Fix truncation issues in piplan, SQLite storage, and history compression; add PIPlanMaxChars configuration
This commit is contained in:
@@ -225,6 +225,9 @@ func runMessageChannel(ctx context.Context, cfg config.Config, engine *agent.Orc
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func(ctx context.Context, chatID, userID string, files []llm.InputFile) ([]string, error) {
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return engine.UploadAndCacheFiles(ctx, chatID, userID, files)
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},
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func(ctx context.Context, chatID string, limit int) ([]memory.Message, error) {
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return engine.GetHistory(chatID, limit)
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},
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)
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default:
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return fmt.Errorf("unsupported message channel: %s", cfg.MessageChannel)
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@@ -280,6 +283,14 @@ func buildWebUIStreamForwarder(callback webui.StreamEventCallback, exposeReasoni
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Content: event.Content,
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Step: event.Step,
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})
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case agent.StreamEventTypeWorkspaceStart, agent.StreamEventTypeWorkspaceDelta, agent.StreamEventTypeWorkspaceEnd:
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return callback(webui.StreamEvent{
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Type: webui.StreamEventType(event.Type),
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Content: event.Content,
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Step: event.Step,
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ToolName: event.ToolName,
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WorkspaceTitle: event.WorkspaceTitle,
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})
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default:
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return nil
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}
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@@ -6,6 +6,7 @@ SKILLS_DIR=./skills
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REACT_MAX_STEPS=4
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TOOL_CALL_TIMEOUT_SEC=15
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TOOL_OUTPUT_MAX_CHARS=4000
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PI_PLAN_MAX_CHARS=40000
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ENABLE_CAPABILITY_GAP=true
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AUTO_SKILL_DIR=./skills
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GAP_DRAFT_TRIGGER_COUNT=3
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140
doc/Artifact_SplitScreen_Design.md
Normal file
140
doc/Artifact_SplitScreen_Design.md
Normal file
@@ -0,0 +1,140 @@
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# Vibe Coding Design Docs: Workspace/Artifact Split-Screen Pattern
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## 1. Context & Objective
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The goal is to implement a UI/UX pattern similar to **Claude Artifacts** or **Gemini Deep Research**. When a specific complex task is triggered (e.g., "Project Planning Skill"), the single-column chat interface should smoothly transition into a split-screen layout:
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- **Left Panel (35%)**: Conversational context, CoT (Chain of Thought) traces, tool calls, and user input.
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- **Right Panel (65%)**: A dedicated "Workspace" or "Artifact" rendering area to display long-form content (Markdown, code, diagrams) generated by the Agent's skills.
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Crucially, this system must support **Reflexion/Iterative generation**. The user can comment on the generated artifact in the left panel, and the agent should update the artifact in the right panel based on the feedback.
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---
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## 2. Frontend Implementation Guide (React + Vite + Tailwind)
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### 2.1 State Management (State & Types)
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Extend the existing frontend state to track the workspace status and content.
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```typescript
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// 1. Extend the StreamEvent type to support UI control and artifact streaming
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type StreamEvent = {
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type:
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| "thought"
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| "tool_call"
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| "tool_result"
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| "message" // Standard chat message
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| "error"
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| "workspace_start" // Trigger right panel open
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| "workspace_delta" // Streaming text for the right panel
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| "workspace_end"; // Streaming completed
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content: string;
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step?: number;
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tool_name?: string;
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workspace_title?: string; // Optional title for the artifact
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};
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// 2. Add Workspace State (Can be added to useReducer or a separate useState)
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type WorkspaceState = {
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isOpen: boolean;
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title: string;
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content: string;
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isGenerating: boolean;
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};
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```
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### 2.2 SSE Parsing Logic
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Modify the `onEvent` handler inside `streamChat` to intercept `workspace_*` events.
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- When `workspace_start` arrives: Set `workspace.isOpen = true`, clear previous content, set `isGenerating = true`.
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- When `workspace_delta` arrives: Append text to `workspace.content`. Do **not** append this text to the left-panel chat history to avoid redundancy.
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- When `workspace_end` arrives: Set `isGenerating = false`.
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### 2.3 Layout & UI Re-architecture
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Refactor the root `<div>` of `PlanningAgent.tsx` to handle dynamic flex layouts. Use Tailwind's transition utilities for smooth scaling.
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```tsx
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<div className="flex h-full w-full overflow-hidden bg-surface">
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{/* Left Panel: Chat & Controls */}
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<div
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className={`flex flex-col h-full transition-all duration-300 ease-in-out ${
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workspace.isOpen ? 'w-[35%] border-r border-border min-w-[350px]' : 'w-full max-w-5xl mx-auto'
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}`}
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>
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{/* Existing Message List & Input Area */}
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</div>
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{/* Right Panel: Workspace / Deep Research Output */}
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{workspace.isOpen && (
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<div className="w-[65%] h-full flex flex-col bg-surface-muted transition-opacity duration-300 animate-fade-in">
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{/* Header */}
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<div className="h-14 border-b border-border flex items-center px-6 justify-between bg-white">
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<h3 className="font-semibold text-txt flex items-center gap-2">
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<IconDocument /> {workspace.title || 'Project Planning Document'}
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</h3>
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{workspace.isGenerating && (
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<span className="text-sm text-magenta animate-pulse flex items-center gap-1">
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<Spinner /> Generating...
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</span>
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)}
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</div>
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{/* Markdown Content Area */}
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<div className="flex-1 overflow-y-auto p-8 prose prose-slate max-w-none">
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<ReactMarkdown remarkPlugins={[remarkGfm]} rehypePlugins={[rehypeRaw]}>
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{workspace.content}
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</ReactMarkdown>
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</div>
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</div>
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)}
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</div>
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```
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---
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## 3. Backend Implementation Guide (Agent / ReAct Loop)
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The backend agent requires structural changes to understand the "Artifact" concept, emit correct SSE events, and maintain the artifact in its memory for iterative edits.
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### 3.1 Tool / Skill Definition
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When defining the `Project Planning Skill` for the LLM, clearly state its output behavior so the LLM knows *when* to use it.
