Files
picoclaw/pkg/tokenizer/estimator.go
T
Liu Yuan 15a70ac45c feat(seahorse): implement short-term memory engine (LCM) (#2285)
* feat(seahorse): implement short-term memory engine of seahorse

Add pkg/seahorse/ module implementing a SQLite-backed DAG-based summary
hierarchy for context management, ported from lossless-claw's LCM design:

- types.go + short_constants.go: core types (Message, Summary, Conversation,
  ContextItem) and configuration constants (fanout, token targets, thresholds)
- migration.go: idempotent DB schema with FTS5 trigram tokenizer for CJK
- store.go: full SQLite CRUD (conversations, messages, summaries DAG,
  context_items with ordinal gap numbering, FTS5 search)
- short_engine.go: Engine lifecycle (NewEngine, Ingest, Assemble, Compact),
  session pattern filtering (ignore/stateless glob→regex compilation),
  per-session mutex via sync.Map
- short_assembler.go: budget-aware context assembly with fresh tail protection
  (32 messages), oldest-first eviction, summary XML formatting, RebuildContextItems
- short_compaction.go: leaf compaction (messages→summary) and condensed
  compaction (summaries→higher-level summary), 3-level LLM escalation,
  CompactUntilUnder for emergency overflow
- short_retrieval.go: lookupByID, FTS5/LIKE search, recursive expand with
  token cap
- context_seahorse.go: agent.ContextManager adapter, registered as "seahorse",
  provider↔seahorse message type conversion (ToolCalls, tool_result)

* fix(seahorse): correct 3 adapter bugs in context management

- TokenCount: use full message (Content+ToolCalls+Media) instead of Content-only
- Empty Content: rebuild Content from tool_result Parts when stored empty
- Duplicate summaries: summaries only in Summary field, not in History messages
- Grep: fix SearchResult.Snippet→Content for summaries
- Schema: fix FTS5 SQL uses VIRTUAL TABLE not TEMP TABLE
- TestFTS5SQLConstants: verify FTS5 SQL syntax correctness
- Test: fix flaky TestCompactLeaf

* fix(agent): ingest steering messages into seahorse SQLite

Steering messages were only persisted to session JSONL but not ingested
into seahorse SQLite, causing them to be missing from context assembly.

Added `ts.ingestMessage(turnCtx, al, pm)` call in the steering message
injection block alongside the existing JSONL persistence.

Test: TestSeahorseSteeringMessageIngested verifies steering messages
appear in seahorse SQLite DB after being processed.

* fix(seahorse): address 3 blocking bugs from code review

- Fix resequenceContextItemsTx scan error handling (store.go:850)
  Changed `return err` to `return scanErr` to properly propagate scan errors
  instead of returning nil (which silently corrupts data)

- Fix sql.NullString for INTEGER column (store.go:847)
  Changed `mid` from sql.NullString to sql.NullInt64 since message_id
  is INTEGER in schema. Removed unnecessary strconv.ParseInt call.

- Fix compactCondensed fallback deleting non-candidate items
  Added ReplaceContextItemsWithSummary method for per-item deletion
  when candidates are not contiguous in ordinal space.
  Optimized to use range deletion when candidates are consecutive.

* fix(seahorse): pass Budget to Compact for correct condensed threshold

Issue #4 from PR review: When Budget was not passed to seahorse.Compact,
it defaulted to `tokensBefore * 0.75`, making `tokensBefore > budget`
always true and causing condensed compaction to trigger unnecessarily.

Changes:
- context_seahorse.go: Forward Budget from CompactRequest to CompactInput
- loop.go: Pass Budget (ContextWindow) in all 3 Compact calls
- Add test verifying condensed is skipped when tokens < threshold
- Fix lint issues in store.go and store_test.go

* fix(seahorse): add mutex for assembler lazy initialization

Issue #5 from PR review: The check-then-create pattern for e.assembler
was a data race when multiple goroutines called Assemble() concurrently:
    if e.assembler == nil {
        e.assembler = &Assembler{...}
    }

Changes:
- Add assemblerMu sync.Mutex to Engine struct
- Add initAssemblerOnce() using double-checked locking (same pattern as initCompactionOnce)
- Add TestAssemblerLazyInitRace to verify thread-safety

* fix(seahorse): handle non-consecutive depths in selectShallowestCondensationCandidate

Issue #8 from PR review: the loop iterated depth 0, 1, 2... assuming
consecutive keys, but break when key was missing caused deeper depths
to never be checked.

