9b96becc5c
* feat: entity labels * feat: entity labels — optional, free_values, multi_value, UI polish Completes the entity labels system: **Schema & extraction** - Dynamic Pydantic Labels model per fact: each group becomes a typed field (Literal | None, list[Literal], str | None, or list[str]) - `optional: bool` flag per group — non-optional enum fields appear in JSON schema required array so structured-output providers enforce them - `free_values: bool` flag per group — accepts any LLM-generated string instead of a predefined enum; example values shown as hints in prompt - New `is_label_entity()` helper for labels-only mode filtering that handles both enum lookup and free_values key-prefix matching - Sentinel rejection: "None"/"null"/"n/a" strings dropped in post-processing **BM25 / dense retrieval** - `text_signals` column on memory_units: entity names + date tokens for enriched BM25 indexing without polluting stored fact text - Dense embedding includes occurred_end when it differs from occurred_start - Alembic migration z1u2v3w4x5y6 (merge revision fixing two heads) **UI (bank-config-view)** - Shadcn Switch replaces custom Toggle for both entity-labels and observations - Shadcn Checkbox for multi/optional/free_values per group - Input heights bumped to h-8 throughout the editor - "Label Groups" → "Entity Labels", "Free-form entities" → "Entities" - Free-text groups show "Example hints" banner in values section **Tests (45 unit + 3 LLM integration)** - build_labels_model: single, multi, mixed, free_values optional/required/multi - is_label_entity: enum match, free_values prefix match, no false positives - Post-processing: null/absent/string-None/free_values/sentinels/multi-value - Schema: labels in required, structured object, no labels when unconfigured - LLM integration: single-value enum, multi-value enum, free_values retain **Docs** - retain.md: new Entity Labels section covering groups, flags, examples - configuration.md: retain_free_form_entities env var + entity_labels note * fix(tests): update hierarchical fields count for entity_labels additions entity_labels and retain_free_form_entities are hierarchical fields, bumping the expected count from 11 to 13. * fix(migration): rename text_signals revision to avoid collision with main Main branch claimed z1u2v3w4x5y6 for observation_scopes. Rename our text_signals migration to a2b3c4d5e6f7, chaining after z1u2v3w4x5y6. * refactor(entity-labels): simplify free_values — always str|None, no multi - free_values groups always produce str | None (multi_value and optional flags are ignored for free text groups — always optional, never multi) - Prompt section for free_values groups shows only key + description, no values list (users put examples in the description instead) - UI: section title "Entities", toggle "Free Form Entities", replace per-group checkboxes with a type dropdown (Enum / Free text); only show multi checkbox and values list when type is Enum - Update tests to reflect new behaviour * refactor(entity-labels): replace free_values/multi_value booleans with type field - LabelGroup now uses type: "value" | "multi-values" | "text" instead of free_values/multi_value boolean pair - Backward-compat migration converts legacy dicts automatically - Rename retain_free_form_entities → entities_allow_free_form throughout - Update UI dropdown to show Single value / Multi-values / Free text - Remove separate multi checkbox (captured by type selection) - Update docs examples and configuration.md - Update all tests to use new field names * fix(migration): backfill observation_scopes column for DBs with swapped z1u2v3w4x5y6 Local DBs that had z1u2v3w4x5y6 applied when it referred to the old text_signals migration (before it was renamed to a2b3c4d5e6f7) won't have observation_scopes in their memory_units table. This migration adds the column with IF NOT EXISTS so it's a no-op on clean installs. * feat(entity-labels): add tag field to auto-populate memory unit tags from labels When a LabelGroup has tag=True, extracted key:value entities for that group are automatically written to the memory unit's tags array. This lets entity labels double as tags, enabling immediate filtering via the existing tags/tags_match API params with no extra infrastructure. - Add tag: bool = False to LabelGroup - _inject_label_tags() helper called in both sync and batch extraction paths - UI: add Tag checkbox per label group row - Docs: document the new tag field - Tests: 4 new unit tests covering all tag injection paths * style: ruff format migration file * fix(migration): fix multiple alembic heads after rebase — point text_signals after nullable_event_date * fix(clients): update timestamp field to use Timestamp wrapper type after timestamp=unset feature * style: ruff format agent.py * fix(docs): update Go quickstart example to use NullableTimestamp for timestamp field
1156 lines
46 KiB
Python
1156 lines
46 KiB
Python
"""
|
|
Clean, pythonic wrapper for the Hindsight API client.
|
|
|
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This file is MAINTAINED and NOT auto-generated. It provides a high-level,
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|
easy-to-use interface on top of the auto-generated OpenAPI client.
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"""
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import asyncio
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import json
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from datetime import datetime
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from pathlib import Path
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from typing import Any, Literal
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import hindsight_client_api
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from hindsight_client_api.api import banks_api, directives_api, files_api, memory_api, mental_models_api
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from hindsight_client_api.models import (
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memory_item,
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recall_request,
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reflect_request,
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retain_request,
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)
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from hindsight_client_api.models.reflect_include_options import ReflectIncludeOptions
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from hindsight_client_api.models.bank_profile_response import BankProfileResponse
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from hindsight_client_api.models.file_retain_response import FileRetainResponse
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from hindsight_client_api.models.list_memory_units_response import ListMemoryUnitsResponse
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from hindsight_client_api.models.recall_response import RecallResponse
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from hindsight_client_api.models.recall_result import RecallResult
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from hindsight_client_api.models.reflect_response import ReflectResponse
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from hindsight_client_api.models.retain_response import RetainResponse
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|
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def _run_async(coro):
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"""Run an async coroutine synchronously."""
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try:
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loop = asyncio.get_event_loop()
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except RuntimeError:
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loop = asyncio.new_event_loop()
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asyncio.set_event_loop(loop)
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return loop.run_until_complete(coro)
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class Hindsight:
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"""
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High-level, easy-to-use Hindsight API client.
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|
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Example:
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```python
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from hindsight_client import Hindsight
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# Without authentication
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client = Hindsight(base_url="http://localhost:8888")
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# With API key authentication
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client = Hindsight(base_url="http://localhost:8888", api_key="your-api-key")
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# Store a memory
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client.retain(bank_id="alice", content="Alice loves AI")
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# Recall memories
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response = client.recall(bank_id="alice", query="What does Alice like?")
