* feat: support timestamp="unset" to retain content without a date
When callers retain timeless content (e.g. fictional documents, static
reference material), passing timestamp="unset" now skips the utcnow()
default so mentioned_at is stored as NULL instead of an artificial date.
- HTTP: validate_timestamp recognises "unset" sentinel and threads it
through api_retain as event_date=None (key present, value None), which
the orchestrator distinguishes from key-absent (still defaults to now)
- Orchestrator: new branching logic separates "key absent" → utcnow()
from "key present but None" → no date
- types.py: RetainContent.event_date and ProcessedFact.mentioned_at are
now datetime | None; removed the unused _now_utc factory
- fact_extraction.py: all event_date params accept datetime | None;
_build_user_message emits "Event Date: Unknown" when None; removed
mentioned_at from the Fact LLM response model (LLM never sets it)
- embedding_processing: skip date suffix when fact_date is None
- entity_resolver: COALESCE(event_date, now()) for first_seen/last_seen
so entities table NOT NULL constraint is preserved
- link_utils: skip temporal linking for units without event_date
- Migration aa2b3c4d5e6f: DROP NOT NULL on memory_units.event_date
- Tests: test_retain_no_timestamp and test_retain_omit_timestamp_defaults_to_now
- Docs + OpenAPI + TypeScript client updated
* refactor: replace _TIMESTAMP_UNKNOWN sentinel with plain string comparison
The sentinel object() was only needed to distinguish "unset" from None
at the boundary — but since the field type is datetime | str | None,
"unset" can pass through the validator unchanged and be compared directly.
* chore: regenerate OpenAPI spec and clients after timestamp type change
timestamp field is now datetime | str | None to accept the "unset" sentinel value.
* feat: observation_scopes field to drive observations granularity
* fix(migration): make a2b3c4d5e6f7 a no-op to fix CI on fresh DB
The z1u2v3w4x5y6 migration already creates observation_scopes directly,
so the rename migration fails on fresh installs where observation_tags
never existed.
* chore: remove no-op migration a2b3c4d5e6f7
* feat: regenerate clients with observation_scopes field
- Add observation_scopes to OpenAPI spec and all generated clients
- Fix Rust build.rs to handle anyOf with >2 variants containing null
(previously only handled 2-item anyOf, causing progenitor to panic
on the observation_scopes union type)
* fix(rust): add observation_scopes: None to MemoryItem struct literals
* fix(api): add title to observation_scopes Field for deterministic client generation
Adding title="ObservationScopes" makes the inline anyOf schema use
the explicit name instead of deriving it from the field name, which
was non-deterministic between arm64 (macOS) and amd64 (CI) Docker.
Also fixes description: "each entity" -> "each tag".
* fix(scripts): use linux/amd64 Docker for client generation to ensure reproducibility
Both Python and Go client generation now use --platform linux/amd64
Docker, ensuring identical output on macOS arm64 (local) and Linux
amd64 (CI). Also switches Go from JAR+Java to Docker to eliminate
Java version variability.
* chore: update generated clients to API v0.4.14
* fix(test): add retry logic to test_retain_chinese_content to handle non-deterministic LLM output
* fix(test): mark test_retain_chinese_content as xfail due to non-deterministic LLM translation
* feat: filter graph memories with tags
* fix(cli): pass new q/tags/tags_match args to get_graph
* docs: use CodeSnippet for tags_match examples in recall.mdx
Change DEFAULT_ENABLE_BANK_CONFIG_API from false to true, update all docs,
error messages, and client docstrings to reflect the new default. Remove
explicit env var overrides in CI and tests that are no longer needed.