Fix: collect all existing depth keys, sort, then iterate in order.

* fix(seahorse): wrap DeleteMessagesAfterID and appendContextItems in transactions

- DeleteMessagesAfterID: wrap all DELETE operations in a transaction for
  atomicity, remove redundant manual FTS delete (handled by trigger)
- appendContextItems: use transaction to fix read-then-write race condition
- Add GetMaxOrdinalTx and resolveItemTokenCountTx for transaction-scoped queries
- Remove unused resolveItemTokenCount function

Fixes PR review issues 6 and 7.

* fix(seahorse): derive readable content from Parts and cap CompactUntilUnder iterations

- Derive readable content from MessageParts in AddMessageWithParts so
  FTS5 indexing and summary formatting can access tool call information
- formatMessagesForSummary and truncateSummary now fall back to Parts
  when Content is empty, fixing blank summaries for Part-based messages
- Add MaxCompactIterations (20) to prevent CompactUntilUnder infinite
  loops; exceeded iterations are logged as warnings
2026-04-05 09:05:16 +08:00

92 lines
2.7 KiB
Go

package tokenizer
import (
"encoding/json"
"unicode/utf8"
"github.com/sipeed/picoclaw/pkg/providers"
)
// EstimateMessageTokens estimates the token count for a single message,
// including Content, ReasoningContent, ToolCalls arguments, ToolCallID
// metadata, and Media items. Uses a heuristic of 2.5 characters per token.
func EstimateMessageTokens(msg providers.Message) int {
contentChars := utf8.RuneCountInString(msg.Content)
// SystemParts are structured system blocks used for cache-aware adapters.
// They carry the same content as Content, but in multiple blocks.
// We estimate them as an alternative representation, not additive.
systemPartsChars := 0
if len(msg.SystemParts) > 0 {
for _, part := range msg.SystemParts {
systemPartsChars += utf8.RuneCountInString(part.Text)
}
// Per-part overhead for JSON structure (type, text, cache_control).
const perPartOverhead = 20
systemPartsChars += len(msg.SystemParts) * perPartOverhead
}
// Use the larger of the two representations to stay conservative.
chars := contentChars
if systemPartsChars > chars {
chars = systemPartsChars
}
chars += utf8.RuneCountInString(msg.ReasoningContent)
for _, tc := range msg.ToolCalls {
chars += len(tc.ID) + len(tc.Type)
if tc.Function != nil {
// Count function name + arguments (the wire format for most providers).
// tc.Name mirrors tc.Function.Name — count only once to avoid double-counting.
chars += len(tc.Function.Name) + len(tc.Function.Arguments)
} else {
// Fallback: some provider formats use top-level Name without Function.
chars += len(tc.Name)
}
}
if msg.ToolCallID != "" {
chars += len(msg.ToolCallID)
}
// Per-message overhead for role label, JSON structure, separators.
const messageOverhead = 12
chars += messageOverhead
tokens := chars * 2 / 5
// Media items (images, files) are serialized by provider adapters into
// multipart or image_url payloads. Add a fixed per-item token estimate
// directly (not through the chars heuristic) since actual cost depends
// on resolution and provider-specific image tokenization.
const mediaTokensPerItem = 256
tokens += len(msg.Media) * mediaTokensPerItem
return tokens
}
// EstimateToolDefsTokens estimates the total token cost of tool definitions
// as they appear in the LLM request.
func EstimateToolDefsTokens(defs []providers.ToolDefinition) int {
if len(defs) == 0 {
return 0
}
totalChars := 0
for _, d := range defs {
totalChars += len(d.Function.Name) + len(d.Function.Description)
if d.Function.Parameters != nil {
if paramJSON, err := json.Marshal(d.Function.Parameters); err == nil {
totalChars += len(paramJSON)
}
}
// Per-tool overhead: type field, JSON structure, separators.
totalChars += 20
}
return totalChars * 2 / 5
}