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for r in response.results:
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print(r.text)
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# Generate contextual answer
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answer = client.reflect(bank_id="alice", query="What are my interests?")
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```
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"""
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def __init__(self, base_url: str, api_key: str | None = None, timeout: float = 300.0):
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"""
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Initialize the Hindsight client.
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Args:
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base_url: The base URL of the Hindsight API server
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api_key: Optional API key for authentication (sent as Bearer token)
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timeout: Request timeout in seconds (default: 300.0)
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"""
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config = hindsight_client_api.Configuration(host=base_url, access_token=api_key)
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self._api_client = hindsight_client_api.ApiClient(config)
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self._timeout = timeout
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self._base_url = base_url.rstrip("/")
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self._api_key = api_key
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if api_key:
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self._api_client.set_default_header("Authorization", f"Bearer {api_key}")
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self._memory_api = memory_api.MemoryApi(self._api_client)
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self._banks_api = banks_api.BanksApi(self._api_client)
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self._mental_models_api = mental_models_api.MentalModelsApi(self._api_client)
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self._directives_api = directives_api.DirectivesApi(self._api_client)
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self._files_api = files_api.FilesApi(self._api_client)
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def __enter__(self):
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"""Context manager entry."""
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return self
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def __exit__(self, exc_type, exc_val, exc_tb):
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"""Context manager exit."""
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self.close()
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def close(self):
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"""Close the API client (sync version - use aclose() in async code)."""
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if self._api_client:
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try:
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loop = asyncio.get_running_loop()
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# We're in an async context - schedule but don't wait
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# The caller should use aclose() instead
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loop.create_task(self._api_client.close())
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except RuntimeError:
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# No running loop - safe to run synchronously
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_run_async(self._api_client.close())
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async def aclose(self):
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"""Close the API client (async version)."""
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if self._api_client:
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await self._api_client.close()
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# Simplified methods for main operations
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def retain(
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self,
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bank_id: str,
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content: str,
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timestamp: datetime | None = None,
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context: str | None = None,
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document_id: str | None = None,
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metadata: dict[str, str] | None = None,
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entities: list[dict[str, str]] | None = None,
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tags: list[str] | None = None,
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) -> RetainResponse:
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"""
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Store a single memory (simplified interface).
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Args:
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bank_id: The memory bank ID
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content: Memory content
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timestamp: Optional event timestamp
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context: Optional context description
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document_id: Optional document ID for grouping
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metadata: Optional user-defined metadata
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entities: Optional list of entities [{"text": "...", "type": "..."}]
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tags: Optional list of tags for filtering memories during recall/reflect
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Returns:
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RetainResponse with success status
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"""
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return self.retain_batch(
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bank_id=bank_id,
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items=[
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{
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"content": content,
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"timestamp": timestamp,
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"context": context,
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"metadata": metadata,
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"entities": entities,
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"tags": tags,
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}
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],
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document_id=document_id,
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)
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def retain_batch(
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self,
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bank_id: str,
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items: list[dict[str, Any]],
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document_id: str | None = None,
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document_tags: list[str] | None = None,
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retain_async: bool = False,
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) -> RetainResponse:
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"""
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Store multiple memories in batch.
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Args:
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bank_id: The memory bank ID
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items: List of memory items with 'content' and optional 'timestamp', 'context', 'metadata', 'document_id', 'entities', 'tags'
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document_id: Optional document ID for grouping memories (applied to items that don't have their own)
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document_tags: Optional list of tags applied to all items in this batch (merged with per-item tags)
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retain_async: If True, process asynchronously in background (default: False)
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Returns:
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RetainResponse with success status and item count
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"""
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from hindsight_client_api.models.entity_input import EntityInput
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from hindsight_client_api.models.timestamp import Timestamp
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memory_items = []
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for item in items:
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entities = None
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if item.get("entities"):
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entities = [EntityInput(text=e["text"], type=e.get("type")) for e in item["entities"]]
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raw_ts = item.get("timestamp")
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timestamp_val = Timestamp(actual_instance=raw_ts) if raw_ts is not None else None
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memory_items.append(
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memory_item.MemoryItem(
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content=item["content"],
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timestamp=timestamp_val,
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context=item.get("context"),
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metadata=item.get("metadata"),
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# Use item's document_id if provided, otherwise fall back to batch-level document_id
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document_id=item.get("document_id") or document_id,
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entities=entities,
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tags=item.get("tags"),
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)
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)
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request_obj = retain_request.RetainRequest(
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items=memory_items,
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async_=retain_async,
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document_tags=document_tags,
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)
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return _run_async(self._memory_api.retain_memories(bank_id, request_obj, _request_timeout=self._timeout))
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def retain_files(
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self,
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bank_id: str,
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files: list[str | Path],
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context: str | None = None,
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files_metadata: list[dict[str, Any]] | None = None,
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) -> FileRetainResponse:
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"""
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Upload files and retain their contents as memories.
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Files are automatically converted to text (PDF, DOCX, images via OCR, audio via
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transcription, and more) and ingested as memories. Processing is always asynchronous
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— use the returned operation IDs to track progress.
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|
Args:
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bank_id: The memory bank ID
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files: List of file paths to upload
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context: Optional context description applied to all files
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files_metadata: Optional per-file metadata list. If provided, must match the
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length of `files`. Each entry can have: context, document_id, tags, metadata.
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Returns:
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FileRetainResponse with operation_ids for tracking progress
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"""
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file_data = []
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for file_path in files:
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path = Path(file_path)
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file_data.append((path.name, path.read_bytes()))
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meta = files_metadata or [{"context": context} if context else {} for _ in files]
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request_body = json.dumps({"files_metadata": meta})
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return _run_async(self._files_api.file_retain(bank_id=bank_id, files=file_data, request=request_body, _request_timeout=self._timeout))
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|
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def recall(
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self,
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bank_id: str,
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query: str,
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types: list[str] | None = None,
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max_tokens: int = 4096,
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budget: str = "mid",
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trace: bool = False,
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query_timestamp: str | None = None,
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include_entities: bool = False,
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max_entity_tokens: int = 500,
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include_chunks: bool = False,
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max_chunk_tokens: int = 8192,
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include_source_facts: bool = False,
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max_source_facts_tokens: int = 4096,
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tags: list[str] | None = None,
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tags_match: Literal["any", "all", "any_strict", "all_strict"] = "any",
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) -> RecallResponse:
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"""
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|
Recall memories using semantic similarity.
