* 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
* 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.
* 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>
* 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
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
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)
* 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
* SEO: add title and description to all integration pages
All 17 integration docs pages were missing title and description
frontmatter, causing Docusaurus to generate unhelpful titles like
"OpenClaw | Hindsight" and pull body text as meta descriptions.
- Add keyword-rich title and description frontmatter to all integration
pages in both docs/ (current) and versioned_docs/version-0.4/
- Add scripts/check-integration-seo.mjs to enforce title + description
on all future integration pages
- Wire the check into the build script so it runs locally and in CI
* Fix missing frontmatter on docs/sdks/integrations/openclaw.md
* Regenerate docs skill after integration page SEO updates
* fix(llamaindex): use uuid for document_id and sync version metadata
- Replace timestamp-based document_id with uuid4 hex to prevent
collisions on rapid retains (timestamp_ms can duplicate in tight loops)
- Sync __version__ in __init__.py to match pyproject.toml (0.1.2)
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* fix(docs): pass memory to run() instead of ReActAgent constructor
LlamaIndex 0.14.x ReActAgent does not accept a memory parameter in
its constructor — it's silently dropped via **kwargs. Memory must be
passed to agent.run(memory=...) where AgentWorkflow picks it up.
Also fixes the undefined `tools` variable (now `tools=[]`).
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* fix(llamaindex): strip ReAct reasoning traces from retained assistant messages
HindsightMemory.put/aput now extracts only the final Answer: text from
assistant messages containing ReAct reasoning (Thought:/Action:/Observation:
prefixes), preventing internal reasoning traces from polluting long-term memory.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* fix(llamaindex): fix docstring example to pass memory to run()
The HindsightMemory class docstring showed the broken pattern of passing
memory= to the ReActAgent constructor, which silently drops it. Updated
to show the correct pattern: pass memory to agent.run().
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
---------
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
Document the new configurable base URL for the ZeroEntropy reranker
provider added in #766. Also fix a type error where RERANK_URL was
renamed to rerank_url but one usage was missed.
The automatic memory example referenced an undefined `tools` variable.
Since HindsightMemory handles retain/recall transparently, no tools
are needed — use an empty list.
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
* refactor(llamaindex): merge two packages into single hindsight-llamaindex
Merge `llama-index-tools-hindsight` and `llama-index-memory-hindsight` into
a single `hindsight-llamaindex` package following our naming convention.
- Rename package to `hindsight-llamaindex` (Python module: `hindsight_llamaindex`)
- Move HindsightToolSpec and HindsightMemory into the same package
- Delete `llamaindex-memory/` directory
- Add CI test job for llamaindex integration
- Update docs, blog post, and integrations.json
* fix(blog): update llamaindex blog post for merged package
- Move date to 2026-03-30
- Add HindsightMemory (automatic BaseMemory) pattern
- Fix "bank must exist first" pitfall — mission auto-creates
- Align all code examples with docs page
- Update architecture diagram to show both patterns
* fix(docs): add llamaindex/openai icons, rename Codex
- Add llamaindex.png and openai.png icons
- Rename "OpenAI Codex CLI" to "Codex" in integrations.json and docs
- Use openai.png icon for Codex integration
* fix(mcp): handle Claude Code GET probe and make stateless_http configurable (#751)
Claude Code v2.1.84+ sends a GET to /mcp/ before POST initialize,
which fails with 405 (stateless) or 400 (stateful). Intercept
sessionless GET requests in MCPMiddleware and return 200 OK so the
client proceeds to POST initialize.
Also make stateless_http configurable via HINDSIGHT_API_MCP_STATELESS
(default: false/stateful) instead of hardcoding true.
Closes#751
* docs: add HINDSIGHT_API_MCP_STATELESS to configuration reference
* fix(codex): cleanup dead code and add to release lifecycle
- Remove orphaned reflect() method from client.py (leftover from dropped auto-mode)
- Remove dead retainToolCalls config default (never wired through)
- Add codex to release-integration.sh valid integrations
- Add settings.json version fallback to release script
- Add codex CI test job in test.yml
- Add codex to integrations.json registry
* docs(codex): add changelog page and link from integration docs
* feat(codex): add hosted installer script (get-codex)
Add self-contained installer at hindsight.vectorize.io/get-codex that
downloads scripts from GitHub, configures hooks, and supports local/cloud
mode selection — no git clone required.
Update docs and README to use the one-liner install:
curl -fsSL https://hindsight.vectorize.io/get-codex | bash
* chore(codex): remove install.sh in favor of hosted get-codex
* fix(docs): use /next/ prefix for codex changelog link
* fix(docs): use GitHub link for codex changelog back-link
* feat(codex): add Hindsight memory integration for OpenAI Codex CLI
Hooks-based integration that gives Codex CLI long-term memory via Hindsight.
Three hooks keep memory in sync: SessionStart (daemon pre-warm), UserPromptSubmit
(recall + context injection), Stop (retain conversation to memory).
Key differences from the Claude Code integration:
- Codex transcript format: JSONL with {msg: {type, message}} (user_message/agent_message)
- No CODEX_PLUGIN_ROOT env var — install.sh writes hooks.json with absolute paths
- State stored in ~/.hindsight/codex/state/ (not CLAUDE_PLUGIN_DATA)
- No async: true in hooks (not supported by Codex)
- No SessionEnd event
- hooks.json written to ~/.codex/hooks.json with codex_hooks = true in config.toml
* fix(codex): fix transcript parser for actual Codex disk format
Codex stores sessions as rollout-*.jsonl with response_item entries:
User: {type:response_item, payload:{type:message, role:user, content:[{type:input_text, text:...}]}}
Assistant: {type:response_item, payload:{type:message, role:assistant, phase:final_answer, content:[{type:output_text, text:...}]}}
Previous parser expected an undocumented {msg:{type:user_message}} format from the Rust protocol spec
that does not match the actual on-disk storage format.
