feat: AutoZero 通用 Agent 框架（从 AutoGo 五阶段拆分完成）
llm（三协议 Provider）/ session（JSONL 持久化）/ tools（Registry、围栏、 builtin、computer）/ cdp（browser）/ skills / mcp / agent（循环、两级压缩、 编排、审批门控）+ 底座 jsonl/textx/execx/diag/scratch/spill/imagecache。 产品装配代码（config 桥接、schedule 工具、memory/plan/retro/prompt） 留在 AutoGo，宿主接入方式见 MIGRATION.md。
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Sakurasan committed
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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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)
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// imageCache 是全局图片缓存实例。
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var imageCache ImageCache
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// ImageCache 是图片缓存接口。
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type ImageCache interface {
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LoadWithMIME(filename string) (string, string, error)
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}
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// SetImageCache 设置全局图片缓存。
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func SetImageCache(cache ImageCache) {
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imageCache = cache
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}
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// OpenAIProvider 走 OpenAI 兼容的 /chat/completions 协议（含大多数国产网关）。
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type OpenAIProvider struct {
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BaseURL string
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APIKey string
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Model string
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HTTP *http.Client
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}
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type oaFunction struct {
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Name string `json:"name"`
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Arguments string `json:"arguments"`
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}
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// modelListResponse 是 OpenAI 兼容 GET /models 的响应。
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type modelListResponse struct {
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Data []struct {
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ID string `json:"id"`
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} `json:"data"`
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}
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// SetModel 运行时切换模型（ModelSwitcher）。
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func (p *OpenAIProvider) SetModel(model string) {
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p.Model = model
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}
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// CurrentModel 报告当前模型（CurrentModeler）。
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func (p *OpenAIProvider) CurrentModel() string { return p.Model }
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// Identity 自报协议与当前模型（Identifier）。
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func (p *OpenAIProvider) Identity() (string, string) { return FormatChatCompletions, p.Model }
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// ListModels 枚举网关可用模型（ModelLister）。
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func (p *OpenAIProvider) ListModels(ctx context.Context) ([]string, error) {
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req, err := http.NewRequestWithContext(ctx, http.MethodGet,
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strings.TrimRight(p.BaseURL, "/")+"/models", nil)
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if err != nil {
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return nil, err
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}
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req.Header.Set("Authorization", "Bearer "+p.APIKey)
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resp, err := p.http().Do(req)
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if err != nil {
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return nil, 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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var buf bytes.Buffer
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_, _ = buf.ReadFrom(io.LimitReader(resp.Body, 4096))
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return nil, fmt.Errorf("openai: ListModels: HTTP %d: %s", resp.StatusCode, buf.String())
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}
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var out modelListResponse
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if err := json.NewDecoder(resp.Body).Decode(&out); err != nil {
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return nil, err
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}
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models := make([]string, 0, len(out.Data))
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for _, d := range out.Data {
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if d.ID != "" {
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models = append(models, d.ID)
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}
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}
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return models, nil
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}
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type oaChunk 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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// 思考内容：网关字段名不统一（DeepSeek 等用 reasoning_content，
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// 部分 OpenAI 兼容网关用 reasoning），两者都收。
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ReasoningContent string `json:"reasoning_content"`
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Reasoning string `json:"reasoning"`
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ToolCalls []struct {
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Index int `json:"index"`
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ID string `json:"id"`
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Function oaFunction `json:"function"`
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} `json:"tool_calls"`
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} `json:"delta"`
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FinishReason string `json:"finish_reason"`
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} `json:"choices"`
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Usage *struct {
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PromptTokens int `json:"prompt_tokens"`
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CompletionTokens int `json:"completion_tokens"`
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// 明细：Chat Completions 的 prompt_tokens 已含缓存命中部分，这里只取 breakdown。
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// 兼容网关不一定返回，缺省为 0。
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PromptDetails struct {
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Cached int `json:"cached_tokens"`
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} `json:"prompt_tokens_details"`
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CompletionDetails struct {
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Reasoning int `json:"reasoning_tokens"`
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} `json:"completion_tokens_details"`
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} `json:"usage"`
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}
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func (p *OpenAIProvider) Stream(ctx context.Context, system string, msgs []Message, tools []ToolDef, opts StreamOptions, onDelta func(StreamDelta)) (Message, error) {
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body := map[string]any{
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"model": p.Model,
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"messages": oaBuildMessages(joinSystem(system, opts.SystemDynamic), msgs),
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"stream": true,
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"stream_options": map[string]any{"include_usage": true},
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}
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if len(tools) > 0 {
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body["tools"] = oaBuildTools(tools)
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// 只禁用调用、不撤定义：工具数组保持不变，prompt cache 前缀才能命中。
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if opts.DisableTools {
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body["tool_choice"] = "none"
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}
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}
