e4f8a157c2
* 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
1427 lines
69 KiB
Python
1427 lines
69 KiB
Python
"""
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Centralized configuration for Hindsight API.
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All environment variables and their defaults are defined here.
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"""
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import json
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import logging
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import os
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import sys
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from dataclasses import dataclass, field, fields
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from datetime import datetime, timezone
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from typing import Any
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from dotenv import find_dotenv, load_dotenv
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# Load .env file, searching current and parent directories (overrides existing env vars)
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load_dotenv(find_dotenv(usecwd=True), override=True)
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logger = logging.getLogger(__name__)
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class ConfigFieldAccessError(AttributeError):
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"""Raised when trying to access a bank-configurable field from global config."""
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pass
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class StaticConfigProxy:
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"""
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Proxy that wraps HindsightConfig and only allows access to static (non-configurable) fields.
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Raises ConfigFieldAccessError when trying to access configurable fields that vary per-bank.
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Forces developers to use get_resolved_config(bank_id, context) for bank-specific settings.
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"""
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def __init__(self, config: "HindsightConfig"):
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object.__setattr__(self, "_config", config)
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object.__setattr__(self, "_configurable_fields", HindsightConfig.get_configurable_fields())
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def __getattribute__(self, name: str):
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if name.startswith("_"):
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return object.__getattribute__(self, name)
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configurable_fields = object.__getattribute__(self, "_configurable_fields")
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if name in configurable_fields:
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raise ConfigFieldAccessError(
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f"Field '{name}' is bank-configurable and cannot be accessed from global config. "
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f"Use ConfigResolver.resolve_full_config(bank_id, context) to get bank-specific config. "
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f"This prevents accidentally using global defaults when bank-specific overrides exist."
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)
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config = object.__getattribute__(self, "_config")
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return getattr(config, name)
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def __setattr__(self, name: str, value):
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raise AttributeError("Config is read-only. Modifications must go through ConfigResolver.")
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# Configuration field markers for hierarchical configuration
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def hierarchical(default_value):
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"""
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Mark a config field as hierarchical (can be overridden per-tenant/bank).
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Hierarchical fields can be customized at the tenant or bank level via database
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configuration. Examples: LLM settings, retention parameters, retrieval settings.
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"""
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return field(default=default_value, metadata={"hierarchical": True})
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def static(default_value):
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"""
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Mark a config field as static (server-level only, cannot be overridden).
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Static fields are infrastructure-level settings that affect the entire server
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and cannot vary per tenant or bank. Examples: database URL, API port, worker settings.
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"""
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return field(default=default_value, metadata={"hierarchical": False})
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# Configuration key normalization utilities
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def normalize_config_key(key: str) -> str:
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"""
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Convert environment variable format to Python field name format.
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Examples:
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HINDSIGHT_API_LLM_PROVIDER -> llm_provider
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LLM_MODEL -> llm_model
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llm_model -> llm_model (already normalized)
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Args:
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key: Environment variable name or Python field name
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Returns:
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Normalized Python field name (lowercase snake_case)
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"""
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if key.startswith("HINDSIGHT_API_"):
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key = key[len("HINDSIGHT_API_") :]
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return key.lower()
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def normalize_config_dict(config: dict[str, Any]) -> dict[str, Any]:
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"""
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Normalize all keys in a config dict to Python field names.
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Allows users to provide config overrides in either format:
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- Python field format: {"llm_provider": "openai"}