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- **Tool Description**: `use_planning_workspace`: "Invoke this tool to generate, structure, or update a major project planning document. The output will be rendered in a dedicated UI workspace."
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### 3.2 Context Injection (Memory for Reflexion)
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To allow the user to say *"extend the testing phase to 2 weeks"*, the LLM **must know what is currently in the right panel**.
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- **Before sending the prompt to the LLM**, query the database/session for the current Artifact state.
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- **Prompt Assembly**:
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```text
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[System Prompt / ReAct Instructions]
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...
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[Current Workspace Artifact (if exists)]
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<workspace>
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# Project Plan
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1. Dev Phase: 1 week
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2. Testing Phase: 1 week
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</workspace>
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[Chat History]
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User: extend the testing phase to 2 weeks.
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```
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### 3.3 Streaming Control (Hijacking the Stream)
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Within the ReAct execution loop, when the Agent decides to execute the `Project Planning Skill`:
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1. The Backend normally streams `thought` or `tool_call` events.
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2. Upon entering the specific Skill execution, the backend emits `{"type": "workspace_start", "workspace_title": "Update: Project Plan"}`.
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3. As the LLM (or a sub-agent) generates the Markdown schema, the backend maps these tokens to `workspace_delta` events and flushes them to the frontend.
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4. (CRITICAL) Do **not** send these tokens as `message` or `final` chat events. The chat bubble should only say something like: *"I have updated the project plan in the workspace area."*
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5. Save the final generated Markdown text into the session memory as the `Current Artifact` for future context injection.
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---
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## 4. Work Flow Summary (For LLM context generation)
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1. `User` sends prompt: "Plan the new feature".
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2. `Agent` thinks (`type: thought`), decides to use `Project Planning Skill` (`type: tool_call`).
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3. `Agent` emits `{"type": "workspace_start"}`.
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4. `Frontend` expands right panel (65% width).
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5. `Agent` streams `{"type": "workspace_delta", "content": "..."}`.
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6. `Frontend` live-renders Markdown in the right panel.
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7. `Agent` finishes, saves artifact to backend session.
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8. `User` reads right panel, types in left panel: "Change point 2".
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9. `Agent` receives Left Panel history + Right Panel Artifact Content.
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10. `Agent` updates document, streaming new `workspace_delta`. Frontend live-updates the right panel.
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@@ -27,6 +27,9 @@ const (
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StreamEventTypeToolResult StreamEventType = "tool_result" // 工具执行结果
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StreamEventTypeFinal StreamEventType = "final" // 最终答案
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StreamEventTypeError StreamEventType = "error" // 错误信息
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StreamEventTypeWorkspaceStart StreamEventType = "workspace_start" // 工具渲染开始
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StreamEventTypeWorkspaceDelta StreamEventType = "workspace_delta" // 工具渲染增量内容
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StreamEventTypeWorkspaceEnd StreamEventType = "workspace_end" // 工具渲染结束
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)
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// StreamEvent 代表流式输出中的一个事件
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@@ -35,6 +38,7 @@ type StreamEvent struct {
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Content string `json:"content"`
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Step int `json:"step,omitempty"`
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ToolName string `json:"tool_name,omitempty"`
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WorkspaceTitle string `json:"workspace_title,omitempty"`
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}
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// StreamEventCallback 是流式事件回调函数类型,用于推送事件到客户端
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@@ -55,10 +59,13 @@ type Orchestrator struct {
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gapLookbackDuration time.Duration
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reactMaxStep int
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enableCapabilityGap bool
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autoSkillDraftEnabled bool
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log *logger.Logger
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skillsMu sync.RWMutex
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pendingFilesMu sync.Mutex
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pendingFiles map[string][]pendingFileRef
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planningSessionsMu sync.Mutex
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planningSessions map[string]planningSessionState
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}
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type pendingFileRef struct {
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@@ -67,6 +74,15 @@ type pendingFileRef struct {
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MimeType string
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}
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type planningSessionState struct {
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Active bool
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LastArtifact string
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AwaitingConfirm bool
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UpdatedAt time.Time
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}
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const planningSessionTTL = 2 * time.Hour
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// NewOrchestrator 创建一个新的编排器对象,初始化关键路径和超时控制等。
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func NewOrchestrator(
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llmClient llm.Client,
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@@ -110,8 +126,10 @@ func NewOrchestrator(
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gapLookbackDuration: gapLookbackDuration,
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reactMaxStep: reactMaxStep,
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enableCapabilityGap: enableCapabilityGap,
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autoSkillDraftEnabled: false,