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|
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|
Args:
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|
bank_id: The memory bank ID
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|
query: Search query
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|
types: Optional list of fact types to filter (world, experience, opinion, observation)
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|
max_tokens: Maximum tokens in results (default: 4096)
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|
budget: Budget level for recall - "low", "mid", or "high" (default: "mid")
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|
trace: Enable trace output (default: False)
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query_timestamp: Optional ISO format date string (e.g., '2023-05-30T23:40:00')
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include_entities: Include entity observations in results (default: False)
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max_entity_tokens: Maximum tokens for entity observations (default: 500)
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|
include_chunks: Include raw text chunks in results (default: False)
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max_chunk_tokens: Maximum tokens for chunks (default: 8192)
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include_source_facts: Include source facts for observation-type results (default: False)
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max_source_facts_tokens: Maximum tokens for source facts (default: 4096)
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tags: Optional list of tags to filter memories by
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|
tags_match: How to match tags - "any" (OR, includes untagged), "all" (AND, includes untagged),
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|
"any_strict" (OR, excludes untagged), "all_strict" (AND, excludes untagged). Default: "any"
|
|
|
|
Returns:
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|
RecallResponse with results, optional entities, optional chunks, optional source_facts, and optional trace
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|
"""
|
|
from hindsight_client_api.models import (
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|
chunk_include_options,
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entity_include_options,
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|
include_options,
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|
source_facts_include_options,
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|
)
|
|
|
|
include_opts = include_options.IncludeOptions(
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entities=entity_include_options.EntityIncludeOptions(max_tokens=max_entity_tokens)
|
|
if include_entities
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|
else None,
|
|
chunks=chunk_include_options.ChunkIncludeOptions(max_tokens=max_chunk_tokens) if include_chunks else None,
|
|
source_facts=source_facts_include_options.SourceFactsIncludeOptions(max_tokens=max_source_facts_tokens)
|
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if include_source_facts
|
|
else None,
|
|
)
|
|
|
|
request_obj = recall_request.RecallRequest(
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|
query=query,
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|
types=types,
|
|
budget=budget,
|
|
max_tokens=max_tokens,
|
|
trace=trace,
|
|
query_timestamp=query_timestamp,
|
|
include=include_opts,
|
|
tags=tags,
|
|
tags_match=tags_match,
|
|
)
|
|
|
|
return _run_async(self._memory_api.recall_memories(bank_id, request_obj, _request_timeout=self._timeout))
|
|
|
|
def reflect(
|
|
self,
|
|
bank_id: str,
|
|
query: str,
|
|
budget: str = "low",
|
|
context: str | None = None,
|
|
max_tokens: int | None = None,
|
|
response_schema: dict[str, Any] | None = None,
|
|
tags: list[str] | None = None,
|
|
tags_match: Literal["any", "all", "any_strict", "all_strict"] = "any",
|
|
include_facts: bool = False,
|
|
) -> ReflectResponse:
|
|
"""
|
|
Generate a contextual answer based on bank identity and memories.
|
|
|
|
Args:
|
|
bank_id: The memory bank ID
|
|
query: The question or prompt
|
|
budget: Budget level for reflection - "low", "mid", or "high" (default: "low")
|
|
context: Optional additional context
|
|
max_tokens: Maximum tokens for the response (server default: 4096)
|
|
response_schema: Optional JSON Schema for structured output. When provided,
|
|
the response will include a 'structured_output' field with the LLM
|
|
response parsed according to this schema.
|
|
tags: Optional list of tags to filter memories by
|
|
tags_match: How to match tags - "any" (OR, includes untagged), "all" (AND, includes untagged),
|
|
"any_strict" (OR, excludes untagged), "all_strict" (AND, excludes untagged). Default: "any"
|
|
include_facts: If True, the response will include a 'based_on' field listing
|
|
the memories, mental models, and directives used to construct the answer.
|
|
|
|
Returns:
|
|
ReflectResponse with answer text, optionally facts used, and optionally
|
|
structured_output if response_schema was provided
|
|
"""
|
|
include = ReflectIncludeOptions(facts={}) if include_facts else None
|
|
request_obj = reflect_request.ReflectRequest(
|
|
query=query,
|
|
budget=budget,
|
|
context=context,
|
|
max_tokens=max_tokens,
|
|
response_schema=response_schema,
|
|
tags=tags,
|
|
tags_match=tags_match,
|
|
include=include,
|
|
)
|
|
|
|
return _run_async(self._memory_api.reflect(bank_id, request_obj, _request_timeout=self._timeout))
|
|
|
|
def list_memories(
|
|
self,
|
|
bank_id: str,
|
|
type: str | None = None,
|
|
search_query: str | None = None,
|
|
limit: int = 100,
|
|
offset: int = 0,
|
|
) -> ListMemoryUnitsResponse:
|
|
"""List memory units with pagination."""
|
|
return _run_async(
|
|
self._memory_api.list_memories(
|
|
bank_id=bank_id,
|
|
type=type,
|
|
q=search_query,
|
|
limit=limit,
|
|
offset=offset,
|
|
_request_timeout=self._timeout,
|
|
)
|
|
)
|
|
|
|
def create_bank(
|
|
self,
|
|
bank_id: str,
|
|
name: str | None = None,
|
|
mission: str | None = None,
|
|
disposition_skepticism: int | None = None,
|
|
disposition_literalism: int | None = None,
|
|
disposition_empathy: int | None = None,
|
|
disposition: dict[str, float] | None = None,
|
|
retain_mission: str | None = None,
|
|
retain_extraction_mode: str | None = None,
|
|
retain_custom_instructions: str | None = None,
|
|
retain_chunk_size: int | None = None,
|
|
enable_observations: bool | None = None,
|
|
observations_mission: str | None = None,
|
|
reflect_mission: str | None = None,
|
|
) -> BankProfileResponse:
|
|
"""Create or update a memory bank.
|
|
|
|
Args:
|
|
bank_id: Unique identifier for the bank
|
|
name: Deprecated. Display label only.
|
|
mission: Deprecated. Use reflect_mission instead.
|
|
disposition_skepticism: Deprecated. Use update_bank_config(disposition_skepticism=...) instead.