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- Env var format: {"HINDSIGHT_API_LLM_PROVIDER": "openai"}
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Args:
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config: Dict with env var or Python field names as keys
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Returns:
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Dict with all keys normalized to Python field names
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"""
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return {normalize_config_key(k): v for k, v in config.items()}
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# Environment variable names
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ENV_DATABASE_URL = "HINDSIGHT_API_DATABASE_URL"
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ENV_DATABASE_SCHEMA = "HINDSIGHT_API_DATABASE_SCHEMA"
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ENV_LLM_PROVIDER = "HINDSIGHT_API_LLM_PROVIDER"
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ENV_LLM_API_KEY = "HINDSIGHT_API_LLM_API_KEY"
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ENV_LLM_MODEL = "HINDSIGHT_API_LLM_MODEL"
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ENV_LLM_BASE_URL = "HINDSIGHT_API_LLM_BASE_URL"
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ENV_LLM_MAX_CONCURRENT = "HINDSIGHT_API_LLM_MAX_CONCURRENT"
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ENV_LLM_MAX_RETRIES = "HINDSIGHT_API_LLM_MAX_RETRIES"
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ENV_LLM_INITIAL_BACKOFF = "HINDSIGHT_API_LLM_INITIAL_BACKOFF"
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ENV_LLM_MAX_BACKOFF = "HINDSIGHT_API_LLM_MAX_BACKOFF"
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ENV_LLM_TIMEOUT = "HINDSIGHT_API_LLM_TIMEOUT"
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ENV_LLM_GROQ_SERVICE_TIER = "HINDSIGHT_API_LLM_GROQ_SERVICE_TIER"
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ENV_LLM_OPENAI_SERVICE_TIER = "HINDSIGHT_API_LLM_OPENAI_SERVICE_TIER"
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# Defaults for service tiers
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DEFAULT_LLM_GROQ_SERVICE_TIER = "auto" # "on_demand", "flex", or "auto"
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DEFAULT_LLM_OPENAI_SERVICE_TIER = None # None (default) or "flex" (50% cheaper)
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# Per-operation LLM configuration (optional, falls back to global LLM config)
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ENV_RETAIN_LLM_PROVIDER = "HINDSIGHT_API_RETAIN_LLM_PROVIDER"
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ENV_RETAIN_LLM_API_KEY = "HINDSIGHT_API_RETAIN_LLM_API_KEY"
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ENV_RETAIN_LLM_MODEL = "HINDSIGHT_API_RETAIN_LLM_MODEL"
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ENV_RETAIN_LLM_BASE_URL = "HINDSIGHT_API_RETAIN_LLM_BASE_URL"
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ENV_RETAIN_LLM_MAX_CONCURRENT = "HINDSIGHT_API_RETAIN_LLM_MAX_CONCURRENT"
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ENV_RETAIN_LLM_MAX_RETRIES = "HINDSIGHT_API_RETAIN_LLM_MAX_RETRIES"
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ENV_RETAIN_LLM_INITIAL_BACKOFF = "HINDSIGHT_API_RETAIN_LLM_INITIAL_BACKOFF"
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ENV_RETAIN_LLM_MAX_BACKOFF = "HINDSIGHT_API_RETAIN_LLM_MAX_BACKOFF"
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ENV_RETAIN_LLM_TIMEOUT = "HINDSIGHT_API_RETAIN_LLM_TIMEOUT"
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ENV_REFLECT_LLM_PROVIDER = "HINDSIGHT_API_REFLECT_LLM_PROVIDER"
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ENV_REFLECT_LLM_API_KEY = "HINDSIGHT_API_REFLECT_LLM_API_KEY"
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ENV_REFLECT_LLM_MODEL = "HINDSIGHT_API_REFLECT_LLM_MODEL"
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ENV_REFLECT_LLM_BASE_URL = "HINDSIGHT_API_REFLECT_LLM_BASE_URL"
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ENV_REFLECT_LLM_MAX_CONCURRENT = "HINDSIGHT_API_REFLECT_LLM_MAX_CONCURRENT"
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ENV_REFLECT_LLM_MAX_RETRIES = "HINDSIGHT_API_REFLECT_LLM_MAX_RETRIES"
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ENV_REFLECT_LLM_INITIAL_BACKOFF = "HINDSIGHT_API_REFLECT_LLM_INITIAL_BACKOFF"
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ENV_REFLECT_LLM_MAX_BACKOFF = "HINDSIGHT_API_REFLECT_LLM_MAX_BACKOFF"
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ENV_REFLECT_LLM_TIMEOUT = "HINDSIGHT_API_REFLECT_LLM_TIMEOUT"
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ENV_CONSOLIDATION_LLM_PROVIDER = "HINDSIGHT_API_CONSOLIDATION_LLM_PROVIDER"
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ENV_CONSOLIDATION_LLM_API_KEY = "HINDSIGHT_API_CONSOLIDATION_LLM_API_KEY"
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ENV_CONSOLIDATION_LLM_MODEL = "HINDSIGHT_API_CONSOLIDATION_LLM_MODEL"
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ENV_CONSOLIDATION_LLM_BASE_URL = "HINDSIGHT_API_CONSOLIDATION_LLM_BASE_URL"
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ENV_CONSOLIDATION_LLM_MAX_CONCURRENT = "HINDSIGHT_API_CONSOLIDATION_LLM_MAX_CONCURRENT"
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ENV_CONSOLIDATION_LLM_MAX_RETRIES = "HINDSIGHT_API_CONSOLIDATION_LLM_MAX_RETRIES"
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ENV_CONSOLIDATION_LLM_INITIAL_BACKOFF = "HINDSIGHT_API_CONSOLIDATION_LLM_INITIAL_BACKOFF"
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ENV_CONSOLIDATION_LLM_MAX_BACKOFF = "HINDSIGHT_API_CONSOLIDATION_LLM_MAX_BACKOFF"
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ENV_CONSOLIDATION_LLM_TIMEOUT = "HINDSIGHT_API_CONSOLIDATION_LLM_TIMEOUT"
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ENV_EMBEDDINGS_PROVIDER = "HINDSIGHT_API_EMBEDDINGS_PROVIDER"
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ENV_EMBEDDINGS_LOCAL_MODEL = "HINDSIGHT_API_EMBEDDINGS_LOCAL_MODEL"
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ENV_EMBEDDINGS_LOCAL_FORCE_CPU = "HINDSIGHT_API_EMBEDDINGS_LOCAL_FORCE_CPU"
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ENV_EMBEDDINGS_LOCAL_TRUST_REMOTE_CODE = "HINDSIGHT_API_EMBEDDINGS_LOCAL_TRUST_REMOTE_CODE"
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ENV_EMBEDDINGS_TEI_URL = "HINDSIGHT_API_EMBEDDINGS_TEI_URL"
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ENV_EMBEDDINGS_OPENAI_API_KEY = "HINDSIGHT_API_EMBEDDINGS_OPENAI_API_KEY"
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ENV_EMBEDDINGS_OPENAI_MODEL = "HINDSIGHT_API_EMBEDDINGS_OPENAI_MODEL"
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ENV_EMBEDDINGS_OPENAI_BASE_URL = "HINDSIGHT_API_EMBEDDINGS_OPENAI_BASE_URL"
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# Cohere configuration (separate for embeddings and reranker)
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ENV_EMBEDDINGS_COHERE_API_KEY = "HINDSIGHT_API_EMBEDDINGS_COHERE_API_KEY"
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ENV_EMBEDDINGS_COHERE_MODEL = "HINDSIGHT_API_EMBEDDINGS_COHERE_MODEL"
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ENV_EMBEDDINGS_COHERE_BASE_URL = "HINDSIGHT_API_EMBEDDINGS_COHERE_BASE_URL"
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ENV_RERANKER_COHERE_API_KEY = "HINDSIGHT_API_RERANKER_COHERE_API_KEY"