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log: log,
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pendingFiles: make(map[string][]pendingFileRef),
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planningSessions: make(map[string]planningSessionState),
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}
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}
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@@ -166,6 +184,11 @@ func (o *Orchestrator) HandleMessageStreamWithFiles(ctx context.Context, chatID,
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return o.handleMessageStreamInternal(ctx, chatID, userID, text, callback)
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}
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// GetHistory 获取指定会话的历史记录。
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func (o *Orchestrator) GetHistory(chatID string, limit int) ([]memory.Message, error) {
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return o.store.LoadRecent(chatID, limit)
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}
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// UploadAndCacheFiles 上传文件到 LLM 并缓存 file_id,供后续同会话文本问答复用。
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func (o *Orchestrator) UploadAndCacheFiles(ctx context.Context, chatID, userID string, files []llm.InputFile) ([]string, error) {
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if len(files) == 0 {
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@@ -342,7 +365,7 @@ func (o *Orchestrator) handleMessageStreamInternal(ctx context.Context, chatID,
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// buildUnifiedSystemPrompt 构建统一 ReAct 循环的 system prompt。
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// 工具定义通过 API 的 tools 字段传递;此处只需包含人格、技能、运行环境和思考指引。
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// routedSkills 为 LLM 路由预选的技能列表;如果为 nil,则回退到关键词匹配。
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func (o *Orchestrator) buildUnifiedSystemPrompt(userInput string, routedSkills []knowledge.Skill) string {
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func (o *Orchestrator) buildUnifiedSystemPrompt(userInput string, recentMessages []memory.Message, routedSkills []knowledge.Skill, planningMode bool) string {
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skillMetaDoc := o.formatSkillSummariesForPrompt()
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var relevantSkillsDoc string
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if routedSkills != nil {
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@@ -352,6 +375,18 @@ func (o *Orchestrator) buildUnifiedSystemPrompt(userInput string, routedSkills [
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}
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runtimeDoc := formatRuntimeContextForPrompt()
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// 提取最近的 Artifact
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artifactDoc := extractLastArtifact(recentMessages)
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planningModeDoc := "当前未处于 PI 规划编辑模式。"
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if planningMode {
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planningModeDoc = strings.Join([]string{
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"当前处于 PI 规划编辑模式。",
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"- 用户的修订意见必须基于现有 Artifact 继续迭代。",
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"- 需要继续调用 safe_pi_planning / publish_pi_plan 相关流程生成更新版本。",
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"- 不要仅给普通文本答复替代蓝图更新。",
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}, "\n")
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}
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return strings.Join([]string{
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"你是一个个人自动化助手,必须遵循如下人格设定并保持一致:",
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o.soul,
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@@ -373,6 +408,12 @@ func (o *Orchestrator) buildUnifiedSystemPrompt(userInput string, routedSkills [
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"===== 运行环境 =====",
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runtimeDoc,
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"",
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"===== 已有结果 (Artifact) =====",
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artifactDoc,
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"",
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"===== PI 规划模式 =====",
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planningModeDoc,
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"",
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"===== 可用技能概览 =====",
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skillMetaDoc,
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"",
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@@ -383,6 +424,21 @@ func (o *Orchestrator) buildUnifiedSystemPrompt(userInput string, routedSkills [
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}, "\n")
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}
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// extractLastArtifact 从消息历史中提取最后一个 Artifact
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func extractLastArtifact(messages []memory.Message) string {
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for i := len(messages) - 1; i >= 0; i-- {
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msg := messages[i]
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if strings.Contains(msg.Content, "<artifact") {
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start := strings.Index(msg.Content, "<artifact")
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end := strings.LastIndex(msg.Content, "</artifact>")
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if end > start {
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return "\n当前正在处理的 Artifact 内容如下:\n" + msg.Content[start:end+11] + "\n如果你需要更新此 Artifact,请输出完整的更新后版本并确保包裹在 <artifact> 标签中。"
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}
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}
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}
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return "当前没有正在处理的 Artifact。"
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}
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// routeSkillsWithLLM 使用轻量 LLM 模型对用户输入进行语义路由,判断是否需要加载技能以及选择哪些技能。
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// 返回匹配到的技能列表(可能为空切片表示不需要技能,nil 表示调用失败应回退)。
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func (o *Orchestrator) routeSkillsWithLLM(ctx context.Context, userInput string) ([]knowledge.Skill, error) {
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@@ -497,9 +553,26 @@ func (o *Orchestrator) runUnifiedReAct(ctx context.Context, chatID, userID, comp
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traceID := logger.TraceIDFromContext(ctx)
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traceLogPrefix := "trace_id=" + traceID
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// ===== LLM 意图路由:使用轻量模型判断是否需要加载技能 =====
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planningMode := false
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if session, ok := o.getPlanningSession(chatID, userID); ok && session.Active {
|
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if shouldExitPlanningMode(userInput) {
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o.clearPlanningSession(chatID, userID)
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if o.log != nil {
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o.log.Infof("%s planning mode exited chat_id=%s", traceLogPrefix, chatID)
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}
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} else {
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planningMode = true
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}
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}
|
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|
