* fix(context): restore turn cap, serialize content parts and tool calls for llm compress, fix AftCompact debug log
Three context-compaction regression fixes after #8226:
1. Restore max_context_length -> enforce_max_turns propagation so
normal turn-based truncation works again.
2. Serialize ContentPart and ToolCall objects into plain dicts in
_message_to_dict so llm_compress no longer fails with JSON
serialization errors.
3. Print _provider_messages (compacted) instead of run_context.messages
(unchanged) in AftCompact debug log; truncate long role lists to
first4,...,last4 to avoid log spam.
Assertions in tests are also hardened to avoid coupling to exact prompt
wording.
* fix(tool_loop_agent_runner): simplify context handling by removing redundant provider messages
* fix(tool_loop_agent_runner): rename context manager variables for clarity
* fix: update context compression to use recent token ratio instead of fixed count
* fix: enhance LLMSummaryCompressor to sanitize contexts and improve message handling
* ruff format
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Co-authored-by: Soulter <905617992@qq.com>
* refactor(ltm): redesign long-term memory with context compaction
- Add raw_records / contexts / summaries data model per group
- Add LLM summary compaction strategy alongside truncation
- Add turn-based (_split_into_rounds) granularity
- Add image caption integration into LTM history
- Add tool_call / tool_result persistence into raw_records
- Add active reply support driven by LTM state
- Improve summary injection prefix with system note and delimiters
- Add info-level logging for summary compaction lifecycle
- Clarify default summary prompt with explicit preserve/drop rules
- Add context_guard for history overflow protection in agent runner
- Add internal agent history compaction in agent_sub_stages
- Add comprehensive LTM unit tests and compaction test suites
* fix(ltm): handle malformed JSON in tool args and clean up lock on session removal
* fix(ltm): guard against duplicate system prompt note injection
* fix(ltm): fall back to user message when internal marker parsing fails
- Treat lines starting with <T:CALL>, <T:RES, or <BOT/ as regular user
messages when their respective parsers return None, instead of silently
dropping them. Defensive guard against malformed internal markers.
* fix(ltm): release session lock during LLM summary generation
* fix(ltm): trim raw_records in handle_message to prevent unbounded growth
* perf(ltm): use len(s) instead of len(s.encode()) in trim loop
Avoid allocating a new bytes object for every string when calculating
buffer size in _trim_raw_records. Character count is sufficient for
the approximate memory cap.
* feat(ltm): make user segment truncation limits configurable
* feat(ltm): pre-fill default LTM summary prompt in config and i18n
* refactor(ltm): hardcode internal segment/trim constants
* refactor(ltm): unify compaction strategy with main agent runner
* feat(ltm): add @mention weight marker for group chat messages
* test: fix test failures from LTM compaction unification
* chore(dashboard): remove obsolete LTM compaction i18n metadata
* chore: shrink codebase
* feat(group-chat): implement group chat context management and related functionality
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Co-authored-by: Tsukumi <112180165+Tsukumi233@users.noreply.github.com>
Co-authored-by: zenfun <zenfun510@gmail.com>
Co-authored-by: Soulter <905617992@qq.com>
* feat: context compressor
Co-authored-by: kawayiYokami <289104862@qq.com>
* Add comprehensive tests for ContextManager and ContextTruncator
- Implemented a full test suite for ContextManager covering initialization, message processing, token-based compression, and error handling.
- Added tests for ContextTruncator focusing on message fixing, truncation by turns, dropping oldest turns, and halving.
- Ensured that both test suites validate edge cases and maintain expected behavior with various message types, including system and tool messages.
* feat: add MockProvider for LLM compression tests
* chore: remove lock
* ruff fix
* fix
* perf
* feat: enhance context compression with token tracking and logging
* feat: update logging for context compression trigger
* feat: implement context compression logic with dynamic threshold and token tracking
* fix: reorder import statements for consistency
* feat: add token_usage tracking to conversations and update related processing logic
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Co-authored-by: kawayiYokami <289104862@qq.com>