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ENV_RERANKER_COHERE_MODEL = "HINDSIGHT_API_RERANKER_COHERE_MODEL"
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ENV_RERANKER_COHERE_BASE_URL = "HINDSIGHT_API_RERANKER_COHERE_BASE_URL"
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# Deprecated: Legacy shared Cohere API key (for backward compatibility)
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ENV_COHERE_API_KEY = "HINDSIGHT_API_COHERE_API_KEY"
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# LiteLLM configuration (separate for embeddings and reranker)
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ENV_EMBEDDINGS_LITELLM_API_BASE = "HINDSIGHT_API_EMBEDDINGS_LITELLM_API_BASE"
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ENV_EMBEDDINGS_LITELLM_API_KEY = "HINDSIGHT_API_EMBEDDINGS_LITELLM_API_KEY"
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ENV_EMBEDDINGS_LITELLM_MODEL = "HINDSIGHT_API_EMBEDDINGS_LITELLM_MODEL"
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ENV_RERANKER_LITELLM_API_BASE = "HINDSIGHT_API_RERANKER_LITELLM_API_BASE"
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ENV_RERANKER_LITELLM_API_KEY = "HINDSIGHT_API_RERANKER_LITELLM_API_KEY"
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ENV_RERANKER_LITELLM_MODEL = "HINDSIGHT_API_RERANKER_LITELLM_MODEL"
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ENV_RERANKER_LITELLM_MAX_TOKENS_PER_DOC = "HINDSIGHT_API_RERANKER_LITELLM_MAX_TOKENS_PER_DOC"
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# LiteLLM SDK configuration (direct API access, no proxy needed)
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ENV_EMBEDDINGS_LITELLM_SDK_API_KEY = "HINDSIGHT_API_EMBEDDINGS_LITELLM_SDK_API_KEY"
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ENV_EMBEDDINGS_LITELLM_SDK_MODEL = "HINDSIGHT_API_EMBEDDINGS_LITELLM_SDK_MODEL"
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ENV_EMBEDDINGS_LITELLM_SDK_API_BASE = "HINDSIGHT_API_EMBEDDINGS_LITELLM_SDK_API_BASE"
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ENV_RERANKER_LITELLM_SDK_API_KEY = "HINDSIGHT_API_RERANKER_LITELLM_SDK_API_KEY"
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ENV_RERANKER_LITELLM_SDK_MODEL = "HINDSIGHT_API_RERANKER_LITELLM_SDK_MODEL"
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ENV_RERANKER_LITELLM_SDK_API_BASE = "HINDSIGHT_API_RERANKER_LITELLM_SDK_API_BASE"
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# Deprecated: Legacy shared LiteLLM config (for backward compatibility)
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ENV_LITELLM_API_BASE = "HINDSIGHT_API_LITELLM_API_BASE"
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ENV_LITELLM_API_KEY = "HINDSIGHT_API_LITELLM_API_KEY"
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ENV_RERANKER_PROVIDER = "HINDSIGHT_API_RERANKER_PROVIDER"
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ENV_RERANKER_LOCAL_MODEL = "HINDSIGHT_API_RERANKER_LOCAL_MODEL"
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ENV_RERANKER_LOCAL_FORCE_CPU = "HINDSIGHT_API_RERANKER_LOCAL_FORCE_CPU"
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ENV_RERANKER_LOCAL_MAX_CONCURRENT = "HINDSIGHT_API_RERANKER_LOCAL_MAX_CONCURRENT"
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ENV_RERANKER_LOCAL_TRUST_REMOTE_CODE = "HINDSIGHT_API_RERANKER_LOCAL_TRUST_REMOTE_CODE"
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ENV_RERANKER_LOCAL_FP16 = "HINDSIGHT_API_RERANKER_LOCAL_FP16"
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ENV_RERANKER_LOCAL_BUCKET_BATCHING = "HINDSIGHT_API_RERANKER_LOCAL_BUCKET_BATCHING"
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ENV_RERANKER_LOCAL_BATCH_SIZE = "HINDSIGHT_API_RERANKER_LOCAL_BATCH_SIZE"
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ENV_RERANKER_TEI_URL = "HINDSIGHT_API_RERANKER_TEI_URL"
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ENV_RERANKER_TEI_BATCH_SIZE = "HINDSIGHT_API_RERANKER_TEI_BATCH_SIZE"
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ENV_RERANKER_TEI_MAX_CONCURRENT = "HINDSIGHT_API_RERANKER_TEI_MAX_CONCURRENT"
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ENV_RERANKER_MAX_CANDIDATES = "HINDSIGHT_API_RERANKER_MAX_CANDIDATES"
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ENV_RERANKER_FLASHRANK_MODEL = "HINDSIGHT_API_RERANKER_FLASHRANK_MODEL"
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ENV_RERANKER_FLASHRANK_CACHE_DIR = "HINDSIGHT_API_RERANKER_FLASHRANK_CACHE_DIR"
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# ZeroEntropy configuration (reranker only)
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ENV_RERANKER_ZEROENTROPY_API_KEY = "HINDSIGHT_API_RERANKER_ZEROENTROPY_API_KEY"
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ENV_RERANKER_ZEROENTROPY_MODEL = "HINDSIGHT_API_RERANKER_ZEROENTROPY_MODEL"
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ENV_VECTOR_EXTENSION = "HINDSIGHT_API_VECTOR_EXTENSION"
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ENV_TEXT_SEARCH_EXTENSION = "HINDSIGHT_API_TEXT_SEARCH_EXTENSION"
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ENV_HOST = "HINDSIGHT_API_HOST"
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ENV_PORT = "HINDSIGHT_API_PORT"
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ENV_BASE_PATH = "HINDSIGHT_API_BASE_PATH"
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ENV_LOG_LEVEL = "HINDSIGHT_API_LOG_LEVEL"
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ENV_LOG_FORMAT = "HINDSIGHT_API_LOG_FORMAT"
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ENV_WORKERS = "HINDSIGHT_API_WORKERS"
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ENV_MCP_ENABLED = "HINDSIGHT_API_MCP_ENABLED"
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ENV_MCP_ENABLED_TOOLS = "HINDSIGHT_API_MCP_ENABLED_TOOLS"
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ENV_ENABLE_BANK_CONFIG_API = "HINDSIGHT_API_ENABLE_BANK_CONFIG_API"
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ENV_GRAPH_RETRIEVER = "HINDSIGHT_API_GRAPH_RETRIEVER"
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ENV_MPFP_TOP_K_NEIGHBORS = "HINDSIGHT_API_MPFP_TOP_K_NEIGHBORS"
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ENV_RECALL_MAX_CONCURRENT = "HINDSIGHT_API_RECALL_MAX_CONCURRENT"
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ENV_RECALL_CONNECTION_BUDGET = "HINDSIGHT_API_RECALL_CONNECTION_BUDGET"
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ENV_RECALL_MAX_QUERY_TOKENS = "HINDSIGHT_API_RECALL_MAX_QUERY_TOKENS"
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ENV_MENTAL_MODEL_REFRESH_CONCURRENCY = "HINDSIGHT_API_MENTAL_MODEL_REFRESH_CONCURRENCY"
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# OpenTelemetry tracing configuration
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ENV_OTEL_TRACES_ENABLED = "HINDSIGHT_API_OTEL_TRACES_ENABLED"
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ENV_OTEL_EXPORTER_OTLP_ENDPOINT = "HINDSIGHT_API_OTEL_EXPORTER_OTLP_ENDPOINT"
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ENV_OTEL_EXPORTER_OTLP_HEADERS = "HINDSIGHT_API_OTEL_EXPORTER_OTLP_HEADERS"
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ENV_OTEL_SERVICE_NAME = "HINDSIGHT_API_OTEL_SERVICE_NAME"
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ENV_OTEL_DEPLOYMENT_ENVIRONMENT = "HINDSIGHT_API_OTEL_DEPLOYMENT_ENVIRONMENT"
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# Vertex AI configuration
