test(dispatcher): 引擎主链路集成测试（pool 抽接口 + 假替身端到端）
把 Orchestrator.pool 从 *llm.Pool 抽成 LLM 接口（Ready/ChatStream/StreamText/Chat）， *llm.Pool 天然满足、main 不变；从而可注入假模型做端到端测试，不依赖网络/Docker/LLM。 新增 integration_test.go（假 LLM/工具/sink/exec 替身）： - runGraph 分支路由：true/false 边标签精确选路（true 边故意列后）。 - runGraph 工具→agent：工具产出注入 agent 上下文。 - runGraph map fan-out：拆项 → 各章并行撰写 → 多章成稿。 - runGraph 输出护栏：流式 token 中疑似密钥被脱敏。 - handleReport：规划 → 分章撰写 → report_store 存源 → 流含标题/各章 + CompleteStream。 全部 go test -race 通过（修了测试替身 fakeExec 的并发追加竞态；生产 ExecSink 安全）。 至此引擎与报告主链路从"仅手动验证"升级为自动化端到端覆盖。 Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
This commit is contained in:
Blizzard
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@@ -84,7 +84,7 @@
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- [x] 后端首批单测（19 纯逻辑用例：引擎/DSL/docx/报告）+ mcp-go 集成测试（Profile 迁移）
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- [x] **真实鉴权（JWT）闭环**：后端注册/登录/校验 + RequireAuth 保护路由 + owner=已验证 uid（去掉 header 兜底）；前端登录/注册门 + 存 token + Bearer + 401 自动登出 + 顶栏用户/登出。实跑验证（含 CORS Authorization 修复）
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- [x] 生产安全硬化：JWT 默认密钥生产 fail-fast · /admin 加 RequireAdmin（ADMIN_USER_IDS 白名单）· CORS 来源可配（CORS_ALLOW_ORIGIN）
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- [ ] 集成/前端测试（`runGraph` / `handleReport` 需 mock pool/tools/sink；前端无测试）
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- [x] 后端集成测试：pool 抽成 LLM 接口，runGraph(分支/工具/map/脱敏)+handleReport 端到端假替身测试(含 -race)；🟡 前端测试仍无
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---
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@@ -0,0 +1,238 @@
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package eino
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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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"sync"
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"testing"
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"github.com/sundynix/sundynix-dispatcher/internal/harness"
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"github.com/sundynix/sundynix-dispatcher/internal/llm"
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"github.com/sundynix/sundynix-shared/contract"
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)
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// ---- 测试替身 ----
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type fakeLLM struct {
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ready bool
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stream func(msgs []llm.ChatMessage) string // ChatStream 要回流的整段文本
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chat func(msgs []llm.ChatMessage) (string, error) // Chat 返回
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}
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func (f *fakeLLM) Ready() bool { return f.ready }
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func (f *fakeLLM) ChatStream(_ context.Context, msgs []llm.ChatMessage, onToken func(string)) error {
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if f.stream != nil {
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onToken(f.stream(msgs))
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}
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return nil
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}
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func (f *fakeLLM) StreamText(_ context.Context, text string, onToken func([]byte)) error {
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onToken([]byte(text))
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return nil
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}
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func (f *fakeLLM) Chat(_ context.Context, msgs []llm.ChatMessage) (string, error) {
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if f.chat != nil {
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return f.chat(msgs)
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}
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return "", nil
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}
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type fakeSink struct {
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mu sync.Mutex
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tokens []string
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done bool
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}
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func (s *fakeSink) PublishToken(_ string, tok []byte) error {
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s.mu.Lock()
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s.tokens = append(s.tokens, string(tok))
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s.mu.Unlock()
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return nil
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}
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func (s *fakeSink) CompleteStream(_ string) error { s.done = true; return nil }
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func (s *fakeSink) text() string {
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s.mu.Lock()
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defer s.mu.Unlock()
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return strings.Join(s.tokens, "")
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}
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type fakeTools struct {
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mu sync.Mutex
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calls []string
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fn func(call *contract.ToolCall) *contract.ToolResult
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}
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func (t *fakeTools) CallTool(_ context.Context, _ string, call *contract.ToolCall) (*contract.ToolResult, error) {
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t.mu.Lock()
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t.calls = append(t.calls, call.Tool)
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t.mu.Unlock()
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if t.fn != nil {
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return t.fn(call), nil
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}
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return &contract.ToolResult{OK: true, Content: ""}, nil
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}
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func (t *fakeTools) called(tool string) bool {
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t.mu.Lock()
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defer t.mu.Unlock()
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for _, c := range t.calls {
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if c == tool {
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return true
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}
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}
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return false
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}
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type fakeExec struct {
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mu sync.Mutex
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events []contract.ExecEvent
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}
