mirror of
https://github.com/alibaba/open-code-review.git
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* fix: ensure current file path is always injected for code_comment and improve line number tracking in resolver * test: Cover blank-line matching in resolveFromFileContent fallback Add a regression test for snippets that omit blank lines while the source file retains them, and document that consecutive matching skips blank lines on both sides. * test: Add tests for resolving line numbers with blank lines and CRLF
427 lines
14 KiB
Go
427 lines
14 KiB
Go
package llmloop
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import (
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"context"
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"encoding/json"
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"fmt"
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"sync"
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"sync/atomic"
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"time"
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"github.com/open-code-review/open-code-review/internal/config/template"
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"github.com/open-code-review/open-code-review/internal/diff"
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"github.com/open-code-review/open-code-review/internal/llm"
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"github.com/open-code-review/open-code-review/internal/model"
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"github.com/open-code-review/open-code-review/internal/session"
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"github.com/open-code-review/open-code-review/internal/stdout"
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"github.com/open-code-review/open-code-review/internal/telemetry"
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"github.com/open-code-review/open-code-review/internal/tool"
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)
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// Deps bundles all per-call dependencies the Runner needs. Both
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// internal/agent (diff review) and internal/scan (full-file scan) build a
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// Deps from their own state and hand it to NewRunner.
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type Deps struct {
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LLMClient llm.LLMClient
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Model string
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Template template.Template
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Tools *tool.Registry
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MainToolDefs []llm.ToolDef
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CommentCollector *tool.CommentCollector
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CommentWorkerPool *CommentWorkerPool
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Session *session.SessionHistory
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// DiffLookup is consulted by the code_comment tool path to resolve
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// line numbers against the file's diff (or against full file content
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// in scan mode — scan adapters return a synthetic Diff whose
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// NewFileContent is the whole file and Diff is empty).
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DiffLookup func(path string) *model.Diff
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}
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// Runner is a per-session (across files) executor of the LLM tool-use
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// loop. Token counters, warnings, and the optional background compression
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// job are aggregated across every RunPerFile call.
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type Runner struct {
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deps Deps
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totalInputTokens int64 // atomically updated
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totalOutputTokens int64
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totalCacheReadTokens int64
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totalCacheWriteTokens int64
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warningsMu sync.Mutex
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warnings []AgentWarning
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toolCallsMu sync.Mutex
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toolCalls map[string]int64
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compressionMu sync.Mutex
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pendingJob *compressionJob
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}
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// NewRunner returns a Runner bound to the given dependencies.
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func NewRunner(deps Deps) *Runner {
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return &Runner{deps: deps}
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}
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// TotalInputTokens returns the accumulated input/prompt tokens from all LLM calls.
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func (r *Runner) TotalInputTokens() int64 { return atomic.LoadInt64(&r.totalInputTokens) }
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// TotalOutputTokens returns the accumulated completion tokens from all LLM calls.
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func (r *Runner) TotalOutputTokens() int64 { return atomic.LoadInt64(&r.totalOutputTokens) }
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// TotalCacheReadTokens returns the accumulated cache read tokens.
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func (r *Runner) TotalCacheReadTokens() int64 { return atomic.LoadInt64(&r.totalCacheReadTokens) }
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// TotalCacheWriteTokens returns the accumulated cache write tokens.
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func (r *Runner) TotalCacheWriteTokens() int64 { return atomic.LoadInt64(&r.totalCacheWriteTokens) }
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// TotalTokensUsed returns input + output.
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func (r *Runner) TotalTokensUsed() int64 {
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return r.TotalInputTokens() + r.TotalOutputTokens()
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}
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// Warnings returns a copy of the accumulated warnings.
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func (r *Runner) Warnings() []AgentWarning {
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r.warningsMu.Lock()
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defer r.warningsMu.Unlock()
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out := make([]AgentWarning, len(r.warnings))
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copy(out, r.warnings)
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return out
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}
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// RecordWarning adds a non-fatal warning.
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func (r *Runner) RecordWarning(warningType, file, message string) {
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r.warningsMu.Lock()
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r.warnings = append(r.warnings, AgentWarning{
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File: file,
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Message: message,
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Type: warningType,
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})
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r.warningsMu.Unlock()
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}
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// ToolCalls returns a snapshot of the per-tool call counts.