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ENV_LLM_VERTEXAI_PROJECT_ID = "HINDSIGHT_API_LLM_VERTEXAI_PROJECT_ID"
|
|
ENV_LLM_VERTEXAI_REGION = "HINDSIGHT_API_LLM_VERTEXAI_REGION"
|
|
ENV_LLM_VERTEXAI_SERVICE_ACCOUNT_KEY = "HINDSIGHT_API_LLM_VERTEXAI_SERVICE_ACCOUNT_KEY"
|
|
|
|
# Gemini safety settings
|
|
ENV_LLM_GEMINI_SAFETY_SETTINGS = "HINDSIGHT_API_LLM_GEMINI_SAFETY_SETTINGS"
|
|
|
|
# Retain settings
|
|
ENV_RETAIN_MAX_COMPLETION_TOKENS = "HINDSIGHT_API_RETAIN_MAX_COMPLETION_TOKENS"
|
|
ENV_RETAIN_CHUNK_SIZE = "HINDSIGHT_API_RETAIN_CHUNK_SIZE"
|
|
ENV_RETAIN_EXTRACT_CAUSAL_LINKS = "HINDSIGHT_API_RETAIN_EXTRACT_CAUSAL_LINKS"
|
|
ENV_RETAIN_EXTRACTION_MODE = "HINDSIGHT_API_RETAIN_EXTRACTION_MODE"
|
|
ENV_RETAIN_MISSION = "HINDSIGHT_API_RETAIN_MISSION"
|
|
ENV_RETAIN_CUSTOM_INSTRUCTIONS = "HINDSIGHT_API_RETAIN_CUSTOM_INSTRUCTIONS"
|
|
ENV_RETAIN_DEFAULT_STRATEGY = "HINDSIGHT_API_RETAIN_DEFAULT_STRATEGY"
|
|
ENV_RETAIN_BATCH_TOKENS = "HINDSIGHT_API_RETAIN_BATCH_TOKENS"
|
|
ENV_RETAIN_ENTITY_LOOKUP = "HINDSIGHT_API_RETAIN_ENTITY_LOOKUP"
|
|
ENV_RETAIN_BATCH_ENABLED = "HINDSIGHT_API_RETAIN_BATCH_ENABLED"
|
|
ENV_RETAIN_BATCH_POLL_INTERVAL_SECONDS = "HINDSIGHT_API_RETAIN_BATCH_POLL_INTERVAL_SECONDS"
|
|
|
|
# File storage configuration
|
|
ENV_FILE_STORAGE_TYPE = "HINDSIGHT_API_FILE_STORAGE_TYPE"
|
|
ENV_FILE_STORAGE_S3_BUCKET = "HINDSIGHT_API_FILE_STORAGE_S3_BUCKET"
|
|
ENV_FILE_STORAGE_S3_REGION = "HINDSIGHT_API_FILE_STORAGE_S3_REGION"
|
|
ENV_FILE_STORAGE_S3_ENDPOINT = "HINDSIGHT_API_FILE_STORAGE_S3_ENDPOINT"
|
|
ENV_FILE_STORAGE_S3_ACCESS_KEY_ID = "HINDSIGHT_API_FILE_STORAGE_S3_ACCESS_KEY_ID"
|
|
ENV_FILE_STORAGE_S3_SECRET_ACCESS_KEY = "HINDSIGHT_API_FILE_STORAGE_S3_SECRET_ACCESS_KEY"
|
|
ENV_FILE_STORAGE_GCS_BUCKET = "HINDSIGHT_API_FILE_STORAGE_GCS_BUCKET"
|
|
ENV_FILE_STORAGE_GCS_SERVICE_ACCOUNT_KEY = "HINDSIGHT_API_FILE_STORAGE_GCS_SERVICE_ACCOUNT_KEY"
|
|
ENV_FILE_STORAGE_AZURE_CONTAINER = "HINDSIGHT_API_FILE_STORAGE_AZURE_CONTAINER"
|
|
ENV_FILE_STORAGE_AZURE_ACCOUNT_NAME = "HINDSIGHT_API_FILE_STORAGE_AZURE_ACCOUNT_NAME"
|
|
ENV_FILE_STORAGE_AZURE_ACCOUNT_KEY = "HINDSIGHT_API_FILE_STORAGE_AZURE_ACCOUNT_KEY"
|
|
ENV_FILE_PARSER = "HINDSIGHT_API_FILE_PARSER"
|
|
ENV_FILE_PARSER_ALLOWLIST = "HINDSIGHT_API_FILE_PARSER_ALLOWLIST"
|
|
ENV_FILE_PARSER_IRIS_TOKEN = "HINDSIGHT_API_FILE_PARSER_IRIS_TOKEN"
|
|
ENV_FILE_PARSER_IRIS_ORG_ID = "HINDSIGHT_API_FILE_PARSER_IRIS_ORG_ID"
|
|
ENV_FILE_CONVERSION_MAX_BATCH_SIZE_MB = "HINDSIGHT_API_FILE_CONVERSION_MAX_BATCH_SIZE_MB"
|
|
ENV_FILE_CONVERSION_MAX_BATCH_SIZE = "HINDSIGHT_API_FILE_CONVERSION_MAX_BATCH_SIZE"
|
|
ENV_ENABLE_FILE_UPLOAD_API = "HINDSIGHT_API_ENABLE_FILE_UPLOAD_API"
|
|
ENV_FILE_DELETE_AFTER_RETAIN = "HINDSIGHT_API_FILE_DELETE_AFTER_RETAIN"
|
|
|
|
# Observations settings (consolidated knowledge from facts)
|
|
ENV_ENABLE_OBSERVATIONS = "HINDSIGHT_API_ENABLE_OBSERVATIONS"
|
|
ENV_CONSOLIDATION_BATCH_SIZE = "HINDSIGHT_API_CONSOLIDATION_BATCH_SIZE"
|
|
ENV_CONSOLIDATION_LLM_BATCH_SIZE = "HINDSIGHT_API_CONSOLIDATION_LLM_BATCH_SIZE"
|
|
ENV_CONSOLIDATION_MAX_TOKENS = "HINDSIGHT_API_CONSOLIDATION_MAX_TOKENS"
|
|
ENV_CONSOLIDATION_SOURCE_FACTS_MAX_TOKENS = "HINDSIGHT_API_CONSOLIDATION_SOURCE_FACTS_MAX_TOKENS"
|
|
ENV_CONSOLIDATION_SOURCE_FACTS_MAX_TOKENS_PER_OBSERVATION = (
|
|
"HINDSIGHT_API_CONSOLIDATION_SOURCE_FACTS_MAX_TOKENS_PER_OBSERVATION"
|
|
)
|
|
ENV_OBSERVATIONS_MISSION = "HINDSIGHT_API_OBSERVATIONS_MISSION"
|
|
ENV_ENABLE_OBSERVATION_HISTORY = "HINDSIGHT_API_ENABLE_OBSERVATION_HISTORY"
|
|
ENV_ENABLE_MENTAL_MODEL_HISTORY = "HINDSIGHT_API_ENABLE_MENTAL_MODEL_HISTORY"
|
|
|
|
# Webhook configuration (global, static - server-level only)
|
|
ENV_WEBHOOK_URL = "HINDSIGHT_API_WEBHOOK_URL"
|
|
ENV_WEBHOOK_SECRET = "HINDSIGHT_API_WEBHOOK_SECRET"
|
|
ENV_WEBHOOK_EVENT_TYPES = "HINDSIGHT_API_WEBHOOK_EVENT_TYPES"
|
|
ENV_WEBHOOK_DELIVERY_POLL_INTERVAL_SECONDS = "HINDSIGHT_API_WEBHOOK_DELIVERY_POLL_INTERVAL_SECONDS"
|
|
|
|
# Optimization flags
|
|
ENV_SKIP_LLM_VERIFICATION = "HINDSIGHT_API_SKIP_LLM_VERIFICATION"
|
|
ENV_LAZY_RERANKER = "HINDSIGHT_API_LAZY_RERANKER"
|
|
|
|
# Database migrations
|
|
ENV_RUN_MIGRATIONS_ON_STARTUP = "HINDSIGHT_API_RUN_MIGRATIONS_ON_STARTUP"
|
|
|
|
# Database connection pool
|
|
ENV_DB_POOL_MIN_SIZE = "HINDSIGHT_API_DB_POOL_MIN_SIZE"
|
|
ENV_DB_POOL_MAX_SIZE = "HINDSIGHT_API_DB_POOL_MAX_SIZE"
|
|
ENV_DB_COMMAND_TIMEOUT = "HINDSIGHT_API_DB_COMMAND_TIMEOUT"
|
|
ENV_DB_ACQUIRE_TIMEOUT = "HINDSIGHT_API_DB_ACQUIRE_TIMEOUT"
|
|
|
|
# Worker configuration (distributed task processing)
|
|
ENV_WORKER_ENABLED = "HINDSIGHT_API_WORKER_ENABLED"
|
|
ENV_WORKER_ID = "HINDSIGHT_API_WORKER_ID"
|
|
ENV_WORKER_POLL_INTERVAL_MS = "HINDSIGHT_API_WORKER_POLL_INTERVAL_MS"
|
|
ENV_WORKER_MAX_RETRIES = "HINDSIGHT_API_WORKER_MAX_RETRIES"
|
|
ENV_WORKER_HTTP_PORT = "HINDSIGHT_API_WORKER_HTTP_PORT"
|
|
ENV_WORKER_MAX_SLOTS = "HINDSIGHT_API_WORKER_MAX_SLOTS"
|
|
ENV_WORKER_CONSOLIDATION_MAX_SLOTS = "HINDSIGHT_API_WORKER_CONSOLIDATION_MAX_SLOTS"
|
|
|
|
# Reflect agent settings
|
|
ENV_REFLECT_MAX_ITERATIONS = "HINDSIGHT_API_REFLECT_MAX_ITERATIONS"
|
|
ENV_REFLECT_MAX_CONTEXT_TOKENS = "HINDSIGHT_API_REFLECT_MAX_CONTEXT_TOKENS"
|
|
ENV_REFLECT_MISSION = "HINDSIGHT_API_REFLECT_MISSION"
|
|
|
|
# Disposition settings
|
|
ENV_DISPOSITION_SKEPTICISM = "HINDSIGHT_API_DISPOSITION_SKEPTICISM"
|
|
ENV_DISPOSITION_LITERALISM = "HINDSIGHT_API_DISPOSITION_LITERALISM"
|
|
ENV_DISPOSITION_EMPATHY = "HINDSIGHT_API_DISPOSITION_EMPATHY"
|
|
|
|
# Default values
|
|
DEFAULT_DATABASE_URL = "pg0"
|
|
DEFAULT_DATABASE_SCHEMA = "public"
|
|
DEFAULT_LLM_PROVIDER = "openai"
|
|
|
|
# Provider-specific default models
|
|
PROVIDER_DEFAULT_MODELS = {
|
|
"openai": "gpt-4o-mini",
|
|
"anthropic": "claude-haiku-4-5-20251001",
|
|
"gemini": "gemini-2.5-flash",
|
|
"groq": "openai/gpt-oss-120b",
|
|
"minimax": "MiniMax-M2.5",
|
|
"ollama": "gemma3:12b",
|
|
"lmstudio": "local-model",
|
|
"vertexai": "google/gemini-2.5-flash-lite",
|
|
"openai-codex": "gpt-5.2-codex",
|
|
"claude-code": "claude-sonnet-4-5-20250929",
|
|
"mock": "mock-model",
|
|
}
|
|
DEFAULT_LLM_MODEL = "gpt-4o-mini" # Fallback if provider not in table
|
|
DEFAULT_LLM_MAX_CONCURRENT = 32
|
|
DEFAULT_LLM_MAX_RETRIES = 10 # Max retry attempts for LLM API calls
|
|
DEFAULT_LLM_INITIAL_BACKOFF = 1.0 # Initial backoff in seconds for retry exponential backoff
|
|
DEFAULT_LLM_MAX_BACKOFF = 60.0 # Max backoff cap in seconds for retry exponential backoff
|
|
DEFAULT_LLM_TIMEOUT = 120.0 # seconds
|
|
|
|
# Vertex AI defaults
|
|
DEFAULT_LLM_VERTEXAI_PROJECT_ID = None # Required for Vertex AI
|
|
DEFAULT_LLM_VERTEXAI_REGION = "us-central1"
|
|
DEFAULT_LLM_VERTEXAI_SERVICE_ACCOUNT_KEY = None # Optional, uses ADC if not set
|
|
|
|
# Gemini safety settings defaults
|
|
DEFAULT_LLM_GEMINI_SAFETY_SETTINGS = None # None = use Gemini default safety settings
|
|
|
|
DEFAULT_EMBEDDINGS_PROVIDER = "local"
|
|
DEFAULT_EMBEDDINGS_LOCAL_MODEL = "BAAI/bge-small-en-v1.5"
|
|
DEFAULT_EMBEDDINGS_LOCAL_FORCE_CPU = False # Force CPU mode for local embeddings (avoids MPS/XPC issues on macOS)
|
|
DEFAULT_EMBEDDINGS_LOCAL_TRUST_REMOTE_CODE = False # Security: disabled by default, required for some models
|
|
DEFAULT_EMBEDDINGS_OPENAI_MODEL = "text-embedding-3-small"
|
|
DEFAULT_EMBEDDING_DIMENSION = 384
|
|
|
|
DEFAULT_RERANKER_PROVIDER = "local"
|
|
DEFAULT_RERANKER_LOCAL_MODEL = "cross-encoder/ms-marco-MiniLM-L-6-v2"
|
|
DEFAULT_RERANKER_LOCAL_FORCE_CPU = False # Force CPU mode for local reranker (avoids MPS/XPC issues on macOS)