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func (e *fakeExec) PublishExec(_ string, data []byte) error {
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var ev contract.ExecEvent
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if json.Unmarshal(data, &ev) == nil {
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e.mu.Lock()
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e.events = append(e.events, ev)
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e.mu.Unlock()
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}
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return nil
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}
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func (e *fakeExec) CompleteExec(_ string) error { return nil }
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func newOrch(ll *fakeLLM, ft *fakeTools, fs *fakeSink, fe *fakeExec) *Orchestrator {
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return &Orchestrator{pool: ll, breaker: harness.NewCircuitBreaker(), sink: fs, tools: ft, exec: fe}
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}
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func task(graph string) *contract.Task {
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return &contract.Task{ID: "t1", Graph: json.RawMessage(graph), Meta: map[string]any{}}
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}
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// ---- 集成测试：runGraph ----
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// 分支按 true/false 边标签精确选路（true 边故意列第二位）。
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func TestRunGraph_BranchRouting(t *testing.T) {
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g := `{"nodes":[
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{"id":"i","kind":"input","config":{"text":"hi"}},
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{"id":"b","kind":"branch","config":{"condition":"%s"}},
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{"id":"a","kind":"agent","config":{"system":"AAA"}},
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{"id":"c","kind":"agent","config":{"system":"BBB"}}
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],"edges":[
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{"source":"i","target":"b"},
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{"source":"b","target":"c","sourceHandle":"false"},
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{"source":"b","target":"a","sourceHandle":"true"}
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]}`
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// fakeLLM 回流"系统提示词"，借此判断哪个 agent 跑了。
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ll := &fakeLLM{ready: true, stream: func(m []llm.ChatMessage) string { return m[0].Content }}
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run := func(cond string) string {
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o := newOrch(ll, &fakeTools{}, &fakeSink{}, &fakeExec{})
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ans, err := o.runGraph(context.Background(), task(strings.Replace(g, "%s", cond, 1)), o.tracer("t1"))
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if err != nil {
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t.Fatal(err)
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}
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return ans
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}
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if a := run("2>1"); !strings.Contains(a, "AAA") || strings.Contains(a, "BBB") {
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t.Errorf("条件真应走 true 标签(AAA)，got %q", a)
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}
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if a := run("1>2"); !strings.Contains(a, "BBB") || strings.Contains(a, "AAA") {
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t.Errorf("条件假应走 false 标签(BBB)，got %q", a)
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}
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}
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// 工具节点产出注入 agent 上下文。
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func TestRunGraph_ToolFeedsAgent(t *testing.T) {
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g := `{"nodes":[
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{"id":"i","kind":"input","config":{"text":"hi"}},
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{"id":"t","kind":"tool","config":{"tool":"wiki_search"}},
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{"id":"a","kind":"agent","config":{"system":"S"}}
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],"edges":[{"source":"i","target":"t"},{"source":"t","target":"a"}]}`
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ll := &fakeLLM{ready: true, stream: func(m []llm.ChatMessage) string { return m[0].Content }}
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ft := &fakeTools{fn: func(c *contract.ToolCall) *contract.ToolResult {
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return &contract.ToolResult{OK: true, Content: "TOOLDATA"}
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}}
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o := newOrch(ll, ft, &fakeSink{}, &fakeExec{})
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ans, err := o.runGraph(context.Background(), task(g), o.tracer("t1"))
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if err != nil {
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t.Fatal(err)
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}
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if !ft.called("wiki_search") {
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t.Error("应调用 wiki_search 工具")
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}
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if !strings.Contains(ans, "TOOLDATA") {
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t.Errorf("工具产出应注入 agent 上下文，got %q", ans)
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}
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}
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// map 并行 fan-out：拆项 → 各章撰写 → 汇成多章成稿。
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func TestRunGraph_MapFanout(t *testing.T) {
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g := `{"nodes":[
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{"id":"i","kind":"input","config":{"text":"猫"}},
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{"id":"m","kind":"map","config":{"splitBy":"要点"}}
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],"edges":[{"source":"i","target":"m"}]}`
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ll := &fakeLLM{ready: true, chat: func(m []llm.ChatMessage) (string, error) {
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u := m[len(m)-1].Content
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if strings.Contains(u, "拆分") {
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return `["第一章","第二章"]`, nil
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}
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return "正文XYZ", nil
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}}
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o := newOrch(ll, &fakeTools{}, &fakeSink{}, &fakeExec{})
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ans, err := o.runGraph(context.Background(), task(g), o.tracer("t1"))