* feat(codex): add reflect mode to UserPromptSubmit hook
Add recallMode config option (default: 'recall') that switches the
UserPromptSubmit hook between:
- 'recall': existing behavior, fast raw facts list
- 'reflect': agentic synthesis loop, returns coherent prose answer
Also adds reflect() method to HindsightClient and HINDSIGHT_RECALL_MODE
env var override. Reflect uses a 25s timeout (vs 10s for recall).
* feat(codex): auto mode for recall/reflect selection
Add recallMode: 'auto' (new default) that picks the operation per-query:
- Synthesis patterns (what do you know, what's my, summarize, etc.) → reflect
- All other prompts → recall (fast, raw facts, better for code tasks)
* feat(codex): add automated test suite and finalize recall-only mode
* docs(codex): add docs page and sidebar entry for Codex CLI integration
* feat: add LlamaIndex integration for Hindsight
Add hindsight-llamaindex package providing persistent memory tools for
LlamaIndex agents via the native BaseToolSpec pattern. Includes retain,
recall, and reflect tools, a convenience factory, global config, full
test suite, docs page, blog post, and integrations.json entry.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* fix: address PR review feedback for llamaindex integration
- Fix ReActAgent API: from_tools() → constructor, chat() → await run()
- Add create_bank step to all quickstart examples
- Add production patterns section to docs (tags, error handling, bank lifecycle)
- Add memory scoping recommendation to README
- Add when-not-to-use section to blog post
- Add LlamaIndex compatibility tests (agent acceptance, FunctionTool.call)
- Fix self-hosted auth wording in cookbook notebook
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* fix: use async client methods and asyncio.run() for runnable examples
- Use await client.acreate_bank() instead of sync create_bank() to
avoid "event loop already running" errors in notebooks and async contexts
- Wrap plain Python examples in async def main() + asyncio.run(main())
so they are copy-paste runnable as scripts
- Add Jupyter notebook tip to docs showing top-level await pattern
- Bank lifecycle example in docs now uses async acreate_bank
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* fix: add async tool methods to avoid event loop conflicts
HindsightToolSpec now provides both sync and async tool implementations
using LlamaIndex's (sync_fn, async_fn) tuple pattern in spec_functions.
Async agents (ReActAgent, etc.) use aretain/arecall/areflect natively,
avoiding the "Timeout context manager should be used inside a task"
error that occurred when sync _run_async() was called from within an
active event loop.
- Add aretain_memory, arecall_memory, areflect_on_memory async methods
- Extract shared kwargs builders (_retain_kwargs, _recall_kwargs, etc.)
- spec_functions now uses tuples: [("retain_memory", "aretain_memory"), ...]
- Tests verify tools have both sync fn and async fn set
- Notebook verified end-to-end with nbclient against local Hindsight
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* chore: remove blog post from integration PR
The blog post will be pulled in separately from its own PR.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* Address PR review: add context label, document_id auto-gen, bank mission, graceful errors
- Add `retain_context` param (default: "llamaindex") as source label on retain ops
- Auto-generate `document_id` as `{session_id}-{timestamp_ms}` when not provided
- Add `retain_async` param (default: True) for non-blocking retain processing
- Add `mission` param for automatic bank creation/management on first use
- Change error handling from raising HindsightError to graceful log + return message
- Add per-operation timeout constants in _client.py
- Add `context` and `mission` fields to config.py and configure()
- Update docs: document as standalone package (not LlamaHub), new params, patterns
- Tests: 51 passing (up from 34), covering all new features
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* Restructure to LlamaIndex namespace packages + add BaseMemory implementation
Tools package (llama-index-tools-hindsight):
- Restructured from hindsight_llamaindex/ to llama_index/tools/hindsight/
- Import: from llama_index.tools.hindsight import HindsightToolSpec
- Follows PEP 420 implicit namespace package convention
- Removed retain_async param (client.retain() doesn't support async_processing)
Memory package (llama-index-memory-hindsight):
- New package: llama_index/memory/hindsight/
- HindsightMemory(BaseMemory) for automatic memory
- put() auto-retains user/assistant messages to Hindsight
- get(input) auto-recalls relevant memories, prepends as system message
- Graceful error handling, bank mission management, document_id generation
- 28 unit tests passing
Both packages follow LlamaIndex community conventions for future LlamaHub submission.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
---------
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
* feat: add max_observations_per_scope bank config
Adds a configurable limit on the number of observations per tag scope.
When the limit is reached, consolidation only updates/deletes existing
observations — no new ones are created. Enforcement is done via a
constrained Pydantic response model (max_length on creates list) so the
LLM structurally cannot exceed the limit, plus prompt guidance.
- Config: HINDSIGHT_API_MAX_OBSERVATIONS_PER_SCOPE (-1 = unlimited)
- Reorder action execution: deletes → updates → creates
- Dynamic _ConsolidationBatchResponse with max_length constraint
- Prompt CAPACITY CONSTRAINT section when near/at limit
- Observations with no tags skip the limit entirely
- Control plane UI field + docs
* fix: strengthen max_observations tests with mock LLM + defensive truncation
- Rewrite integration tests to use MockLLM with deterministic responses
(one observation per fact) instead of relying on real LLM behavior
- Add defensive truncation in _consolidate_batch_with_llm as belt-and-
suspenders — catches LLM providers that ignore JSON schema max_length
- Tests now assert exact counts, not just upper bounds
* fix(migrations): use HINDSIGHT_API_MIGRATION_DATABASE_URL when set
Session-level advisory locks are broken when the database URL goes
through PgBouncer in transaction mode: the backend connection is
returned to the pool on COMMIT, orphaning the lock, so multiple pods
can simultaneously run migrations for the same schema.
