Commit graph

10 commits

Author SHA1 Message Date
shun yi
417fac61e4
feat: add support for ark and volcano LLM providers (#714)
- Add 'ark' and 'volcano' as valid LLM providers (both are aliases for Volcano Engine)
- Set default model to 'doubao-pro-32k' for both providers
- Add them to OpenAICompatibleLLM provider list
- Exclude from json_object response format support

Co-authored-by: yishun.eason <yishun.eason@bytedance.com>
2026-03-26 17:14:13 +01:00
Nicolò Boschi
9e5a066d26
feat: add 'none' LLM provider for chunk-only storage mode (#691)
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
2026-03-25 18:01:20 +01:00
Nicolò Boschi
5095d5e36f
feat(reflect): make source facts in search_observations configurable (#688)
* 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
2026-03-25 17:54:49 +01:00
Nicolò Boschi
db70fdbe5e
feat: add LiteLLM LLM provider for Bedrock and 100+ providers (#679)
* 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).
2026-03-25 14:17:38 +01:00
Nicolò Boschi
58e68f3e4a
feat: remove hardcoded default models from integrations (#670)
* 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
2026-03-24 17:20:15 +01:00
Petr Plenkov
8ce06e3e7c
Add wall-clock timeout to reflect operations (#643)
* Initial plan

* feat: add wall-clock timeout to reflect operations (fixes vectorize-io/hindsight#642)

Add a configurable wall-clock timeout (default: 300s / 5 minutes) for
the entire reflect operation. This prevents reflect calls from hanging
for up to 40 minutes when LLM calls are slow or iteration counts are
high.

Changes:
- Add DEFAULT_REFLECT_WALL_TIMEOUT (300s) config constant
- Add HINDSIGHT_API_REFLECT_WALL_TIMEOUT env variable support
- Wrap run_reflect_agent() with asyncio.wait_for() in reflect_async()
- Return HTTP 504 on timeout in the reflect HTTP endpoint
- Add unit test for wall-clock timeout enforcement

Co-authored-by: ThePlenkov <6381507+ThePlenkov@users.noreply.github.com>
Agent-Logs-Url: https://github.com/ThePlenkov/hindsight/sessions/a123d68b-aca1-4040-8bba-8c4f0fab2e2c

* fix: address PR review findings (OpenAPI 504, docs, type hints, main.py TypeError, overlapping exceptions, lazy logging)

Co-authored-by: ThePlenkov <6381507+ThePlenkov@users.noreply.github.com>
Agent-Logs-Url: https://github.com/ThePlenkov/hindsight/sessions/dd574a88-53a3-4f9e-bba7-5a40b0eddb99

---------

Co-authored-by: copilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com>
Co-authored-by: ThePlenkov <6381507+ThePlenkov@users.noreply.github.com>
2026-03-23 09:19:26 +01:00
Octopus
1f1462a5f6
feat: upgrade MiniMax default model from M2.5 to M2.7 (#606)
* 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>
2026-03-18 17:15:20 +01:00
Nicolò Boschi
e4f8a157c2
feat(retain): verbatim, chunks modes and named retain strategies (#593)
* 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
2026-03-17 18:08:25 +01:00
Fabio Scarsi
e7da7d0e4f
feat: local reranker FP16, bucket batching, and transformers 5.x compatibility (#588)
Three independent, cumulative improvements to LocalSTCrossEncoder:

1. transformers 5.x compatibility patch for XLM-RoBERTa models (Jina v2)
2. FP16 inference (opt-in via HINDSIGHT_API_RERANKER_LOCAL_FP16)
3. Length-sorted bucket batching (opt-in via HINDSIGHT_API_RERANKER_LOCAL_BUCKET_BATCHING)

All behind .env switches with conservative defaults preserving current behavior.

Fixes #586, Closes #587
2026-03-16 15:38:33 +01:00
Nicolò Boschi
15ea23d5d6
feat: introduce hindsight-api-slim and hindsight-all-slim packages (#560)
* 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)
2026-03-13 13:50:03 +01:00
Renamed from hindsight-api/hindsight_api/config.py (Browse further)