* feat: ai sdk integration
* more fixes
* fix(security): mental model refresh tag-based security
- Mental model refresh now passes tags with all_strict matching
- Consolidation only triggers refresh for mental models with matching tags
- Consolidation filters related observations by tags (all_strict)
- Added tests to verify tag-based security boundaries
- Updated OpenAPI spec to include tags and text_preview in list_documents
- Added tags column to documents UI table
* chore: regenerate OpenAPI spec after rebase
* fix: improve consolidation prompt for contradiction handling and mental model refresh security
- Enhanced consolidation prompt to be more explicit about capturing temporal changes in contradictions
- Fixed mental model refresh security: tagged memories now only trigger refresh of mental models with matching tags
- Added stricter tag filtering to prevent cross-scope mental model refreshes
Fixes test_consolidation_merges_contradictions by improving LLM instructions to use temporal markers like "used to X, now Y" when merging contradictory facts.
Note: test_refresh_with_tags_only_accesses_same_tagged_models still needs investigation - REFLECT operation may need additional tag filtering.
* fix: mental model refresh security - proper tag filtering in search
Fixed tool_search_mental_models to properly handle all_strict tag matching mode by using the centralized build_tags_where_clause function. Previously, the function only handled "all" vs "any" modes and always included untagged mental models when using non-"all" modes.
This ensures that when a tagged mental model is refreshed with all_strict matching, it cannot access untagged mental models, preventing cross-scope information leakage.
Fixes test_refresh_with_tags_only_accesses_same_tagged_models.
Note: test_sensory_dimension_preservation is failing but this is a pre-existing issue on main branch - the LLM model (gpt-oss-20b) is not extracting facts from sensory text. Not related to security changes.
* chore: apply formatting from pre-commit hook
* fix: allow untagged mental models to be refreshed by any consolidation
Untagged mental models are considered "global" and should be refreshed
by any consolidation, regardless of whether tagged or untagged memories
were consolidated. This maintains security boundaries while allowing
global mental models to stay fresh.
When tagged memories are consolidated:
- Refresh mental models with matching tags (security boundary)
- Also refresh untagged mental models (they're global)
- DO NOT refresh mental models with different tags
When untagged memories are consolidated:
- Only refresh untagged mental models
- DO NOT refresh tagged mental models (security boundary)
Fixes test_consolidation_only_refreshes_matching_tagged_models.
* feat: improve mental models ux on control plane
* feat: improve mental models ux on control plane
* gen
* feat(cli): add --id flag to mental model create command
* fix(cli): revert unused variable underscore prefix that breaks compilation
The underscore prefix on stdout/stderr variables was added to suppress
warnings, but these variables are actually used in assert messages,
causing compilation errors. Reverting to original names.
* chore: remove dead code
* chore: remove extract_opinions from test and regenerate openapi
- Remove extract_opinions parameter from test_fact_extraction_analysis
- Regenerate OpenAPI spec after removing entity observations code
* chore: update generated files and apply formatting
- Regenerate Python and TypeScript client SDKs after main merge
- Apply ruff formatting to llm_wrapper.py
* fix: accept and filter deprecated 'opinion' fact type in recall
The dead code removal eliminated support for the 'opinion' fact type,
but existing clients may still pass it. Instead of rejecting it with
a ValueError, silently filter it out before validation to maintain
backward compatibility.
* feat: support vertex as llm provider
* fix
* fix: add uv index-strategy to resolve dependency conflicts with pytorch index
When using pytorch index for faster torch downloads in CI,
filelock dependency resolution was failing because pytorch index
only has older versions. Adding unsafe-best-match strategy allows
uv to search all configured indexes.
Also fix type checking warnings from ty.
* fix: add index-strategy to root pyproject.toml for workspace-level uv resolution
* chore: regenerate client SDKs after Vertex AI support
* 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
* Fix: Pass api_key to Hindsight client in litellm integration
The recall(), reflect(), and retain() wrapper functions were creating
Hindsight client instances without passing the api_key from the config.
This caused 401 Unauthorized errors when using hindsight-litellm with
authenticated Hindsight API servers.
Also added api_key parameter to:
- HindsightOpenAI and HindsightAnthropic wrapper classes
- wrap_openai() and wrap_anthropic() functions
* Add sensible defaults for simpler API usage
Make it easier to get started with hindsight-litellm by providing
sensible defaults:
- Default API URL: https://api.hindsight.vectorize.io (production)
- Default bank_id: "default"
- Read api_key from HINDSIGHT_API_KEY environment variable
Now users can simply do:
client = wrap_openai(OpenAI())
With just the HINDSIGHT_API_KEY env var set, and it works.
Also adds comprehensive unit tests for the new defaults behavior.