When HINDSIGHT_API_MIGRATION_DATABASE_URL is set, use it for both
the advisory lock connection and the Alembic run. Callers should
point this at the direct PostgreSQL endpoint (bypassing the pooler)
so the session-level lock is held for the full migration duration.
* refactor(migrations): move MIGRATION_DATABASE_URL to standard config
Wire HINDSIGHT_API_MIGRATION_DATABASE_URL through HindsightConfig
instead of reading os.getenv() directly in migrations.py. Add the
field to the dataclass, from_env(), log_config(), all call sites,
.env.example, and the configuration docs page.
* fix: update test mocks for migration_database_url kwarg and regenerate docs skill
---------
Co-authored-by: Nicolò Boschi <boschi1997@gmail.com>
- Add AG2 integration doc with quick start, configuration, GroupChat example, and API reference
- Add to sidebar, versioned sidebar, and integrations hub
- Add AG2 icon
* docs: add Volcano Engine as supported LLM provider
Follow-up to #714. Add Volcano Engine (ByteDance) to the documentation:
- LLM providers grid component
- Provider list in configuration docs
- Provider example with base URL and default model
- Default model table in models page
* chore: regenerate docs skill references
* feat(openclaw): add recallInjectionPosition config to preserve prompt cache
Add configurable injection position for recalled memories to avoid
breaking prefix-based prompt caching (Anthropic/Google) when agents
have large static system prompts.
Options: 'prepend' (default, current behavior), 'append' (end of
system prompt, preserves cache), 'user' (before user message).
Closes#703
* docs(openclaw): document all plugin config flags
Add missing config options to the OpenClaw docs: recallTopK,
recallTypes, recallContextTurns, recallMaxQueryChars,
recallPromptPreamble, recallInjectionPosition, recallRoles,
retainEveryNTurns, retainOverlapTurns, and debug.
* docs(claude-code): tidy configuration reference and sync README
Add missing settings (retainMode, retainToolCalls, retainTags,
retainMetadata, embedPackagePath, llmApiKeyEnv, agentName, and
several recall options) that existed in code but not in docs.
Restructure config tables with prose introductions, clearer
descriptions, and consistent layout across both files.
* refactor(claude-code): remove recallTopK setting
Unused client-side cap — Hindsight server already controls result
count via recallBudget and recallMaxTokens.
* docs: add supported platforms section and Windows installation guide
Adds a platform compatibility table (Linux, macOS, Windows) and a
dedicated Windows setup section with step-by-step instructions for
installing PostgreSQL + pgvector and running Hindsight natively.
Follows up on #699 which added Windows native support.
Also fixes a ty type-check error in metrics.py for the conditional
resource module import.
* chore: sync generated clients and lock file after #699
Regenerate client SDKs to pick up ValidationError model changes
and update uv.lock with platform-specific uvloop/winloop deps.
* docs: update Windows section — pg0 now supports Windows
pg0 v0.12.0 added Windows support, so embedded DB works everywhere.
Restructure Windows section to show simple install-and-run first,
with external PostgreSQL as an optional alternative.
* chore: sync generated docs skill and openapi references
Adds a proper 'none' provider option so users can run Hindsight as a
chunk store with semantic search but without any LLM dependency, replacing
the hacky workaround of setting provider to 'mock'.
When HINDSIGHT_API_LLM_PROVIDER=none:
- Retain automatically uses chunks mode (no fact extraction)
- Recall works normally (semantic search, BM25, graph retrieval)
- Reflect returns HTTP 400 with clear error message
- Consolidation/observations are disabled
- Mental model refresh returns HTTP 400
- No API key required
* feat(reflect): make source facts in search_observations configurable
The recent fix (#669) hardcoded include_source_facts=False in
search_observations to prevent context overflow. This makes it
configurable via HINDSIGHT_API_REFLECT_SOURCE_FACTS_MAX_TOKENS
(env/tenant/bank), defaulting to -1 (disabled).
- -1: source facts disabled (current behavior, default)
- 0: source facts enabled with no token limit
- >0: source facts enabled with a token budget
* docs: add reflect_source_facts_max_tokens to configuration reference
* fix: update configurable fields count in tests and regenerate docs skill
* feat(hermes): file-based config + updated docs
Replace the old dataclass/configure() singleton with a plain dict
config loaded from ~/.hindsight/hermes.json — same field names and
conventions as the openclaw and claude-code integrations.
Loading order: defaults → config file → env var overrides.
- config.py: rewritten with load_config() returning a plain dict,
DEFAULTS matching openclaw/claude-code fields, ENV_OVERRIDES with
typed casting
- tools.py: register() uses load_config() instead of raw env vars
- __init__.py: clean exports (removed configure/get_config/reset_config)
- README.md: full rewrite with config file examples, tables by category
- docs/hermes.md: full rewrite with quick start, architecture, all
config tables, gateway section, troubleshooting
- tests: updated for new config pattern, 46 tests pass
* ci: add test job for hermes integration
* chore: regenerate docs skill for hermes integration
* feat: add LiteLLM LLM provider for Bedrock and 100+ providers
Add a new `litellm` LLM provider that uses the LiteLLM SDK for chat
completions and tool calling, enabling AWS Bedrock and 100+ other
providers for Hindsight's core engine (retain, recall, reflect).
- New LiteLLMLLM provider in engine/providers/litellm_llm.py
- Registered in factory, valid providers list, and no-api-key set
- Refactored API key validation to use requires_api_key() helper
- Added boto3 dependency for Bedrock auth
- Updated docs: configuration, models, monitoring, providers grid
* feat: add bedrock as first-class LLM provider alias
Add `bedrock` as a dedicated provider name that auto-prepends the
`bedrock/` prefix to model names and delegates to LiteLLMLLM under
the hood. This makes Bedrock support more discoverable — users set
`HINDSIGHT_API_LLM_PROVIDER=bedrock` with plain Bedrock model IDs.
