Trigger token consolidation before prompt usage reaches the full context window so response tokens and tokenizer estimation drift still fit safely within the model budget.
Made-with: Cursor
Replace fire-and-forget consolidation with archive_messages(), which
retries until the raw-dump fallback triggers — making it effectively
infallible. /new now clears the session immediately and archives in
the background. Pending archive tasks are drained on shutdown via
close_mcp() so no data is lost on process exit.
- Require both history_entry and memory_update, reject null/empty values
- Fallback to tool_choice=auto when provider rejects forced function call
- After 3 consecutive consolidation failures, raw-archive messages to
HISTORY.md without LLM summarization to prevent context window overflow
Some providers (e.g. Dashscope in thinking mode) reject object-style
tool_choice with "does not support being set to required or object".
Retry once with tool_choice="auto" instead of failing silently.
Made-with: Cursor
Fix issue #1823: Memory consolidation does not inherit agent temperature
and maxTokens configuration.
The agent's configured generation parameters were not being passed through
to the memory consolidation call, causing it to fall back to default values.
This resulted in the consolidation response being truncated before the
save_memory tool call was emitted.
- Pass temperature, max_tokens, reasoning_effort from AgentLoop to
MemoryConsolidator and then to MemoryStore.consolidate()
- Forward these parameters to the provider.chat_with_retry() call
Fixes#1823
Move consolidation policy into MemoryConsolidator, keep backward compatibility for legacy config, and compress history by token budget instead of message count.
Major changes:
- Replace message-count-based memory window with token-budget-based compression
- Add max_tokens_input, compression_start_ratio, compression_target_ratio config
- Implement _maybe_compress_history() that triggers based on prompt token usage
- Use _build_compressed_history_view() to provide compressed history to LLM
- Refactor MemoryStore.consolidate() -> consolidate_chunk() for chunk-based compression
- Remove last_consolidated from Session, use _compressed_until metadata instead
- Add background compression scheduling to avoid blocking message processing
Key improvements:
- Compression now based on actual token usage, not arbitrary message counts
- Better handling of long conversations with large context windows
- Non-destructive compression: old messages remain in session, but excluded from prompt
- Automatic compression when history exceeds configured token thresholds
Some LLM providers return tool_calls[0].arguments as a list instead of
dict or str. Add handling to extract the first dict element from the list.
Fixes /new command warning: 'unexpected arguments type list'
Fixes#1042. When the LLM returns tool call arguments as a dict or
JSON string instead of parsed values, memory consolidation would fail
with "TypeError: data must be str, not dict".
Changes:
- Add type guard in MemoryStore.consolidate() to parse string arguments
and reject unexpected types gracefully
- Add regression tests covering dict args, string args, and edge cases
Xubin Ren
ethanclaw
shenchengtsi
VITOHJL
nanobot-contributor
alairjt