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if err != nil {
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t.Fatal(err)
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}
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if !strings.Contains(ans, "## 第一章") || !strings.Contains(ans, "## 第二章") || !strings.Contains(ans, "正文XYZ") {
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t.Errorf("map 应产出多章成稿，got %q", ans)
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}
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}
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// 输出护栏：发射的 token 中疑似密钥被脱敏。
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func TestRunGraph_OutputRedaction(t *testing.T) {
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g := `{"nodes":[{"id":"i","kind":"input","config":{"text":"hi"}},{"id":"a","kind":"agent","config":{"system":"S"}}],"edges":[{"source":"i","target":"a"}]}`
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ll := &fakeLLM{ready: true, stream: func(m []llm.ChatMessage) string {
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return "你的 key 是 sk-912cf85b16d04b22bcb95f4576423bfb 请保密"
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}}
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fs := &fakeSink{}
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o := newOrch(ll, &fakeTools{}, fs, &fakeExec{})
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if _, err := o.runGraph(context.Background(), task(g), o.tracer("t1")); err != nil {
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t.Fatal(err)
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}
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out := fs.text()
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if strings.Contains(out, "sk-912cf85b16d04b22bcb95f4576423bfb") {
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t.Errorf("流式输出未脱敏密钥: %q", out)
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}
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if !strings.Contains(out, "[已脱敏]") {
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t.Errorf("应出现脱敏标记: %q", out)
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}
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}
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// ---- 集成测试：handleReport ----
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func TestHandleReport_PlanWriteStore(t *testing.T) {
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ll := &fakeLLM{ready: true, chat: func(m []llm.ChatMessage) (string, error) {
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u := m[len(m)-1].Content
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if strings.Contains(u, "大纲") {
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return `{"title":"咖啡报告","sections":["提神","风险"]}`, nil
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}
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return "本章正文。", nil
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}}
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ft := &fakeTools{fn: func(c *contract.ToolCall) *contract.ToolResult {
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return &contract.ToolResult{OK: true, Content: "/tmp/x.json"}
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}}
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fs := &fakeSink{}
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o := newOrch(ll, ft, fs, &fakeExec{})
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tk := &contract.Task{ID: "r1", Graph: json.RawMessage(`{}`), Meta: map[string]any{contract.MetaTopic: "咖啡"}}
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if err := o.handleReport(context.Background(), tk, o.tracer("r1")); err != nil {
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t.Fatal(err)
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}
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if !ft.called("report_store") {
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t.Error("应调用 report_store 存源")
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}
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out := fs.text()
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if !strings.Contains(out, "# 咖啡报告") || !strings.Contains(out, "## 提神") || !strings.Contains(out, "## 风险") {
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t.Errorf("报告流应含标题与各章，got %q", out)
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}
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if !fs.done {
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t.Error("报告结束应 CompleteStream")
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}
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}
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@@ -27,12 +27,20 @@ type ToolCaller interface {
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CallTool(ctx context.Context, subject string, call *contract.ToolCall) (*contract.ToolResult, error)
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}
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// LLM 是编排所需的语言模型能力（生产由 *llm.Pool 实现）。抽成接口便于测试注入假模型。
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type LLM interface {
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Ready() bool
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ChatStream(ctx context.Context, msgs []llm.ChatMessage, onToken func(string)) error
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StreamText(ctx context.Context, text string, onToken func([]byte)) error
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Chat(ctx context.Context, msgs []llm.ChatMessage) (string, error)
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}
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// 工具调用超时；超时即降级（不带工具上下文继续推理）。
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const toolCallTimeout = 3 * time.Second
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// Orchestrator 把每个 DSL 任务动态编译为 Eino 图并执行（记忆召回 → 工具节点 → 注入 → 流式）。
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type Orchestrator struct {
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pool *llm.Pool
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pool LLM
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breaker *harness.CircuitBreaker
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eval *harness.Evaluator
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sink TokenSink
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@@ -42,7 +50,7 @@ type Orchestrator struct {
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// NewOrchestrator 持有依赖；图按任务的 DSL 在 Handle 内动态编译。
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// exec 为执行可视化事件出口（可为 nil，则不发轨迹事件）；eval 为自动化评测（可为 nil）。
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func NewOrchestrator(pool *llm.Pool, breaker *harness.CircuitBreaker, eval *harness.Evaluator, sink TokenSink, tools ToolCaller, exec ExecSink) (*Orchestrator, error) {
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func NewOrchestrator(pool LLM, breaker *harness.CircuitBreaker, eval *harness.Evaluator, sink TokenSink, tools ToolCaller, exec ExecSink) (*Orchestrator, error) {
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return &Orchestrator{pool: pool, breaker: breaker, eval: eval, sink: sink, tools: tools, exec: exec}, nil
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}
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Reference in New Issue
Block a user