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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package llm
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import (
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"context"
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"encoding/json"
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"strings"
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"testing"
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)
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// 三家 provider 的 token 记账必须归一到同一口径（见 Usage 注释）：
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// InputTokens 含缓存段。Anthropic 尤其容易写错——它把命中/写入单列，
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// 照抄 input_tokens 就会在缓存命中时把 10 万上下文记成 5 千。
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func TestAnthropicUsageIncludesCache(t *testing.T) {
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sse := strings.Join([]string{
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`data: {"type":"message_start","message":{"usage":{"input_tokens":120,"cache_read_input_tokens":90000,"cache_creation_input_tokens":500}}}`,
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"",
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`data: {"type":"content_block_start","index":0,"content_block":{"type":"text","text":""}}`,
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"",
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`data: {"type":"content_block_delta","index":0,"delta":{"type":"text_delta","text":"ok"}}`,
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"",
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`data: {"type":"content_block_stop","index":0}`,
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"",
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// message_delta 常常不回缓存明细：必须沿用 message_start 学到的数
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`data: {"type":"message_delta","usage":{"output_tokens":7}}`,
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"",
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`data: {"type":"message_stop"}`,
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"",
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}, "\n")
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var got map[string]any
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srv := captureServer(&got, sse)
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defer srv.Close()
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p := &AnthropicProvider{BaseURL: srv.URL, APIKey: "k", Model: "claude-x"}
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msg, err := p.Stream(context.Background(), "sys",
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[]Message{{Role: RoleUser, Content: "hi"}}, nil, StreamOptions{}, nil)
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if err != nil {
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t.Fatal(err)
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}
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u := msg.Usage
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if u == nil {
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t.Fatal("没有 usage")
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}
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if u.InputTokens != 90620 {
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t.Errorf("InputTokens = %d, want 90620（120 + cache_read 90000 + cache_write 500）", u.InputTokens)
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}
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if u.CacheReadTokens != 90000 || u.CacheCreationTokens != 500 {
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t.Errorf("缓存明细 = %d/%d, want 90000/500", u.CacheReadTokens, u.CacheCreationTokens)
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}
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if u.OutputTokens != 7 {
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t.Errorf("OutputTokens = %d, want 7", u.OutputTokens)
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}
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if msg.Content != "ok" {
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t.Errorf("Content = %q", msg.Content)
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}
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}
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func TestOpenAIUsageDetails(t *testing.T) {
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sse := strings.Join([]string{
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`data: {"choices":[{"delta":{"content":"hi"}}]}`,
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"",
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`data: {"choices":[{"finish_reason":"stop"}],"usage":{"prompt_tokens":1000,"completion_tokens":20,` +
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`"prompt_tokens_details":{"cached_tokens":950},"completion_tokens_details":{"reasoning_tokens":8}}}`,
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"",
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`data: [DONE]`,
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"",
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}, "\n")
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var got map[string]any
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srv := captureServer(&got, sse)
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defer srv.Close()
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p := &OpenAIProvider{BaseURL: srv.URL, APIKey: "k", Model: "gpt-x"}
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msg, err := p.Stream(context.Background(), "sys",
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[]Message{{Role: RoleUser, Content: "hi"}}, nil, StreamOptions{}, nil)
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if err != nil {
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t.Fatal(err)
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}
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u := msg.Usage
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if u == nil {
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t.Fatal("没有 usage")
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}
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// prompt_tokens 本身已含缓存：总量不许二次相加。
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if u.InputTokens != 1000 || u.CacheReadTokens != 950 || u.ReasoningTokens != 8 || u.OutputTokens != 20 {
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t.Errorf("usage 归一错误：%+v", u)
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}
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}
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func TestResponsesUsageDetails(t *testing.T) {
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sse := strings.Join([]string{
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`data: {"type":"response.output_text.delta","delta":"hi"}`,
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"",
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`data: {"type":"response.completed","response":{"status":"completed","usage":` +
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`{"input_tokens":800,"output_tokens":15,"input_tokens_details":{"cached_tokens":700},` +
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`"output_tokens_details":{"reasoning_tokens":5}}}}`,
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"",
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}, "\n")
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var got map[string]any
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srv := captureServer(&got, sse)
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defer srv.Close()
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p := &ResponsesProvider{BaseURL: srv.URL, APIKey: "k", Model: "rsp-x"}
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msg, err := p.Stream(context.Background(), "sys",
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[]Message{{Role: RoleUser, Content: "hi"}}, nil, StreamOptions{}, nil)
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if err != nil {
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t.Fatal(err)
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}
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u := msg.Usage
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if u == nil {
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t.Fatal("没有 usage")
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}
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if u.InputTokens != 800 || u.CacheReadTokens != 700 || u.ReasoningTokens != 5 || u.OutputTokens != 15 {
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t.Errorf("usage 归一错误：%+v", u)
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}
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}
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// TestProviderIdentity：三家都自报协议与当前模型（会话落盘的归因戳）。
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// 换了模型（SetModel）之后 Identity 必须跟着变，否则戳是假的。
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func TestProviderIdentity(t *testing.T) {
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var cases = []struct {
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p Provider
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wantFmt string
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wantAttr string
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}{
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{&OpenAIProvider{Model: "gpt-a"}, FormatChatCompletions, "gpt-a"},
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{&AnthropicProvider{Model: "claude-a"}, FormatAnthropic, "claude-a"},
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{&ResponsesProvider{Model: "rsp-a"}, FormatResponses, "rsp-a"},
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}
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for _, c := range cases {
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id, ok := c.p.(Identifier)
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if !ok {
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t.Fatalf("%T 没实现 Identifier", c.p)
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}
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f, m := id.Identity()
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if f != c.wantFmt || m != c.wantAttr {
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t.Errorf("%T Identity = %q/%q, want %q/%q", c.p, f, m, c.wantFmt, c.wantAttr)
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}
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if sw, ok := c.p.(ModelSwitcher); !ok {
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t.Errorf("%T 应可切模型", c.p)
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} else {
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sw.SetModel("后到")
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if _, m := id.Identity(); m != "后到" {
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t.Errorf("SetModel 后 Identity 仍报 %q", m)
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}
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}
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}
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}
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// TestUsageSerializesIntoTranscript：新增明细字段要能落进会话文件，
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// 同时不给旧消息添噪声（omitempty）。
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func TestUsageSerializesIntoTranscript(t *testing.T) {
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old := Message{Role: RoleAssistant, Usage: &Usage{InputTokens: 5, OutputTokens: 2}}
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b, err := json.Marshal(old)
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if err != nil {
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t.Fatal(err)
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}
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for _, noise := range []string{"cache_read_tokens", "reasoning_tokens", "format", "model"} {
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if strings.Contains(string(b), noise) {
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t.Errorf("零值不该序列化出 %q：%s", noise, b)
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}
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}
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withCache := Message{Role: RoleAssistant, Format: FormatAnthropic, Model: "claude-x",
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Usage: &Usage{InputTokens: 90620, OutputTokens: 7, CacheReadTokens: 90000}}
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b2, err := json.Marshal(withCache)
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if err != nil {
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t.Fatal(err)
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}
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for _, want := range []string{"cache_read_tokens", "90000", `"format":"anthropic"`, `"model":"claude-x"`} {
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if !strings.Contains(string(b2), want) {
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t.Errorf("序列化缺 %q：%s", want, b2)
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}
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}
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}
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