* feat(recall): add proof_count boost to combined scoring
Observations with more supporting evidence now rank slightly higher
in recall results. proof_count is threaded through the retrieval
pipeline and applied as a multiplicative boost in reranking:
- types.py: add proof_count field to RetrievalResult
- retrieval.py: include proof_count in SELECT columns
- reranking.py: add log1p-normalized proof_count boost (alpha=0.1)
The boost uses the same multiplicative pattern as recency and temporal
signals. proof_count=1 is neutral, proof_count=50 gives ~+5% boost.
Non-observation fact types are unaffected (neutral 0.5).
* fix(retrieval): Apply proof_count boost to graph and temporal retrieval, normalize scaling
* fix(retrieval): correct proof_norm math to zero-center at count 1
* fix(retrieval): Apply proof_count boost to link_expansion retrieval
* fix: remove BFS zombie, clamp proof_norm to [0,1], fix test comment (log1p->math.log)
- Add CI job for paperclip integration tests with change detection
- Add paperclip to valid release integrations
- Validate hindsightApiUrl is set in loadConfig()
- Log warnings on recall/retain failures instead of silently swallowing
- Remove hardcoded timeout from reflect call
- Fix tsconfig module resolution to Node16
- Update tests to pass required hindsightApiUrl
When the daemon is already running, ensure_running() calls _register_profile()
with a config dict using short keys (llm_api_key, llm_provider, etc.) that do
not match the HINDSIGHT_API_* prefix filter. This caused api_config to always
be empty, and create_profile() would overwrite the existing .env with an empty
file on every CLI command.
Add an early return guard so _register_profile() skips the create_profile()
call when api_config is empty, preserving any existing profile configuration.
Fixes#894
DateparserQueryAnalyzer.analyze() called dateparser.search.search_dates()
without any error handling, so internal bugs in the third-party library
propagated all the way up the search/consolidation pipeline and failed
the calling task.
Observed traceback:
File ".../engine/query_analyzer.py", line 140, in analyze
results = self._search_dates(query, settings=settings)
File ".../dateparser/search/search.py", line 294, in search_dates
"Dates": self.search.search_parse(...)
File ".../dateparser/search/search.py", line 168, in search_parse
translated, original = self.search(shortname, text, settings)
File ".../dateparser/languages/locale.py", line 224, in translate_search
[original_tokens[i], original_tokens[i + 1]],
IndexError: list index out of range
Wrap the call in a try/except so any parser failure is treated as
"no temporal constraint found" — the caller can then fall back to
non-temporal retrieval instead of erroring out the whole task. The
failure is logged at WARNING level so we still notice it.
Add a regression test that monkey-patches _search_dates to raise an
IndexError and asserts the analyzer returns an empty constraint and
emits a warning log.
* Fix AttributeError when event_date is None in fact_extraction
`_extract_facts_from_chunk` crashes with `'NoneType' object has no
attribute 'isoformat'` when retaining documents without a timestamp.
Two locations fixed:
- Line 1058: debug log called `event_date.isoformat()` without a None
check
- Line 921: `parse_datetime_flexible()` can return None, so re-check
before calling `.strftime()` / `.isoformat()`
Fixes#874
* Revert unnecessary None guard on line 921
The original `if event_date is not None:` already guards that block.
Only line 1058 needed the fix.
- Add cross-platform file locking support
- Use fcntl on Unix-like systems, msvcrt on Windows
- Add detailed documentation explaining why we don't use external libraries
- Fixes issue where module couldn't be imported on Windows due to missing fcntl
Co-authored-by: yishun.eason <yishun.eason@bytedance.com>
* feat(helm): add persistent volume for local model cache
When using local reranker (e.g., BAAI/bge-reranker-v2-m3) or local
embedding models, the models are downloaded to /home/hindsight/.cache
on every pod restart, causing slow startup and unnecessary bandwidth.
Add optional persistent volume support:
- api: PVC mounted at /home/hindsight/.cache
- worker: volumeClaimTemplate (StatefulSet) at same path
Disabled by default. Enable via:
api.persistence.modelCache.enabled: true
worker.persistence.modelCache.enabled: true
Closes#860
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
* feat(helm): add extraVolumes and extraVolumeMounts for api and worker
Allow users to mount arbitrary volumes (configMaps, secrets, emptyDir,
etc.) into api and worker pods via values, following common helm chart
library conventions.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
---------
Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Mistral (and several other providers) reject 'max_completion_tokens' with a 422
because they haven't adopted the newer OpenAI parameter name. When the openai
provider is configured with a custom base_url (e.g. Mistral, Together AI),
fall back to the widely-supported 'max_tokens' parameter.
Native OpenAI (no custom base_url) and Groq still use 'max_completion_tokens'.