* test: add Bedrock to CI provider tests
- Add bedrock/us.amazon.nova-lite-v1:0 to MODEL_MATRIX in test_llm_provider.py
- Add AWS credential check in should_skip_provider()
- Pass AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY, AWS_REGION_NAME secrets to test-api job
- Update default bedrock model to amazon.nova-2-lite-v1:0
* fix: regenerate docs skill files and bump memory test timeout
- Regenerate skills/hindsight-docs references after docs changes
- Bump test_llm_provider_memory_operations timeout to 600s for slower
providers like Bedrock via LiteLLM
* test: skip bedrock lite models in memory operations test
Nova Lite has a 10K output token limit which is too low for fact
extraction (requires 64K). The api_methods test (completion, tools,
structured output) already validates the provider works correctly.
* test: use Nova Pro for bedrock CI tests to cover full memory pipeline
Nova Lite only supports 10K output tokens, too low for fact extraction.
Switch to Nova Pro which supports the full 64K output needed for
retain/reflect operations. This ensures bedrock is tested on all
Hindsight functionalities, not just basic API methods.
* test: switch bedrock CI to Nova 2 Lite (supports 64K output tokens)
Nova v1 models (Pro, Lite) have a 10K output token limit which is
too low for fact extraction. Nova 2 Lite supports 64K+ output tokens,
enabling full memory pipeline testing (retain + reflect).
* feat: add Strands Agents SDK integration with Hindsight memory tools
* fix: add strands docs to versioned docs so build link check passes
* fix(strands): run hindsight client calls in thread pool to avoid event loop conflict with Strands
* feat(openclaw): remove hardcoded default models, rely on Hindsight API defaults
* feat(claude-code): remove hardcoded default models, rely on Hindsight API defaults
* feat(claude-code,docs): remove hardcoded default models from claude-code integration and docs
* feat: use claude-haiku-4-5 as default Anthropic model
* doc: add Claude Code + Telegram + Hindsight blog post
* doc: add fabioscarsi to blog authors
* doc: update fabioscarsi title to Contributor
* doc: remove horizontal rule dividers from blog post
* doc: update cover image and add image frontmatter for claude-code-telegram blog post
* doc: remove horizontal rule dividers
* doc: align Hindsight setup steps with PR #661 README
* fix: move marketplace.json to repo root and update source path
* doc: add Claude Code integration page, sidebar, and integrations hub entry
* doc: update versioned docs to 0.4.19
---------
Co-authored-by: Ben <ben.bartholomew@vectorize.io>
* feat: add LangGraph integration with tools, nodes, and store patterns
Add hindsight-langgraph SDK providing three integration patterns:
- Tools: retain/recall/reflect as LangChain tools for ReAct agents
- Nodes: automatic memory injection and storage as graph steps
- Store: LangGraph BaseStore implementation for checkpoint-based memory
Fix: remove `from __future__ import annotations` in nodes.py which
prevented LangGraph from passing RunnableConfig to node functions
(runtime type inspection saw string annotations instead of actual types).
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* chore: register langgraph with independent versioning system
- Set version to 0.1.0 (integrations are versioned independently)
- Add langgraph to VALID_INTEGRATIONS in release-integration.sh
- Add changelog page for langgraph integration
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* chore: remove manual cookbook recipe page
The sync-cookbook script will auto-generate this from the notebook
in hindsight-cookbook once PR #17 is merged.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* fix: comprehensive improvements to langgraph integration
Code fixes:
- Retain node only stores latest messages instead of all history (prevents duplicates)
- Handle multimodal msg.content (list type) in nodes
- Fix store docstring separator "/" → "."
- Apply search filters before pagination in store
- Add ttl parameter to store.aput for LangGraph BaseStore compat
- Fix _ensure_bank to not cache failed bank creations
- Fix falsy value bugs (or → is not None) in tools
- Remove from __future__ import annotations from all files
- Consistent default budget="mid" across tools/nodes/store
- Bump langgraph floor to >=0.3.0, remove duplicate dev deps
Docs fixes:
- Fix broken Cloud client example (base_url is required)
- Complete API reference tables with all parameters
- Add Limitations and Notes section (async-only store, etc.)
- Add Requirements section
- Fix broken cookbook link and Cloud claim in blog post
All 61 unit tests pass. E2E tested against Hindsight Cloud:
tools, nodes, store, configure(), multimodal content.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* chore: remove blog post (lives in hindsight-marketing-content)
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* chore: remove Hindsight Cloud section from langgraph docs
Keep OSS docs self-hosted-first, consistent with other integration
docs (crewai, pydantic-ai, agno). Cloud setup details live in the
cookbook notebooks.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* docs: explicitly mention LangChain compatibility in langgraph integration
The tools pattern (create_hindsight_tools) only depends on
langchain-core and works with plain LangChain via bind_tools() —
no LangGraph required. Update docs to make this clear with both
LangGraph and LangChain quick start examples.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* fix: address PR review findings
1. Guard manual test files with if __name__ == "__main__" so pytest
doesn't collect and execute them during test runs
2. Remove semantic fallback in HindsightStore.aget() — only return
exact document_id matches, not unrelated semantic search hits
3. Make langgraph an optional dependency — tools pattern only needs
langchain-core. Install with pip install hindsight-langgraph[langgraph]
for nodes and store patterns. Lazy imports with clear error messages.