|
|
disposition_literalism: Deprecated. Use update_bank_config(disposition_literalism=...) instead.
|
|
disposition_empathy: Deprecated. Use update_bank_config(disposition_empathy=...) instead.
|
|
disposition: Deprecated. Use update_bank_config(disposition_skepticism=...) instead.
|
|
retain_mission: Steers what gets extracted during retain(). Injected alongside built-in rules.
|
|
retain_extraction_mode: Fact extraction mode: 'concise' (default), 'verbose', or 'custom'.
|
|
retain_custom_instructions: Custom extraction prompt (only active when mode is 'custom').
|
|
retain_chunk_size: Maximum token size for each content chunk during retain.
|
|
enable_observations: Toggle automatic observation consolidation after retain().
|
|
observations_mission: Controls what gets synthesised into observations. Replaces built-in rules.
|
|
reflect_mission: Mission/context for Reflect operations.
|
|
"""
|
|
return _run_async(
|
|
self._acreate_bank(
|
|
bank_id,
|
|
name=name,
|
|
mission=mission,
|
|
reflect_mission=reflect_mission,
|
|
disposition_skepticism=disposition_skepticism,
|
|
disposition_literalism=disposition_literalism,
|
|
disposition_empathy=disposition_empathy,
|
|
disposition=disposition,
|
|
retain_mission=retain_mission,
|
|
retain_extraction_mode=retain_extraction_mode,
|
|
retain_custom_instructions=retain_custom_instructions,
|
|
retain_chunk_size=retain_chunk_size,
|
|
enable_observations=enable_observations,
|
|
observations_mission=observations_mission,
|
|
)
|
|
)
|
|
|
|
async def _acreate_bank(
|
|
self,
|
|
bank_id: str,
|
|
name: str | None = None,
|
|
mission: str | None = None,
|
|
reflect_mission: str | None = None,
|
|
disposition_skepticism: int | None = None,
|
|
disposition_literalism: int | None = None,
|
|
disposition_empathy: int | None = None,
|
|
disposition: dict[str, float] | None = None,
|
|
retain_mission: str | None = None,
|
|
retain_extraction_mode: str | None = None,
|
|
retain_custom_instructions: str | None = None,
|
|
retain_chunk_size: int | None = None,
|
|
enable_observations: bool | None = None,
|
|
observations_mission: str | None = None,
|
|
) -> BankProfileResponse:
|
|
import aiohttp
|
|
|
|
body: dict[str, Any] = {}
|
|
if name is not None:
|
|
body["name"] = name
|
|
if mission is not None:
|
|
body["mission"] = mission
|
|
if reflect_mission is not None:
|
|
body["reflect_mission"] = reflect_mission
|
|
# Individual disposition fields take priority over legacy disposition dict
|
|
if disposition_skepticism is not None:
|
|
body["disposition_skepticism"] = disposition_skepticism
|
|
elif disposition is not None:
|
|
body["disposition_skepticism"] = disposition.get("skepticism")
|
|
if disposition_literalism is not None:
|
|
body["disposition_literalism"] = disposition_literalism
|
|
elif disposition is not None:
|
|
body["disposition_literalism"] = disposition.get("literalism")
|
|
if disposition_empathy is not None:
|
|
body["disposition_empathy"] = disposition_empathy
|
|
elif disposition is not None:
|
|
body["disposition_empathy"] = disposition.get("empathy")
|
|
if retain_mission is not None:
|
|
body["retain_mission"] = retain_mission
|
|
if retain_extraction_mode is not None:
|
|
body["retain_extraction_mode"] = retain_extraction_mode
|
|
if retain_custom_instructions is not None:
|
|
body["retain_custom_instructions"] = retain_custom_instructions
|
|
if retain_chunk_size is not None:
|
|
body["retain_chunk_size"] = retain_chunk_size
|
|
if enable_observations is not None:
|
|
body["enable_observations"] = enable_observations
|
|
if observations_mission is not None:
|
|
body["observations_mission"] = observations_mission
|
|
|
|
url = f"{self._base_url}/v1/default/banks/{bank_id}"
|
|
headers = {"Authorization": f"Bearer {self._api_key}"} if self._api_key else {}
|
|
async with aiohttp.ClientSession() as session:
|
|
async with session.put(
|
|
url, json=body, headers=headers, timeout=aiohttp.ClientTimeout(total=self._timeout)
|
|
) as resp:
|
|
resp.raise_for_status()
|
|
data = await resp.json()
|
|
return BankProfileResponse.model_validate(data)
|
|
|
|
def set_mission(self, bank_id: str, mission: str) -> dict[str, Any]:
|
|
"""Deprecated. Use update_bank_config(reflect_mission=...) instead."""
|
|
return self.create_bank(bank_id, mission=mission)
|
|
|
|
def set_reflect_mission(self, bank_id: str, reflect_mission: str) -> dict[str, Any]:
|
|
"""Deprecated alias for set_mission()."""
|
|
return self.set_mission(bank_id, reflect_mission)
|
|
|
|
# Async methods (native async, no _run_async wrapper)
|
|
|
|
async def acreate_bank(
|
|
self,
|
|
bank_id: str,
|
|
name: str | None = None,
|
|
mission: str | None = None,
|
|
disposition_skepticism: int | None = None,
|
|
disposition_literalism: int | None = None,
|
|
disposition_empathy: int | None = None,
|
|
disposition: dict[str, float] | None = None,
|
|
retain_mission: str | None = None,
|
|
retain_extraction_mode: str | None = None,
|
|
retain_custom_instructions: str | None = None,
|
|
retain_chunk_size: int | None = None,
|
|
enable_observations: bool | None = None,
|
|
observations_mission: str | None = None,
|
|
reflect_mission: str | None = None,
|
|
) -> BankProfileResponse:
|
|
"""Create or update a memory bank (async).
|
|
|
|
Args:
|
|
bank_id: Unique identifier for the bank
|
|
name: Deprecated. Display label only.
|
|
mission: Deprecated. Use reflect_mission instead.
|
|
disposition_skepticism: Deprecated. Use update_bank_config(disposition_skepticism=...) instead.
|
|
disposition_literalism: Deprecated. Use update_bank_config(disposition_literalism=...) instead.
|
|
disposition_empathy: Deprecated. Use update_bank_config(disposition_empathy=...) instead.