Fixes#852
* fix(ci): resolve all CI failures — unversioned integrations, test retries
- Move integration docs to separate unversioned docs plugin (docs-integrations/)
so new integrations don't need to be duplicated across versioned_docs
- Remove integration pages from versioned_docs (v0.3, v0.4) — sidebar
entries now use links instead of doc refs
- Add missing title/description SEO frontmatter to autogen.md
- Add retry logic (2 attempts) to test-doc-examples.sh for transient
LLM timeouts
- Add pytest-rerunfailures to test-api with --reruns 2 for flaky
Gemini-dependent integration tests
* ci: retrigger
* fix: graph entity inheritance, SyncTaskBackend error propagation, fact_type test regressions
- Fix observation entity inheritance in get_graph_data: the unit_entities
query only fetched entities for visible observation IDs, not their source
memory IDs, so the inheritance loop always found an empty entity_map
- Remove error swallowing in SyncTaskBackend._execute_task so test failures
surface instead of being silently logged
- Wrap remaining consolidation submission call sites with try/except since
consolidation is non-critical for those operations
- Fix test_sync_backend test to expect errors to propagate
- Remove fact_type=["world"] filter from test_document_upsert_behavior and
test_mentioned_at_from_context_string (same PR #848 regression)
- Remove flaky marker from consolidation test (now deterministic)
* feat(paperclip): add hindsight-paperclip TypeScript integration
Adds long-term memory for Paperclip AI agents via a lightweight
TypeScript/Node.js npm package with no runtime dependencies.
- recall() / retain() functions for heartbeat lifecycle hooks
- createMemoryMiddleware() for Express HTTP adapter agents
- Bank ID strategy: paperclip::{companyId}::{agentId} (configurable)
- Skill file for agents to call Hindsight REST API directly
- 27 unit tests covering bank derivation, recall, and retain
- Docs page at sdks/integrations/paperclip
* Remove skills file from paperclip integration
* Rename package to @vectorize-io/hindsight-paperclip
* feat(api): add bank template import/export endpoints
Add POST /banks/{bank_id}/import and GET /banks/{bank_id}/export
endpoints for declarative bank setup via JSON manifests.
A template manifest (version 1) can include bank config overrides
and mental model definitions. Import creates or updates mental
models matched by id, applies config as per-bank overrides, and
returns async operation IDs for content generation.
Export dumps a bank's explicit overrides and mental models as a
manifest that can be re-imported into another bank.
Includes control plane UI: bank creation dialog now accepts an
optional template JSON to pre-configure the bank on creation.
* docs: add Template Gallery page and bank templates reference
- Template Gallery (/templates) with search, category filter, manifest
preview modal with copy-to-clipboard
- 5 starter templates: Customer Support, Research Assistant, Personal
Journal, Code Review Buddy, Meeting Notes
- Bank Templates API reference doc (developer/api/bank-templates)
- Sidebar entry under API section
* docs: add Template Gallery links to navbar and sidebar
- Top navbar: "Templates" link between Integrations and Changelog
- Sidebar: "Template Gallery" in Resources section
* fix(docs): remove emoji icons, autofocus search, fix placeholder in template gallery
* docs: rename to Bank Templates, move to Resources sidebar only
* docs: add Bank Templates to Resources navbar dropdown
* feat(api): add directives to bank template import/export
- Add BankTemplateDirective model with name, content, priority, is_active, tags
- Import creates/updates directives matched by name
- Export includes all directives (active and inactive)
- Validation: duplicate names rejected, empty name/content caught
- Tests: 24 tests covering directives create/update, existing vs new
bank import, validation, export with directives, full round-trip
* docs: add directives to bank templates docs and sample templates
* feat(api): add JSON Schema endpoint for bank template validation
- GET /v1/default/bank-template-schema returns the JSON Schema
auto-generated from the Pydantic BankTemplateManifest model
- Static schema file at docs/static/bank-template-schema.json
- Docs updated with schema endpoint, static file link, and
validation examples (Python jsonschema, Node ajv-cli)
* feat(api): live schema validation on import, fix schema endpoint path
- Move schema endpoint to /v1/bank-template-schema (system-level, not per-bank)
- Import endpoint now accepts raw JSON and validates with Pydantic manually,
returning clean 400 errors instead of raw 422s for all validation failures
- All validation (schema + semantic) returns consistent 400 with detailed messages
* docs: add interactive JSON Schema viewer to Bank Templates page
Renders the Pydantic-generated schema as a collapsible property tree
with types, required badges, defaults, and descriptions. The schema
is imported from the static bank-template-schema.json file.
* ui: add template toggle switch and browse link to bank creation dialog
- Replace always-visible textarea with a switch toggle ("Import from template")
- Textarea only shows when switch is on, keeping the dialog clean by default
- Add "Browse templates" link pointing to hindsight.vectorize.io/templates
- Reset template state when switch is toggled off or dialog is cancelled
* ui: add empty state with Add Document CTA to data view
When a bank has 0 memories, the data view (all tabs: constellation,
graph, table, timeline) shows a centered empty state with a CTA
button that opens the Add Document dialog.
* docs: replace templates with Conversation and Coding Agent
Remove generic placeholder templates. Add two practical templates
based on actual integration patterns:
- Conversation: for chat agents (LiteLLM, LangGraph, Pydantic AI,
Vercel AI SDK). Tracks user preferences, open threads.
