feat: add Moonshot provider + path-based canonical content format#1
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Add MoonshotProvider extending OpenAICompatibleProvider for Kimi API. Supports image and video input via base64-encoded content blocks.
Replace base64-inline canonical format with path-based MediaBlocks.
Encoding is now provider's concern, not the canonical format.
- Add TextBlock, MediaBlock TypedDicts and ContentBlock union in types.py
- Add shared read_media_as_base64() helper for OpenAI/Anthropic/Moonshot
- FileIOResource emits {"type": ..., "media_type": ..., "path": ...}
- Gemini reads raw bytes directly (no base64 round-trip)
- Delete multimodal_converter.py (logic moved to provider methods)
- All tests updated to use tmp_path with real temp files
- Add GitHub Actions workflow running lint + mocked tests on PRs to develop, stable, main, and main/** branches - Remove unused prepare_anthropic_messages standalone function - Fix test_create_moonshot_provider to expect MoonshotProvider - Fix test_star_agent_deprecated_codec_parameter (warning never emitted)
- Upgrade to setup-uv@v6 with dependency caching - Use setup-python@v5 for Python setup - Filter tests with -m "not live and not deep" - Add --durations=10 for slow test visibility - Add workflow_dispatch for manual triggers
GPT-5+ rejects max_tokens param. Add rename support to MODEL_RESTRICTIONS so _filter_params_for_model automatically remaps it.
- Install dev extras in CI workflow (uv sync --extra dev) so ruff is available - Add .pre-commit-config.yaml with ruff, format, and safety checks - Fix all 23 ruff lint errors (import sorting, unused imports/vars, quotes)
- Fix .gitignore: lib/ → /lib/ so dana/lib/ is not excluded - Add dana/lib/ (agents, workflows, resources, memory, search) - Fix ruff errors: missing HTML_PARSER import, dead version block
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…t_sessions (GH-1) Timeline serializer now goes through the repository interface only — no direct file I/O, no Path/glob, no _events_path access. Compaction mints sibling logical sessions {base}__compact__{ISO-ts} instead of rolling snapshot files, making the compression feature usable with any TimelineRepositoryProtocol implementation (including in-memory and remote repos, not just filesystem-backed). - Add list_sessions(prefix) to TimelineRepositoryProtocol + local impl. - Add TimelineRepositoryDefaultsMixin so external repos without list_sessions get a no-op default (empty list → single-session fallback). - Rewrite TimelineSerializerMixin (448→347 LOC) to use only save/ read_session_entries/list_sessions. - Drop native_messages persistence — recomputed from entries on load. - Rename CompressedTimeline state: _active_snapshot_path → _active_compact_session_id, _active_snapshot_compression_at → _active_compact_compression_at. - Use microsecond precision in compact session timestamps to prevent same-second collisions that would break audit retention. - Add in-memory test fixture + parity test proving behavior matches across local-fs and in-memory backends. - Keep LocalTimelineRepository._resolve_timeline_file_for_read for backward-compat reads of legacy timeline-after-compress-*.json. Refs: GH-1 Plan: plans/260420-2141-GH-1-timeline-repository-compatibility/ Tests: 132/132 timeline+compression tests pass.
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* feat(timeline): compression parity upgrades (P2+P3+P6)
Close three compression gaps vs OpenClaude while staying single-tier,
LLM-agnostic, KISS. Always uses len(str)/4 heuristic — zero provider
coupling. System+tools coverage via optional caller-supplied callbacks.
