Logan
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266 lines
8.7 KiB
Go
266 lines
8.7 KiB
Go
// openai.go - OpenAI 兼容 LLM 客户端实现 // Logan.Li
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// 复用 aiops 既有 LLM 调用模式（model.LLMConfig + resolveEndpoint + /chat/completions + Bearer）。
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// 支持所有 OpenAI 兼容后端：openai / deepseek / qwen / moonshot / ollama / custom。
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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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// Config LLM 客户端配置（endpoint 已由上层解析为完整 base url） // Logan.Li
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type Config struct {
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Protocol string // "openai" | "anthropic"，由 client.go 工厂决定具体实现
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Endpoint string // 完整 base url，如 https://api.deepseek.com/v1
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APIKey string // Bearer token
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Model string // 模型名，如 deepseek-chat / gpt-4o-mini
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Temperature float64 // 采样温度
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MaxTokens int // 单次最大输出 token
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ReasoningEnabled bool // 是否启用推理/Plan 模式（OpenAI o-series / DeepSeek R1 等） // Logan.Li
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Timeout time.Duration // HTTP 超时（0 表示使用默认 180s）
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}
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// OpenAIClient OpenAI 兼容客户端 // Logan.Li
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type OpenAIClient struct {
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cfg Config
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client *http.Client
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}
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// NewOpenAIClient 创建 OpenAI 兼容客户端 // Logan.Li
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// 顶层工厂在 client.go（按 Protocol 路由到 OpenAI / Anthropic 实现）。
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func NewOpenAIClient(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 &OpenAIClient{
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cfg: cfg,
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client: &http.Client{Timeout: timeout},
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}
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}
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// Name 返回客户端名称 // Logan.Li
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func (c *OpenAIClient) Name() string { return "openai-compatible(" + c.cfg.Model + ")" }
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// isOpenAIReasoningModel 判断是否为需要 reasoning_effort 的 OpenAI o-series 模型 // Logan.Li
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func isOpenAIReasoningModel(model string) bool {
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m := strings.ToLower(model)
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return strings.Contains(m, "o1") || strings.Contains(m, "o3")
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}
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// isGenericReasoningModel 判断是否为通用推理开关模型（DeepSeek R1 等） // Logan.Li
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func isGenericReasoningModel(model string) bool {
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m := strings.ToLower(model)
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return strings.Contains(m, "reasoning") || strings.Contains(m, "r1") || strings.Contains(m, "deepseek-reasoner")
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}
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// applyReasoningParams 根据模型类型应用 reasoning 参数 // Logan.Li
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func applyReasoningParams(payload *openaiRequest, enabled bool) {
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if !enabled {
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return
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}
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if isOpenAIReasoningModel(payload.Model) {
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// OpenAI o-series 使用 reasoning_effort，temperature 必须固定为 1（不传） // Logan.Li
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payload.ReasoningEffort = "medium"
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payload.Temperature = 0
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return
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}
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if isGenericReasoningModel(payload.Model) {
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payload.Reasoning = true
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}
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}
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// openaiRequest OpenAI chat/completions 请求体 // Logan.Li
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type openaiRequest struct {
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Model string `json:"model"`
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Messages []Message `json:"messages"`
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Tools []Tool `json:"tools,omitempty"`
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ToolChoice string `json:"tool_choice,omitempty"` // "auto" 让模型自主决定
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Temperature float64 `json:"temperature,omitempty"`
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MaxTokens int `json:"max_tokens,omitempty"`
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Stream bool `json:"stream,omitempty"` // 流式补全（Stream 方法置 true）
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ReasoningEffort string `json:"reasoning_effort,omitempty"` // OpenAI o-series 推理强度 // Logan.Li
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Reasoning bool `json:"reasoning,omitempty"` // DeepSeek 等部分平台推理开关 // Logan.Li
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}
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// openaiResponse OpenAI chat/completions 响应体 // Logan.Li
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type openaiResponse struct {
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Choices []struct {
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Message struct {
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Role string `json:"role"`
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Content string `json:"content"`
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ToolCalls []ToolCall `json:"tool_calls"`
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} `json:"message"`
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} `json:"choices"`
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Usage Usage `json:"usage"`
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Error *struct {
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Message string `json:"message"`
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Type string `json:"type"`
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} `json:"error,omitempty"`
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}
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// Complete 调用 OpenAI 兼容接口完成一轮补全 // Logan.Li
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// 返回 assistant 消息（含思考文本 content 与工具调用计划 tool_calls）+ token 统计。