- Coding Agent: for Claude Code/Codex. Tracks technical decisions,
project context, developer preferences. High literalism.
* docs: rename gallery to Bank Templates Hub, keep API doc as Bank Templates
* docs: register layout-template and file-json icons in navbar and sidebar
* docs: register layout-template icon in DefaultNavbarItem for dropdown items
* docs: show integration icons on template cards
Templates now have an optional `integrations` field referencing
integration IDs from integrations.json. Icons are resolved at render
time and shown in the card header next to the category badge.
* docs: add Personal Assistant template for OpenClaw, Hermes, NemoClaw
* feat: add Export Template to bank actions + map all integrations to templates
- Add "Export Template" to the bank Actions dropdown — exports config,
mental models, and directives as JSON, copies to clipboard
- Add export API route and client method
- Map remaining integrations to templates: CrewAI, AG2, Agno, Strands,
LlamaIndex, local-mcp, skills → Conversation; hindclaw → Personal Assistant
* feat: add --template flag to LoCoMo benchmark + remove schema from Hub
- LoCoMo benchmark accepts --template <path> to apply a bank template
manifest (config, mental models, directives) before ingestion
- Template is applied per-bank in both single-phase and two-phase modes
- BenchmarkRunner.apply_template() reuses the same engine methods as
the /import API endpoint
- Remove Manifest Schema section from Bank Templates Hub page
(schema stays in the API reference doc)
* refactor: remove description field from bank template manifest
* docs: remove tags, fact_types, and directives from starter templates
* docs: remove reflect_mission and disposition fields from starter templates
* build: validate template manifests against JSON Schema during docs build
* cleanup: remove unused JsonSchemaViewer component
* docs: remove retain_extraction_mode from starter templates
* ui: enable word wrap in template manifest preview
* docs: add link to Bank Templates reference doc from Hub page
* docs: convert bank templates doc to mdx with multi-language code snippets
- Convert bank-templates.md to .mdx with Tabs/CodeSnippet components
- Add example files: bank-templates.py, .mjs, .sh, .go with doc markers
- Examples cover import, dry-run, export, round-trip, and schema
- Regenerate OpenAPI spec and all client SDKs (Python, TS, Rust, Go)
* fix: migration revision collision + use typed models in benchmark template
- Rename merge migration d6e7f8a9b0c1 -> d6e7f8a9b0c2 to resolve
revision ID collision with case_insensitive_entities_trgm_index
- Update a4b5c6d7e8f9 down_revision to point to the renamed migration
- Fix f-string lint in case_insensitive migration
- BenchmarkRunner.apply_template() now validates manifest through
BankTemplateManifest Pydantic model instead of raw dict access
- Remove redundant inline imports (json, Path already at module top)
* fix(docs): add missing Go tab to dry-run code snippet
* ci: retrigger
* fix: sync skills openapi.json + fix bankId null type error in export
- Copy updated openapi.json to skills/hindsight-docs/references/
- Add null guard for bankId in Export Template onClick handler
* fix: sync generated files (memory_engine formatting, docs skill references)
* cleanup: remove obsolete migration collision workaround
* fix(retain): preserve normalized experience fact types and remove deprecated opinion type
The ExtractedFactType conversion was re-checking for raw "assistant" fact_type
after the parsing layer had already normalized it to "experience". Since
fact_from_llm.fact_type was always "experience" (never "assistant"), the ternary
always fell through to "world", silently losing experience classification.
Also removes the deprecated "opinion" fact type from internal extraction models,
database constraints/indexes (via migration), and dead code paths. The public API
surface (descriptions, response models, backwards-compat filter) is unchanged.
* refactor(retain): drop unused confidence_score column
The confidence_score column was only ever non-null for opinion facts
(which are now removed). It was always written as NULL and never read
back from the database. Remove it from:
- DB model and migration (DROP COLUMN)
- INSERT queries in fact_storage.py
- retain_async/retain_batch_async parameters
- RetainContext/RetainResult extension models
- RetainBatch dataclass
* feat: add detail parameter to list/get mental models (#825)
Add a `detail` query parameter (metadata|content|full) to both list and get
mental model endpoints (HTTP + MCP) to control response size. This reduces
payload for agent boot flows and MCP clients where context budget is limited.
Closes#825
* fix: update Rust CLI for optional mental model fields
The generated Rust client now has content/source_query as Option<String>
after the detail parameter was added. Update CLI code to handle optionals.
* fix(embed): clear stale daemon on port before starting new one (#843)
When `uvx hindsight-embed@latest` resolves to a new version, the old
daemon may still be bound to the port, causing EADDRINUSE. Before
starting a daemon, check if the port is occupied, verify it's a
hindsight process via /health, and SIGTERM it if so.
* chore: remove unused signal import from test
* refactor: use cross-platform port check instead of lsof-only
Use socket for port check (works on all platforms), extract PID lookup
into a helper with Windows (netstat) and Unix (lsof) paths, and
extract kill logic into a testable static method.