Phase 1 — Heuristic threshold (P3)
- New env knob DANA_COMPACT_TRIGGER_TOKENS (default 150000, clamp [8k, 2M])
- CompressedTimeline accepts optional system_tokens_fn / tools_tokens_fn
callbacks; folded into needs_compression() estimate
- star_agent passes len(system_prompt)//4 + len(json.dumps(tools))//4
Phase 2 — Cheap client-side shrink (P6)
- cheap_shrink_tool_results() stubs old tool_result bodies to
"[cleared for context budget]" preserving tool_call_id
- Predictive gate blocks mutation when savings insufficient (avoids
vacuous summary over stubs)
- Idempotent via content-equality (no metadata flag)
- Opt-in via enable_cheap_shrink_tool_results; off by default
Phase 3 — Reactive compact + circuit breaker (P2)
- PromptTooLongError typed exception; provider mapping for Anthropic
(invalid_request_error + "prompt is too long"), OpenAI-compat
(context_length_exceeded), Gemini (post-hoc WARNING on MAX_TOKENS)
- llm_caller._invoke_llm_sync/async wraps with PTL catch →
reactive_compact(attempt) → retry with 1s/3s backoff
- reactive_compact drops 5→10→20 oldest + _remove_forward_orphans +
full re-summary (no shrink-bypass)
- Per-session circuit breaker with cooldown recovery
(DANA_CIRCUIT_COOLDOWN_SECONDS, default 300s) + half-open probe
- Kill switch via DANA_DISABLE_REACTIVE_COMPACT=1
- star_agent._maybe_compress_timeline re-raises PTL explicitly
Phase 4 — Telemetry & polish
- CompressionLogFields TypedDict allowlist + new_compaction_id()
- AST-based test asserts log extra={} keys stay within allowlist
Known gaps (documented in review report, follow-up PRs):
- PTL retry closes over captured messages list; post-compact retry
re-sends stale oversized payload
- Recent huge tool_result cannot be reclaimed (shrink keep_recent
blocks it; reactive_compact drops oldest only)
- Multi-compression does not preserve prior summary text
- Stubbed content persisted across reload produces vacuous summaries
* fix(timeline): compression review blockers + snapshot persistence
Addresses the code review in
plans/reports/code-review-260420-1112-compression-parity-triggering.md.
Scope: two CRITICAL merge-blockers, one HIGH bug, and the user-requested
snapshot-based persistence. HIGH-2/HIGH-3 and MEDIUM/LOW items are
intentionally deferred.
CRITICAL-1 — stale messages on PTL retry (llm_caller):
_invoke_llm_sync/async closed over `messages`, so after reactive_compact
trimmed the timeline, retries re-sent the same oversized payload and the
circuit opened on genuinely-recoverable sessions. Added a
`messages_fn: Callable[[], list[LLMMessage]]` parameter threaded through
call_llm → _call_with_failover → _invoke_llm_sync/async. After each
reactive_compact, the factory is re-invoked so the retry observes the
compacted payload. star_agent passes a factory that re-calls
runtime.build_prompt. Backwards-compatible (parameter defaults to None).
CRITICAL-2 — unreclaimable giant tool_result:
Single huge tool_result in the keep-recent window couldn't be stubbed
(cheap_shrink skips recent) nor dropped (reactive_compact drops oldest),
wedging sessions after one big call. Fixed at ingest time:
maybe_dump_oversized_content writes bodies >50KB (env-tunable via
DANA_TOOL_RESULT_DUMP_THRESHOLD_CHARS) to
{session}/tool_results/{tool_call_id}.txt and replaces the timeline
content with a compact marker that preserves tool_call_id. A new
ToolResultDumpResource exposes a read_tool_result tool with
offset/limit slicing; auto-wired into STARAgent (opt-out via
DANA_DISABLE_TOOL_RESULT_DUMP_RESOURCE=1).
HIGH-1 — vacuous summaries on reload with stubs:
_format_entries_for_compression now emits
[Tool result id=X: previously cleared — content unavailable] instead
of feeding the literal [cleared for context budget] stub back into
the LLM, so re-summarization after reload is not dominated by
"the agent cleared tool results".
New — snapshot-based persistence (user requested):
timeline.json is frozen at the first compression. Each compression
rolls timeline-after-compress-{ISO-ts}.json; subsequent saves within
a generation update the same snapshot in place. Full audit retention
— older snapshots are never deleted. Repository read and the
serializer loader both prefer the newest snapshot and fall back to
timeline.json, then legacy path. Reload rehydrates the active
snapshot so a fresh process does not roll a new file on every save.
Tests: 4 new CRITICAL-1 tests (assert retry token count < first attempt),
14 new tool-result dump tests, 7 new snapshot persistence tests. Two
existing failover tests updated for the new messages_fn parameter. Full
suite: 1148 unit + 72 integration passing.
* fix(timeline): decouple context-window budget from compression trigger
`StarAgent` unconditionally aliased `max_context_tokens` as the compression
trigger, so any agent that set a context budget (e.g. `EnergyWasteAnalyst`
at 200k) transparently overrode `DANA_COMPACT_TRIGGER_TOKENS` — ops had no
reachable knob through the agent path.