4. Clean up README to be self-hosted-first, consistent with other
integration docs
5. Update docs requirements section to reflect optional langgraph dep
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* fix: address PR review feedback for langgraph integration
- Fix#2: Add per-bank asyncio.Lock to _ensure_bank for concurrency safety
- Fix#3: Clamp search score to max(0.0, ...) to prevent negative values
- Fix#4: Implement suffix matching in _handle_list_namespaces
- Fix#5: Truncate namespaces to max_depth instead of filtering (per BaseStore contract)
- Fix#6: Remove list_namespaces/alist_namespaces overrides — let base class handle prefix=/suffix= kwargs
- Fix#7: Document ephemeral namespace tracking and get() limitations in class docstring
- Fix#8: Add stable ID to recall node SystemMessage, document ordering behavior
- Fix#9: Change budget/max_tokens/recall_tags_match defaults to None so global config fallback works
- Fix#10: Conditionally populate __all__ so import * works without langgraph installed
- Fix#11: Bump langgraph lower bound from >=0.3.0 to >=0.5.0
- Fix#12: Extract _resolve_client to shared _client.py module
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* fix: address remaining review gaps for langgraph integration
- Add output_key parameter to create_recall_node for prompt ordering control
- Add prefix/suffix/combined filter tests for list_namespaces
- Add output_key unit tests (memory text, none on empty, none on error)
- Remove unused imports and backward-compat alias in tools.py
- Update docs with output_key usage example and API reference
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* fix: relax langgraph version constraint to >=0.3.0
Research confirmed all required APIs (BaseStore, SearchItem, Result,
GetOp, PutOp, SearchOp, ListNamespacesOp) are available since
langgraph-checkpoint 2.0.7, which maps to langgraph >=0.2.63.
Using >=0.3.0 as a clean semver boundary — >=0.5.0 was unnecessarily
conservative and excluded many compatible versions.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
---------
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
* feat: independent versioning for integrations
- Add per-integration changelog pages at /changelog/integrations/<name>
- Move main changelog to changelog/index.md (URL unchanged)
- Add --integration flag to generate-changelog for LLM-based per-integration changelog generation
- Add scripts/release-integration.sh <name> <version> for cutting integration releases
- Add .github/workflows/release-integration.yml to publish on integrations/** tags
- Remove integrations from main release.sh and release.yml cycle
* fix: add agno and hermes integration docs to version-0.4 for production build
* chore: apply ruff formatting to generate_changelog.py
* feat: add 4-tab code parity across all documentation examples
Every code snippet Tabs block now has Python, Node.js, CLI, and Go variants.
Raw HTTP/curl tabs replaced with proper SDK calls.
New example files:
- Go: retain.go, recall.go, reflect.go, memory-banks.go, directives.go,
mental-models.go, documents.go, main-methods.go
- Shell: memory-banks.sh, directives.sh, mental-models.sh
- Node.js: mental-models.mjs
Extended example files with missing sections:
- recall.mjs/sh: world/experience/observation types, token-budget, all tag modes
- reflect.sh: reflect-with-params, reflect-disposition, reflect-sources, reflect-with-tags
- reflect.mjs: reflect-with-tags, fixed reflect-sources API usage
- retain.mjs/sh: retain-conversation, retain-batch, retain-files-batch
SDK/CLI additions:
- TypeScript: getMentalModelHistory method
- CLI recall: --tags, --tags-match flags
- CLI reflect: --tags, --tags-match, --include-facts flags
- CLI directive update: --is-active flag
- CLI bank set-config: --retain-mission, --retain-extraction-mode,
--observations-mission, --reflect-mission, --disposition-* flags
Build validation:
- scripts/check-code-parity.mjs validates 4-tab parity across all MDX files
- Integrated into npm run build — fails if any Tabs block is missing a variant
* fix: fix doc examples for Go, Node.js, CLI + add mental model with-id examples
- Fix Go Budget constants: BUDGET_HIGH/LOW/MID → HIGH/LOW/MID
- Fix Go documents.go: ListDocuments returns []map[string]interface{}, use map access
- Fix Go retain.go: use correct relative path for sample.pdf
- Fix Node.js createMentalModel: use positional args (name, sourceQuery) not object
- Add CLI 'history' subcommand for mental models (api.rs, main.rs, mental_model.rs)
- Rebuild TypeScript/Python clients to support id param in createMentalModel
- Add create-mental-model-with-id examples across all 4 languages and docs
* fix: move id param to end of create_mental_model signature for backwards compat
* feat: upgrade MiniMax default model from M2.5 to M2.7
MiniMax has released MiniMax-M2.7, their latest model with a 1M context
window (up from 204K). This updates the default model across config,
docs, and examples. M2.5 remains fully compatible for users who prefer it.
- Update PROVIDER_DEFAULT_MODELS to MiniMax-M2.7
- Update .env.example and documentation references
- Add test_minimax_provider.py with M2.7 and backward compat tests
* chore: remove test file per review feedback
---------
Co-authored-by: PR Bot <pr-bot@minimaxi.com>
* feat(typescript-client): add Deno compatibility
- Switch build from tsc to tsup for dual CJS + ESM output with proper exports field
- Add deno_setup.ts preload that injects Jest-compatible globals (describe/test/expect) via @std/testing/bdd and @std/expect
- Fix generated client.gen.ts: exclude hey-api internal `client` field from RequestInit spread to avoid conflict with Deno.HttpClient
- Add test:deno npm script using --unstable-sloppy-imports and --preload
- Add test-typescript-client-deno CI job using denoland/setup-deno@v2 (v2.x)
- Update docs: rename page to TypeScript / JavaScript Client, add Deno installation section
* feat: add Deno compatibility to ai-sdk and chat integrations
- Switch ai-sdk and chat builds from tsc to tsup (ESM bundle, eliminates
extension-less import issues in Deno)
- Add deno.json import map to ai-sdk redirecting 'vitest' to a custom
vitest-compat.ts shim and bare npm specifiers to npm: URLs
- Add vitest-compat.ts shim implementing vi.fn()/vi.spyOn()/vi.mocked()
using @std/expect's Symbol.for("@MOCK") interface so toHaveBeenCalledWith
and other mock matchers work under Deno
- Add test:deno script to ai-sdk (all 30 tests pass under Deno)
* ci: add Deno test job for ai-sdk integration
Adds a new test-ai-sdk-integration-deno CI job that runs the ai-sdk
unit tests under Deno LTS, verifying Deno compatibility of the package.