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func (r *Runner) ToolCalls() map[string]int64 {
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r.toolCallsMu.Lock()
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defer r.toolCallsMu.Unlock()
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out := make(map[string]int64, len(r.toolCalls))
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for k, v := range r.toolCalls {
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out[k] = v
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}
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return out
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}
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func (r *Runner) recordToolCall(name string) {
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r.toolCallsMu.Lock()
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if r.toolCalls == nil {
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r.toolCalls = make(map[string]int64)
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}
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r.toolCalls[name]++
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r.toolCallsMu.Unlock()
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}
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// RecordUsage adds the prompt/completion/cache tokens reported by an LLM
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// response to the runner's aggregate counters. Used by callers (plan phase
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// in agent / future scan phases) that perform their own LLM calls outside
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// RunPerFile.
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func (r *Runner) RecordUsage(u *llm.UsageInfo) {
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if u == nil {
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return
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}
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atomic.AddInt64(&r.totalInputTokens, u.PromptTokens)
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atomic.AddInt64(&r.totalOutputTokens, u.CompletionTokens)
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atomic.AddInt64(&r.totalCacheReadTokens, u.CacheReadTokens)
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atomic.AddInt64(&r.totalCacheWriteTokens, u.CacheWriteTokens)
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}
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// CollectPendingComments awaits any async comment-processing workers and
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// returns the aggregated comments from the collector. Safe to call once
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// per session at the end.
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func (r *Runner) CollectPendingComments() []model.LlmComment {
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if r.deps.CommentWorkerPool != nil {
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r.deps.CommentWorkerPool.Await()
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}
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return r.deps.CommentCollector.Comments()
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}
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// RunPerFile drives the main LLM conversation loop for a single file.
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// It sends messages with the configured tool definitions, executes any
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// tool calls returned by the model, and collects review comments until
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// task_done is called or limits are reached. Token usage and warnings
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// are aggregated on the Runner across all files.
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func (r *Runner) RunPerFile(ctx context.Context, messages []llm.Message, newPath string) error {
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toolReqCount := r.deps.Template.MaxToolRequestTimes
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const maxConsecutiveEmptyRounds = 3
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consecutiveEmptyRounds := 0
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for toolReqCount > 0 {
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select {
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case <-ctx.Done():
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return ctx.Err()
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default:
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}
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toolReqCount--
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fs := r.deps.Session.GetOrCreateFileSession(newPath)
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rec := fs.AppendTaskRecord(session.MainTask, append([]llm.Message(nil), messages...))
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startTime := time.Now()
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resp, err := r.deps.LLMClient.CompletionsWithCtx(ctx, llm.ChatRequest{
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Model: r.deps.Model,
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Messages: messages,
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Tools: r.deps.MainToolDefs,
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MaxTokens: r.deps.Template.MaxTokens,
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})
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duration := time.Since(startTime)
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if err != nil {
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rec.SetError(err, duration)
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telemetry.RecordLLMRequest(ctx, r.deps.Model, duration, 0, "error")
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return fmt.Errorf("LLM completion error: %w", err)
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}
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rec.SetResponse(resp, duration)
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totalTokens := int64(0)
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if resp.Usage != nil {
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totalTokens = resp.Usage.TotalTokens
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atomic.AddInt64(&r.totalInputTokens, resp.Usage.PromptTokens)
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atomic.AddInt64(&r.totalOutputTokens, resp.Usage.CompletionTokens)
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atomic.AddInt64(&r.totalCacheReadTokens, resp.Usage.CacheReadTokens)
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atomic.AddInt64(&r.totalCacheWriteTokens, resp.Usage.CacheWriteTokens)
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}
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telemetry.RecordLLMRequest(ctx, r.deps.Model, duration, totalTokens, "ok")
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content := resp.Content()
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calls := resp.ToolCalls()
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if len(calls) == 0 {
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fmt.Fprintf(stdout.Writer(), "[ocr] No tool calls parsed for %s, retrying...\n", newPath)
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messages = append(messages, llm.NewTextMessage("user", "You did not successfully call any tools. Please try again or use task_done if finished."))
