feat(loop): Top5#5 上下文溢出压缩 + 每轮 assemble（对齐 OpenClaw context-engine）——Top5 全完成
- 每轮 assemble(transformContext 等价)：run.go 每 step 前 assembleContext——依次 Inject(每轮 重新 Retriever.Inject 不缓存首轮)、WorkingMemory 前置 Summarize、可插拔 TransformContext 投影/ 过滤；生成的 view 交 step，msgs 保持纯对话供工具结果追加，记忆不重复注入、不写回 checkpoint。 - Compactor：结构分支感知压缩——estimateContextTokens 启发式超 MaxContextTokens 且消息≥3 才动； findKeepStart 按 user 消息切整轮从后往前累加(至少保留最后一整轮→尾随工具结果绝不切片/不跨轮)； 旧轮 user/assistant 对压成一条 RoleSystem 摘要置顶，既有摘要前缀识别合并防叠；capSummary 上限 4000 rune；ctx 即 abortSignal(取消返回 ctx.Err，压缩失败仅记日志不中断 run)。 - 选项：Options 增 MaxContextTokens/Compactor/TransformContext，均 nil-tolerant(默认=现有行为， 零值不压缩)；DefaultMaxContextTokens=32768。Compactor 接口预留注入 LLM 摘要。 go build/vet/test -count=1 全绿 + windows/darwin 交叉编译。12 断言覆盖尾随工具结果保留/不跨轮切割/ 摘要上限/摘要合并/ctx 取消/每轮重检索/TransformContext 逐轮/超限压缩/默认关闭。-race 受宿主 TSan VMA 限制无法运行(与代码无关)。 **至此 Top5(1~5) 全部完成并推库。**
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package loop
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import (
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"context"
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"fmt"
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"strings"
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"unicode/utf8"
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"git.yeij.top/AskaEth/Cyrene_v2/internal/runtime/model"
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)
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// Compaction tuning constants. These bound the compactor so it stays
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// deterministic and offline: the summary is capped, the recent tail is a share
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// of the budget, and very short conversations are left alone even when they
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// exceed the budget (design §1.3 上下文溢出压缩).
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const (
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// DefaultMaxContextTokens is the context budget a caller can assign to
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// Options.MaxContextTokens to enable overflow compaction (design §1.3).
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DefaultMaxContextTokens = 32768
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// keepRecentFraction is the share of the budget reserved for the recent tail
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// during compaction; the remainder is left for the summary message and prompt.
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keepRecentFraction = 0.5
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// minKeepTokens is the floor for the recent-tail budget so a tiny
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// MaxContextTokens does not force every turn into the summary.
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minKeepTokens = 128
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// summaryMarker tags a compaction summary system message so the compactor can
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// recognize an existing summary prefix and preserve (merge into) it rather
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// than re-summarize it on a later compaction.
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summaryMarker = "[前文摘要 · history summary]"
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// maxSummaryChars caps the compaction summary so repeated compactions cannot
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// inflate the summary without bound (design §1.3 摘要容量上限).
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maxSummaryChars = 4000
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// minCompactMessages is the smallest conversation the compactor will touch; a
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// shorter one is left alone even when it is over budget.
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minCompactMessages = 3
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// messageOverheadTokens is the per-message token overhead charged for the role
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// and separator tokens the provider adds around each message.
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messageOverheadTokens = 4
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// imageTokens is the rough token charge for a single image part.
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imageTokens = 1000
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// charsPerToken is the character-to-token divisor used by the offline estimate.
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charsPerToken = 4
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// summarySampleChars bounds the per-message text sampled into a naive summary.
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summarySampleChars = 120
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)
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// Compactor compacts an over-budget conversation by summarizing older turns into
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// a single leading summary message while preserving the recent tail — including
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// the trailing tool results — unmodified (design §1.3, aligned with OpenClaw's
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// context-engine). It is injected through Options.Compactor so a caller can swap
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// in an LLM-backed summarizer; the loop ships a structural default that never
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// calls a model.
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type Compactor interface {
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// Compact returns messages with older turns compressed into a leading summary
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// when the estimated tokens exceed budget. It returns the input unchanged when
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// the messages already fit within budget or there is nothing safe to
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// summarize. ctx is the abort signal: a canceled context stops compaction and
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// returns a wrapped context.Canceled so the caller can bail out.
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Compact(ctx context.Context, messages []model.Message, budget int) ([]model.Message, error)
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}
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// defaultCompactor is the built-in structural compactor. It is stateless and
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// safe for concurrent use.
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type defaultCompactor struct{}
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// Compact implements Compactor.
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func (defaultCompactor) Compact(ctx context.Context, messages []model.Message, budget int) ([]model.Message, error) {
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if ctx == nil {
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ctx = context.Background()
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}
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if err := ctx.Err(); err != nil {
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return nil, fmt.Errorf("loop: compact: %w", err)
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}
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return compactMessages(ctx, messages, budget)
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}
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// compactMessages is the shared compaction implementation. It never mutates the
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// input slices; a compacted result is always freshly allocated.
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func compactMessages(ctx context.Context, messages []model.Message, budget int) ([]model.Message, error) {
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if budget <= 0 || len(messages) < minCompactMessages {
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return messages, nil
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}
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if estimateContextTokens(messages) <= budget {
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return messages, nil
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}
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prefixEnd := summaryPrefixEnd(messages)
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keepTokens := max(int(float64(budget)*keepRecentFraction), minKeepTokens)
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keepStart := findKeepStart(messages, prefixEnd, keepTokens)
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if keepStart <= prefixEnd {
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// Everything is being kept; there is no safe prefix to summarize.
