| 2026-04-15 |
Expand summarization budget for better context quality
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- _MAX_SUMMARY_INPUT_CHARS: 12k → 24k chars (2x input fed to summarizer)
- context_keep_recent: 10 → 8 turns (2 more turns go into each summary batch)
- Summarizer prompt: replace "Be brief" with "Be thorough" — capture code/config
snippets and enough detail to continue the conversation without original messages
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Eugene Sukhodolskiy
committed
on 15 Apr
|
| 2026-04-14 |
Expose compression summary as collapsible debug card in chat UI
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ContextCompressed event now carries the full summary text produced by the
LLM. Compression notice in chat becomes a <details> element showing
message count (before→after) with the summary expandable on click.
Rendered as markdown via marked.js.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Eugene Sukhodolskiy
committed
on 14 Apr
|
| 2026-04-10 |

Add stop button and fix context compression hang
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Stop generation:
- Client: send button toggles to red ■ during streaming; sends {type:stop} via WS
- Server: _stream_recv concurrently reads incoming messages during streaming using
asyncio.wait — stop signal is handled immediately without polling
- Cooperative stop via asyncio.Event (current_stop_event ContextVar): agent breaks
out of LLM async-for cleanly so aclose() fires → Ollama stream closes gracefully,
model stays in VRAM. No task.cancel() which would eject the model.
- StreamStopped event propagates through run_stream/run_ephemeral; sub-agents stop
via the same shared stop_event inherited through task context
Context compression fix:
- compress_context passes think=False to llm.complete() — no extended reasoning
during summarization which caused GPU hang
- Input truncated to 12k chars before sending to summarizer
- LLMBackend.complete() / OllamaBackend.complete() accept think: bool | None override
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Eugene Sukhodolskiy
committed
on 10 Apr
|
| 2026-04-08 |
Review fixes: events module, circular imports, deps, vision-aware compression
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- Extract all AgentEvent dataclasses to navi/core/events.py; import from
there in agent.py and __init__.py — eliminates circular import between
workers and core
- workers/compressor.py: remove runtime import hack, use navi.core.events
- workers/base.py: WorkerResult.events typed as list[AgentEvent] (was Any)
- api/deps.py: replace @lru_cache on mutable list with module-level
singletons (_registries, _workers)
- core/compressor.py: _format_for_summary returns (text, images); images
passed to summarization LLM so vision models describe them in summary;
non-vision models silently ignore the images field; docstring updated
- client/js/app.js: add comment explaining is_summary backward compat branch
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Eugene Sukhodolskiy
committed
on 8 Apr
|

Separate display history from LLM context; formalize worker system
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Architecture change:
- session.messages: full display history, never modified by compression
- session.context: what the LLM sees, may be compressed by workers
- System messages go only into context (not display history)
- Image injections (synthetic) go only into context
- User/assistant/tool messages go into both
SQLite: add context column with backward-compat migration
(empty context → initialized from messages on load)
Workers (navi/workers/):
- Worker ABC + WorkerContext + WorkerResult (base.py)
- CompressionWorker: compresses session.context when above threshold
- build_default_workers() returns [CompressionWorker()]
- Agent accepts workers list, runs them after StreamEnd
- Workers injected via deps.py get_workers() (lru_cached singleton)
- WebSocket agent construction also receives workers
Compressor: compress_context() now takes context[], not messages[]
Config: context_keep_recent 6 → 10
Agent: _run_workers() collects events from all workers and yields them
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Eugene Sukhodolskiy
committed
on 8 Apr
|

Add context compression: rolling summarization when context fills up
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Mechanism:
- After streaming ends, if context_tokens >= threshold (80% of num_ctx),
compress old turns into a summary message using the same LLM
- Partition: keep system msg + last N turns verbatim (default 6);
everything older goes to the summarizer
- Tool call groups (assistant + tool results) never split across boundary
- Existing summary messages folded into new compression pass — no stack growth
- Summary stored as Message(role=user, is_summary=True) after system msg
- On failure: logged, session left unchanged (non-fatal)
New files:
- navi/core/compressor.py: should_compress, partition_messages,
compress_session (pure logic, testable without agent)
New config (navi/config.py):
- context_compression_enabled: bool = True
- context_compression_threshold: float = 0.80
- context_keep_recent: int = 6
- context_summary_temperature: float = 0.3
New agent event: ContextCompressed(messages_before, messages_after)
Message.is_summary: bool field marks compressed history blocks
Client:
- context_compressed WS event → subtle inline notice in message list
- loadHistory: is_summary messages rendered as collapsible summary cards
- style.css: .summary-card, .compression-notice
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Eugene Sukhodolskiy
committed
on 8 Apr
|