* fix: remove broken link to non-existent n8n blog post in streamlit post
* fix: patch client.gen.ts for Deno compatibility during generation
Add a post-generation patch step to generate-clients.sh that removes
the hey-api internal 'client' field from the RequestInit spread in
client.gen.ts. Deno's Request constructor rejects 'client' because it
conflicts with the Deno.HttpClient option name.
* feat(retain): add verbatim extraction mode
Adds retain_extraction_mode="verbatim" that stores each chunk as-is
without LLM summarization. The LLM still runs to extract entities,
temporal info, and location for full indexability — only the fact text
is replaced with the original chunk content (one memory per chunk).
Useful for RAG-style indexing and benchmarks where original text
must be preserved in memory.
- Add "verbatim" to RETAIN_EXTRACTION_MODES in config.py
- Add VERBATIM_FACT_EXTRACTION_PROMPT with instructions to preserve text
- Add _collapse_to_verbatim() post-processing to enforce 1 fact/chunk
- Expose in bank config UI dropdown with updated description
- Update configuration.md docs with verbatim mode description
- Add unit test for _collapse_to_verbatim and integration test via LLM
- Fix pre-existing main.py CLI override missing new reranker fields
- Fix pre-existing cross_encoder.py ty type error via setattr
* refactor(retain): verbatim mode skips 'what' field entirely
Instead of asking the LLM to echo the chunk text back into 'what' and
then discarding it, verbatim mode now uses a dedicated schema
(VerbatimExtractedFact) that omits the 'what' field altogether.
The LLM only returns metadata (entities, temporal info, location, who),
saving output tokens and avoiding any risk of paraphrasing before the
backfill.
- Add VerbatimExtractedFact / VerbatimFactExtractionResponse models
- Verbatim mode skips causal-relations section (nothing to relate causally)
- _extract_facts_from_chunk: allow missing 'what' in verbatim mode,
set combined_text="" (backfilled by _collapse_to_verbatim)
- Update verbatim prompt to say DO NOT include 'what'
* feat(retain): add index_only extraction mode
Zero-LLM retain mode: chunks are stored as-is with no LLM call, no
entity extraction, and no temporal indexing. Embeddings still run for
semantic search. User-provided entities via RetainContent.entities
are the sole source of entity data.
Early return placed before the batch-API check so no LLM queue or
concurrency locks are acquired.
- Add "index_only" to RETAIN_EXTRACTION_MODES
- Add _extract_facts_index_only() with pure Python chunking path
- Add to UI dropdown and update description
- Update configuration.md with index_only docs and table entry
- Add unit test asserting zero token usage and exact text preservation
* feat(retain): add named retain strategies
Allows mixing extraction modes in a single bank via named strategies.
Each strategy is a set of hierarchical config overrides (extraction_mode,
chunk_size, entity_labels, entities_allow_free_form, etc.) applied on
top of the resolved bank config at retain time.
- retain_strategies: dict of strategy_name → config overrides (bank config)
- retain_default_strategy: default strategy when none specified (bank config)
- strategy field on /retain request: per-call override
- apply_strategy() in config_resolver applies overrides via dataclasses.replace()
- strategy propagates through retain_batch_async → _retain_batch_async_internal
and through the async worker task payload
- Any hierarchical field is overridable per strategy, including entity_labels
and entities_allow_free_form
- Docs updated with strategy configuration example and RRF fairness note
- Unit test for apply_strategy covering overrides, unknown strategy, and
non-hierarchical field filtering
* feat(retain): add per-item strategy and strategy tests
- Add `strategy` field to `MemoryItem` so individual items in a retain
request can override the request-level strategy
- Add `strategy` field to `FileRetainMetadata` for per-file strategy
override in file retain requests
- Group memory items by effective strategy in `api_retain`; each group
is processed as a separate batch, results are aggregated
- Thread strategy through `submit_async_file_retain` →
`_handle_file_convert_retain` → retain task payload
- Add `operation_ids` to `RetainResponse` for async requests with
mixed per-item strategies
- Add `test_strategy_overrides_extraction_mode_for_index_only`: unit
test verifying a named strategy with index_only bypasses the LLM
- Add `test_retain_request_per_item_strategy_field`: unit test for
per-item strategy grouping logic
* feat(ui): add retain strategies and default strategy to bank config UI
- Add StrategiesEditor component: per-strategy cards with name input and
JSON overrides textarea; supports add/remove; validates JSON inline
- Add Default Strategy text input (retain_default_strategy)
- Update RetainEdits type and retainSlice() to include both new fields
- Regenerate OpenAPI spec (retain_strategies, retain_default_strategy,
per-item strategy on MemoryItem/FileRetainMetadata, operation_ids on
RetainResponse)
* refactor(ui): move retain strategies into its own dedicated config section
* feat(ui): improve retain strategies UX and add strategy to document dialog
- Strategy form now includes entity section (free form toggle + entity labels editor)
- Default strategy selector moved outside tab panel, above strategy chips
- Strategy tabs redesigned with underline indicator style for clarity
- Remove strategy confirms with AlertDialog
- Fix tab re-render bug when typing strategy name (skipSyncRef)
- Add strategy field to Add New Document dialog (text + per-file for uploads)
- File upload collapsible uses same Document/Tags/Source tabbed layout
- API: validate empty strategy names in config_resolver
- api.ts: add strategy field to retain and uploadFiles types
* fix: forward strategy through HTTP layer and SDK; add integration test
- route.ts: extract and forward `strategy` from request body to retainBatch
- TypeScript SDK: accept and forward `strategy` in retainBatch options and per-item
- config_resolver.py: validate empty strategy name keys on update
- bank-config-view.tsx: merge entity fields into RetainStrategyForm, redesign strategy tabs with underline style, add confirmation dialog for removal, fix tab-reset-on-typing with skipSyncRef, move default strategy selector outside panel
- bank-selector.tsx: add strategy field to Add Document dialog (per-file in tabbed collapsible)
- test_retain.py: add end-to-end integration test verifying named strategy application (index_only = 0 LLM tokens)
* fix: regenerate TypeScript client with strategy field in RetainRequest/MemoryItem
- Regenerate OpenAPI spec to include strategy field in RetainRequest and MemoryItem
- Regenerate TypeScript client from updated spec
- Add strategy to MemoryItemInput interface
- Remove (item as any) cast now that strategy is properly typed
* rename: index_only extraction mode → chunks
* remove top-level strategy from RetainRequest; strategy is per-item only
* fix(clients): update Go and Python generated clients with strategy/operation_ids fields
* fix(ci): update hierarchical field count, add strategy to Rust MemoryItem initializers
* fix(go-client): minimal targeted YAML updates for strategy/operation_ids fields
* docs: add config vars for local reranker FP16 and bucket batching (#588)
* fix: add missing reranker local fields to CLI config override and fix ty type error
- Add reranker_local_fp16, reranker_local_bucket_batching, reranker_local_batch_size
to the manual HindsightConfig() constructor call in main.py (CLI override block)
- Replace direct module attribute assignment with setattr() in the transformers 5.x
monkey-patch so ty can resolve it without raising unresolved-attribute
* feat: add compound tag filtering via tag_groups
Adds tag_groups to RecallRequest and ReflectRequest to express arbitrary
boolean tag predicates: leaf {tags, match}, and/or/not compounds.