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// 思考级别：仅开启时发送，默认关闭保持请求体不变。
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if opts.Thinking.Enabled() {
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body["reasoning_effort"] = string(opts.Thinking)
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}
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payload, err := json.Marshal(body)
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if err != nil {
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return Message{}, err
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}
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req, err := http.NewRequestWithContext(ctx, http.MethodPost,
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strings.TrimRight(p.BaseURL, "/")+"/chat/completions", bytes.NewReader(payload))
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if err != nil {
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return Message{}, err
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}
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req.Header.Set("Content-Type", "application/json")
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req.Header.Set("Authorization", "Bearer "+p.APIKey)
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resp, err := doWithRetry(ctx, p.http(), req, payload)
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if err != nil {
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return Message{}, 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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var buf bytes.Buffer
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_, _ = buf.ReadFrom(io.LimitReader(resp.Body, 4096))
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return Message{}, fmt.Errorf("openai: HTTP %d: %s", resp.StatusCode, buf.String())
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}
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final := Message{Role: RoleAssistant}
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var callsByIndex = map[int]*ToolCall{}
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maxIndex := -1
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emitted := map[int]bool{}
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// emitReady 把 index < upTo 的工具调用视为参数完整并提前通知。
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// OpenAI 的增量协议没有显式"调用结束"事件：下一个 index 出现、或
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// finish_reason 到达，前一个调用的参数就完整了。
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emitReady := func(upTo int) {
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if onDelta == nil {
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return
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}
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for i := 0; i < upTo; i++ {
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if emitted[i] {
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continue
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}
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c := callsByIndex[i]
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if c == nil || c.Name == "" {
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continue
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}
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emitted[i] = true
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tc := *c
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onDelta(StreamDelta{ToolCall: &tc})
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}
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}
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sg := guardStream(resp.Body, streamIdleTimeout)
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defer sg.Stop()
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sc := bufio.NewScanner(sg)
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sc.Buffer(make([]byte, 1<<20), 1<<20)
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var st streamState
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for sc.Scan() {
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line := sc.Text()
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if !strings.HasPrefix(line, "data: ") {
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continue
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}
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data := strings.TrimPrefix(line, "data: ")
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if data == "[DONE]" {
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st.doneSeen = true
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break
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}
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var ck oaChunk
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if err := json.Unmarshal([]byte(data), &ck); err != nil {
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continue
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}
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if ck.Usage != nil {
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st.usageSeen = true
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final.Usage = &Usage{
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InputTokens: ck.Usage.PromptTokens,
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OutputTokens: ck.Usage.CompletionTokens,
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CacheReadTokens: ck.Usage.PromptDetails.Cached,
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ReasoningTokens: ck.Usage.CompletionDetails.Reasoning,
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}
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}
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for _, ch := range ck.Choices {
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if ch.FinishReason != "" {
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st.doneSeen = true // finish_reason 也是终止证据
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if marksOutputLimit(ch.FinishReason) {
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final.OutputLimited = true
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}
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}
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reasoning := ch.Delta.ReasoningContent
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if reasoning == "" {
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reasoning = ch.Delta.Reasoning
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}
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if reasoning != "" {
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final.Reasoning += reasoning
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if onDelta != nil {
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onDelta(StreamDelta{Reasoning: reasoning})
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}
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}
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if ch.Delta.Content != "" {
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final.Content += ch.Delta.Content
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if onDelta != nil {
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onDelta(StreamDelta{Text: ch.Delta.Content})
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}
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}
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for _, tc := range ch.Delta.ToolCalls {
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cur := callsByIndex[tc.Index]
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if cur == nil {
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cur = &ToolCall{}
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callsByIndex[tc.Index] = cur
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}
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if tc.Index > maxIndex {
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maxIndex = tc.Index
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}
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if tc.ID != "" {
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cur.ID = tc.ID
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}
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if tc.Function.Name != "" {
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cur.Name = tc.Function.Name
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}
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if tc.Function.Arguments != "" {
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cur.Input += tc.Function.Arguments
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}
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emitReady(tc.Index)
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}
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if ch.FinishReason != "" {