* refactor: reuse cross-platform helpers in stop() and stop_ui()
DELETE /v1/default/banks/{id}/memories and the MCP clear_memories tool
were calling delete_bank() without distinguishing from the actual delete-bank
endpoint. When no fact_type filter was provided, the bank row itself was
deleted along with its memories.
Add a delete_bank_profile parameter to delete_bank() (default True) and
pass False from all clear-memories callers so the bank profile, disposition,
and background are preserved.
When the external Hindsight API is unreachable, retain requests are
buffered as JSON lines in a local file and automatically flushed once
connectivity is restored. Queue survives process restarts.
- Only active in external API mode (local daemon handles its own persistence)
- Zero dependencies — uses only Node built-ins (fs, crypto)
- Bulk removal via removeMany() for O(1) file rewrites during flush
- Cached item count so size() is O(1)
- Configurable: retainQueuePath, retainQueueMaxAgeMs (-1 = forever),
retainQueueFlushIntervalMs (default 60s)
- Flushes on successful retain and on a periodic timer
- All logging routed through structured logger (api.logger)
Co-authored-by: billy <billy@oclaw.local>
Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Co-authored-by: Antoine Khater <ak@ptgroup.eu>
The 3-phase retain pipeline (914ba796) introduced several regressions:
1. **Per-content tags lost** — streaming pipeline used `contents[0].tags`
for ALL chunks, breaking tag-based visibility. Fixed by tracking
chunk-to-content mapping so each chunk uses its source content's tags.
2. **Multi-document batches broken** — batches with per-content
`document_id` values were merged into a single document. Fixed by
grouping by document_id and processing each group independently.
3. **Migration ID collision** — `d6e7f8a9b0c1` was used by both
`drop_documents_metadata` and `case_insensitive_entities_trgm_index`.
Renamed trgm migration to `e8f9a0b1c2d3`, fixed chain, added missing
schema prefix on DROP INDEX.
4. **Graph entity inheritance** — `get_graph_data` queried entities for
observation IDs only, but observations inherit entities from source
memories. Fixed by querying `all_relevant_ids`.
5. **Docstring false positives** — link_utils.py docstrings triggered
the SQL schema safety test's unqualified table reference check.
6. **Config test count** — `retain_chunk_batch_size` added to
`_CONFIGURABLE_FIELDS` without updating the test assertion.
* feat: add AutoGen integration for Hindsight
Adds hindsight-autogen package providing FunctionTool instances that give
AutoGen agents persistent long-term memory via retain/recall/reflect APIs.
- Package: hindsight_autogen with create_hindsight_tools() factory
- 31 unit tests covering tool creation, invocation, config fallback, errors
- Docs page and integrations.json entry
- README with quickstart and configuration reference
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* fix: address PR review feedback for autogen integration
- Fix install instructions to include autogen-agentchat and autogen-ext[openai]
- Add autogen.svg icon to prevent broken image in integrations grid
- Change icon reference from .png to .svg in integrations.json
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* fix: add sleep between retain/recall and close clients in examples
- Add time.sleep(3) between retain and recall to wait for async processing
- Close Hindsight client and model client to avoid unclosed session warnings
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* fix: use asyncio.sleep instead of time.sleep in async examples
time.sleep blocks the event loop; asyncio.sleep yields control.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* fix: address PR review feedback - validation, defaults, release script
- Add autogen to VALID_INTEGRATIONS in release-integration.sh
- Remove unused verbose config field
- Extract DEFAULT_BUDGET/MAX_TOKENS/RECALL_TAGS_MATCH constants in config.py,
import from tools.py to eliminate default duplication
- Add Literal types for budget and recall_tags_match validation
- Modernize type hints to X | None with from __future__ import annotations
- Add [tool.ruff] line-length = 120 to match monorepo convention
- Add py.typed PEP 561 marker
- Re-raise HindsightError before broad Exception catch
- Expand asyncio.sleep(3) comment explaining when/why it's needed
- Remove verbose from docs configure() reference table
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
---------
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
* fix: resolve remaining Dependabot security alerts
- Regenerate package-lock.json so npm overrides take effect
(serialize-javascript, handlebars, path-to-regexp, brace-expansion)
- Upgrade Pygments 2.19.2 -> 2.20.0 in crewai and integration-tests
lockfiles (fixes ReDoS via GUID matching)
* fix: resolve duplicate alembic revision ID d6e7f8a9b0c1
Two migrations shared the same revision ID: the merge migration
(drop_documents_metadata_column) and the trigram index migration
(case_insensitive_entities_trgm_index). Assign a new unique ID
to the trigram migration and update the downstream dependency.