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return messages, nil
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}
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if err := ctx.Err(); err != nil {
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return nil, fmt.Errorf("loop: compact: %w", err)
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}
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existing := ""
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if prefixEnd > 0 {
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existing = strings.TrimPrefix(messageText(messages[0]), summaryMarker+"\n\n")
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}
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fresh := buildSummary(messages[prefixEnd:keepStart])
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if fresh == "" && existing == "" {
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return messages, nil
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}
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full := fresh
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if existing != "" {
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full = existing + "\n\n" + fresh
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}
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summary := model.TextMessage(model.RoleSystem, summaryMarker+"\n\n"+capSummary(full, maxSummaryChars))
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out := make([]model.Message, 0, len(messages)-(keepStart-prefixEnd)+1)
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out = append(out, summary)
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out = append(out, messages[keepStart:]...)
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return out, nil
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}
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// summaryPrefixEnd returns the count of leading compaction-summary messages,
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// which are never re-summarized. It is 0 (no summary) or 1 (a single summary
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// prefix), since compaction always emits exactly one leading summary.
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func summaryPrefixEnd(messages []model.Message) int {
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if len(messages) == 0 || messages[0].Role != model.RoleSystem {
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return 0
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}
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if strings.HasPrefix(messageText(messages[0]), summaryMarker) {
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return 1
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}
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return 0
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}
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// findKeepStart returns the index of the first message to keep given that the
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// recent tail should fit within keepTokens. It always keeps whole turns: a turn
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// starts at a user message and runs to the next user message. It scores turns
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// from the back, so the most recent turns survive and a trailing tool result is
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// never sliced apart. When no user turn exists (unusual), it keeps nothing extra
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// and returns from, so nothing is summarized.
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func findKeepStart(messages []model.Message, from, keepTokens int) int {
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n := len(messages)
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turns := make([]int, 0, 8)
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for i := from; i < n; i++ {
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if messages[i].Role == model.RoleUser {
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turns = append(turns, i)
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}
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}
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if len(turns) == 0 {
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return from
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}
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acc := 0
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keptStart := turns[len(turns)-1]
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for i := len(turns) - 1; i >= 0; i-- {
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to := n
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if i+1 < len(turns) {
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to = turns[i+1]
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}
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if i == len(turns)-1 || acc+estimateContextTokens(messages[turns[i]:to]) <= keepTokens {
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acc += estimateContextTokens(messages[turns[i]:to])
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keptStart = turns[i]
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} else {
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break
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}
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}
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return keptStart
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}
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// estimateContextTokens returns a conservative token estimate for messages. It is
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// a heuristic (chars ÷ charsPerToken with a per-message and per-image overhead)
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// so it stays dependency-free and offline, but it is monotonic enough to drive
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// the compact decision.
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func estimateContextTokens(messages []model.Message) int {
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total := 0
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for _, m := range messages {
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total += messageOverheadTokens
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for _, part := range m.Content {
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switch part.Type {
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case model.ContentTypeText:
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total += estimateStringTokens(part.Text)
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case model.ContentTypeImage:
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total += imageTokens
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}
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}
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}
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return total
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}
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// estimateStringTokens is the character-level token estimate for one text string,
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// weighting wide (CJK) runes double and dividing by charsPerToken. An empty string
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// costs nothing; a non-empty one costs at least one token.
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func estimateStringTokens(s string) int {
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if s == "" {
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return 0
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}
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runes := utf8.RuneCountInString(s)
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wide := 0
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for _, r := range s {
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if r >= 0x2E80 {
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wide++
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}
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}
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t := (runes + wide) / charsPerToken
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if t < 1 {
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t = 1
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}
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return t
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}
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// buildSummary renders a compact structural summary of the given messages: a role
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// distribution plus the most recent user and assistant text. It is the default
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// (offline, no-model) summarizer; a caller that wants a semantic digest injects
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// its own Compactor instead.
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func buildSummary(messages []model.Message) string {
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if len(messages) == 0 {
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return ""
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}
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counts := map[model.Role]int{}
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lastUser, lastAssistant := "", ""
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for _, m := range messages {
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counts[m.Role]++
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text := messageText(m)
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if text == "" {
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continue
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}
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switch m.Role {
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case model.RoleUser:
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lastUser = text
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case model.RoleAssistant:
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lastAssistant = text
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}
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}
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var b strings.Builder
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fmt.Fprintf(&b, "已压缩 %d 条历史消息（", len(messages))
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first := true
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for _, role := range []model.Role{model.RoleSystem, model.RoleUser, model.RoleAssistant, model.RoleTool} {
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if c := counts[role]; c > 0 {
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if !first {
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b.WriteString("，")
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}
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first = false
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fmt.Fprintf(&b, "%s %d", role, c)
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}
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}
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b.WriteString("）")
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if lastUser != "" {
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fmt.Fprintf(&b, "。最近用户: %s", truncateRunes(lastUser, summarySampleChars))
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}
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if lastAssistant != "" {
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fmt.Fprintf(&b, "。最近助手: %s", truncateRunes(lastAssistant, summarySampleChars))
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}
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return b.String()
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}
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// capSummary truncates s to at most max runes, appending a "..." marker when it
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// had to cut. It is rune-safe so it never slices a multi-byte rune in half.
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func capSummary(s string, max int) string {
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runes := []rune(s)
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if len(runes) <= max {
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return s
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}
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if max < 3 {
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return string(runes[:max])
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}
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return string(runes[:max-3]) + "..."
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}
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// truncateRunes shortens s to at most n runes, Unicode-safe.
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func truncateRunes(s string, n int) string {
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runes := []rune(s)
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if len(runes) <= n {
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return s
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}
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return string(runes[:n])
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}
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