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// ===== LLM 意图路由:使用轻量模型判断是否需要加载技能(规划模式下使用粘性技能) =====
|
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var routedSkills []knowledge.Skill
|
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if o.routerLLM != nil {
|
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if planningMode {
|
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routedSkills = o.getSafePIPlanningSkills()
|
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if o.log != nil {
|
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o.log.Infof("%s planning mode sticky skill activated chat_id=%s matched=%d", traceLogPrefix, chatID, len(routedSkills))
|
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}
|
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} else if o.routerLLM != nil {
|
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routed, routeErr := o.routeSkillsWithLLM(ctx, userInput)
|
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if routeErr != nil {
|
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if o.log != nil {
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@@ -517,8 +590,12 @@ func (o *Orchestrator) runUnifiedReAct(ctx context.Context, chatID, userID, comp
|
||||
}
|
||||
}
|
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}
|
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if containsSafePIPlanningSkill(routedSkills) {
|
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planningMode = true
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o.activatePlanningSession(chatID, userID, "", false)
|
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}
|
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|
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systemPrompt := o.buildUnifiedSystemPrompt(userInput, routedSkills)
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systemPrompt := o.buildUnifiedSystemPrompt(userInput, nil, routedSkills, planningMode)
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|
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if o.log != nil {
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o.log.Infof("%s unified react start", traceLogPrefix)
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@@ -544,6 +621,18 @@ func (o *Orchestrator) runUnifiedReAct(ctx context.Context, chatID, userID, comp
|
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// 加入当前用户消息
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messages = append(messages, llm.PromptMessage{Role: "user", Content: userInput})
|
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|
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// 获取最近消息以提取 Artifact
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recent, _ := o.store.LoadRecent(chatID, 16)
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systemPrompt = o.buildUnifiedSystemPrompt(userInput, recent, routedSkills, planningMode)
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|
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// 更新 system message
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messages[0].Content = systemPrompt
|
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|
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if o.log != nil {
|
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o.log.Infof("%s unified react start", traceLogPrefix)
|
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o.log.Debugf("%s system_prompt_len=%d", traceLogPrefix, len(systemPrompt))
|
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}
|
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|
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// 构建工具定义列表(通过 API tools 字段传递)
|
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toolDefs := o.buildToolDefinitions()
|
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if o.log != nil {
|
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@@ -598,6 +687,16 @@ func (o *Orchestrator) runUnifiedReAct(ctx context.Context, chatID, userID, comp
|
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for _, tc := range completion.ToolCalls {
|
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toolName := strings.ToLower(strings.TrimSpace(tc.Function.Name))
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toolInput := extractToolInput(tc.Function.Arguments)
|
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if planningMode && toolName == "create_gitea_ticket" && !isPlanningConfirmation(userInput) {
|
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obs := formatToolErrorObservation("WAIT_USER_CONFIRM", toolName, "需用户确认后才能创建工单,请先征求用户确认")
|
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messages = append(messages, llm.PromptMessage{
|
||||
Role: "tool",
|
||||
ToolCallID: tc.ID,
|
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Name: tc.Function.Name,
|
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Content: obs,
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})
|
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continue
|
||||
}
|
||||
|
||||
tool, ok := o.tools.Get(toolName)
|
||||
if !ok {
|
||||
@@ -624,6 +723,14 @@ func (o *Orchestrator) runUnifiedReAct(ctx context.Context, chatID, userID, comp
|
||||
if obs == "" {
|
||||
obs = "(empty output)"
|
||||
}
|
||||
if isPIPlanningToolName(toolName) && toolErr == nil && strings.TrimSpace(obs) != "" {
|
||||
o.activatePlanningSession(chatID, userID, obs, true)
|
||||
if err := o.store.SaveMessage(chatID, userID, "assistant", wrapPIArtifact(obs)); err != nil {
|
||||
if o.log != nil {
|
||||
o.log.Warnf("%s save planning artifact failed chat_id=%s err=%v", traceLogPrefix, chatID, err)
|
||||
}
|
||||
}
|
||||
}
|
||||
if toolErr != nil {
|
||||
obs = formatToolErrorObservation("TOOL_EXEC_ERROR", toolName, toolErr.Error()) + "\nOUTPUT:\n" + obs
|
||||
o.emitCapabilityGap(chatID, userID, userInput, "tool_call_failed:"+toolName)
|
||||
@@ -657,9 +764,26 @@ func (o *Orchestrator) runUnifiedReActStream(ctx context.Context, chatID, userID
|
||||
traceID := logger.TraceIDFromContext(ctx)
|
||||
traceLogPrefix := "trace_id=" + traceID
|
||||
|
||||
// ===== LLM 意图路由:使用轻量模型判断是否需要加载技能 =====
|
||||
planningMode := false
|
||||
if session, ok := o.getPlanningSession(chatID, userID); ok && session.Active {
|
||||
if shouldExitPlanningMode(userInput) {
|
||||
o.clearPlanningSession(chatID, userID)
|
||||
if o.log != nil {
|
||||
o.log.Infof("%s planning mode exited chat_id=%s", traceLogPrefix, chatID)
|
||||
}
|
||||
} else {
|
||||
planningMode = true
|
||||
}
|
||||
}
|
||||
|
||||
// ===== LLM 意图路由:使用轻量模型判断是否需要加载技能(规划模式下使用粘性技能) =====
|
||||
var routedSkills []knowledge.Skill
|
||||
if o.routerLLM != nil {
|
||||
if planningMode {
|
||||
routedSkills = o.getSafePIPlanningSkills()
|
||||
if o.log != nil {
|
||||
o.log.Infof("%s planning mode sticky skill activated chat_id=%s matched=%d", traceLogPrefix, chatID, len(routedSkills))
|
||||
}
|
||||
} else if o.routerLLM != nil {
|
||||
routed, routeErr := o.routeSkillsWithLLM(ctx, userInput)
|
||||
if routeErr != nil {
|
||||
if o.log != nil {
|
||||
@@ -676,8 +800,20 @@ func (o *Orchestrator) runUnifiedReActStream(ctx context.Context, chatID, userID
|
||||
}
|
||||
}
|
||||
}
|
||||
if containsSafePIPlanningSkill(routedSkills) {
|
||||
planningMode = true
|
||||
o.activatePlanningSession(chatID, userID, "", false)
|
||||
}
|
||||
routedToSafePIPlanning := false
|
||||
for _, sk := range routedSkills {
|
||||
name := strings.ToLower(strings.TrimSpace(sk.Name))
|
||||
if strings.Contains(name, "safe") || strings.Contains(name, "pi 规划") || strings.Contains(name, "pi planning") {
|
||||
routedToSafePIPlanning = true
|
||||
break
|
||||
}
|
||||
}
|
||||
|
||||
systemPrompt := o.buildUnifiedSystemPrompt(userInput, routedSkills)
|
||||
systemPrompt := o.buildUnifiedSystemPrompt(userInput, nil, routedSkills, planningMode)
|
||||
|
||||
if o.log != nil {
|
||||
o.log.Infof("%s unified react stream start", traceLogPrefix)
|
||||
@@ -699,6 +835,18 @@ func (o *Orchestrator) runUnifiedReActStream(ctx context.Context, chatID, userID
|
||||
messages = append(messages, parseCompressedHistoryMessages(compressedContext)...)
