- Introduced a new design document for research backend integration, outlining scope, architecture, and API specifications. - Added frontend API service functions for managing research agents, nodes, and reports. - Extended existing Go backend packages to support new research functionalities. feat: Implement PicoClaw context window improvements - Created a design document detailing seven context-window improvements to enhance performance and prevent errors. - Improvements include token estimation fixes, structured error handling, and proactive context management strategies. fix: Document known issues and resolutions - Added a known issues document detailing a critical compile error related to invalid Unicode escapes in Go, including the fix applied. docs: Add context management skill documentation - Introduced a new skill for context management, detailing usage scenarios, project mapping, state persistence, and integration with PicoClaw.
102 lines
3.1 KiB
Go
102 lines
3.1 KiB
Go
package tokenizer
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import (
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"encoding/json"
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"unicode/utf8"
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"github.com/sipeed/picoclaw/pkg/providers"
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)
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// EstimateMessageTokens estimates the token count for a single message,
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// including Content, ReasoningContent, ToolCalls arguments, ToolCallID
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// metadata, and Media items. Uses a heuristic of 2.5 characters per token.
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func EstimateMessageTokens(msg providers.Message) int {
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contentChars := utf8.RuneCountInString(msg.Content)
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// SystemParts are structured system blocks used for cache-aware adapters.
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// They carry the same content as Content, but in multiple blocks.
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// We estimate them as an alternative representation, not additive.
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systemPartsChars := 0
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if len(msg.SystemParts) > 0 {
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for _, part := range msg.SystemParts {
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systemPartsChars += utf8.RuneCountInString(part.Text)
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}
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// Per-part overhead for JSON structure (type, text, cache_control).
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const perPartOverhead = 20
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systemPartsChars += len(msg.SystemParts) * perPartOverhead
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}
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// Use the larger of the two representations to stay conservative.
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chars := contentChars
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if systemPartsChars > chars {
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chars = systemPartsChars
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}
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chars += utf8.RuneCountInString(msg.ReasoningContent)
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for _, tc := range msg.ToolCalls {
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chars += len(tc.ID) + len(tc.Type)
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if tc.Function != nil {
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// Count function name + arguments (the wire format for most providers).
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// tc.Name mirrors tc.Function.Name — count only once to avoid double-counting.
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chars += len(tc.Function.Name) + len(tc.Function.Arguments)
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} else {
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// Fallback: some provider formats use top-level Name without Function.
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chars += len(tc.Name)
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}
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}
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if msg.ToolCallID != "" {
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chars += len(msg.ToolCallID)
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}
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// Per-message overhead for role label, JSON structure, separators.
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const messageOverhead = 12
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chars += messageOverhead
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// Use 4 characters per token (conservative estimate, matching OpenCode's approach).
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// The previous 2.5 chars/token was too optimistic and led to context
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// window overflow errors. English text typically uses ~4 chars/token.
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tokens := chars / 4
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if chars%4 != 0 {
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tokens++ // Round up
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}
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// Media items (images, files) are serialized by provider adapters into
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// multipart or image_url payloads. Add a fixed per-item token estimate
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// directly (not through the chars heuristic) since actual cost depends
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// on resolution and provider-specific image tokenization.
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const mediaTokensPerItem = 256
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tokens += len(msg.Media) * mediaTokensPerItem
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return tokens
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}
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// EstimateToolDefsTokens estimates the total token cost of tool definitions
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// as they appear in the LLM request.
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func EstimateToolDefsTokens(defs []providers.ToolDefinition) int {
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if len(defs) == 0 {
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return 0
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}
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totalChars := 0
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for _, d := range defs {
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totalChars += len(d.Function.Name) + len(d.Function.Description)
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if d.Function.Parameters != nil {
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if paramJSON, err := json.Marshal(d.Function.Parameters); err == nil {
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totalChars += len(paramJSON)
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}
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}
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// Per-tool overhead: type field, JSON structure, separators.
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totalChars += 20
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}
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// Use 4 characters per token (conservative estimate, matching OpenCode)
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result := totalChars / 4
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if totalChars%4 != 0 {
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result++ // Round up
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}
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return result
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}
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