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[email protected]andClaude Opus 4.6
4bc7ffdf0c
Budget enforcement in ExecutionLoop: - max_tokens_total: cumulative token limit, checked before each iteration - max_duration: wall-clock timeout for entire thread - max_consecutive_errors: consecutive error steps threshold (resets on success, matching official RLM behavior) - All produce ThreadOutcome::Failed with descriptive messages Context compaction (from RLM paper, 85% threshold): - estimate_tokens(): char-based estimation (chars/4, matching RLM) - should_compact(): triggers when tokens >= threshold_pct * context_limit - compact_messages(): asks LLM to summarize progress, replaces history with [system, summary, continuation_note], preserves intermediate results - Configurable via ThreadConfig: model_context_limit, compaction_threshold Dual model routing: - LlmCallConfig gains depth field (0=root, 1+=sub-call) - Implementations can route to cheaper models for sub-calls - ExecutionLoop passes thread depth to every LLM call Reflection pipeline (reflection/pipeline.rs): - reflect(thread, llm): analyzes completed thread via LLM - Produces Summary doc (always), Lesson doc (if errors), Issue doc (if failed) - Builds transcript from thread messages + error events - Returns ReflectionResult with docs + token usage ThreadConfig extended with: max_tokens_total, max_consecutive_errors, model_context_limit, enable_compaction, compaction_threshold, depth, max_depth. 78 tests passing, zero clippy warnings. Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]>