Top-level groups are AND-ed. Existing tags/tags_match unchanged.
Examples:
Step filter AND user scope:
tag_groups: [{tags: ["step:5","step:8"], match: "any_strict"},
{tags: ["user:alice"], match: "all_strict"}]
Exclusion:
tag_groups: [{tags: ["user:alice"], match: "all_strict"},
{not: {tags: ["archived"], match: "any_strict"}}]
- Recursive SQL builder (build_tag_groups_where_clause) threads through
all 4 retrieval strategies (semantic/BM25, temporal, graph, MPFP)
- Python-side filter (filter_results_by_tag_groups) for post-traversal
- 22 new unit tests
- OpenAPI spec + all clients regenerated (Rust, Python, TypeScript, Go)
* fix: add tag_groups: None to Rust CLI struct initializers
* fix: add tag_groups: None to Rust client test RecallRequest initializer
* feat: reject tags+tag_groups together, add tag_groups integration tests
- Add model_validator to RecallRequest and ReflectRequest that returns 422
when both `tags` and `tag_groups` are set (mutually exclusive)
- Add 5 integration tests for tag_groups compound filtering:
* validation: 422 when both fields are set
* AND filter: two leaf groups (step scope AND user scope)
* OR compound: user:alice OR user:bob
* NOT compound: user:alice AND NOT archived
* Nested: user:alice AND (step:5 OR step:8)
* ci: trigger CI run
* docs: revamp sidebar with icon grid components and language support
- Merge Clients and Integrations sections into the developer sidebar
(removed top-level SDKs navbar item)
- Reorder sidebar: Architecture → API → Clients → Integrations → Hosting
- Unify icon system using react-icons (LuXxx/SiXxx) via customProps.icon
- Add uppercase section titles with increased spacing and reduced indentation
- Rename Node.js → "JavaScript / TypeScript" with TypeScript icon
- Add reusable IconGrid and SupportedGrids components (ClientsGrid,
IntegrationsGrid, LLMProvidersGrid)
- Use grids in FAQ, Models, Overview, and Quick Start pages
- Convert developer/index.md, models.md, faq.md to MDX for JSX support
* fix: use inline style for label color to prevent link color inheritance
* fix: label visibility and rename JavaScript/TypeScript to TypeScript
* feat: add HTTP client to grid and OpenAI Compatible to LLM providers grid
* feat: introduce hindsight-api-slim and hindsight-all-slim packages
Closes#552
- Move all source code from hindsight-api/ to new hindsight-api-slim/
- hindsight-api-slim has heavy ML deps (torch, sentence-transformers,
transformers, einops, flashrank, mlx, mlx-lm, safetensors) and
pg0-embedded as optional extras: [local-ml], [embedded-db], [all]
- hindsight-api becomes a zero-code meta-package depending on
hindsight-api-slim[all] for full backward compatibility
- Add hindsight-all-slim meta-package: hindsight-api-slim + client + embed
- hindsight-all updated to depend on hindsight-api-slim[all]
- pg0.py: lazy-import pg0 with clear ImportError pointing to [embedded-db]
- Dockerfile: replace sed hack with proper uv sync --extra flags
- Update release.yml, test.yml, lint.sh, release.sh, CLAUDE.md and
all path references throughout the repo
* refactor: rename hindsight/ directory to hindsight-all/
* docs: document hindsight-api-slim and hindsight-all-slim package variants
Add package variants table and extras explanation to installation.md
* docs: remove emojis from installation.md, use professional tone
* docs: link Docker slim variant to pip package variants section
* docs: consolidate Docker image variants into single table
* ci: fix working-directory paths after package restructure
- Replace all hindsight-api → hindsight-api-slim in test.yml
- Replace hindsight → hindsight-all in test.yml
- Add --extra embedded-db to test-embed API install step
* ci: add local-ml and embedded-db extras to API sync steps
These extras were previously implicit in the old hindsight-api package
(which bundled everything). Now that hindsight-api-slim uses optional
extras, we must explicitly request local-ml and embedded-db in CI.
* ci: add API install step with embedded-db to test-embed smoke test
The smoke test starts hindsight-api as a daemon, which requires pg0-embedded.