|
||||
messages = append(messages, llm.PromptMessage{Role: "user", Content: userInput})
|
||||
|
||||
// 获取最近消息以提取 Artifact
|
||||
recent, _ := o.store.LoadRecent(chatID, 16)
|
||||
systemPrompt = o.buildUnifiedSystemPrompt(userInput, recent, routedSkills, planningMode)
|
||||
|
||||
// 更新 system message
|
||||
messages[0].Content = systemPrompt
|
||||
|
||||
if o.log != nil {
|
||||
o.log.Infof("%s unified react stream start", traceLogPrefix)
|
||||
o.log.Debugf("%s system_prompt_len=%d", traceLogPrefix, len(systemPrompt))
|
||||
}
|
||||
|
||||
// 构建工具定义列表
|
||||
toolDefs := o.buildToolDefinitions()
|
||||
if o.log != nil {
|
||||
@@ -709,6 +857,7 @@ func (o *Orchestrator) runUnifiedReActStream(ctx context.Context, chatID, userID
|
||||
o.log.Debugf("%s tool_defs_count=%d names=%v", traceLogPrefix, len(toolDefs), toolNames)
|
||||
}
|
||||
|
||||
workspaceSentThisTurn := false
|
||||
const maxSteps = 20
|
||||
for step := 1; step <= maxSteps; step++ {
|
||||
if o.log != nil {
|
||||
@@ -729,10 +878,15 @@ func (o *Orchestrator) runUnifiedReActStream(ctx context.Context, chatID, userID
|
||||
}
|
||||
}
|
||||
|
||||
// 推送思考过程事件
|
||||
// 推送思考过程事件(剥离 artifact 标签,避免前端重复渲染工作区)
|
||||
if completion.Content != "" {
|
||||
displayContent := completion.Content
|
||||
if planningMode {
|
||||
displayContent = stripArtifactTags(displayContent)
|
||||
}
|
||||
if displayContent != "" {
|
||||
// 分割内容为逐步推送的片段
|
||||
segments := splitContentIntoSegments(completion.Content, 50) // 每段50字符
|
||||
segments := splitContentIntoSegments(displayContent, 50) // 每段50字符
|
||||
for _, segment := range segments {
|
||||
if err := callback(StreamEvent{
|
||||
Type: StreamEventTypeThought,
|
||||
@@ -743,6 +897,7 @@ func (o *Orchestrator) runUnifiedReActStream(ctx context.Context, chatID, userID
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// ========== 无 tool_calls → 最终回答 ==========
|
||||
if len(completion.ToolCalls) == 0 {
|
||||
@@ -750,6 +905,45 @@ func (o *Orchestrator) runUnifiedReActStream(ctx context.Context, chatID, userID
|
||||
if finalText == "" {
|
||||
finalText = "已完成处理。"
|
||||
}
|
||||
if planningMode && !workspaceSentThisTurn {
|
||||
// 提取 artifact 标签内的文档内容作为工作区内容
|
||||
workspaceContent := extractArtifactContent(finalText)
|
||||
if workspaceContent == "" {
|
||||
workspaceContent = stripArtifactTags(finalText)
|
||||
}
|
||||
if workspaceContent == "" {
|
||||
workspaceContent = finalText
|
||||
}
|
||||
o.activatePlanningSession(chatID, userID, workspaceContent, true)
|
||||
if err := o.store.SaveMessage(chatID, userID, "assistant", wrapPIArtifact(workspaceContent)); err != nil {
|
||||
if o.log != nil {
|
||||
o.log.Warnf("%s save planning artifact failed chat_id=%s err=%v", traceLogPrefix, chatID, err)
|
||||
}
|
||||
}
|
||||
if err := callback(StreamEvent{
|
||||
Type: StreamEventTypeWorkspaceStart,
|
||||
WorkspaceTitle: "PI Planning Document",
|
||||
}); err != nil {
|
||||
return "", fmt.Errorf("callback error: %w", err)
|
||||
}
|
||||
if err := callback(StreamEvent{
|
||||
Type: StreamEventTypeWorkspaceDelta,
|
||||
Content: workspaceContent,
|
||||
}); err != nil {
|
||||
return "", fmt.Errorf("callback error: %w", err)
|
||||
}
|
||||
if err := callback(StreamEvent{Type: StreamEventTypeWorkspaceEnd}); err != nil {
|
||||
return "", fmt.Errorf("callback error: %w", err)
|
||||
}
|
||||
workspaceSentThisTurn = true
|
||||
finalText = "我已根据你的意见更新 PI 规划,请查看右侧工作区;如确认无误,请回复“确认”进入工单创建。"
|
||||
} else if planningMode {
|
||||
// 工作区已在本轮通过工具调用发送,剥离 final 内容中的 artifact 标签
|
||||
finalText = stripArtifactTags(finalText)
|
||||
if finalText == "" {
|
||||
finalText = "已完成处理。"
|
||||
}
|
||||
}
|
||||
if o.log != nil {
|
||||
o.log.Debugf("%s react stream final at step=%d answer_len=%d", traceLogPrefix, step, len(finalText))
|
||||
}
|
||||
@@ -817,11 +1011,66 @@ func (o *Orchestrator) runUnifiedReActStream(ctx context.Context, chatID, userID
|
||||
o.log.Debugf("%s react stream step=%d tool=%s input=%q", traceLogPrefix, step, toolName, toolInput)
|
||||
}
|
||||
|
||||
if planningMode && toolName == "create_gitea_ticket" && !isPlanningConfirmation(userInput) {
|
||||
obs := formatToolErrorObservation("WAIT_USER_CONFIRM", toolName, "需用户确认后才能创建工单,请先征求用户确认")
|
||||
if err := callback(StreamEvent{
|
||||
Type: StreamEventTypeToolResult,
|
||||
Content: obs,
|
||||
Step: step,
|
||||
ToolName: toolName,
|
||||
}); err != nil {
|
||||
return "", fmt.Errorf("callback error: %w", err)
|
||||
}
|
||||
messages = append(messages, llm.PromptMessage{
|
||||
Role: "tool",
|
||||
ToolCallID: tc.ID,
|
||||
Name: tc.Function.Name,
|
||||
Content: obs,
|
||||
})
|
||||
continue
|
||||
}
|
||||
|
||||
// 当路由命中 SAFe PI 规划技能或调用 publish_pi_plan 工具时,触发 workspace 事件。
|
||||
isArtifactTool := strings.Contains(toolName, "safe_pi_planning") || toolName == "publish_pi_plan" || (routedToSafePIPlanning && strings.Contains(toolName, "publish_pi_plan"))
|
||||
if isArtifactTool {
|
||||
if err := callback(StreamEvent{
|
||||
Type: StreamEventTypeWorkspaceStart,
|
||||
WorkspaceTitle: "PI Planning Document",
|
||||
ToolName: toolName,
|
||||
}); err != nil {
|
||||
return "", fmt.Errorf("callback error: %w", err)
|
||||
}
|
||||
workspaceSentThisTurn = true
|
||||
}
|
||||
|
||||
toolOut, toolErr := tool.Call(ctx, toolInput)
|
||||
obs := strings.TrimSpace(toolOut)
|
||||
if obs == "" {
|
||||
obs = "(empty output)"
|
||||
}
|
||||
|
||||
if isArtifactTool && toolErr == nil {
|
||||
o.activatePlanningSession(chatID, userID, obs, true)
|
||||
if err := o.store.SaveMessage(chatID, userID, "assistant", wrapPIArtifact(obs)); err != nil {
|
||||
if o.log != nil {
|
||||