|
|
DEFAULT_RERANKER_LOCAL_MAX_CONCURRENT = 4 # Limit concurrent CPU-bound reranking to prevent thrashing
|
|
DEFAULT_RERANKER_LOCAL_TRUST_REMOTE_CODE = (
|
|
False # Security: disabled by default, required for some models like jina-reranker-v2
|
|
)
|
|
DEFAULT_RERANKER_LOCAL_FP16 = False # FP16 inference: opt-in, faster on MPS/CUDA (not CPU)
|
|
DEFAULT_RERANKER_LOCAL_BUCKET_BATCHING = False # Length-sorted bucket batching: opt-in, 36-54% speedup
|
|
DEFAULT_RERANKER_LOCAL_BATCH_SIZE = 32 # Batch size for local reranker predict() calls
|
|
DEFAULT_RERANKER_TEI_BATCH_SIZE = 128
|
|
DEFAULT_RERANKER_TEI_MAX_CONCURRENT = 8
|
|
DEFAULT_RERANKER_MAX_CANDIDATES = 300
|
|
DEFAULT_RERANKER_FLASHRANK_MODEL = "ms-marco-MiniLM-L-12-v2" # Best balance of speed and quality
|
|
DEFAULT_RERANKER_FLASHRANK_CACHE_DIR = None # Use default cache directory
|
|
|
|
DEFAULT_EMBEDDINGS_COHERE_MODEL = "embed-english-v3.0"
|
|
DEFAULT_RERANKER_COHERE_MODEL = "rerank-english-v3.0"
|
|
|
|
DEFAULT_RERANKER_ZEROENTROPY_MODEL = "zerank-2"
|
|
|
|
# Vector extension (pgvector, vchord, or pgvectorscale)
|
|
DEFAULT_VECTOR_EXTENSION = "pgvector" # Options: "pgvector", "vchord", "pgvectorscale"
|
|
|
|
# Text search extension (native PostgreSQL, vchord BM25, or Timescale pg_textsearch)
|
|
DEFAULT_TEXT_SEARCH_EXTENSION = "native" # Options: "native", "vchord", "pg_textsearch"
|
|
|
|
# LiteLLM defaults
|
|
DEFAULT_LITELLM_API_BASE = "http://localhost:4000"
|
|
DEFAULT_EMBEDDINGS_LITELLM_MODEL = "text-embedding-3-small"
|
|
DEFAULT_RERANKER_LITELLM_MODEL = "cohere/rerank-english-v3.0"
|
|
DEFAULT_RERANKER_LITELLM_MAX_TOKENS_PER_DOC: int | None = None
|
|
|
|
# LiteLLM SDK defaults
|
|
DEFAULT_EMBEDDINGS_LITELLM_SDK_MODEL = "cohere/embed-english-v3.0"
|
|
DEFAULT_RERANKER_LITELLM_SDK_MODEL = "cohere/rerank-english-v3.0"
|
|
|
|
DEFAULT_HOST = "0.0.0.0"
|
|
DEFAULT_PORT = 8888
|
|
DEFAULT_BASE_PATH = "" # Empty string = root path
|
|
DEFAULT_LOG_LEVEL = "info"
|
|
DEFAULT_LOG_FORMAT = "text" # Options: "text", "json"
|
|
DEFAULT_WORKERS = 1
|
|
DEFAULT_MCP_ENABLED = True
|
|
DEFAULT_MCP_ENABLED_TOOLS: list[str] | None = None # None = all tools enabled
|
|
DEFAULT_ENABLE_BANK_CONFIG_API = True
|
|
DEFAULT_GRAPH_RETRIEVER = "link_expansion" # Options: "link_expansion", "mpfp", "bfs"
|
|
DEFAULT_MPFP_TOP_K_NEIGHBORS = 20 # Fan-out limit per node in MPFP graph traversal
|
|
DEFAULT_RECALL_MAX_CONCURRENT = 32 # Max concurrent recall operations per worker
|
|
DEFAULT_RECALL_CONNECTION_BUDGET = 4 # Max concurrent DB connections per recall operation
|
|
DEFAULT_RECALL_MAX_QUERY_TOKENS = 500 # Maximum tokens allowed in recall query
|
|
DEFAULT_MENTAL_MODEL_REFRESH_CONCURRENCY = 8 # Max concurrent mental model refreshes
|
|
|
|
# Retain settings
|
|
DEFAULT_RETAIN_MAX_COMPLETION_TOKENS = 64000 # Max tokens for fact extraction LLM call
|
|
DEFAULT_RETAIN_CHUNK_SIZE = 3000 # Max chars per chunk for fact extraction
|
|
DEFAULT_RETAIN_EXTRACT_CAUSAL_LINKS = True # Extract causal links between facts
|
|
DEFAULT_RETAIN_EXTRACTION_MODE = "concise" # Extraction mode: "concise", "verbose", or "custom"
|
|
RETAIN_EXTRACTION_MODES = ("concise", "verbose", "custom", "verbatim", "chunks") # Allowed extraction modes
|
|
DEFAULT_RETAIN_MISSION = None # Declarative spec of what to retain (injected into any extraction mode)
|
|
DEFAULT_RETAIN_CUSTOM_INSTRUCTIONS = None # Custom extraction guidelines (only used when mode="custom")
|
|
DEFAULT_RETAIN_DEFAULT_STRATEGY = None # Default strategy name (None = no strategy override)
|
|
DEFAULT_RETAIN_STRATEGIES: dict | None = None # Named retain strategies (dict of name → config overrides)
|
|
DEFAULT_RETAIN_BATCH_TOKENS = 10_000 # ~40KB of text # Max chars per sub-batch for async retain auto-splitting
|
|
DEFAULT_RETAIN_ENTITY_LOOKUP = "trigram" # "full" or "trigram"
|
|
DEFAULT_RETAIN_BATCH_ENABLED = False # Use LLM Batch API for fact extraction (only when async=True)
|
|
DEFAULT_RETAIN_BATCH_POLL_INTERVAL_SECONDS = 60 # Batch API polling interval in seconds
|
|
|
|
# File storage defaults
|
|
DEFAULT_FILE_STORAGE_TYPE = "native" # PostgreSQL BYTEA storage
|
|
DEFAULT_FILE_PARSER = "markitdown" # Default parser fallback chain (comma-separated, e.g. "iris,markitdown")
|
|
DEFAULT_FILE_PARSER_ALLOWLIST = None # Allowlist of parsers clients may request (None = all registered parsers)
|
|
DEFAULT_FILE_CONVERSION_MAX_BATCH_SIZE_MB = 100 # Max total batch size in MB (all files combined)
|
|
DEFAULT_FILE_CONVERSION_MAX_BATCH_SIZE = 10 # Max files per batch upload
|
|
DEFAULT_ENABLE_FILE_UPLOAD_API = True # Enable file upload endpoint
|
|
DEFAULT_FILE_DELETE_AFTER_RETAIN = True # Delete file bytes after retain (saves storage)
|
|
|
|
# Observations defaults (consolidated knowledge from facts)
|
|
DEFAULT_ENABLE_OBSERVATIONS = True # Observations enabled by default
|
|
DEFAULT_ENABLE_OBSERVATION_HISTORY = True # Observation history tracking enabled by default
|
|
DEFAULT_ENABLE_MENTAL_MODEL_HISTORY = True # Mental model history tracking enabled by default
|
|
DEFAULT_CONSOLIDATION_BATCH_SIZE = 50 # Memories to load per batch (internal memory optimization)
|
|
DEFAULT_CONSOLIDATION_LLM_BATCH_SIZE = 8 # Facts per LLM call (1 = no batching; >1 = batch mode)
|
|
DEFAULT_CONSOLIDATION_MAX_TOKENS = 512 # Max tokens for recall when finding related observations
|
|
DEFAULT_CONSOLIDATION_SOURCE_FACTS_MAX_TOKENS = (
|
|
-1
|
|
) # Total token budget for source facts in consolidation recall (-1 = unlimited)
|
|
DEFAULT_CONSOLIDATION_SOURCE_FACTS_MAX_TOKENS_PER_OBSERVATION = (
|
|
256 # Max tokens of source facts per observation in consolidation prompt (-1 = unlimited)
|
|
)
|
|
DEFAULT_OBSERVATIONS_MISSION = None # Declarative spec of what observations are for this bank
|
|
|
|
# Database migrations
|
|
DEFAULT_RUN_MIGRATIONS_ON_STARTUP = True
|
|
|
|
# Database connection pool
|
|
DEFAULT_DB_POOL_MIN_SIZE = 5
|
|
DEFAULT_DB_POOL_MAX_SIZE = 100
|
|
DEFAULT_DB_COMMAND_TIMEOUT = 60 # seconds
|
|
DEFAULT_DB_ACQUIRE_TIMEOUT = 30 # seconds
|
|
|
|
# Worker configuration (distributed task processing)
|
|
DEFAULT_WORKER_ENABLED = True # API runs worker by default (standalone mode)
|
|
DEFAULT_WORKER_ID = None # Will use hostname if not specified
|
|
DEFAULT_WORKER_POLL_INTERVAL_MS = 500 # Poll database every 500ms
|
|
DEFAULT_WORKER_MAX_RETRIES = 3 # Max retries before marking task failed
|
|
DEFAULT_WORKER_HTTP_PORT = 8889 # HTTP port for worker metrics/health
|
|
DEFAULT_WORKER_MAX_SLOTS = 10 # Total concurrent tasks per worker
|
|
DEFAULT_WORKER_CONSOLIDATION_MAX_SLOTS = 2 # Max concurrent consolidation tasks per worker
|
|
|
|
# Reflect agent settings
|
|
DEFAULT_REFLECT_MAX_ITERATIONS = 10 # Max tool call iterations before forcing response
|
|
DEFAULT_REFLECT_MAX_CONTEXT_TOKENS = 100_000 # Max accumulated context tokens before forcing final prompt
|
|
|
|
# Disposition defaults (None = not set, fall back to bank DB value or 3)
|
|
DEFAULT_DISPOSITION_SKEPTICISM = None
|
|
DEFAULT_DISPOSITION_LITERALISM = None
|
|
DEFAULT_DISPOSITION_EMPATHY = None
|
|
|
|
# OpenTelemetry tracing configuration
|
|
DEFAULT_OTEL_TRACES_ENABLED = False # Disabled by default for backward compatibility
|
|
DEFAULT_OTEL_SERVICE_NAME = "hindsight-api"
|
|
DEFAULT_OTEL_DEPLOYMENT_ENVIRONMENT = "development"
|
|
|
|
# Default MCP tool descriptions (can be customized via env vars)
|
|
DEFAULT_MCP_RETAIN_DESCRIPTION = """Store important information to long-term memory.