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if content != "" {
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messages = append(messages[:len(messages)-1], llm.NewTextMessage("assistant", content), messages[len(messages)-1])
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}
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continue
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}
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var results []tool.ToolCallResult
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taskCompleted := false
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hasValidResult := false
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for _, call := range calls {
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cp := r.executeToolCall(ctx, newPath, call, rec)
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if cp.Completed {
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results = append(results, tool.ToolCallResult{
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ToolCallID: call.ID,
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Name: call.Function.Name,
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Result: "Task completed successfully.",
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})
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taskCompleted = true
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} else if cp.Data != "" {
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results = append(results, tool.ToolCallResult{
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ToolCallID: call.ID,
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Name: call.Function.Name,
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Result: cp.Data,
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})
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hasValidResult = true
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} else {
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results = append(results, tool.ToolCallResult{
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ToolCallID: call.ID,
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Name: call.Function.Name,
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Result: "Error: Tool execution returned no result.",
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})
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}
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}
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if taskCompleted {
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break
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}
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if !hasValidResult {
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consecutiveEmptyRounds++
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if consecutiveEmptyRounds >= maxConsecutiveEmptyRounds {
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fmt.Fprintf(stdout.Writer(), "[ocr] Too many empty retries for %s, stopping.\n", newPath)
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break
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}
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fmt.Fprintf(stdout.Writer(), "[ocr] No valid tool results for %s, retrying...\n", newPath)
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} else {
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consecutiveEmptyRounds = 0
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}
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succeed := r.addNextMessage(ctx, content, calls, results, &messages, newPath)
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if !succeed {
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fmt.Fprintf(stdout.Writer(), "[ocr] Context compression exceeded threshold for %s, stopping.\n", newPath)
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break
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}
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}
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if toolReqCount <= 0 {
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fmt.Fprintf(stdout.Writer(), "[ocr] Max tool requests reached for %s.\n", newPath)
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}
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return nil
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}
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// executeToolCall dispatches a single tool call from the LLM response and
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// records the result in session history. code_comment handling includes
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// optional async dispatch through CommentWorkerPool plus line-number
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// resolution / re-location.
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func (r *Runner) executeToolCall(ctx context.Context, newPath string, call llm.ToolCall, rec *session.TaskRecord) tool.TaskCheckpoint {
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t := tool.OfName(call.Function.Name)
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if !t.IsKnown() {
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return tool.Of(tool.NotAvailableMsg)
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}
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if t == tool.TaskDone {
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return tool.Complete()
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}
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p := lookupTool(r.deps.Tools, t)
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if p == nil {
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return tool.Of(tool.NotAvailableMsg)
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}
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r.recordToolCall(t.Name())
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var args map[string]any
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if err := json.Unmarshal([]byte(call.Function.Arguments), &args); err != nil {
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return tool.Of(fmt.Sprintf("Error parsing tool arguments for %s: %v", t.Name(), err))
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}
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// Always inject the current file path for code_comment.
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// The model sometimes hallucinates a path, so we override it.
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if t == tool.CodeComment && newPath != "" {
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args["path"] = newPath
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}
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startTime := time.Now()
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if t == tool.CodeComment {
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telemetry.PrintToolCallStarted(t.Name(), args)
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comments, errMsg := tool.ParseComments(args)
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if errMsg != "" {
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telemetry.RecordToolCall(ctx, t.Name(), time.Since(startTime), false)
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return tool.Of(errMsg)
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}
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resolveAndCollect := func(rctx context.Context) {
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for i := range comments {
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cm := &comments[i]
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var d *model.Diff
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if r.deps.DiffLookup != nil {
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d = r.deps.DiffLookup(cm.Path)
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}
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if d != nil {
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if !diff.ResolveComment(cm, d) && r.deps.Template.ReLocationTask != nil {
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rlStart := time.Now()
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_, resp, msgs := diff.ReLocateComment(rctx, cm, d, r.deps.LLMClient, r.deps.Template.ReLocationTask, r.deps.Model, r.deps.Template.MaxTokens)
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if msgs != nil {
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fs := r.deps.Session.GetOrCreateFileSession(cm.Path)
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rlRec := fs.AppendTaskRecord(session.ReLocationTask, msgs)
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if resp != nil {