o.log.Warnf("%s save planning artifact failed chat_id=%s err=%v", traceLogPrefix, chatID, err)
|
||||
}
|
||||
}
|
||||
// 将工具输出通过 workspace_delta 发送给前端
|
||||
if err := callback(StreamEvent{
|
||||
Type: StreamEventTypeWorkspaceDelta,
|
||||
Content: obs,
|
||||
}); err != nil {
|
||||
return "", fmt.Errorf("callback error: %w", err)
|
||||
}
|
||||
if err := callback(StreamEvent{
|
||||
Type: StreamEventTypeWorkspaceEnd,
|
||||
}); err != nil {
|
||||
return "", fmt.Errorf("callback error: %w", err)
|
||||
}
|
||||
workspaceSentThisTurn = true
|
||||
}
|
||||
|
||||
if toolErr != nil {
|
||||
obs = formatToolErrorObservation("TOOL_EXEC_ERROR", toolName, toolErr.Error()) + "\nOUTPUT:\n" + obs
|
||||
o.emitCapabilityGap(chatID, userID, userInput, "tool_call_failed:"+toolName)
|
||||
@@ -1171,6 +1420,118 @@ func defaultIfEmpty(v, fallback string) string {
|
||||
return v
|
||||
}
|
||||
|
||||
func shouldExitPlanningMode(userInput string) bool {
|
||||
text := strings.ToLower(strings.TrimSpace(userInput))
|
||||
if text == "" {
|
||||
return false
|
||||
}
|
||||
markers := []string{"退出规划", "结束规划", "关闭分屏", "结束分屏", "停止规划", "cancel planning", "exit planning"}
|
||||
for _, marker := range markers {
|
||||
if strings.Contains(text, marker) {
|
||||
return true
|
||||
}
|
||||
}
|
||||
return false
|
||||
}
|
||||
|
||||
func isPlanningConfirmation(userInput string) bool {
|
||||
text := strings.ToLower(strings.TrimSpace(userInput))
|
||||
if text == "" {
|
||||
return false
|
||||
}
|
||||
markers := []string{
|
||||
"确认", "同意", "可以创建", "开始创建", "继续创建", "执行下一步", "没问题,继续",
|
||||
"confirm", "approved", "go ahead", "proceed",
|
||||
}
|
||||
for _, marker := range markers {
|
||||
if strings.Contains(text, marker) {
|
||||
return true
|
||||
}
|
||||
}
|
||||
return false
|
||||
}
|
||||
|
||||
func containsSafePIPlanningSkill(skills []knowledge.Skill) bool {
|
||||
for _, sk := range skills {
|
||||
if isSafePIPlanningSkill(sk) {
|
||||
return true
|
||||
}
|
||||
}
|
||||
return false
|
||||
}
|
||||
|
||||
func isSafePIPlanningSkill(sk knowledge.Skill) bool {
|
||||
name := strings.ToLower(strings.TrimSpace(sk.Name))
|
||||
source := strings.ToLower(strings.TrimSpace(sk.Source))
|
||||
if strings.Contains(name, "safe") || strings.Contains(name, "pi 规划") || strings.Contains(name, "pi planning") {
|
||||
return true
|
||||
}
|
||||
if strings.Contains(source, "safe_pi_planning") {
|
||||
return true
|
||||
}
|
||||
return false
|
||||
}
|
||||
|
||||
func (o *Orchestrator) getSafePIPlanningSkills() []knowledge.Skill {
|
||||
all := o.getSkillsSnapshot()
|
||||
out := make([]knowledge.Skill, 0, 1)
|
||||
for _, sk := range all {
|
||||
if isSafePIPlanningSkill(sk) {
|
||||
out = append(out, sk)
|
||||
}
|
||||
}
|
||||
return out
|
||||
}
|
||||
|
||||
func isPIPlanningToolName(toolName string) bool {
|
||||
t := strings.ToLower(strings.TrimSpace(toolName))
|
||||
return strings.Contains(t, "safe_pi_planning") || t == "publish_pi_plan"
|
||||
}
|
||||
|
||||
func wrapPIArtifact(markdown string) string {
|
||||
content := strings.TrimSpace(markdown)
|
||||
if content == "" {
|
||||
return ""
|
||||
}
|
||||
return "<artifact type=\"safe_pi_planning\" title=\"PI Planning Document\">\n" + content + "\n</artifact>"
|
||||
}
|
||||
|
||||
func (o *Orchestrator) activatePlanningSession(chatID, userID, artifact string, awaitingConfirm bool) {
|
||||
key := pendingFileKey(chatID, userID)
|
||||
o.planningSessionsMu.Lock()
|
||||
defer o.planningSessionsMu.Unlock()
|
||||
state := o.planningSessions[key]
|
||||
state.Active = true
|
||||
if strings.TrimSpace(artifact) != "" {
|
||||
state.LastArtifact = strings.TrimSpace(artifact)
|
||||
}
|
||||
state.AwaitingConfirm = awaitingConfirm
|
||||
state.UpdatedAt = time.Now().UTC()
|
||||
o.planningSessions[key] = state
|
||||
}
|
||||
|
||||
func (o *Orchestrator) clearPlanningSession(chatID, userID string) {
|
||||
key := pendingFileKey(chatID, userID)
|
||||
o.planningSessionsMu.Lock()
|
||||
defer o.planningSessionsMu.Unlock()
|
||||
delete(o.planningSessions, key)
|
||||
}
|
||||
|
||||
func (o *Orchestrator) getPlanningSession(chatID, userID string) (planningSessionState, bool) {
|
||||
key := pendingFileKey(chatID, userID)
|
||||
o.planningSessionsMu.Lock()
|
||||
defer o.planningSessionsMu.Unlock()
|
||||
state, ok := o.planningSessions[key]
|
||||
if !ok {
|
||||
return planningSessionState{}, false
|
||||
}
|
||||
if time.Since(state.UpdatedAt) > planningSessionTTL {
|
||||
delete(o.planningSessions, key)
|
||||
return planningSessionState{}, false
|
||||
}
|
||||
return state, true
|
||||
}
|
||||
|
||||
// formatRelevantSkillsForPrompt 返回与当前用户问题最相关的技能内容。
|
||||
func (o *Orchestrator) formatSelectedSkillsForPrompt(userInput string, selected []knowledge.Skill) string {
|
||||
skills := selected
|
||||
@@ -1331,6 +1692,14 @@ func (o *Orchestrator) emitCapabilityGap(chatID, userID, intent, reason string)
|
||||
return
|
||||
}
|
||||
|
||||
// 暂时关闭基于历史能力缺口的自动技能草稿生成。
|
||||
if !o.autoSkillDraftEnabled {
|
||||
if o.log != nil {
|
||||
o.log.Debugf("auto skill draft generation disabled temporarily")
|
||||
}
|
||||
return
|
||||
}
|
||||
|
||||
// 提取出高频率缺口并在超出阈值后进行 draft 生成
|
||||
clusters, err := o.store.TopCapabilityGapClusters(20, time.Now().UTC().Add(-o.gapLookbackDuration))
|
||||
if err != nil {
|
||||
@@ -1573,6 +1942,50 @@ func sanitizeUserFacingAnswer(raw string) string {
|
||||
return strings.TrimSpace(strings.Join(cleaned, "\n"))
|
||||
}
|
||||
|
||||
// stripArtifactTags removes <artifact ...>...</artifact> blocks from text,
|
||||
// returning only the surrounding non-artifact content.