|
|
disposition: Deprecated. Use update_bank_config(disposition_skepticism=...) instead.
|
|
retain_mission: Steers what gets extracted during retain(). Injected alongside built-in rules.
|
|
retain_extraction_mode: Fact extraction mode: 'concise' (default), 'verbose', or 'custom'.
|
|
retain_custom_instructions: Custom extraction prompt (only active when mode is 'custom').
|
|
retain_chunk_size: Maximum token size for each content chunk during retain.
|
|
enable_observations: Toggle automatic observation consolidation after retain().
|
|
observations_mission: Controls what gets synthesised into observations. Replaces built-in rules.
|
|
reflect_mission: Mission/context for Reflect operations.
|
|
"""
|
|
return await self._acreate_bank(
|
|
bank_id,
|
|
name=name,
|
|
mission=mission,
|
|
reflect_mission=reflect_mission,
|
|
disposition_skepticism=disposition_skepticism,
|
|
disposition_literalism=disposition_literalism,
|
|
disposition_empathy=disposition_empathy,
|
|
disposition=disposition,
|
|
retain_mission=retain_mission,
|
|
retain_extraction_mode=retain_extraction_mode,
|
|
retain_custom_instructions=retain_custom_instructions,
|
|
retain_chunk_size=retain_chunk_size,
|
|
enable_observations=enable_observations,
|
|
observations_mission=observations_mission,
|
|
)
|
|
|
|
async def aset_mission(self, bank_id: str, mission: str) -> dict[str, Any]:
|
|
"""Deprecated. Use update_bank_config(reflect_mission=...) instead."""
|
|
return await self.acreate_bank(bank_id, mission=mission)
|
|
|
|
async def aset_reflect_mission(self, bank_id: str, reflect_mission: str) -> dict[str, Any]:
|
|
"""Deprecated alias for aset_mission()."""
|
|
return await self.aset_mission(bank_id, reflect_mission)
|
|
|
|
async def aretain_batch(
|
|
self,
|
|
bank_id: str,
|
|
items: list[dict[str, Any]],
|
|
document_id: str | None = None,
|
|
document_tags: list[str] | None = None,
|
|
retain_async: bool = False,
|
|
) -> RetainResponse:
|
|
"""
|
|
Store multiple memories in batch (async).
|
|
|
|
Args:
|
|
bank_id: The memory bank ID
|
|
items: List of memory items with 'content' and optional 'timestamp', 'context', 'metadata', 'document_id', 'entities', 'tags'
|
|
document_id: Optional document ID for grouping memories (applied to items that don't have their own)
|
|
document_tags: Optional list of tags applied to all items in this batch (merged with per-item tags)
|
|
retain_async: If True, process asynchronously in background (default: False)
|
|
|
|
Returns:
|
|
RetainResponse with success status and item count
|
|
"""
|
|
from hindsight_client_api.models.entity_input import EntityInput
|
|
from hindsight_client_api.models.timestamp import Timestamp
|
|
|
|
memory_items = []
|
|
for item in items:
|
|
entities = None
|
|
if item.get("entities"):
|
|
entities = [EntityInput(text=e["text"], type=e.get("type")) for e in item["entities"]]
|
|
raw_ts = item.get("timestamp")
|
|
timestamp_val = Timestamp(actual_instance=raw_ts) if raw_ts is not None else None
|
|
memory_items.append(
|
|
memory_item.MemoryItem(
|
|
content=item["content"],
|
|
timestamp=timestamp_val,
|
|
context=item.get("context"),
|
|
metadata=item.get("metadata"),
|
|
# Use item's document_id if provided, otherwise fall back to batch-level document_id
|
|
document_id=item.get("document_id") or document_id,
|
|
entities=entities,
|
|
tags=item.get("tags"),
|
|
)
|
|
)
|
|
|
|
request_obj = retain_request.RetainRequest(
|
|
items=memory_items,
|
|
async_=retain_async,
|
|
document_tags=document_tags,
|
|
)
|
|
|
|
return await self._memory_api.retain_memories(bank_id, request_obj, _request_timeout=self._timeout)
|
|
|
|
async def aretain(
|
|
self,
|
|
bank_id: str,
|
|
content: str,
|
|
timestamp: datetime | None = None,
|
|
context: str | None = None,
|
|
document_id: str | None = None,
|
|
metadata: dict[str, str] | None = None,
|
|
entities: list[dict[str, str]] | None = None,
|
|
tags: list[str] | None = None,
|
|
) -> RetainResponse:
|
|
"""
|
|
Store a single memory (async).
|
|
|
|
Args:
|
|
bank_id: The memory bank ID
|
|
content: Memory content
|
|
timestamp: Optional event timestamp
|
|
context: Optional context description
|
|
document_id: Optional document ID for grouping
|
|
metadata: Optional user-defined metadata
|
|
entities: Optional list of entities [{"text": "...", "type": "..."}]
|
|
tags: Optional list of tags for filtering memories during recall/reflect
|
|
|
|
Returns:
|
|
RetainResponse with success status
|
|
"""
|
|
return await self.aretain_batch(
|
|
bank_id=bank_id,
|
|
items=[
|
|
{
|
|
"content": content,
|
|
"timestamp": timestamp,
|
|
"context": context,
|
|
"metadata": metadata,
|
|
"entities": entities,
|
|
"tags": tags,
|
|
}
|
|
],
|
|
document_id=document_id,
|
|
)
|
|
|
|
async def arecall(
|
|
self,
|
|
bank_id: str,
|
|
query: str,
|
|
types: list[str] | None = None,
|
|
max_tokens: int = 4096,
|
|
budget: str = "mid",
|
|
trace: bool = False,
|
|
query_timestamp: str | None = None,
|
|
include_entities: bool = False,
|
|
max_entity_tokens: int = 500,
|
|
include_chunks: bool = False,
|
|
max_chunk_tokens: int = 8192,
|
|
include_source_facts: bool = False,
|
|
max_source_facts_tokens: int = 4096,
|
|
tags: list[str] | None = None,
|
|
tags_match: Literal["any", "all", "any_strict", "all_strict"] = "any",
|
|
) -> RecallResponse:
|
|
"""
|
|
Recall memories using semantic similarity (async).