* chore: fix lint formatting for generated and existing files
* perf: 3-phase retain pipeline — fix deadlocks, cap temporal links, query-time entity expansion
Major retain pipeline overhaul addressing deadlocks, write amplification,
and TimeoutErrors. Restructures retain into three phases:
Phase 1: Entity resolution on separate connection (read-heavy)
Phase 2: Core write transaction (atomic) — facts, unit_entities, links
Phase 3: Best-effort display data (error-isolated) — entity viz links, stats
Key changes:
- Sorted bulk INSERT FROM unnest() prevents deadlocks
- Temporal links capped to top-20 per unit (95% reduction)
- Batched semantic ANN via temp table + LATERAL
- Query-time entity expansion via unit_entities self-join
- Entity viz links moved to Phase 3 (post-transaction)
- HINDSIGHT_API_RETAIN_MAX_CONCURRENT config (default: 32)
* fix: increase semantic link top_k from 5 to 20
The hardcoded top_k=5 was artificially limiting semantic link creation.
Link expansion retrieval can consume up to budget (50-200) semantic
neighbors per seed set, but each fact only had 5 outgoing edges — making
the bidirectional graph very sparse.
Increasing to 20 gives retrieval 4x more edges to work with. The ANN
probe cost is unchanged (same HNSW traversal per fact, just returning
more rows). INSERT cost is negligible (~14k rows via bulk INSERT).
Also: all 18 TimeoutErrors in the latest benchmark (beam-1m-u20) were
from Gemini LLM calls, zero from the database — confirming the entity
resolution split eliminated DB timeouts entirely.
* perf: move semantic ANN search to Phase 1 to avoid transaction timeouts
The batched LATERAL ANN query (700 HNSW probes) was the last remaining
source of DB TimeoutErrors — all 29 in the latest benchmark were from
create_semantic_links_batch inside the Phase 2 write transaction.
Split semantic link creation into three phases:
- Phase 1 (separate conn, autocommit): ANN search via temp table + LATERAL.
No transaction locks, no contention with concurrent writers.
- Phase 2 (write transaction): within-batch numpy similarities (instant) +
INSERT of both within-batch and Phase 1 ANN results. No DB reads.
- Phase 3 (flush_pending_stats): future hook point for re-checking ANN
results after commit to catch links missed by concurrent batches.
Also adds 7 unit tests for compute_semantic_links_within_batch covering
empty input, identical/orthogonal embeddings, threshold filtering, top_k
cap, and tuple structure validation.
* fix: handle placeholder unit_ids in Phase 1 ANN search (not valid UUIDs)
* test: add Phase 1 ANN cross-batch test + configurable test PG port
- New test_semantic_links_phase1_ann_cross_batch verifies that the Phase 1
ANN search with placeholder unit IDs correctly creates cross-batch
semantic links after remapping to real IDs.
- Test PG port now configurable via HINDSIGHT_TEST_PG_PORT env var
(default: 5556) to avoid conflicts with running benchmark daemons.
* perf: remove retry_with_backoff from retain, set semaphore default to 4
Remove retry_with_backoff from _run_db_work and _run_delta_db_work:
- Deadlocks are prevented by sorted bulk INSERT (no need for retry)
- Transient timeouts are handled by the worker poller's task-level retry
(3 attempts, 60s spacing) which is better than rapid internal retries
that amplify I/O pressure during contention storms
Set HINDSIGHT_API_RETAIN_MAX_CONCURRENT default from 32 to 4:
- The semaphore gates Phase 1 (ANN + entity resolution) + Phase 2 (writes)
- At 4 concurrent, HNSW index I/O is manageable; at 10+ concurrent the
probes saturate disk and cause cascading timeouts
- LLM extraction still runs at full parallelism (semaphore acquired after)
* fix: add fact_type filter to Phase 1 ANN query to use per-bank HNSW indexes
The LATERAL ANN query was falling back to sequential scan + sort (90ms/probe)
because the per-bank HNSW indexes are partial indexes filtered on fact_type.
Without fact_type in the WHERE clause, PostgreSQL couldn't use them.
Fix: iterate over ('world', 'experience') and run one HNSW-indexed ANN per
type. EXPLAIN shows 8ms/probe (was 90ms) — 11x faster.
700 probes × 8ms × 2 types = ~11s total (was ~63s via seq scan).
* fix: scope temporal links by fact_type + add integration tests
Temporal links now filter by fact_type in the LATERAL query — world facts
only link to world facts, experience to experience. This matches how
retrieval filters results and avoids wasted cross-type link rows.
New integration tests:
- test_semantic_ann_uses_hnsw_index: verifies Phase 1 ANN creates
cross-batch semantic links (tests fact_type filter + placeholder remap)
- test_temporal_links_scoped_by_fact_type: verifies world facts get
temporal links to other world facts but NOT to experience facts
* fix: tolerate individual chunk LLM failures instead of failing entire batch
Changed asyncio.gather(*tasks) to asyncio.gather(*tasks, return_exceptions=True)
in both chunk-level and content-level fact extraction. A single chunk timeout
(e.g., Gemini >90s) no longer discards all other successfully extracted facts.
For a 50MB document with 17k chunks, even a 2% chunk failure rate previously
caused 0 completions (entire batch discarded). Now 16,700 facts are extracted
and only the 300 failed chunks are skipped with a warning log.
