Aska
518bd0a230
批次A admin 端点（原本 404 变 200 真实数据）：
- GET /admin/llm：读 s.cfg.LLM 组 openai+anthropic 两 provider（enabled=当前 Provider、multimodal=配 VisionModel），APIKey 不进 wire 零泄露。
- GET /admin/automations：*automations.Service.List()（reminders+event rules+cron schedules，cron 加只读登记）。
- GET /admin/users：cfg.AdminUser + *auth.APIKey.List()（密钥掩码）；无用户存储，恒先返回当前 admin 账号。
- GET /admin/backthink：*backthink.Backthink.List(ctx,50)。均只读、owner/admin RBAC、{data} 信封。
批次B 视觉真推理 + 语音：
- rest.go chatRequest 加 Image?；流式 publishChatStream 带 image；userChatMessages 构造 ImageMessage(model.go:71)。
- loop/vision.go：ImageResolver 可注入（MVP 先看图再对话）；run.go Run 开头 resolveImages，无 resolver 透传直交主模型。
- vision/resolver.go：MessageResolver 调 vision.Router.Route——KindMain 保留图片交主模型多模态、KindVisionTool/OCRTool 经 dispatcher.Invoke 折叠成 [图片内容] 文本、KindUnsupported 记日志保留原图不崩。
- gateway/voice.go：VoiceService 接口 + SetVoice 注入点 + handleVoiceInput（未注入回 error 不崩）+ runVoiceTurn 异步 STT→loop chat→TTS→定向 voice_output 帧。
- ws_hub/ws_route：voice_input 接 handleVoiceInput；前端 ws.ts decodeBase64/playVoiceAudio/case voice_output。
第3步 wire.go 收口（唯一碰 wire.go 的一步）：
- Deps 补传 Automations:a.automation / Backthink:a.backthink / Users:auth.NewAPIKey(a.cfg.Auth)（*auth.APIKey 原生满足 UserStore，避免 admin 重复的复合类型）。
- gw.SetVoice(a.voice)；loop.Options.Vision = vision.NewMessageResolver(router, info, dispatcher.Invoke)（router=NewRouter(WithVisionTool/WithOCRTool)、info=cfg.LLM.VisionModel）。
实机验证：四 admin 端点 200 真实数据（llm 双 provider 脱敏、users=admin,yeij0942,owner）；WS 握手正常。go build/vet/test 全绿 + 前端 tsc。wire.go 557 行。
97 lines
5.1 KiB
Go
97 lines
5.1 KiB
Go
package loop
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import (
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"context"
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"log/slog"
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"git.yeij.top/AskaEth/Cyrene_v2/internal/runtime/agent"
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"git.yeij.top/AskaEth/Cyrene_v2/internal/runtime/guardrail"
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"git.yeij.top/AskaEth/Cyrene_v2/internal/runtime/memory"
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"git.yeij.top/AskaEth/Cyrene_v2/internal/runtime/model"
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"git.yeij.top/AskaEth/Cyrene_v2/internal/runtime/persist"
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"git.yeij.top/AskaEth/Cyrene_v2/internal/runtime/tool"
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"git.yeij.top/AskaEth/Cyrene_v2/internal/runtime/trace"
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)
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// Options configures a Loop. All fields are optional and nil is tolerated until
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// the step that actually needs the field: the agent is required for Run (Run
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// returns ErrNilAgent otherwise); a missing tool dispatcher causes a requested
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// call to be fed back as an error; a missing retriever/persona skips memory
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// injection; a missing extractor/store skips the memory hook; a missing
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// checkpoint skips persistence; a missing tracer skips tracing.
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type Options struct {
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// Agent is the loop's execution unit: an instruction string plus a backend
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// adapter, an optional tool dispatcher and optional guardrails.
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Agent *agent.Agent
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// Tools is the tool dispatcher used to execute model-requested calls. When
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// nil the loop falls back to the agent's own dispatcher (if any).
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Tools *tool.Dispatcher
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// Memory is the long-term memory store used to persist extracted items.
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Memory *memory.Store
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// Retriever injects relevant memories into the context, re-evaluated every
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// round (see assembleContext) so retrieval tracks the latest conversation.
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Retriever *memory.Retriever
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// WorkingMemory is the per-session sliding window, provided for the
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// orchestrator to inspect; the loop does not mutate it.
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WorkingMemory *memory.WorkingMemory
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// Extractor derives memory items to persist after every step.
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Extractor memory.Extractor
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// Checkpoint persists a durable snapshot of the loop state at every step.
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Checkpoint *persist.Store
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// Tracer emits a structured span for every step, LLM call and tool call.
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Tracer *trace.Tracer
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// Guards validates request/response payloads on the streaming path, where
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// RunStep is bypassed. On the non-streaming path the agent runs its own
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// guardrails inside RunStep.
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Guards *guardrail.Pipeline
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// PersonaID scopes memory retrieval and extraction. Blank skips both.
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PersonaID string
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// MaxRounds is the tool-loop upper bound. Non-positive selects
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// DefaultMaxRounds (8).
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MaxRounds int
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// OnStream, when non-nil, switches the loop to the streaming path: the model
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// adapter's ChatStream is driven directly and each structured stream event is
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// forwarded to this callback (model.StreamEvent), so the frontend can render
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// body text, tool calls and (eventually) reasoning segments independently.
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OnStream func(model.StreamEvent)
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// ToolExecution selects how a batch of tool calls is run: "parallel" (the
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// default) or "sequential". Empty means parallel.
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ToolExecution string
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// ToolParallelism caps how many tool calls run concurrently when ToolExecution
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// is "parallel". Non-positive selects DefaultToolParallelism (4).
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ToolParallelism int
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// Hooks installs optional per-batch/per-call tool-loop hooks. Every field is
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// nil-tolerant; these are reserved for "敏感操作代审" (design/11) and the
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// future asynchronous-tool path. A zero Hooks value is a no-op.
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Hooks ToolLoopHooks
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// MaxContextTokens is the context budget that triggers overflow compaction.
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// Non-positive (the zero value) disables compaction, preserving the loop's
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// previous behavior. Setting it to a positive value (e.g.
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// DefaultMaxContextTokens) enables compaction: when the loop's estimated
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// context exceeds the budget it summarizes older turns into a leading summary
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// message while keeping the recent tail (including trailing tool results)
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// intact (design §1.3). Nil-tolerant: leaving it unset changes nothing.
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MaxContextTokens int
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// Compactor compacts an over-budget conversation. Nil selects the built-in
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// structural compactor (no model call); a non-nil value lets a caller inject
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// an LLM-backed or custom summarizer. It is only invoked when
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// MaxContextTokens is positive.
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Compactor Compactor
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// Vision, when non-nil, rewrites an image-bearing user message at the start
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// of Run so the main model can reason over the image (design/06 §0). The
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// concrete resolver (vision.MessageResolver) decides via the vision Router
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// whether to keep the image for a vision-capable main model or fold it into a
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// text description from the vision/OCR tool ("先看图再对话"). Nil keeps the
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// image content as-is, passing it through to a vision-capable main model.
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Vision ImageResolver
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// TransformContext, when non-nil, is called immediately before every model
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// step with the assembled message list (after memory injection and any
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// compaction) and the current round number (1-based). It may project, filter
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// or re-order the messages the model sees. It is the loop's equivalent of
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// OpenClaw's transformContext (design §1.3). Nil = no projection.
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TransformContext func(ctx context.Context, messages []model.Message, round int) []model.Message
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// Log is the base logger. Nil is replaced with a discard logger tagged with
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// source "runtime/loop".
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Log *slog.Logger
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}
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