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rlRec.SetResponse(resp, time.Since(rlStart))
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if resp.Usage != nil {
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atomic.AddInt64(&r.totalInputTokens, resp.Usage.PromptTokens)
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atomic.AddInt64(&r.totalOutputTokens, resp.Usage.CompletionTokens)
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atomic.AddInt64(&r.totalCacheReadTokens, resp.Usage.CacheReadTokens)
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atomic.AddInt64(&r.totalCacheWriteTokens, resp.Usage.CacheWriteTokens)
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}
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} else {
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rlRec.SetError(fmt.Errorf("re-location LLM call failed"), time.Since(rlStart))
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}
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}
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}
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}
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r.deps.CommentCollector.Add(*cm)
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}
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}
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if r.deps.CommentWorkerPool != nil {
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if rec != nil {
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rec.AddToolResult(t.Name(), call.Function.Arguments, "(async)")
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}
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pool := r.deps.CommentWorkerPool
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asyncCtx := context.WithoutCancel(ctx)
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toolName := t.Name()
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pool.Submit(func() ([]model.LlmComment, error) {
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resolveAndCollect(asyncCtx)
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telemetry.PrintToolCallFinished(toolName, time.Since(startTime))
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return []model.LlmComment{}, nil
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})
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telemetry.RecordToolCall(asyncCtx, toolName, time.Since(startTime), true)
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return tool.Of(tool.CommentSucceed)
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}
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resolveAndCollect(ctx)
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dur := time.Since(startTime)
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telemetry.RecordToolCall(ctx, t.Name(), dur, true)
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telemetry.PrintToolCallFinished(t.Name(), dur)
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if rec != nil {
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rec.AddToolResult(t.Name(), call.Function.Arguments, tool.CommentSucceed)
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}
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return tool.Of(tool.CommentSucceed)
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}
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// Synchronous path for all other tools
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telemetry.PrintToolCallStarted(t.Name(), args)
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result, err := p.Execute(ctx, args)
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dur := time.Since(startTime)
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ok := err == nil
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telemetry.RecordToolCall(ctx, t.Name(), dur, ok)
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if err != nil {
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telemetry.PrintToolCallError(t.Name(), err)
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return tool.Of(fmt.Sprintf("Error executing tool %s: %v", t.Name(), err))
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}
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telemetry.PrintToolCallFinished(t.Name(), dur)
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if rec != nil {
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rec.AddToolResult(t.Name(), call.Function.Arguments, result)
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}
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return tool.Of(result)
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}
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// addNextMessage extends the conversation with the assistant message and
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// tool responses, applying three-zone compression at the soft (60%) and
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// warning (80%) MaxTokens thresholds. Returns false when even after
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// synchronous compression the conversation is still over the warning
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// threshold — caller should stop the loop in that case.
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func (r *Runner) addNextMessage(ctx context.Context, assistantContent string, toolCalls []llm.ToolCall, results []tool.ToolCallResult, messages *[]llm.Message, filePath string) bool {
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maxAllowed := r.deps.Template.MaxTokens
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softLimit := int(float64(maxAllowed) * tokenSoftThreshold)
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warnLimit := int(float64(maxAllowed) * tokenWarningThreshold)
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r.tryApplyPendingCompression(messages)
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tokenCount := CountMessagesTokens(*messages)
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if tokenCount > warnLimit {
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r.cancelPendingCompression()
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*messages, _ = r.runCompression(ctx, *messages, filePath)
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tokenCount = CountMessagesTokens(*messages)
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}
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if tokenCount > softLimit && r.pendingJob == nil {
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r.triggerAsyncCompression(ctx, *messages, filePath)
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}
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if len(toolCalls) > 0 {
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*messages = append(*messages, llm.NewToolCallMessage(assistantContent, toolCalls))
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} else if assistantContent != "" {
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*messages = append(*messages, llm.NewTextMessage("assistant", assistantContent))
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}
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for _, rs := range results {
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*messages = append(*messages, llm.NewToolResultMessage(rs.ToolCallID, rs.Result))
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}
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finalCount := CountMessagesTokens(*messages)
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if finalCount > warnLimit {
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r.cancelPendingCompression()
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*messages, _ = r.runCompression(ctx, *messages, filePath)
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}
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return CountMessagesTokens(*messages) < warnLimit
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}
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// lookupTool returns the provider for a given tool from the registry, or
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// nil when not registered.
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func lookupTool(reg *tool.Registry, t tool.Tool) tool.Provider {
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p, ok := reg.Get(t.Name())
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if !ok {
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return nil
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}
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return p
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}
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