Split the two concerns:
- `CompressedTimeline.__init__` gains a dedicated `max_context_tokens` kwarg.
Trigger resolution: explicit → env → 150k default. Budget resolution:
explicit → falls back to resolved trigger for callers that haven't split
yet. `cutoff_when_token_reach` stays pinned to the trigger.
- `StarAgent.__init__` gains `compress_trigger_tokens: int | None = None`
and threads the two knobs separately. `compress_trigger_tokens=None`
(default) defers to the env var, which is the intended ops contract.
Regression guards cover: budget set alone leaves trigger on env, env wins
when only the budget is explicit, explicit trigger still beats env, and
legacy single-knob callers still alias (backward compat).
* fix(timeline): resume via load_from_entries must not clobber timeline.json
After compression rolls a snapshot, resuming a session via
`CompressedTimeline.load_from_entries(entries)` (without native_messages)
skipped the snapshot-state rehydration that `read_since` does. The save
path then fell through to `session_folder / "timeline.json"` and
overwrote it with post-compression state on every turn — leaving the
snapshot file frozen and the canonical `timeline.json` polluted.
The Honeywell Django caller (agent_service.py) takes exactly this path:
reads entries via snapshot-aware `read_session_entries`, then calls
`load_from_entries(entries)` without the `native_messages` arg, so the
load-side rehydration in `_try_load_native_messages_from_repository`
never runs.
Fix in `_resolve_snapshot_write_path`: when no active snapshot is
tracked but the session folder already contains one or more
`timeline-after-compress-*.json`, adopt the newest as the write target
and stamp `_active_snapshot_compression_at` from its filename. Symmetric
with `LocalTimelineRepository.read_session_entries` which already
prefers newest snapshot for reads.
Regression test (`test_resume_via_load_from_entries_adopts_newest_snapshot_on_save`)
mirrors the Honeywell caller: compress, fresh timeline, load_from_entries,
add entry, save, assert write landed in the snapshot and timeline.json
stayed frozen.
* refactor(timeline): decouple compression from filesystem via repo.list_sessions (GH-1)
Timeline serializer now goes through the repository interface only — no
direct file I/O, no Path/glob, no _events_path access. Compaction mints
sibling logical sessions {base}__compact__{ISO-ts} instead of rolling
snapshot files, making the compression feature usable with any
TimelineRepositoryProtocol implementation (including in-memory and
remote repos, not just filesystem-backed).
- Add list_sessions(prefix) to TimelineRepositoryProtocol + local impl.
- Add TimelineRepositoryDefaultsMixin so external repos without
list_sessions get a no-op default (empty list → single-session fallback).
- Rewrite TimelineSerializerMixin (448→347 LOC) to use only save/
read_session_entries/list_sessions.
- Drop native_messages persistence — recomputed from entries on load.
- Rename CompressedTimeline state: _active_snapshot_path →
_active_compact_session_id, _active_snapshot_compression_at →
_active_compact_compression_at.
- Use microsecond precision in compact session timestamps to prevent
same-second collisions that would break audit retention.
- Add in-memory test fixture + parity test proving behavior matches
across local-fs and in-memory backends.
- Keep LocalTimelineRepository._resolve_timeline_file_for_read for
backward-compat reads of legacy timeline-after-compress-*.json.
Refs: GH-1
Plan: plans/260420-2141-GH-1-timeline-repository-compatibility/
Tests: 132/132 timeline+compression tests pass.
* fix(grep): auto-promote files_with_matches to content on single-file path
When SearchResource.grep receives a file path with the default
output_mode=files_with_matches, the engine returns only the bare path
— which LLM callers frequently misread as an empty result. Auto-promote
to content mode with an explanatory header note so the output actually
conveys what matched. Also refactors the AUTO-mode engine chain into a
for/break/else loop so the capture-then-prepend flow stays clean.
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Summary
MoonshotProviderextending OpenAI-compatible base with image and video supportconvert_multimodal_content():read_media_as_base64()helperTextBlock,MediaBlock,ContentBlockunion for type safetymultimodal_converter.py— logic moved into provider methods (was duplicated)Test plan
test_multi_modal.py) — image across Anthropic, OpenAI, Gemini, Moonshot; audio+video on Gemini