* fix: batch temporal LATERAL query for large documents (16k+ chunks)
The LATERAL query for temporal links passed all unit_ids at once into
unnest(), causing PostgreSQL timeouts on documents with 16k+ chunks.
Split into batches of 500 units per query to keep each under the
command_timeout.
Also identified: HNSW index creation on shared pg0 instances with
50k+ existing units exceeds the 60s command_timeout. This is a
test infrastructure issue (shared pg0 accumulates data) but also
affects production when creating new banks on large instances.
* feat: streaming chunk batching for large documents (RETAIN_CHUNK_BATCH_SIZE)
Process chunks in mini-batches of N (default 500), committing each batch
to the DB before starting the next. This prevents OOM kills on large
documents (50MB / 17k+ chunks) by keeping only ~500 facts + embeddings
in memory at a time instead of 50k+.
Each mini-batch goes through the full Phase 1 → 2 → 3 pipeline
independently, sharing the same document_id. On recovery (process dies
mid-way), delta retain detects already-committed chunks via content_hash
and skips them — only remaining chunks get re-extracted.
Config: HINDSIGHT_API_RETAIN_CHUNK_BATCH_SIZE (default: 500, 0 to disable)
Per-bank configurable via the hierarchical config system.
Tests:
- test_streaming_chunk_batching_produces_same_facts
- test_streaming_chunk_batching_recovery (delta retain skips committed chunks)
- test_streaming_disabled_for_small_docs
* perf(retain): producer-consumer pipeline + deferred semantic ANN
Replace the sequential streaming loop with a producer-consumer pipeline:
- LLM producer fires concurrent chunk extractions (semaphore-bounded)
- DB consumer drains queue in batches, runs Phase 1+2+3 per batch
- LLM and DB work overlap instead of running sequentially
Defer semantic links to a single final ANN pass after all batches commit:
- Remove within-batch semantic links from Phase 2 (was 2.6s/batch)
- Run parallel ANN (4 connections) after all facts committed
- top_k reduced from 50 to 20 (recall uses at most 20 neighbors)
- Recovery via operation result_metadata checkpoint
Additional optimizations:
- skip_exists_check on temporal/causal link INSERT (saves ~0.5s/batch)
- WHERE EXISTS guard on semantic link INSERT (handles document upsert)
- timeout=300s on ANN queries and bulk INSERT for large banks
- Demote [ANN] debug logs to logger.debug()
- Fix docstring typos (agent_id → bank_id)
- Fix content_index remapping in producer-consumer batches
- Fix delta retain passing contents vs delta_contents
50MB benchmark (mock LLM): 9.2 min (was 23 min) — 2.5x faster.
BEAM 10m benchmark: zero deadlocks, zero DB errors.
* refactor(retain): remove legacy fallback code paths
- Remove process_entities_batch (legacy single-connection entity processing)
- Remove extract_entities_batch_optimized (only caller was the above)
- Remove fallback entity processing inside Phase 2 transaction
- Remove legacy ANN inline fallback in create_semantic_links_batch
- Remove fallback entity_links direct-insert path in Phase 3
- Make resolved_entity_ids/entity_to_unit/unit_to_entity_ids required params
* refactor(retain): replace tuple returns with dataclasses, remove dead code
- Add EntityResolutionResult and Phase1Result dataclasses in types.py
- Replace 4-tuple return from _pre_resolve_phase1 with Phase1Result
- Remove dead `entity_links = []` variables in retain_batch and _try_delta_retain
- Remove unused `confidence_score` parameter from orchestrator.retain_batch
and _retain_batch_async_internal (was accepted but never used)
* fix(entity-resolver): remove LIKE full-scan fallbacks, use index-only trigram matching
The entity resolution query had LIKE '%...' substring conditions that bypassed
the GIN trigram index, causing full sequential scans of the entities table.
On banks with 10k+ entities, this caused TimeoutErrors (observed in BEAM 10m).
Changes:
- Remove LIKE fallbacks, use trigram % operator only (GIN index-based)
- Lower similarity threshold from 0.3 to 0.15 to catch substring relationships
- Use LOWER() on both sides for case-insensitive matching
- Migration: recreate GIN trigram index on LOWER(canonical_name)
* fix: remove schema prefix from index names in trigram migration
* fix(delta-retain): use same chunk_size as streaming path (3000 vs 120000)
_chunk_contents_for_delta defaulted to chunk_size=120000 while the streaming
path used 3000. On retry, delta re-chunked the document with different
boundaries, found 0 matching chunks, and fell through to full re-extraction.
This wasted all LLM calls on already-committed chunks.
Fix: use the same default (3000) so chunk hashes match on recovery.
* fix(retain): persist generated document_id in operation metadata for retry recovery
When no document_id is provided, retain generates a UUID. On retry, a new UUID
was generated, making delta retain and streaming chunk-hash recovery unable to
find previously committed chunks. All LLM extraction was wasted on retry.
