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。
2026-10-26 00:54:46 +08:00
commit d5dac5a6fc
@@ -0,0 +1,129 @@
+package llm
+
+import (
+	"context"
+	"strings"
+	"testing"
+)
+
+// 输出上限切断的识别：三家的叫法不同，归一成 Message.OutputLimited 一个信号。
+// 每个 fixture 都带正文——"什么都没有"是空回复那条路（ErrEmptyCompletion），
+// 这里要抓的是"合法、有内容、但没写完"。
+func TestProvidersDetectOutputLimit(t *testing.T) {
+	cases := []struct {
+		name string
+		sse  string
+		call func(url string) (Provider, error)
+		want bool
+	}{
+		{
+			name: "chat_completions：finish_reason=length",
+			sse: "data: {\"choices\":[{\"delta\":{\"content\":\"第一段写完了，第二段\"}}]}\n\n" +
+				"data: {\"choices\":[{\"delta\":{},\"finish_reason\":\"length\"}],\"usage\":{\"prompt_tokens\":5,\"completion_tokens\":7}}\n\n" +
+				"data: [DONE]\n\n",
+			call: func(u string) (Provider, error) { return &OpenAIProvider{BaseURL: u, APIKey: "k", Model: "m"}, nil },
+			want: true,
+		},
+		{
+			name: "chat_completions：finish_reason=stop 是正常收尾",
+			sse: "data: {\"choices\":[{\"delta\":{\"content\":\"说完了\"}}]}\n\n" +
+				"data: {\"choices\":[{\"delta\":{},\"finish_reason\":\"stop\"}],\"usage\":{\"prompt_tokens\":5,\"completion_tokens\":3}}\n\n" +
+				"data: [DONE]\n\n",
+			call: func(u string) (Provider, error) { return &OpenAIProvider{BaseURL: u, APIKey: "k", Model: "m"}, nil },
+			want: false,
+		},
+		{
+			// 上下文满 ≠ 输出被切断：续写只会连着撞同一堵墙，该走压缩。
+			name: "chat_completions：context window 不算输出切断",
+			sse: "data: {\"choices\":[{\"delta\":{\"content\":\"半截\"}}]}\n\n" +
+				"data: {\"choices\":[{\"delta\":{},\"finish_reason\":\"model_context_window_exceeded\"}],\"usage\":{\"prompt_tokens\":5,\"completion_tokens\":2}}\n\n" +
+				"data: [DONE]\n\n",
+			call: func(u string) (Provider, error) { return &OpenAIProvider{BaseURL: u, APIKey: "k", Model: "m"}, nil },
+			want: false,
+		},
+		{
+			name: "anthropic：message_delta 的 stop_reason=max_tokens",
+			sse: "data: {\"type\":\"content_block_start\",\"index\":0,\"content_block\":{\"type\":\"text\",\"text\":\"\"}}\n\n" +
+				"data: {\"type\":\"content_block_delta\",\"index\":0,\"delta\":{\"type\":\"text_delta\",\"text\":\"还在写\"}}\n\n" +
+				"data: {\"type\":\"message_delta\",\"delta\":{\"stop_reason\":\"max_tokens\"},\"usage\":{\"output_tokens\":64}}\n\n" +
+				"data: {\"type\":\"message_stop\"}\n\n",
+			call: func(u string) (Provider, error) {
+				return &AnthropicProvider{BaseURL: u, APIKey: "k", Model: "m", MaxTokens: 128}, nil
+			},
+			want: true,
+		},
+		{
+			name: "responses：incomplete + max_output_tokens",
+			sse: "data: {\"type\":\"response.output_text.delta\",\"delta\":\"写了一半\"}\n\n" +
+				"data: {\"type\":\"response.incomplete\",\"response\":{\"status\":\"incomplete\",\"output\":[],\"incomplete_details\":{\"reason\":\"max_output_tokens\"},\"usage\":{\"input_tokens\":4,\"output_tokens\":9}}}\n\n",