|
|
|
|
Use this tool PROACTIVELY whenever the user shares:
|
|
- Personal facts, preferences, or interests
|
|
- Important events or milestones
|
|
- User history, experiences, or background
|
|
- Decisions, opinions, or stated preferences
|
|
- Goals, plans, or future intentions
|
|
- Relationships or people mentioned
|
|
- Work context, projects, or responsibilities"""
|
|
|
|
DEFAULT_MCP_RECALL_DESCRIPTION = """Search memories to provide personalized, context-aware responses.
|
|
|
|
Use this tool PROACTIVELY to:
|
|
- Check user's preferences before making suggestions
|
|
- Recall user's history to provide continuity
|
|
- Remember user's goals and context
|
|
- Personalize responses based on past interactions"""
|
|
|
|
# Default embedding dimension (used by initial migration, adjusted at runtime)
|
|
EMBEDDING_DIMENSION = DEFAULT_EMBEDDING_DIMENSION
|
|
|
|
# Webhook configuration defaults
|
|
DEFAULT_WEBHOOK_URL = None # None = no global webhook configured
|
|
DEFAULT_WEBHOOK_SECRET = None # None = no signing
|
|
DEFAULT_WEBHOOK_EVENT_TYPES = "consolidation.completed" # Comma-separated; default = all supported events
|
|
DEFAULT_WEBHOOK_DELIVERY_POLL_INTERVAL_SECONDS = 30 # How often to poll for pending deliveries
|
|
|
|
|
|
class JsonFormatter(logging.Formatter):
|
|
"""JSON formatter for structured logging.
|
|
|
|
Outputs logs in JSON format with a 'severity' field that cloud logging
|
|
systems (GCP, AWS CloudWatch, etc.) can parse to correctly categorize log levels.
|
|
"""
|
|
|
|
SEVERITY_MAP = {
|
|
logging.DEBUG: "DEBUG",
|
|
logging.INFO: "INFO",
|
|
logging.WARNING: "WARNING",
|
|
logging.ERROR: "ERROR",
|
|
logging.CRITICAL: "CRITICAL",
|
|
}
|
|
|
|
def format(self, record: logging.LogRecord) -> str:
|
|
log_entry = {
|
|
"severity": self.SEVERITY_MAP.get(record.levelno, "DEFAULT"),
|
|
"message": record.getMessage(),
|
|
"timestamp": datetime.now(timezone.utc).isoformat(),
|
|
"logger": record.name,
|
|
}
|
|
|
|
# Add exception info if present
|
|
if record.exc_info:
|
|
log_entry["exception"] = self.formatException(record.exc_info)
|
|
|
|
return json.dumps(log_entry)
|
|
|
|
|
|
def _parse_str_list(value: str) -> list[str]:
|
|
"""Parse a comma-separated string into a non-empty list of stripped tokens."""
|
|
return [v.strip() for v in value.split(",") if v.strip()]
|
|
|
|
|
|
def _validate_extraction_mode(mode: str) -> str:
|
|
"""Validate and normalize extraction mode."""
|
|
mode_lower = mode.lower()
|
|
if mode_lower not in RETAIN_EXTRACTION_MODES:
|
|
logger.warning(
|
|
f"Invalid extraction mode '{mode}', must be one of {RETAIN_EXTRACTION_MODES}. "
|
|
f"Defaulting to '{DEFAULT_RETAIN_EXTRACTION_MODE}'."
|
|
)
|
|
return DEFAULT_RETAIN_EXTRACTION_MODE
|
|
return mode_lower
|
|
|
|
|
|
def _get_default_model_for_provider(provider: str) -> str:
|
|
"""Get the default model for a given provider."""
|
|
return PROVIDER_DEFAULT_MODELS.get(provider.lower(), DEFAULT_LLM_MODEL)
|
|
|
|
|
|
@dataclass
|
|
class HindsightConfig:
|
|
"""Configuration container for Hindsight API."""