* feat: include source facts in observation recall
* feat: include source facts in observation recall
* feat: include source facts in observation recall
* feat: include source facts in observation recall
* fix(cli): add missing source_facts field to IncludeOptions initializer
* feat: accept pdf, images and office files
* refactor: rename FileConverter to FileParser, simplify file retain API
- Rename engine/converters/ → engine/parsers/, FileConverter → FileParser,
ConverterRegistry → FileParserRegistry, MarkitdownConverter → MarkitdownParser
- Rename env var HINDSIGHT_API_FILE_CONVERTER → HINDSIGHT_API_FILE_PARSER
- Remove async/document_tags params from FileRetainRequest (always async now)
- Add retain_files() to Python Hindsight client and retainFiles() to TypeScript client
- Add sample.pdf to doc examples for working file upload demonstrations
- Update test_file_retain.py to use new parser names and always-async behavior
- Fix Go client missing os import in api_files.go
- Simplify postgresql.py storage to minimal schema
* fix: update rust CLI tests to use is_supported_file instead of is_text_file
* fix: patch Go api_files.go to add missing 'os' import after generation
* fix: insert 'os' import after 'net/url' in api_files.go patch for correct position
* chore: regenerate OpenAPI spec and clients (converter→parser description update)
* feat: allow chunks only in recall
* feat: fetch chunks independently of max_tokens filtering
Changes:
- Chunks now fetched BEFORE max_tokens filtering (Step 5.5)
- Implements batching: (max_chunk_tokens / retain_chunk_size) * 2
- Loop-based fetching until budget exhausted or no more chunks
- Handles varying chunk sizes across documents
- When max_tokens=0: returns 0 facts but still returns chunks
- When max_tokens>0: backward compatible (chunks match filtered facts)
Tests:
- Added test_recall_chunks_independence.py with 5 comprehensive tests
- Tests chunk independence, batching, ordering, and backward compat
Docs:
- Updated recall.mdx to explain new chunk behavior
- Updated memory_engine.py docstrings
Fixes chunk-related test failures by reordering chunks to match
filtered facts when max_tokens > 0 (backward compatibility).
* fix: fetch chunks after token filtering when max_tokens>0
Changes:
- When max_tokens=0: fetch chunks BEFORE token filtering (new behavior)
- When max_tokens>0: fetch chunks AFTER token filtering (backward compat)
- This ensures chunk ordering matches filtered facts for max_tokens>0
- Fixes test failures in test_chunks_and_entities_follow_fact_order,
test_chunk_fact_mapping, test_chunk_ordering_preservation, etc.
The previous approach tried to reorder prefetched chunks, but that
caused issues when the chunk budget was exhausted before all facts
were processed. The new approach fetches chunks based on the correct
fact set for each scenario.
* fix: use ConfigResolver for bank-specific retain_chunk_size
Fixes error: Field 'retain_chunk_size' is bank-configurable and cannot
be accessed from global config.
Changed from:
- config.retain_chunk_size (global config, not allowed)
To:
- bank_config.retain_chunk_size (resolved from ConfigResolver)
This ensures the correct chunk size is used for each bank, respecting
any bank-specific overrides.
* fix: correct Budget import in test_recall_chunks_independence
Changed from:
- from hindsight_api.engine.interface import Budget (incorrect)
To:
- from hindsight_api.engine.memory_engine import Budget (correct)
This fixes the ImportError that was preventing the tests from running.
* fix: prevent infinite loop in chunk fetching and improve test content
- Add max(1, ...) to estimated_batch_size to prevent division resulting in 0
- Update test content to use more substantial examples that generate facts
- Add request_context parameter to all retain_async and recall_async test calls
* refactor: simplify chunk fetching to always use pre-filtering approach
Remove backward compatibility code that fetched chunks after token
filtering. Now chunks are always fetched from top-scored results
before max_tokens filtering, regardless of max_tokens value.
This simplifies the code by:
- Removing duplicate chunk fetching logic
- Eliminating conditional behavior based on max_tokens
- Making chunk fetching behavior consistent and predictable
Chunks are still fetched in batches and respect max_chunk_tokens limit.
* fix: misc fixes for observations and mental models
* feat: improve graph retrieval for observations
- Update LinkExpansionRetriever to traverse through source_memory_ids
for observation entity connections (avoiding data duplication)
- Remove entity link copy from world facts to observations in consolidator
- Add tests for link expansion graph retrieval
- Add directives_applied field to ReflectResult
- Include user's other changes (CLI, docs, client updates)
* fix: CI test failures
- Add mental_model_id parameter to create_mental_model function
- Fix ToolCallTrace not including reason field from ToolCall
- Improve test_link_expansion_observation_graph_retrieval to wait for consolidation with retry
* chore: reduce link expansion log verbosity
* Revert "chore: reduce link expansion log verbosity"
This reverts commit 3ce759391cead1012157785fa78fef16ef9bfe3b.