+			call: func(u string) (Provider, error) { return &ResponsesProvider{BaseURL: u, APIKey: "k", Model: "m"}, nil },
+			want: true,
+		},
+		{
+			// 审核拦下的 incomplete 续写无意义（模型不是没写完，是不肯写完）。
+			name: "responses：incomplete 但原因是内容审核",
+			sse: "data: {\"type\":\"response.output_text.delta\",\"delta\":\"抱歉\"}\n\n" +
+				"data: {\"type\":\"response.incomplete\",\"response\":{\"status\":\"incomplete\",\"output\":[],\"incomplete_details\":{\"reason\":\"content_filter\"},\"usage\":{\"input_tokens\":4,\"output_tokens\":2}}}\n\n",
+			call: func(u string) (Provider, error) { return &ResponsesProvider{BaseURL: u, APIKey: "k", Model: "m"}, nil },
+			want: false,
+		},
+	}
+	for _, c := range cases {
+		t.Run(c.name, func(t *testing.T) {
+			var body map[string]any
+			srv := captureServer(&body, c.sse)
+			defer srv.Close()
+			p, err := c.call(srv.URL)
+			if err != nil {
+				t.Fatal(err)
+			}
+			m, err := p.Stream(context.Background(), "sys",
+				[]Message{{Role: RoleUser, Content: "hi"}}, nil, StreamOptions{}, nil)
+			if err != nil {
+				t.Fatalf("这一轮有正文，不该报错：%v", err)
+			}
+			if m.OutputLimited != c.want {
+				t.Errorf("OutputLimited = %v，want %v（正文 %q）", m.OutputLimited, c.want, m.Content)
+			}
+			if strings.TrimSpace(m.Content) == "" {
+				t.Error("fixture 没把正文收进来，用例本身失效")
+			}
+		})
+	}
+}
+
+// TestToolCallAtOutputLimitIsNotMarkedCut：带工具调用的响应不算"被切断的最终回答"。
+// 真是 length 也说明参数 JSON 已经残缺，续写救不回来——标了反而让上层去续一个
+// 不该续的东西。
+func TestToolCallAtOutputLimitIsNotMarkedCut(t *testing.T) {
+	sse := "data: {\"choices\":[{\"delta\":{\"tool_calls\":[{\"index\":0,\"id\":\"c1\",\"type\":\"function\"," +
+		"\"function\":{\"name\":\"bash\",\"arguments\":\"{\\\"command\\\":\\\"ls\\\"}\"}}]}}]}\n\n" +
+		"data: {\"choices\":[{\"delta\":{},\"finish_reason\":\"length\"}],\"usage\":{\"prompt_tokens\":3,\"completion_tokens\":4}}\n\n" +
+		"data: [DONE]\n\n"
+	var body map[string]any
+	srv := captureServer(&body, sse)
+	defer srv.Close()
+	p := &OpenAIProvider{BaseURL: srv.URL, APIKey: "k", Model: "m"}
+	m, err := p.Stream(context.Background(), "sys", []Message{{Role: RoleUser, Content: "hi"}}, nil, StreamOptions{}, nil)
+	if err != nil {
+		t.Fatal(err)
+	}
+	if len(m.ToolCalls) != 1 {
+		t.Fatalf("工具调用没收到：%+v", m.ToolCalls)
+	}
+	if m.OutputLimited {
+		t.Error("带 tool_calls 的响应被标成了输出切断")
+	}
+}
+
+func TestMarksOutputLimit(t *testing.T) {
+	for r, want := range map[string]bool{
+		"length": true, "LENGTH": true, " max_tokens": true, "max_output_tokens": true,
+		"stop": false, "tool_calls": false, "": false, "model_context_window_exceeded": false,
+		"content_filter": false,
+	} {
+		if got := marksOutputLimit(r); got != want {
+			t.Errorf("marksOutputLimit(%q) = %v，want %v", r, got, want)
+		}
+	}
+}