* Fix test using non-existent 'enabled' parameter in configure()
The test was calling configure(enabled=False) but configure() doesn't
have an enabled parameter. Changed to test is_configured() returns False
when reset_config() has been called.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
* Fix: rename 'background' parameter to 'mission' in Python client create_bank()
The parameter was named 'background' but the internal code used 'mission',
causing undefined variable errors. The tests also expected 'mission'.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
---------
Co-authored-by: Nicolò Boschi <boschi1997@gmail.com>
Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>
* feat(litellm): async retain with sync option, fix client session cleanup
- Add sync parameter to retain() for blocking vs background operation
- Default to async retain (sync=False) for better performance
- Add get_pending_retain_errors() to check async failures
- Fix "Unclosed client session" warnings by properly closing clients
- Fix "Timeout context manager" asyncio errors by creating fresh clients
- Each API call now creates and closes its own client (aiohttp limitation)
- Add _get_client() and _close_client() helpers for consistent handling
- Update recall(), reflect(), _retain_sync() and _inject_memories()
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
* feat(litellm): add reflect support and require explicit hindsight_query
- Make hindsight_query required when inject_memories=True to enforce
intentional memory queries (no automatic last-user-message fallback)
- Add reflect_context parameter for shaping LLM reasoning in reflect
- Add reflect_response_schema for structured JSON output from reflect
- Add _reflect_sync() and _reflect_async() methods in callbacks
- Update wrappers.py to support response_schema in reflect/areflect
This improves the developer experience by making memory injection
explicit and adds full reflect API support through the integration.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
* feat(litellm): rename recall_budget to budget, add per-call reflect context
- Rename `recall_budget` parameter to `budget` for consistency with API
- Add `hindsight_reflect_context` kwarg for per-call reflect context override
- Fix reflect() to not pass None values for optional parameters
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
* docs(litellm): update README for new API structure and features
- Document configure() vs set_defaults() separation
- Add hindsight_query requirement when inject_memories=True
- Document async retain (sync=False default) and get_pending_retain_errors()
- Add hindsight_reflect_context per-call override documentation
- Document budget parameter (renamed from recall_budget)
- Add reflect_context and reflect_response_schema options
- Update all code examples to use new API structure
- Add new functions to API Reference table
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
* test(litellm): update tests for new configure/set_defaults API
- Update tests to use separate configure() and set_defaults() calls
- Fix test assertions to check config vs defaults appropriately
- Add tests for legacy parameter backwards compatibility
- Add new TestSetDefaults test class
- Fix _format_memories test call signature (settings, config order)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
* feat: add set_bank_mission(), deprecate set_bank_background()
- Add mission parameter to hindsight_client.create_bank()
- Add set_bank_mission() function to hindsight_litellm
- Deprecate set_bank_background() with DeprecationWarning
- Update _create_or_update_bank() to support mission parameter
- Update README and docstrings to document the new API
The 'background' field has been deprecated in the Hindsight API in favor
of 'mission' which is used for mental model generation.
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
* Remove deprecated background parameter and legacy configure() parameters
- Remove set_bank_background() in favor of set_bank_mission()
- Remove background parameter from _create_or_update_bank()
- Remove background parameter from hindsight_client.create_bank()
- Remove legacy parameters from configure() (bank_id, document_id, budget, etc.)
- These have been replaced by the set_defaults() API
- Remove legacy test cases for deprecated parameters
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
* fix: update tests and docs to use mission instead of background
The create_bank() parameter was renamed from background to mission.
Update all tests and doc examples to use the new parameter name.
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
---------
Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>
Co-authored-by: Nicolò Boschi <boschi1997@gmail.com>
* chore: run benchmarks with reflect mode
* chore: run benchmarks with reflect mode
* fixes
* new mm
* bunch of fixes
* initial commit
* fixes
* fixes
* fixes
* fix: sometimes memories gets extracted in the wrong language
* ci: frozen uv sync
* fix: add missing authorization parameter to get_agent_stats in CLI
The generated Rust client was updated with an authorization header
parameter for get_agent_stats, but the CLI code wasn't updated.
* 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 Python SDK not sending Authorization header
The Python SDK accepts an api_key parameter but never sends it as a
Bearer token in requests. The OpenAPI-generated Configuration class
stores the key in access_token, but auth_settings() returns an empty
dict because the OpenAPI spec doesn't define a security scheme.
This fix manually sets the Authorization header on the ApiClient,
bypassing the broken auth_settings() mechanism.
Tested against api.dev.hindsight.vectorize.io:
- Before: 401 "Authentication failed: API key required"
- After: Success
* chore: update Rust client Cargo.lock for CI verification
Run generate-clients.sh to sync Cargo.lock with current dependencies.