|
|
|
|
# Database
|
|
database_url: str
|
|
database_schema: str
|
|
vector_extension: str # "pgvector" or "vchord"
|
|
text_search_extension: str # "native" or "vchord"
|
|
|
|
# LLM (default, used as fallback for per-operation config)
|
|
llm_provider: str
|
|
llm_api_key: str | None
|
|
llm_model: str
|
|
llm_base_url: str | None
|
|
llm_max_concurrent: int
|
|
llm_max_retries: int
|
|
llm_initial_backoff: float
|
|
llm_max_backoff: float
|
|
llm_timeout: float
|
|
llm_groq_service_tier: str # Groq: "on_demand", "flex", or "auto"
|
|
llm_openai_service_tier: str | None # OpenAI: None (default) or "flex" (50% cheaper)
|
|
|
|
# Vertex AI configuration
|
|
llm_vertexai_project_id: str | None
|
|
llm_vertexai_region: str
|
|
llm_vertexai_service_account_key: str | None
|
|
|
|
# Gemini safety settings (None = use Gemini defaults; list of dicts with category/threshold)
|
|
llm_gemini_safety_settings: list | None
|
|
|
|
# Per-operation LLM configuration (None = use default LLM config)
|
|
retain_llm_provider: str | None
|
|
retain_llm_api_key: str | None
|
|
retain_llm_model: str | None
|
|
retain_llm_base_url: str | None
|
|
retain_llm_max_concurrent: int | None
|
|
retain_llm_max_retries: int | None
|
|
retain_llm_initial_backoff: float | None
|
|
retain_llm_max_backoff: float | None
|
|
retain_llm_timeout: float | None
|
|
|
|
reflect_llm_provider: str | None
|
|
reflect_llm_api_key: str | None
|
|
reflect_llm_model: str | None
|
|
reflect_llm_base_url: str | None
|
|
reflect_llm_max_concurrent: int | None
|
|
reflect_llm_max_retries: int | None
|
|
reflect_llm_initial_backoff: float | None
|
|
reflect_llm_max_backoff: float | None
|
|
reflect_llm_timeout: float | None
|
|
|
|
consolidation_llm_provider: str | None
|
|
consolidation_llm_api_key: str | None
|
|
consolidation_llm_model: str | None
|
|
consolidation_llm_base_url: str | None
|
|
consolidation_llm_max_concurrent: int | None
|
|
consolidation_llm_max_retries: int | None
|
|
consolidation_llm_initial_backoff: float | None
|
|
consolidation_llm_max_backoff: float | None
|
|
consolidation_llm_timeout: float | None
|
|
|
|
# Embeddings
|
|
embeddings_provider: str
|
|
embeddings_local_model: str
|
|
embeddings_local_force_cpu: bool
|
|
embeddings_local_trust_remote_code: bool
|
|
embeddings_tei_url: str | None
|
|
embeddings_openai_base_url: str | None
|
|
embeddings_cohere_api_key: str | None
|
|
embeddings_cohere_model: str
|
|
embeddings_cohere_base_url: str | None
|
|
embeddings_litellm_api_base: str
|
|
embeddings_litellm_api_key: str | None
|
|
embeddings_litellm_model: str
|
|
embeddings_litellm_sdk_api_key: str | None
|
|
embeddings_litellm_sdk_model: str
|
|
embeddings_litellm_sdk_api_base: str | None
|
|
|
|
# Reranker
|
|
reranker_provider: str
|
|
reranker_local_model: str
|
|
reranker_local_force_cpu: bool
|
|
reranker_local_max_concurrent: int
|
|
reranker_local_trust_remote_code: bool
|
|
reranker_local_fp16: bool
|
|
reranker_local_bucket_batching: bool
|
|
reranker_local_batch_size: int
|
|
reranker_tei_url: str | None
|
|
reranker_tei_batch_size: int
|
|
reranker_tei_max_concurrent: int
|
|
reranker_max_candidates: int
|
|
reranker_cohere_api_key: str | None
|
|
reranker_cohere_model: str
|
|
reranker_cohere_base_url: str | None
|
|
reranker_litellm_api_base: str
|
|
reranker_litellm_api_key: str | None
|
|
reranker_litellm_model: str
|
|
reranker_litellm_max_tokens_per_doc: int | None
|
|
reranker_litellm_sdk_api_key: str | None
|
|
reranker_litellm_sdk_model: str
|
|
reranker_litellm_sdk_api_base: str | None
|
|
reranker_zeroentropy_api_key: str | None
|
|
reranker_zeroentropy_model: str
|
|
|
|
# Server
|
|
host: str
|
|
port: int
|
|
base_path: str
|
|
log_level: str
|
|
log_format: str
|
|
mcp_enabled: bool
|
|
mcp_enabled_tools: list[str] | None # None = all tools; explicit list = allowlist
|
|
enable_bank_config_api: bool
|
|
|
|
# Recall
|
|
graph_retriever: str
|
|
mpfp_top_k_neighbors: int
|
|
recall_max_concurrent: int
|
|
recall_connection_budget: int
|
|
recall_max_query_tokens: int
|
|
mental_model_refresh_concurrency: int
|
|
|
|
# Retain settings
|
|
retain_max_completion_tokens: int
|
|
retain_chunk_size: int
|
|
retain_extract_causal_links: bool
|
|
retain_extraction_mode: str
|
|
retain_mission: str | None
|
|
retain_custom_instructions: str | None
|
|
retain_default_strategy: str | None
|
|
retain_strategies: dict | None
|
|
retain_batch_tokens: int
|
|
retain_batch_enabled: bool
|
|
retain_batch_poll_interval_seconds: int
|
|
retain_entity_lookup: str # "full" or "trigram"
|
|
|
|
# File storage (static - server-level only)
|
|
file_storage_type: str # "native" (PostgreSQL) or "s3" (S3-compatible)
|
|
file_storage_s3_bucket: str | None # S3 bucket name (required for s3 storage)
|
|
file_storage_s3_region: str | None # S3 region (optional, uses SDK default)
|
|
file_storage_s3_endpoint: str | None # S3 endpoint URL (for MinIO, R2, etc.)
|
|
file_storage_s3_access_key_id: str | None # S3 access key (optional, uses env/IAM)
|
|
file_storage_s3_secret_access_key: str | None # S3 secret key (optional, uses env/IAM)
|
|
file_storage_gcs_bucket: str | None # GCS bucket name (required for gcs storage)
|
|
file_storage_gcs_service_account_key: str | None # GCS service account key JSON (optional, uses ADC)
|
|
file_storage_azure_container: str | None # Azure container name (required for azure storage)
|
|
file_storage_azure_account_name: str | None # Azure storage account name
|
|
file_storage_azure_account_key: str | None # Azure storage account key
|
|
file_parser: list[str] # Ordered fallback chain of parsers (e.g. ["iris", "markitdown"])
|
|
file_parser_allowlist: list[str] | None # Parsers clients may request (None = all registered)
|
|
file_parser_iris_token: str | None # Vectorize API token for iris parser (VECTORIZE_TOKEN)
|
|
file_parser_iris_org_id: str | None # Vectorize org ID for iris parser (VECTORIZE_ORG_ID)
|
|
file_conversion_max_batch_size_mb: int # Max total batch size in MB (all files combined)
|
|
file_conversion_max_batch_size: int # Max files per request
|
|
enable_file_upload_api: bool
|
|
file_delete_after_retain: bool
|
|
|
|
# Observations settings (consolidated knowledge from facts)
|
|
enable_observations: bool
|
|
enable_observation_history: bool
|
|
enable_mental_model_history: bool
|
|
consolidation_batch_size: int
|
|
consolidation_llm_batch_size: int
|
|
consolidation_max_tokens: int
|
|
consolidation_source_facts_max_tokens: int
|
|
consolidation_source_facts_max_tokens_per_observation: int
|
|
observations_mission: str | None
|
|
|
|
# Entity labels (controlled vocabulary of key:value classification labels extracted at retain time)
|
|
# List of label group dicts: [{key, description, type, optional, values: [{value, description}]}]
|
|
entity_labels: list | None
|
|
# Whether to extract regular named entities alongside entity labels (default: True)
|
|
# When False: only label entities are extracted (or no entities at all if no labels configured)
|
|
entities_allow_free_form: bool
|
|
|
|
# Reflect agent settings
|
|
reflect_mission: str | None
|
|
|
|
# Disposition settings (hierarchical - can be overridden per bank; None = fall back to DB)
|
|
disposition_skepticism: int | None
|
|
disposition_literalism: int | None
|
|
disposition_empathy: int | None
|
|
|
|
# Optimization flags
|
|
skip_llm_verification: bool
|
|
lazy_reranker: bool
|
|
|
|
# Database migrations
|
|
run_migrations_on_startup: bool
|
|
|
|
# Database connection pool
|
|
db_pool_min_size: int
|
|
db_pool_max_size: int
|
|
db_command_timeout: int
|
|
db_acquire_timeout: int
|
|
|
|
# Worker configuration (distributed task processing)
|
|
worker_enabled: bool
|
|
worker_id: str | None
|
|
worker_poll_interval_ms: int
|
|
worker_max_retries: int
|
|
worker_http_port: int
|
|
worker_max_slots: int
|
|
worker_consolidation_max_slots: int
|
|
|
|
# Reflect agent settings
|
|
reflect_max_iterations: int
|
|
reflect_max_context_tokens: int
|
|
|
|
# OpenTelemetry tracing configuration
|
|
otel_traces_enabled: bool
|
|
otel_exporter_otlp_endpoint: str | None
|
|
otel_exporter_otlp_headers: str | None
|
|
otel_service_name: str
|
|
otel_deployment_environment: str
|
|
|
|
# Webhook configuration (static - server-level only, not per-bank)
|
|
webhook_url: str | None # Global webhook URL (None = disabled)
|
|
webhook_secret: str | None # HMAC signing secret (None = unsigned)
|
|
webhook_event_types: list[str] # Event types to deliver globally
|
|
webhook_delivery_poll_interval_seconds: int # How often the delivery worker polls