* feat: add semantic/temporal/entity links as fallback in graph retrieval
- Add fallback query for semantic, temporal, and entity links from memory_links
- Check both directions (outgoing and incoming links)
- Weight fallback results at 0.5x to prioritize entity links via unit_entities
- Fixes graph retrieval returning 0 when data has cross-cluster temporal connections
* fix: enable observations fixture for link expansion test
- Add enable_observations fixture to ensure observations are created
- Increase wait time from 10 to 30 seconds for CI reliability
* feat: Record LLM token metrics via Prometheus
Wire up the existing token metrics infrastructure to actually record
token usage from LLM calls. The MetricsCollector already had
record_tokens() method and Prometheus counters (hindsight.tokens.input,
hindsight.tokens.output), but they were never being populated.
Changes:
- Import get_metrics_collector in llm_wrapper.py
- Call record_tokens() after successful LLM calls for:
- OpenAI/Groq (using response.usage.prompt_tokens, completion_tokens)
- Anthropic (using response.usage.input_tokens, output_tokens)
- Gemini (using response.usage_metadata.prompt_token_count, candidates_token_count)
- Add test file to verify token metrics are recorded
Note: Ollama's native API doesn't return token usage, so metrics
are not recorded for that provider.
The token metrics will now be available via /metrics endpoint:
- hindsight_tokens_input_total
- hindsight_tokens_output_total
* feat: add per-request token usage tracking to retain and reflect endpoints
- Add TokenUsage model with input_tokens, output_tokens, total_tokens
- Return usage metrics in retain response (sync operations only)
- Return usage metrics in reflect response
- Update Python, TypeScript, and Rust clients
- Add API documentation for usage fields
- Add changelog entry
* Fix main-methods.py: entities is a dict, use .items() and .canonical_name
* Migrate docs to use CodeSnippet components
- Convert quickstart.md, retain.md, recall.md, reflect.md, memory-banks.md to .mdx
- Use CodeSnippet to pull code from validated example scripts
- Add missing 'name' parameter to create_bank calls
- Fix main-methods.py entities iteration (dict not list)
- Remove retain-new.mdx demo file
* Migrate existing docs to match testing pattern with code snippet and add CLI tests to the CI
* Fix doc-id issue + add main-method tests
* CLI fixes
* Update openAPI json
* Fix rust build issues
* increase sleep time for Hindsight to process the document
* Added a polling sleep instead of fixed
* Delete immediately fails, so create the doc a earlier in the test to get the doc ready
* Add debug logs
* Remove debug logs
* Add documentation code validation system
- Create runnable example scripts in examples/api/ (19 files)
- Add CodeSnippet component for extracting marked sections
- Add raw-loader dependency for importing source files
- Create sample retain-new.mdx showing new approach
- Add README documenting coverage and gaps
* Fix wheel glob expansion in test-doc-examples CI job
* Fix CI issue
* Fix wheel path - uv build outputs to repo root dist/
* Fix: use explicit shell expansion for wheel install
* Fix: run cd in subshell so install runs from repo root
* Add documentation code validation CI job
- Use uv sync + uv run pattern (matches existing CI)
- Add requests to test dependencies for cleanup scripts
* Fix async API client usage in documents.py example
* Fix main-methods.py: RecallResult and ReflectFact don't have weight attribute
* Fix opinions.py: use actual API attributes instead of non-existent ones
* Fix example scripts: remove non-existent API attributes
- recall.py: remove .weight, fix entities iteration (dict not list)
- retain.mjs: remove result.async check
* bump pg0 0.11.x and improve documentation
* bump pg0 0.11.x and improve documentation
* bump pg0 0.11.x and improve documentation
* ci: test notebooks on ci
* ci: test notebooks on ci
* rm llms-full from repo
* formatting
* formatting
