readErr != nil {
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break
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}
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}
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return &CompletionResponse{
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Model: c.cfg.Model,
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Message: Message{Role: "assistant", Content: contentBuilder.String()},
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Usage: usage,
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}, nil
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}
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