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func (c *OpenAIClient) Complete(ctx context.Context, req *CompletionRequest) (*CompletionResponse, error) {
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payload := openaiRequest{
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Model: c.cfg.Model,
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Messages: req.Messages,
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Tools: req.Tools,
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ToolChoice: "auto",
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Temperature: c.cfg.Temperature,
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MaxTokens: c.cfg.MaxTokens,
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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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applyReasoningParams(&payload, req.ReasoningEnabled || c.cfg.ReasoningEnabled)
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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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url := c.cfg.Endpoint + "/chat/completions"
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httpReq, err := http.NewRequestWithContext(ctx, http.MethodPost, url, 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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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 openaiResponse
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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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if len(parsed.Choices) == 0 {
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return nil, fmt.Errorf("LLM 未返回任何结果")
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}
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choice := parsed.Choices[0].Message
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return &CompletionResponse{
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Model: c.cfg.Model,
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Message: Message{
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Role: choice.Role,
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Content: choice.Content,
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ToolCalls: choice.ToolCalls,
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},
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Usage: parsed.Usage,
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}, nil
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}
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// Stream 流式补全（OpenAI 兼容 SSE），逐 token 回调 onDelta，返回聚合响应 // Logan.Li
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// 解析 data: {"choices":[{"delta":{"content":"..."}}]} 增量；[DONE] 结束；末块 usage 若有则取。
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func (c *OpenAIClient) Stream(ctx context.Context, req *CompletionRequest, onDelta func(string)) (*CompletionResponse, error) {
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payload := openaiRequest{
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Model: c.cfg.Model,
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Messages: req.Messages,
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Tools: req.Tools,
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ToolChoice: "auto",
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Temperature: c.cfg.Temperature,
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MaxTokens: c.cfg.MaxTokens,
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Stream: true,
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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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applyReasoningParams(&payload, req.ReasoningEnabled || c.cfg.ReasoningEnabled)
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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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url := c.cfg.Endpoint + "/chat/completions"
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httpReq, err := http.NewRequestWithContext(ctx, http.MethodPost, url, 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("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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reader := bufio.NewReader(resp.Body)
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for {
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line, readErr := reader.ReadString('\n')
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line = strings.TrimSpace(line)
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if line != "" && strings.HasPrefix(line, "data:") {
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data := strings.TrimSpace(strings.TrimPrefix(line, "data:"))
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if data == "[DONE]" {
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break
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}
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var chunk struct {
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Choices []struct {
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Delta struct {
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Content string `json:"content"`
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} `json:"delta"`
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} `json:"choices"`
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Usage *Usage `json:"usage"`
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}
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if json.Unmarshal([]byte(data), &chunk) == nil {
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if len(chunk.Choices) > 0 && chunk.Choices[0].Delta.Content != "" {
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delta := chunk.Choices[0].Delta.Content
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contentBuilder.WriteString(delta)
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if onDelta != nil {
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onDelta(delta)
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}
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}
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if chunk.Usage != nil {
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usage = *chunk.Usage
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}
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}
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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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// extractErrorMessage 从上游错误响应提取 message 字段 // Logan.Li
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func extractErrorMessage(raw []byte) string {
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var m struct {
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Error struct {
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Message string `json:"message"`
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} `json:"error"`
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}
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if json.Unmarshal(raw, &m) == nil && m.Error.Message != "" {
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return m.Error.Message
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}
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return string(raw)
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}
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