|
||||
func stripArtifactTags(s string) string {
|
||||
for {
|
||||
start := strings.Index(s, "<artifact")
|
||||
if start == -1 {
|
||||
break
|
||||
}
|
||||
end := strings.Index(s[start:], "</artifact>")
|
||||
if end == -1 {
|
||||
s = strings.TrimSpace(s[:start])
|
||||
break
|
||||
}
|
||||
end += start + len("</artifact>")
|
||||
before := strings.TrimSpace(s[:start])
|
||||
after := strings.TrimSpace(s[end:])
|
||||
if before != "" && after != "" {
|
||||
s = before + "\n\n" + after
|
||||
} else {
|
||||
s = before + after
|
||||
}
|
||||
}
|
||||
return strings.TrimSpace(s)
|
||||
}
|
||||
|
||||
// extractArtifactContent returns the text inside the first <artifact ...>...</artifact> block.
|
||||
// Returns empty string if no artifact tags are found.
|
||||
func extractArtifactContent(s string) string {
|
||||
start := strings.Index(s, "<artifact")
|
||||
if start == -1 {
|
||||
return ""
|
||||
}
|
||||
tagEnd := strings.Index(s[start:], ">")
|
||||
if tagEnd == -1 {
|
||||
return ""
|
||||
}
|
||||
contentStart := start + tagEnd + 1
|
||||
end := strings.Index(s, "</artifact>")
|
||||
if end == -1 {
|
||||
return strings.TrimSpace(s[contentStart:])
|
||||
}
|
||||
return strings.TrimSpace(s[contentStart:end])
|
||||
}
|
||||
|
||||
// splitContentIntoSegments splits a string into smaller segments of the specified size (by rune count).
|
||||
func splitContentIntoSegments(content string, segmentSize int) []string {
|
||||
runes := []rune(content)
|
||||
|
||||
@@ -18,6 +18,7 @@ type Config struct {
|
||||
ReactMaxSteps int
|
||||
ToolCallTimeoutSec int
|
||||
ToolOutputMaxChars int
|
||||
PIPlanMaxChars int // PI 规划工具专用输出上限,独立于 TOOL_OUTPUT_MAX_CHARS
|
||||
EnableCapabilityGap bool
|
||||
AutoSkillDir string
|
||||
GapDraftTriggerCount int
|
||||
@@ -95,6 +96,7 @@ func Load() (Config, error) {
|
||||
ReactMaxSteps: intFromEnv("REACT_MAX_STEPS", 0),
|
||||
ToolCallTimeoutSec: intFromEnv("TOOL_CALL_TIMEOUT_SEC", 15),
|
||||
ToolOutputMaxChars: intFromEnv("TOOL_OUTPUT_MAX_CHARS", 4000),
|
||||
PIPlanMaxChars: intFromEnv("PI_PLAN_MAX_CHARS", 40000),
|
||||
EnableCapabilityGap: boolFromEnv("ENABLE_CAPABILITY_GAP", true),
|
||||
AutoSkillDir: defaultIfEmpty(os.Getenv("AUTO_SKILL_DIR"), filepath.Join(agentWorkspaceDir, "skills")),
|
||||
GapDraftTriggerCount: intFromEnv("GAP_DRAFT_TRIGGER_COUNT", 3),
|
||||
@@ -157,6 +159,9 @@ func Load() (Config, error) {
|
||||
if cfg.ToolOutputMaxChars < 256 || cfg.ToolOutputMaxChars > 200000 {
|
||||
return Config{}, fmt.Errorf("TOOL_OUTPUT_MAX_CHARS must be between 256 and 200000")
|
||||
}
|
||||
if cfg.PIPlanMaxChars < 1000 || cfg.PIPlanMaxChars > 500000 {
|
||||
return Config{}, fmt.Errorf("PI_PLAN_MAX_CHARS must be between 1000 and 500000")
|
||||
}
|
||||
if cfg.GapDraftTriggerCount < 1 || cfg.GapDraftTriggerCount > 100 {
|
||||
return Config{}, fmt.Errorf("GAP_DRAFT_TRIGGER_COUNT must be between 1 and 100")
|
||||
}
|
||||
|
||||
@@ -72,7 +72,7 @@ func RunChild(ctx context.Context, cfg config.Config, log *logger.Logger) error
|
||||
cfg.ToolOutputMaxChars,
|
||||
fileDocLog,
|
||||
))
|
||||
registry.Register(piplan.New(cfg.ToolOutputMaxChars, piPlanLog))
|
||||
registry.Register(piplan.New(cfg.PIPlanMaxChars, piPlanLog))
|
||||
registry.Register(giteaticket.New(
|
||||
giteaticket.Config{
|
||||
BaseURL: cfg.Gitea.BaseURL,
|
||||
|
||||
@@ -15,6 +15,8 @@ import (
|
||||
"laodingbot/internal/config"
|
||||
"laodingbot/internal/llm"
|
||||
"laodingbot/internal/logger"
|
||||
"laodingbot/internal/memory"
|
||||
"strconv"
|
||||
)
|
||||
|
||||
type IncomingMessage struct {
|
||||
@@ -32,6 +34,10 @@ const (
|
||||
StreamEventTypeToolResult StreamEventType = "tool_result" // 工具执行结果
|
||||
StreamEventTypeFinal StreamEventType = "final" // 最终答案
|
||||
StreamEventTypeError StreamEventType = "error" // 错误信息
|
||||
|
||||
StreamEventTypeWorkspaceStart StreamEventType = "workspace_start" // 工具渲染开始
|
||||
StreamEventTypeWorkspaceDelta StreamEventType = "workspace_delta" // 工具渲染增量内容
|
||||
StreamEventTypeWorkspaceEnd StreamEventType = "workspace_end" // 工具渲染结束
|
||||