|
|
|
|
Args:
|
|
bank_id: The memory bank ID
|
|
query: Search query
|
|
types: Optional list of fact types to filter (world, experience, opinion, observation)
|
|
max_tokens: Maximum tokens in results (default: 4096)
|
|
budget: Budget level for recall - "low", "mid", or "high" (default: "mid")
|
|
trace: Enable trace output (default: False)
|
|
query_timestamp: Optional ISO format date string (e.g., '2023-05-30T23:40:00')
|
|
include_entities: Include entity observations in results (default: False)
|
|
max_entity_tokens: Maximum tokens for entity observations (default: 500)
|
|
include_chunks: Include raw text chunks in results (default: False)
|
|
max_chunk_tokens: Maximum tokens for chunks (default: 8192)
|
|
include_source_facts: Include source facts for observation-type results (default: False)
|
|
max_source_facts_tokens: Maximum tokens for source facts (default: 4096)
|
|
tags: Optional list of tags to filter memories by
|
|
tags_match: How to match tags - "any" (OR, includes untagged), "all" (AND, includes untagged),
|
|
"any_strict" (OR, excludes untagged), "all_strict" (AND, excludes untagged). Default: "any"
|
|
|
|
Returns:
|
|
RecallResponse with results, optional entities, optional chunks, optional source_facts, and optional trace
|
|
"""
|
|
from hindsight_client_api.models import (
|
|
chunk_include_options,
|
|
entity_include_options,
|
|
include_options,
|
|
source_facts_include_options,
|
|
)
|
|
|
|
include_opts = include_options.IncludeOptions(
|
|
entities=entity_include_options.EntityIncludeOptions(max_tokens=max_entity_tokens)
|
|
if include_entities
|
|
else None,
|
|
chunks=chunk_include_options.ChunkIncludeOptions(max_tokens=max_chunk_tokens) if include_chunks else None,
|
|
source_facts=source_facts_include_options.SourceFactsIncludeOptions(max_tokens=max_source_facts_tokens)
|
|
if include_source_facts
|
|
else None,
|
|
)
|
|
|
|
request_obj = recall_request.RecallRequest(
|
|
query=query,
|
|
types=types,
|
|
budget=budget,
|
|
max_tokens=max_tokens,
|
|
trace=trace,
|
|
query_timestamp=query_timestamp,
|
|
include=include_opts,
|
|
tags=tags,
|
|
tags_match=tags_match,
|
|
)
|
|
|
|
return await self._memory_api.recall_memories(bank_id, request_obj, _request_timeout=self._timeout)
|
|
|
|
async def areflect(
|
|
self,
|
|
bank_id: str,
|
|
query: str,
|
|
budget: str = "low",
|
|
context: str | None = None,
|
|
max_tokens: int | None = None,
|
|
response_schema: dict[str, Any] | None = None,
|
|
tags: list[str] | None = None,
|
|
tags_match: Literal["any", "all", "any_strict", "all_strict"] = "any",
|
|
) -> ReflectResponse:
|
|
"""
|
|
Generate a contextual answer based on bank identity and memories (async).
|
|
|
|
Args:
|
|
bank_id: The memory bank ID
|
|
query: The question or prompt
|
|
budget: Budget level for reflection - "low", "mid", or "high" (default: "low")
|
|
context: Optional additional context
|
|
max_tokens: Maximum tokens for the response (server default: 4096)
|
|
response_schema: Optional JSON Schema for structured output. When provided,
|
|
the response will include a 'structured_output' field with the LLM
|
|
response parsed according to this schema.
|
|
tags: Optional list of tags to filter memories by
|
|
tags_match: How to match tags - "any" (OR, includes untagged), "all" (AND, includes untagged),
|
|
"any_strict" (OR, excludes untagged), "all_strict" (AND, excludes untagged). Default: "any"
|
|
|
|
Returns:
|
|
ReflectResponse with answer text, optionally facts used, and optionally
|
|
structured_output if response_schema was provided
|
|
"""
|
|
request_obj = reflect_request.ReflectRequest(
|
|
query=query,
|
|
budget=budget,
|
|
context=context,
|
|
max_tokens=max_tokens,
|
|
response_schema=response_schema,
|
|
tags=tags,
|
|
tags_match=tags_match,
|
|
)
|
|
|
|
return await self._memory_api.reflect(bank_id, request_obj, _request_timeout=self._timeout)
|
|
|
|
# Mental Models methods
|
|
|
|
def create_mental_model(
|
|
self,
|
|
bank_id: str,
|
|
name: str,
|
|
source_query: str,
|
|
tags: list[str] | None = None,
|
|
max_tokens: int | None = None,
|
|
trigger: dict[str, Any] | None = None,
|
|
):
|
|
"""
|
|
Create a mental model (runs reflect in background).
|
|
|
|
Args:
|
|
bank_id: The memory bank ID
|
|
name: Human-readable name for the mental model
|
|
source_query: The query to run to generate content
|
|
tags: Optional tags for filtering during retrieval
|
|
max_tokens: Optional maximum tokens for the mental model content
|
|
trigger: Optional trigger settings (e.g., {"refresh_after_consolidation": True})
|
|
|
|
Returns:
|
|
CreateMentalModelResponse with operation_id
|
|
"""
|
|
from hindsight_client_api.models import create_mental_model_request, mental_model_trigger
|
|
|
|
trigger_obj = None
|
|
if trigger:
|
|
trigger_obj = mental_model_trigger.MentalModelTrigger(**trigger)
|
|
|
|
request_obj = create_mental_model_request.CreateMentalModelRequest(
|
|
name=name,
|
|
source_query=source_query,
|
|
tags=tags,
|
|
max_tokens=max_tokens,
|
|
trigger=trigger_obj,
|
|
)
|
|
|
|
return _run_async(self._mental_models_api.create_mental_model(bank_id, request_obj, _request_timeout=self._timeout))
|
|
|
|
def list_mental_models(self, bank_id: str, tags: list[str] | None = None):
|
|
"""
|
|
List all mental models in a bank.
|
|
|
|
Args:
|
|
bank_id: The memory bank ID
|
|
tags: Optional tags to filter by
|
|
|
|
Returns:
|
|
ListMentalModelsResponse with items
|
|
"""
|
|
return _run_async(self._mental_models_api.list_mental_models(bank_id, tags=tags, _request_timeout=self._timeout))
|
|
|
|
def get_mental_model(self, bank_id: str, mental_model_id: str):
|
|
"""
|
|
Get a specific mental model.