Add a dedicated install step for hindsight-api-slim with embedded-db extra
so the daemon can start successfully.
* ci: remove --no-install-project when using optional extras
When --no-install-project is combined with --extra, the optional deps
are not installed because extras require the project to be active.
Remove --no-install-project from steps that need local-ml or embedded-db.
* ci: fix ordering of uv sync steps to preserve optional extras
When uv sync runs for a different workspace member, it removes optional
extras installed for other members. Fix by always running extra-requiring
API sync last, after other workspace member syncs.
Also remove --no-install-project from embedded-db sync in test-embed,
as --no-install-project prevents optional extras from being active.
* ci: add local-ml extra to test-embed API install for smoke test
The smoke test starts the full API server which needs sentence-transformers
for local embeddings (default provider). Add local-ml extra to the install.
* ci: simplify extras with --all-extras and add slim pip smoke test
- Replace explicit --extra local-ml --extra embedded-db with --all-extras
for cleaner, more maintainable sync steps
- Add test-pip-slim job: tests hindsight-api-slim[embedded-db] without
local ML models, using Cohere for embeddings/reranking (mirrors Docker
slim smoke test approach)
* ci: simplify slim smoke test to health check only (mirrors Docker test)
* fix: register embedded profiles in CLI metadata on daemon start
When HindsightEmbedded(profile="myapp") starts a daemon, the profile
was never written to metadata.json or given a .env file, making it
invisible to `hindsight-embed profile list` and other CLI commands.
Add _register_profile() to DaemonEmbedManager which saves HINDSIGHT_API_*
config to ~/.hindsight/profiles/{name}.env and registers the port in
metadata.json. Called after a successful new daemon start and when the
daemon is already running, so orphaned profiles also get registered on
next use.
* fix: truncate documents exceeding LiteLLM reranker context limit
Add HINDSIGHT_API_RERANKER_LITELLM_MAX_TOKENS_PER_DOC env var for both
litellm and litellm-sdk reranker providers. When set, documents are
truncated to the configured token limit using tiktoken (cl100k_base)
before being sent to the reranker, preventing BadRequestError for
models with small context windows (e.g. 1024-token limit).
* refactor: use shared _tiktoken_encoder for doc truncation in LiteLLM reranker
* refactor: use _get_tiktoken_encoding() consistently, remove eager module-level encoder instance
* doc: add HINDSIGHT_API_RERANKER_LITELLM_MAX_TOKENS_PER_DOC to configuration reference
Add MiniMax as a supported LLM provider via the OpenAI-compatible interface.
- Register MiniMax in the provider factory and valid providers list
- Set default base URL to https://api.minimax.io/v1
- Set default model to MiniMax-M2.5 in PROVIDER_DEFAULT_MODELS
- Add temperature clamping for MiniMax (must be >0, ≤1.0)
- Add API key validation (MiniMax requires an API key)
- Add MiniMax configuration example to .env.example
- Update documentation (models.md, configuration.md, embed.md, CLAUDE.md, README.md)
- Add unit and integration tests for MiniMax provider
Co-authored-by: octo-patch <octo-patch@users.noreply.github.com>
* feat: add JinaMLXCrossEncoder for native Apple Silicon reranking
Adds a new `jina-mlx` reranker provider backed by jinaai/jina-reranker-v3-mlx,
a 0.6B multilingual listwise reranker running via the MLX framework on Apple Silicon.
The model is downloaded automatically from HuggingFace Hub on first use.
Benchmarked latencies (Apple Silicon): 1 doc→32ms, 5→45ms, 10→60ms, 20→94ms.
Sub-linear scaling because all docs are ranked in a single forward pass.
- Embeds the MLX reranker implementation (_MLXReranker / _MLPProjector) directly
in cross_encoder.py with no transformers/PyTorch dependency
- Adds `mlx`, `mlx-lm`, `safetensors` to pyproject.toml optional deps (uv add)
- Updates configuration.md with provider docs and benchmark table
* refactor: import MLXReranker from repo rerank.py instead of duplicating code
Use importlib to load MLXReranker directly from the model repo's own rerank.py
(downloaded via snapshot_download). Also pin exact minimum versions for
mlx>=0.31.0, mlx-lm>=0.31.1, safetensors>=0.6.2 (verified against installed versions).
* refactor: move MLX reranker impl to dedicated jina_mlx_reranker.py
Replaces the importlib hack with a proper module. jina_mlx_reranker.py is
adapted from jinaai/jina-reranker-v3-mlx/rerank.py (CC BY-NC 4.0) with the
source clearly documented at the top of the file.
* docs: simplify jina-mlx reranker docs
* fix: disable GIN fastupdate on source_memory_ids index to prevent deadlocks
GIN fastupdate buffers inserts in a pending list and flushes it with
AccessExclusiveLock when full. Under concurrent test load (8 xdist workers
all running retain_async), two workers can trigger a flush simultaneously
and deadlock. Recreating the index with fastupdate=off eliminates the
flush/lock cycle at the cost of slightly slower individual inserts.
* fix: drop per-bank HNSW indexes after transaction to avoid AccessExclusiveLock deadlock
When deleting a bank, the previous code dropped HNSW indexes inside the
same transaction as the DELETE FROM memory_units. Since DROP INDEX needs
AccessExclusiveLock on the parent table and DELETE holds RowExclusiveLock,
two concurrent bank deletions deadlocked on the same table lock.
Fix: capture internal_id inside the transaction, commit, then drop the
indexes outside the transaction so no row-level locks are held.
* doc: add 0.4.17 release blog post
* feat: make recall max query tokens configurable via env var
Add HINDSIGHT_API_RECALL_MAX_QUERY_TOKENS env var (default: 500) to
replace the hardcoded MAX_QUERY_TOKENS constant in http.py.