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emitReady(maxIndex + 1)
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}
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}
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}
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if err := sc.Err(); err != nil {
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// 被静默看门狗掐断时，说真实原因：那句 "read on closed response body"
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// 对排查毫无帮助，看起来像我们自己的连接坏了。
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if stall := sg.Err(); stall != nil {
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return Message{}, fmt.Errorf("openai: %w", stall)
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}
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return Message{}, fmt.Errorf("openai: stream: %w", err)
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}
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// 没等到 [DONE] 就结束，且是看门狗掐断的：不能把半截回复当完整结果返回。
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if stall := sg.Err(); stall != nil {
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return Message{}, fmt.Errorf("openai: %w", stall)
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}
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// 流结束还没发完的通知（例如只有一个 tool call、没有下一个 index）在这里补齐。
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emitReady(maxIndex + 1)
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for i := 0; i <= maxIndex; i++ {
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if c, ok := callsByIndex[i]; ok {
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final.ToolCalls = append(final.ToolCalls, *c)
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}
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}
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return completion("openai", final, st)
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}
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// joinSystem 把动态 system 追加到稳定 system 尾部。只要动态段在整条消息的末尾，
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// 稳定前缀仍然逐 token 相同，OpenAI 的自动前缀缓存就能继续命中；用一条消息也
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// 避免部分兼容网关不接受多条 system 消息。
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func joinSystem(system, dynamic string) string {
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if dynamic == "" {
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return system
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}
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if system == "" {
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return dynamic
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}
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return system + "\n\n" + dynamic
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}
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func oaBuildMessages(system string, msgs []Message) []map[string]any {
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out := []map[string]any{}
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if system != "" {
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out = append(out, map[string]any{"role": "system", "content": system})
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}
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for _, m := range msgs {
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switch {
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case m.Role == RoleTool:
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out = append(out, map[string]any{"role": "tool", "content": m.Content, "tool_call_id": m.ToolCallID})
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// OpenAI tool 消息不支持图片：以 user 消息附图（紧随 tool result）。
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if len(m.Images) > 0 {
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out = append(out, map[string]any{
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"role": "user",
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"content": oaContentParts("[image(s) attached from tool result]", m.Images),
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})
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}
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case len(m.ToolCalls) > 0:
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tcs := []map[string]any{}
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for _, tc := range m.ToolCalls {
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tcs = append(tcs, map[string]any{
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"id": tc.ID, "type": "function",
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"function": map[string]any{"name": tc.Name, "arguments": tc.Input},
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})
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}
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out = append(out, map[string]any{"role": "assistant", "content": m.Content, "tool_calls": tcs})
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case len(m.Images) > 0:
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out = append(out, map[string]any{"role": string(m.Role), "content": oaContentParts(m.Content, m.Images)})
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default:
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out = append(out, map[string]any{"role": string(m.Role), "content": m.Content})
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}
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}
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return out
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}
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// oaContentParts 构造 OpenAI 多模态 content 数组；读取失败的图降级为文本说明。
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// 支持两种图片引用方式：
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// 1. Filename: 从缓存目录加载（优先）
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// 2. Path: 直接文件路径（兼容旧格式）
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func oaContentParts(text string, imgs []Image) []map[string]any {
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parts := []map[string]any{}
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if text != "" {
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parts = append(parts, map[string]any{"type": "text", "text": text})
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}
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for _, img := range imgs {
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b64, mt, err := loadImageRef(img)
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if err != nil {
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parts = append(parts, map[string]any{"type": "text", "text": imageUnavailable(img, err)})
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continue
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}
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parts = append(parts, map[string]any{
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"type": "image_url",
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"image_url": map[string]any{"url": "data:" + mt + ";base64," + b64},
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})
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}
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return parts
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}
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func oaBuildTools(tools []ToolDef) []map[string]any {
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out := make([]map[string]any, 0, len(tools))
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for _, t := range tools {
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out = append(out, map[string]any{
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"type": "function",
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"function": map[string]any{
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"name": t.Name,
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"description": t.Description,
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"parameters": t.Parameters,
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},
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})
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}
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return out
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}
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func (p *OpenAIProvider) http() *http.Client {
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if p.HTTP != nil {
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return p.HTTP
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}
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return defaultHTTPClient
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}
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