|
|
|
|
Args:
|
|
bank_id: The memory bank ID
|
|
mental_model_id: The mental model ID
|
|
|
|
Returns:
|
|
MentalModelResponse
|
|
"""
|
|
return _run_async(self._mental_models_api.get_mental_model(bank_id, mental_model_id, _request_timeout=self._timeout))
|
|
|
|
def refresh_mental_model(self, bank_id: str, mental_model_id: str):
|
|
"""
|
|
Refresh a mental model to update with current knowledge.
|
|
|
|
Args:
|
|
bank_id: The memory bank ID
|
|
mental_model_id: The mental model ID
|
|
|
|
Returns:
|
|
RefreshMentalModelResponse with operation_id
|
|
"""
|
|
return _run_async(self._mental_models_api.refresh_mental_model(bank_id, mental_model_id, _request_timeout=self._timeout))
|
|
|
|
def update_mental_model(
|
|
self,
|
|
bank_id: str,
|
|
mental_model_id: str,
|
|
name: str | None = None,
|
|
source_query: str | None = None,
|
|
tags: list[str] | None = None,
|
|
max_tokens: int | None = None,
|
|
trigger: dict[str, Any] | None = None,
|
|
):
|
|
"""
|
|
Update a mental model's metadata.
|
|
|
|
Args:
|
|
bank_id: The memory bank ID
|
|
mental_model_id: The mental model ID
|
|
name: Optional new name
|
|
source_query: Optional new source query
|
|
tags: Optional new tags
|
|
max_tokens: Optional new max tokens
|
|
trigger: Optional trigger settings (e.g., {"refresh_after_consolidation": True})
|
|
|
|
Returns:
|
|
MentalModelResponse
|
|
"""
|
|
from hindsight_client_api.models import mental_model_trigger, update_mental_model_request
|
|
|
|
trigger_obj = None
|
|
if trigger:
|
|
trigger_obj = mental_model_trigger.MentalModelTrigger(**trigger)
|
|
|
|
request_obj = update_mental_model_request.UpdateMentalModelRequest(
|
|
name=name,
|
|
source_query=source_query,
|
|
tags=tags,
|
|
max_tokens=max_tokens,
|
|
trigger=trigger_obj,
|
|
)
|
|
|
|
return _run_async(self._mental_models_api.update_mental_model(bank_id, mental_model_id, request_obj, _request_timeout=self._timeout))
|
|
|
|
def delete_mental_model(self, bank_id: str, mental_model_id: str):
|
|
"""
|
|
Delete a mental model.
|
|
|
|
Args:
|
|
bank_id: The memory bank ID
|
|
mental_model_id: The mental model ID
|
|
"""
|
|
return _run_async(self._mental_models_api.delete_mental_model(bank_id, mental_model_id, _request_timeout=self._timeout))
|
|
|
|
# Directives methods
|
|
|
|
def create_directive(
|
|
self,
|
|
bank_id: str,
|
|
name: str,
|
|
content: str,
|
|
priority: int = 0,
|
|
is_active: bool = True,
|
|
tags: list[str] | None = None,
|
|
):
|
|
"""
|
|
Create a directive (hard rule for reflect).
|
|
|
|
Args:
|
|
bank_id: The memory bank ID
|
|
name: Human-readable name for the directive
|
|
content: The directive content/rules
|
|
priority: Priority level (higher = injected first)
|
|
is_active: Whether the directive is active
|
|
tags: Optional tags for filtering
|
|
|
|
Returns:
|
|
DirectiveResponse
|
|
"""
|
|
from hindsight_client_api.models import create_directive_request
|
|
|
|
request_obj = create_directive_request.CreateDirectiveRequest(
|
|
name=name,
|
|
content=content,
|
|
priority=priority,
|
|
is_active=is_active,
|
|
tags=tags,
|
|
)
|
|
|
|
return _run_async(self._directives_api.create_directive(bank_id, request_obj, _request_timeout=self._timeout))
|
|
|
|
def list_directives(self, bank_id: str, tags: list[str] | None = None):
|
|
"""
|
|
List all directives in a bank.
|
|
|
|
Args:
|
|
bank_id: The memory bank ID
|
|
tags: Optional tags to filter by
|
|
|
|
Returns:
|
|
ListDirectivesResponse with items
|
|
"""
|
|
return _run_async(self._directives_api.list_directives(bank_id, tags=tags, _request_timeout=self._timeout))
|
|
|
|
def get_directive(self, bank_id: str, directive_id: str):
|
|
"""
|
|
Get a specific directive.
|
|
|
|
Args:
|
|
bank_id: The memory bank ID
|
|
directive_id: The directive ID
|
|
|
|
Returns:
|
|
DirectiveResponse
|
|
"""
|
|
return _run_async(self._directives_api.get_directive(bank_id, directive_id, _request_timeout=self._timeout))
|
|
|
|
def update_directive(
|
|
self,
|
|
bank_id: str,
|
|
directive_id: str,
|
|
name: str | None = None,
|
|
content: str | None = None,
|
|
priority: int | None = None,
|
|
is_active: bool | None = None,
|
|
tags: list[str] | None = None,
|
|
):
|
|
"""
|
|
Update a directive.
|
|
|
|
Args:
|
|
bank_id: The memory bank ID
|
|
directive_id: The directive ID
|
|
name: Optional new name
|
|
content: Optional new content
|
|
priority: Optional new priority
|
|
is_active: Optional new active status
|
|
tags: Optional new tags
|
|
|
|
Returns:
|
|
DirectiveResponse
|
|
"""
|
|
from hindsight_client_api.models import update_directive_request
|
|
|
|
request_obj = update_directive_request.UpdateDirectiveRequest(
|
|
name=name,
|
|
content=content,
|
|
priority=priority,
|
|
is_active=is_active,
|
|
tags=tags,
|
|
)
|
|
|
|
return _run_async(self._directives_api.update_directive(bank_id, directive_id, request_obj, _request_timeout=self._timeout))
|
|
|
|
def delete_directive(self, bank_id: str, directive_id: str):
|
|
"""
|
|
Delete a directive.