Fix: resolve document_id early in retain_batch (before delta), persist it to
operation result_metadata, and recover it on retry. Both delta and streaming
paths now see the same document_id across attempts.
* refactor(retain): unify into single streaming pipeline, remove non-streaming path
All retains now go through the producer-consumer streaming pipeline,
regardless of document size. Small documents are processed as a single batch.
This eliminates the maintenance burden of two separate code paths.
Also fix document upsert: compare content hash to distinguish recovery
(same content, partially committed) from update (different content, needs
cascade-delete). Previously, existing chunks always triggered recovery mode.
* refactor(retain): remove dead code, replace raw dicts with Phase3Context dataclass
- Remove dead _handle_zero_facts_documents (no callers after path unification)
- Remove unused imports: defaultdict, EntityLink
- Replace raw dict phase3_context with typed Phase3Context dataclass
- Update _build_and_insert_entity_links_phase3 to use typed parameter
Rewrite consolidation prompt rules to produce clean, single-facet observations:
- One observation per distinct facet (count, named entity, relationship)
- Match updates by entity/facet, not topic similarity
- No computation — never infer/calculate values not explicitly stated
- Cascade state changes to all affected observations
- Preserve event history (sold, died, moved) — conservative deletes
- Include dates on state changes when available
- Keep observations concise — no cross-facet narrative bloat
Add test_horse_observations.py exercising a realistic sequence of retain
operations (farm with horses being named, sold, dying) and verifying that
observations track history correctly and mental models can synthesize them.
Remove the BFS spreading activation and MPFP (Multi-Path Fact Propagation)
graph retrieval strategies, leaving link_expansion as the sole graph
retrieval algorithm. Rename MPFPTimings to GraphRetrievalTimings and
mpfp_timings field to graph_timings since the timing struct is used by
LinkExpansionRetriever.
Deleted:
- hindsight-api-slim/hindsight_api/engine/search/mpfp_retrieval.py
- hindsight-api-slim/tests/test_mpfp_retrieval.py
Removed config: HINDSIGHT_API_MPFP_TOP_K_NEIGHBORS
* fix(db): respect vector extension config in per-bank index migration
Migration d5e6f7a8b9c0 hardcoded HNSW when creating per-bank partial
vector indexes, ignoring HINDSIGHT_API_VECTOR_EXTENSION. This caused
banks migrated from pre-v0.4.18 to get HNSW indexes even when
pgvectorscale (DiskANN) or vchord was configured.
- Fix the original migration to read the vector extension config
- Add migration a4b5c6d7e8f9 to detect and recreate mismatched indexes
(skipped entirely when extension is pgvector, since those are correct)
* chore: regenerate openapi.json for v0.4.22 version bump
Add a new "Constellation" memory visualization as the default view in the
control plane, powered by @chenglou/pretext for DOM-free text layout on canvas.
- Canvas-rendered zoomable/pannable memory map with spatial label deconfliction
- Nodes colored by link-count heat gradient (Hindsight brand teal→cyan→blue)
- Star-like rendering with varied size/opacity based on connectivity
- Hover shows rich tooltip with full memory metadata (text, entities, tags, dates)
- Hover highlights connected nodes and their links, dims the rest
- Click to select and view memory details in the side panel
- Fullscreen mode toggle
- Link type legend and heat gradient legend on the HUD
Also optimizes the graph API endpoint:
- Entity query now filters by visible unit IDs (was doing full table scan)
- Links query caps at 10k edges sorted by weight (was returning 500k+ uncapped)
- Replaced expensive DISTINCT ON with LEAST/GREATEST sort with simple ORDER BY
* fix(deps): address critical and high severity security vulnerabilities
Bump vulnerable dependencies to patched versions across the monorepo:
Python (critical/high):
- fastmcp >=2.14.0 → >=3.2.0 (SSRF, path traversal, OAuth confused deputy, command injection)
- langchain-core >=1.2.11 → >=1.2.22 (path traversal in legacy load_prompt)
Python (low):
- cryptography >=46.0.5 → >=46.0.6 (incomplete DNS name constraint enforcement)
- pygments: add >=2.20.0 pin (ReDoS via GUID regex)
Node.js:
- serialize-javascript ^7.0.3 → ^7.0.5 (CPU exhaustion DoS)
- handlebars: add >=4.7.9 override (JS injection via AST type confusion)
- path-to-regexp: add >=0.1.13 override (ReDoS via route params)
- brace-expansion: add version range override (process hang/memory exhaustion)
Also adds type: ignore comments for FastMCP 2.x private attribute access that
ty now flags since FastMCP 3.x removed _tool_manager (guarded by try/except
and hasattr at runtime).
Regenerated all lock files across API, integrations, and tests.
* fix(deps): add ajv v8 scoped overrides for schema-utils and ajv-keywords
The global ajv ^6.14.0 override caused schema-utils and ajv-keywords to
receive ajv v6, but they require ajv v8 (for dist/compile/codegen). Add
scoped overrides to ensure these packages get ajv v8 while the global
override remains for packages that need v6.