)
|
||||
|
||||
// StreamEvent 代表流式输出中的一个事件
|
||||
@@ -40,12 +46,14 @@ type StreamEvent struct {
|
||||
Content string `json:"content"`
|
||||
Step int `json:"step,omitempty"`
|
||||
ToolName string `json:"tool_name,omitempty"`
|
||||
WorkspaceTitle string `json:"workspace_title,omitempty"` // 仅用于 workspace_start 类型
|
||||
}
|
||||
|
||||
type ChatHandler func(context.Context, IncomingMessage) (string, error)
|
||||
type StreamChatHandler func(context.Context, IncomingMessage, StreamEventCallback) (string, error)
|
||||
type StreamEventCallback func(event StreamEvent) error
|
||||
type UploadHandler func(context.Context, string, string, []llm.InputFile) ([]string, error)
|
||||
type HistoryHandler func(context.Context, string, int) ([]memory.Message, error)
|
||||
|
||||
type Bot struct {
|
||||
listenAddr string
|
||||
@@ -55,6 +63,7 @@ type Bot struct {
|
||||
chatHandler ChatHandler
|
||||
streamChatHandler StreamChatHandler
|
||||
uploadHandler UploadHandler
|
||||
historyHandler HistoryHandler
|
||||
counter uint64
|
||||
}
|
||||
|
||||
@@ -118,7 +127,7 @@ func NewBot(cfg config.WebUIConfig, log *logger.Logger) (*Bot, error) {
|
||||
}, nil
|
||||
}
|
||||
|
||||
func (b *Bot) Run(ctx context.Context, chatHandler ChatHandler, streamChatHandler StreamChatHandler, uploadHandler UploadHandler) error {
|
||||
func (b *Bot) Run(ctx context.Context, chatHandler ChatHandler, streamChatHandler StreamChatHandler, uploadHandler UploadHandler, historyHandler HistoryHandler) error {
|
||||
if chatHandler == nil {
|
||||
return fmt.Errorf("nil webui chat handler")
|
||||
}
|
||||
@@ -128,11 +137,13 @@ func (b *Bot) Run(ctx context.Context, chatHandler ChatHandler, streamChatHandle
|
||||
b.chatHandler = chatHandler
|
||||
b.streamChatHandler = streamChatHandler
|
||||
b.uploadHandler = uploadHandler
|
||||
b.historyHandler = historyHandler
|
||||
|
||||
mux := http.NewServeMux()
|
||||
mux.HandleFunc("/api/chat", b.handleChat)
|
||||
mux.HandleFunc("/api/chat/stream", b.handleChatStream)
|
||||
mux.HandleFunc("/api/upload", b.handleUpload)
|
||||
mux.HandleFunc("/api/history", b.handleHistory)
|
||||
|
||||
srv := &http.Server{
|
||||
Addr: b.listenAddr,
|
||||
@@ -220,6 +231,42 @@ func (b *Bot) handleChat(w http.ResponseWriter, r *http.Request) {
|
||||
})
|
||||
}
|
||||
|
||||
func (b *Bot) handleHistory(w http.ResponseWriter, r *http.Request) {
|
||||
if r.Method != http.MethodGet {
|
||||
writeJSON(w, http.StatusMethodNotAllowed, errorResponse{Error: "method not allowed"})
|
||||
return
|
||||
}
|
||||
if b.historyHandler == nil {
|
||||
writeJSON(w, http.StatusInternalServerError, errorResponse{Error: "history handler not ready"})
|
||||
return
|
||||
}
|
||||
|
||||
sessionID := strings.TrimSpace(r.URL.Query().Get("session_id"))
|
||||
if sessionID == "" {
|
||||
writeJSON(w, http.StatusBadRequest, errorResponse{Error: "session_id is required"})
|
||||
return
|
||||
}
|
||||
|
||||
limitStr := strings.TrimSpace(r.URL.Query().Get("limit"))
|
||||
limit := 20
|
||||
if limitStr != "" {
|
||||
if l, err := strconv.Atoi(limitStr); err == nil && l > 0 {
|
||||
limit = l
|
||||
}
|
||||
}
|
||||
|
||||
history, err := b.historyHandler(r.Context(), sessionID, limit)
|
||||
if err != nil {
|
||||
if b.log != nil {
|
||||
b.log.Errorf("webui history handler failed session_id=%s err=%v", sessionID, err)
|
||||
}
|
||||
writeJSON(w, http.StatusInternalServerError, errorResponse{Error: "load history failed"})
|
||||
return
|
||||
}
|
||||
|
||||
writeJSON(w, http.StatusOK, history)
|
||||
}
|
||||
|
||||
func firstNonEmpty(vals ...string) string {
|
||||
|
||||
for _, v := range vals {
|
||||
|
||||
@@ -86,8 +86,8 @@ func (t *Tool) Call(ctx context.Context, input string) (string, error) {
|
||||
|
||||
output := render(plan)
|
||||
|
||||
if len(output) > t.maxOutputChars {
|
||||
output = output[:t.maxOutputChars]
|
||||
if len([]rune(output)) > t.maxOutputChars {
|
||||
output = string([]rune(output)[:t.maxOutputChars])
|
||||
}
|
||||
return output, nil
|
||||
}
|
||||
|
||||
Reference in New Issue
Block a user