|
|
|
|
Args:
|
|
bank_id: The memory bank ID
|
|
directive_id: The directive ID
|
|
"""
|
|
return _run_async(self._directives_api.delete_directive(bank_id, directive_id, _request_timeout=self._timeout))
|
|
|
|
def get_bank_config(self, bank_id: str) -> dict[str, Any]:
|
|
"""
|
|
Get the resolved configuration for a bank, including any bank-level overrides.
|
|
|
|
Can be disabled on the server by setting ``HINDSIGHT_API_ENABLE_BANK_CONFIG_API=false``.
|
|
|
|
Args:
|
|
bank_id: The memory bank ID
|
|
|
|
Returns:
|
|
dict with ``bank_id``, ``config`` (fully resolved), and ``overrides`` (bank-level only)
|
|
"""
|
|
return _run_async(self._aget_bank_config(bank_id))
|
|
|
|
async def _aget_bank_config(self, bank_id: str) -> dict[str, Any]:
|
|
import aiohttp
|
|
|
|
url = f"{self._base_url}/v1/default/banks/{bank_id}/config"
|
|
headers = {"Authorization": f"Bearer {self._api_key}"} if self._api_key else {}
|
|
async with aiohttp.ClientSession() as session:
|
|
async with session.get(url, headers=headers, timeout=aiohttp.ClientTimeout(total=self._timeout)) as resp:
|
|
resp.raise_for_status()
|
|
return await resp.json()
|
|
|
|
def update_bank_config(
|
|
self,
|
|
bank_id: str,
|
|
*,
|
|
reflect_mission: str | None = None,
|
|
retain_mission: str | None = None,
|
|
retain_extraction_mode: str | None = None,
|
|
retain_custom_instructions: str | None = None,
|
|
retain_chunk_size: int | None = None,
|
|
enable_observations: bool | None = None,
|
|
observations_mission: str | None = None,
|
|
disposition_skepticism: int | None = None,
|
|
disposition_literalism: int | None = None,
|
|
disposition_empathy: int | None = None,
|
|
) -> dict[str, Any]:
|
|
"""
|
|
Update configuration overrides for a bank.
|
|
|
|
Can be disabled on the server by setting ``HINDSIGHT_API_ENABLE_BANK_CONFIG_API=false``.
|
|
|
|
Args:
|
|
bank_id: The memory bank ID
|
|
reflect_mission: Identity and reasoning framing for reflect().
|
|
retain_mission: Steers what gets extracted during retain().
|
|
retain_extraction_mode: Fact extraction mode: 'concise', 'verbose', or 'custom'.
|
|
retain_custom_instructions: Custom extraction prompt (only active when mode is 'custom').
|
|
retain_chunk_size: Maximum token size for each content chunk during retain.
|
|
enable_observations: Toggle automatic observation consolidation after retain().
|
|
observations_mission: Controls what gets synthesised into observations.
|
|
disposition_skepticism: How skeptical vs trusting (1=trusting, 5=skeptical).
|
|
disposition_literalism: How literally to interpret information (1=flexible, 5=literal).
|
|
disposition_empathy: How much to consider emotional context (1=detached, 5=empathetic).
|
|
|
|
Returns:
|
|
dict with ``bank_id``, ``config`` (fully resolved), and ``overrides`` (bank-level only)
|
|
"""
|
|
updates = {
|
|
k: v
|
|
for k, v in {
|
|
"reflect_mission": reflect_mission,
|
|
"retain_mission": retain_mission,
|
|
"retain_extraction_mode": retain_extraction_mode,
|
|
"retain_custom_instructions": retain_custom_instructions,
|
|
"retain_chunk_size": retain_chunk_size,
|
|
"enable_observations": enable_observations,
|
|
"observations_mission": observations_mission,
|
|
"disposition_skepticism": disposition_skepticism,
|
|
"disposition_literalism": disposition_literalism,
|
|
"disposition_empathy": disposition_empathy,
|
|
}.items()
|
|
if v is not None
|
|
}
|
|
return _run_async(self._aupdate_bank_config(bank_id, updates))
|
|
|
|
async def _aupdate_bank_config(self, bank_id: str, updates: dict[str, Any]) -> dict[str, Any]:
|
|
import aiohttp
|
|
|
|
url = f"{self._base_url}/v1/default/banks/{bank_id}/config"
|
|
headers = {"Authorization": f"Bearer {self._api_key}"} if self._api_key else {}
|
|
async with aiohttp.ClientSession() as session:
|
|
async with session.patch(
|
|
url, json={"updates": updates}, headers=headers, timeout=aiohttp.ClientTimeout(total=self._timeout)
|
|
) as resp:
|
|
resp.raise_for_status()
|
|
return await resp.json()
|
|
|
|
def reset_bank_config(self, bank_id: str) -> dict[str, Any]:
|
|
"""
|
|
Reset all bank-level configuration overrides, reverting to server defaults.
|
|
|
|
Can be disabled on the server by setting ``HINDSIGHT_API_ENABLE_BANK_CONFIG_API=false``.
|
|
|
|
Args:
|
|
bank_id: The memory bank ID
|
|
|
|
Returns:
|
|
dict with ``bank_id``, ``config`` (fully resolved), and ``overrides`` (now empty)
|
|
"""
|
|
return _run_async(self._areset_bank_config(bank_id))
|
|
|
|
async def _areset_bank_config(self, bank_id: str) -> dict[str, Any]:
|
|
import aiohttp
|
|
|
|
url = f"{self._base_url}/v1/default/banks/{bank_id}/config"
|
|
headers = {"Authorization": f"Bearer {self._api_key}"} if self._api_key else {}
|
|
async with aiohttp.ClientSession() as session:
|
|
async with session.delete(url, headers=headers, timeout=aiohttp.ClientTimeout(total=self._timeout)) as resp:
|
|
resp.raise_for_status()
|
|
return await resp.json()
|
|
|
|
def delete_bank(self, bank_id: str):
|
|
"""
|
|
Delete a memory bank.
|
|
|
|
Args:
|
|
bank_id: The memory bank ID
|
|
"""
|
|
return _run_async(self._banks_api.delete_bank(bank_id, _request_timeout=self._timeout))
|
|
|
|
async def adelete_bank(self, bank_id: str):
|
|
"""
|
|
Delete a memory bank (async).
|
|
|
|
Args:
|
|
bank_id: The memory bank ID
|
|
"""
|
|
return await self._banks_api.delete_bank(bank_id, _request_timeout=self._timeout)
|