* fix(tests): remove stateless_http from FastMCP() constructor calls
FastMCP 3.x no longer accepts stateless_http in the constructor. The
tests call tools directly without HTTP transport, so the parameter is
not needed.
* fix: update MCP tests for FastMCP 3.x _tool_manager removal
FastMCP 3.x removed _tool_manager. Tests now use
_local_provider._components for sync tool dict access and
mcp.list_tools() for async filtered tool listing.
* fix: resolve docusaurus build failures (ajv overrides + missing blog date)
- Remove global ajv ^6.14.0 override and scoped ajv-keywords/schema-utils
overrides that caused webpack compilation errors manifesting as
"Cannot read properties of undefined (reading 'date')" during SSR
and "these parameters are deprecated" warnings. Natural version
resolution (v6.12.6+ for v6 consumers, v8+ for v8 consumers) already
satisfies the security fix (>= 6.12.3).
- Add missing date frontmatter to learning-capabilities blog post.
* chore: regenerate openapi spec and docs skill
* Initial plan
* Fix timeline sort to use numeric datetime comparison instead of string localeCompare
* chore: remove accidentally committed root package-lock.json
Agent-Logs-Url: https://github.com/ThePlenkov/hindsight/sessions/d02f10c5-cc48-4977-84a9-48870f9460ec
Co-authored-by: ThePlenkov <6381507+ThePlenkov@users.noreply.github.com>
* chore: restore package-lock.json to its original state from main
Agent-Logs-Url: https://github.com/ThePlenkov/hindsight/sessions/2ede4783-55ef-4f36-8ea7-7d65c5362a0a
Co-authored-by: ThePlenkov <6381507+ThePlenkov@users.noreply.github.com>
---------
Co-authored-by: copilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com>
Co-authored-by: ThePlenkov <6381507+ThePlenkov@users.noreply.github.com>
When a mental model has tags, refresh_mental_model hardcoded
tags_match="all_strict", causing empty results when most memories
are untagged. Add configurable tags_match and tag_groups fields
to MentalModelTrigger so users can control refresh filtering.
- Add tags_match (any/all/any_strict/all_strict) to override default
- Add tag_groups for compound boolean tag expressions during refresh
- Default behavior unchanged (all_strict when tags present)
- Update both refresh paths (task-based and direct)
- Add UI controls in Create/Update mental model dialogs
- Regenerate OpenAPI spec and client SDKs
CI failures are unrelated to this PR:
- test_mental_models_dimension_change_empty_table: database OID error (infrastructure flake)
- test_reflect_searches_mental_models_when_available: LLM-dependent assertion (flaky)
When using Azure AI Foundry Cohere rerank endpoints, the Cohere SDK
incorrectly appends /v1/rerank to the base_url, but Azure endpoints
already include the full path (e.g., /models/.../invoke). This causes
double-pathing and 404 errors.
This commit modifies CohereCrossEncoder to detect when base_url is
provided and use httpx directly for custom endpoints, while keeping
the native Cohere SDK for standard API usage. The Azure Cohere API
response format is compatible with the native format.
Fixes#783
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
Enable passing arbitrary extra_body parameters to OpenAI-compatible API
calls via a JSON-encoded env var. This supports custom model servers
(e.g. vLLM) that need parameters like chat_template_kwargs to control
thinking mode.
Co-authored-by: EMIRHAN GAZI <emirhan.gazi+tcell@turkcell.com.tr>
Replace the `pull_request_target` + `safe-to-test` label mechanism with
`pull_request_review` (submitted, approved). External contributor PRs now
get basic builds/lints on open, and full secret-dependent CI only after
a maintainer approves — no manual labeling needed.
* feat: add optional LiteLLM SDK embedding output dimensions
Allow configuring an optional output dimension for litellm-sdk embeddings and pass it through only when set, while preserving default behavior.
Made-with: Cursor
* test: assert wrapped init error for invalid dimensions
Add a LiteLLM SDK embeddings test that verifies invalid OpenAI dimensions fail during initialize() and preserve provider error details in the wrapped RuntimeError.
Made-with: Cursor
* feat: expose document_metadata in API and control plane
Add document_metadata (sourced from retain_params.metadata) to both
list and get document endpoints. Display it in the control plane
documents table and detail panel. Drop the unused metadata column
from the documents table (was always stored as empty {}).
* fix: code review fixes for document_metadata feature
- Remove unnecessary `import json as _json` (json already imported at module level)
- Simplify redundant truthiness checks in retain_params parsing
- Regenerate OpenAPI spec and client SDKs (Python, TypeScript, Go)
- Add tests for document_metadata in get_document and list_documents
* feat(ui): improve documents table and detail panel
- Relative timestamps with full date on hover
- Remove context column from table
- Metadata shown as k=v badges (blue, like tags)
- Size in bytes instead of chars
- Document IDs wrap instead of truncating
- Detail panel wider (560px)
- Retain params: context, event_date, metadata badges