|
|
|
|
# Class-level sets for configuration categorization
|
|
|
|
# CREDENTIAL_FIELDS: Never exposed via API, never configurable per-tenant/bank
|
|
_CREDENTIAL_FIELDS = {
|
|
# API Keys
|
|
"llm_api_key",
|
|
"retain_llm_api_key",
|
|
"reflect_llm_api_key",
|
|
"consolidation_llm_api_key",
|
|
# Base URLs (could expose infrastructure)
|
|
"llm_base_url",
|
|
"retain_llm_base_url",
|
|
"reflect_llm_base_url",
|
|
"consolidation_llm_base_url",
|
|
"embeddings_tei_base_url",
|
|
"reranker_tei_base_url",
|
|
"reranker_cohere_base_url",
|
|
# Service Account Keys
|
|
"llm_vertexai_service_account_key",
|
|
# File storage credentials
|
|
"file_storage_s3_access_key_id",
|
|
"file_storage_s3_secret_access_key",
|
|
"file_storage_gcs_service_account_key",
|
|
"file_storage_azure_account_key",
|
|
# File parser credentials
|
|
"file_parser_iris_token",
|
|
}
|
|
|
|
# CONFIGURABLE_FIELDS: Safe behavioral settings that can be customized per-tenant/bank
|
|
# These fields are manually tagged as safe to expose and modify.
|
|
# Excludes credentials, infrastructure config, provider/model selection, and performance tuning.
|
|
_CONFIGURABLE_FIELDS = {
|
|
# MCP tool access control
|
|
"mcp_enabled_tools",
|
|
# Retention settings (behavioral)
|
|
"retain_chunk_size",
|
|
"retain_extraction_mode",
|
|
"retain_mission",
|
|
"retain_custom_instructions",
|
|
"retain_default_strategy",
|
|
"retain_strategies",
|
|
# Entity labels (controlled vocabulary for entity classification)
|
|
"entity_labels",
|
|
"entities_allow_free_form",
|
|
# Consolidation settings
|
|
"enable_observations",
|
|
"consolidation_llm_batch_size",
|
|
"consolidation_source_facts_max_tokens",
|
|
"consolidation_source_facts_max_tokens_per_observation",
|
|
"observations_mission",
|
|
# Reflect settings
|
|
"reflect_mission",
|
|
# Disposition settings
|
|
"disposition_skepticism",
|
|
"disposition_literalism",
|
|
"disposition_empathy",
|
|
# Gemini safety settings (controls content filtering for Gemini/VertexAI providers)
|
|
"llm_gemini_safety_settings",
|
|
}
|
|
|
|
@property
|
|
def file_conversion_max_batch_size_bytes(self) -> int:
|
|
"""Get maximum total batch size in bytes."""
|
|
return self.file_conversion_max_batch_size_mb * 1024 * 1024
|
|
|
|
@classmethod
|
|
def get_configurable_fields(cls) -> set[str]:
|
|
"""
|
|
Get set of field names that are configurable per-tenant/bank via API.
|
|
|
|
Configurable fields are manually tagged behavioral settings that are safe
|
|
to expose and modify (e.g., retain_chunk_size, custom_instructions).
|
|
Excludes credentials, infrastructure config, and provider/model selection.
|
|
|
|
Returns:
|
|
Set of configurable field names
|
|
"""
|
|
return cls._CONFIGURABLE_FIELDS.copy()
|
|
|
|
@classmethod
|
|
def get_credential_fields(cls) -> set[str]:
|
|
"""
|
|
Get set of field names that are credentials (NEVER exposed via API).
|
|
|
|
Credential fields include API keys, base URLs, and service account keys.
|
|
These must never be returned in API responses or accepted in updates.
|
|
|
|
Returns:
|
|
Set of credential field names
|
|
"""
|
|
return cls._CREDENTIAL_FIELDS.copy()
|
|
|
|
@classmethod
|
|
def get_hierarchical_fields(cls) -> set[str]:
|
|
"""
|
|
DEPRECATED: Use get_configurable_fields() instead.
|
|
|
|
Kept for backward compatibility during migration.
|
|
"""
|
|
return cls.get_configurable_fields()
|
|
|
|
@classmethod
|
|
def get_static_fields(cls) -> set[str]:
|
|
"""
|
|
Get set of field names that are static (server-level only).
|
|
|
|
Static fields are infrastructure-level settings that cannot vary
|
|
per tenant or bank. These include database config, API port, worker settings, etc.
|
|
Also includes credential fields which are never configurable.
|
|
|
|
Returns:
|
|
Set of static field names
|
|
"""
|
|
# Get all field names from dataclass
|
|
all_fields = {f.name for f in fields(cls)}
|
|
# Static fields = all fields - configurable fields
|
|
return all_fields - cls._CONFIGURABLE_FIELDS
|
|
|
|
def validate(self) -> None:
|
|
"""Validate configuration values and raise errors for invalid combinations."""
|
|
# Validate vector_extension
|
|
valid_extensions = ("pgvector", "vchord", "pgvectorscale")
|
|
if self.vector_extension not in valid_extensions:
|
|
raise ValueError(
|
|
f"Invalid vector_extension: {self.vector_extension}. Must be one of: {', '.join(valid_extensions)}"
|
|
)
|
|
|
|
# Validate text_search_extension
|
|
valid_text_search = ("native", "vchord", "pg_textsearch")
|
|
if self.text_search_extension not in valid_text_search:
|
|
raise ValueError(
|
|
f"Invalid text_search_extension: {self.text_search_extension}. Must be one of: {', '.join(valid_text_search)}"
|
|
)
|
|
|
|
# RETAIN_MAX_COMPLETION_TOKENS must be greater than RETAIN_CHUNK_SIZE
|
|
# to ensure the LLM has enough output capacity to extract facts from chunks
|
|
if self.retain_max_completion_tokens <= self.retain_chunk_size:
|
|
raise ValueError(
|
|
f"Invalid configuration: HINDSIGHT_API_RETAIN_MAX_COMPLETION_TOKENS "
|
|
f"({self.retain_max_completion_tokens}) must be greater than "
|
|
f"HINDSIGHT_API_RETAIN_CHUNK_SIZE ({self.retain_chunk_size}). "
|
|
f"\n\nYou have two options to fix this:"
|
|
f"\n 1. Increase HINDSIGHT_API_RETAIN_MAX_COMPLETION_TOKENS to a value > {self.retain_chunk_size}"
|
|
f"\n 2. Use a model that supports at least {self.retain_max_completion_tokens} output tokens"
|
|
f"\n (current model: {self.retain_llm_model or self.llm_model}, "
|
|
f"provider: {self.retain_llm_provider or self.llm_provider})"
|
|
)
|
|
|
|
@classmethod
|
|
def from_env(cls) -> "HindsightConfig":
|
|
"""Create configuration from environment variables."""
|
|
# Get provider first to determine default model
|
|
llm_provider = os.getenv(ENV_LLM_PROVIDER, DEFAULT_LLM_PROVIDER)
|
|
llm_model = os.getenv(ENV_LLM_MODEL) or _get_default_model_for_provider(llm_provider)
|
|
|
|
config = cls(
|
|
# Database
|
|
database_url=os.getenv(ENV_DATABASE_URL, DEFAULT_DATABASE_URL),
|
|
database_schema=os.getenv(ENV_DATABASE_SCHEMA, DEFAULT_DATABASE_SCHEMA),
|
|
vector_extension=os.getenv(ENV_VECTOR_EXTENSION, DEFAULT_VECTOR_EXTENSION).lower(),
|
|
text_search_extension=os.getenv(ENV_TEXT_SEARCH_EXTENSION, DEFAULT_TEXT_SEARCH_EXTENSION).lower(),
|
|
# LLM
|
|
llm_provider=llm_provider,
|
|
llm_api_key=os.getenv(ENV_LLM_API_KEY),
|
|
llm_model=llm_model,
|
|
llm_base_url=os.getenv(ENV_LLM_BASE_URL) or None,
|
|
llm_max_concurrent=int(os.getenv(ENV_LLM_MAX_CONCURRENT, str(DEFAULT_LLM_MAX_CONCURRENT))),
|
|
llm_max_retries=int(os.getenv(ENV_LLM_MAX_RETRIES, str(DEFAULT_LLM_MAX_RETRIES))),
|
|
llm_initial_backoff=float(os.getenv(ENV_LLM_INITIAL_BACKOFF, str(DEFAULT_LLM_INITIAL_BACKOFF))),
|
|
llm_max_backoff=float(os.getenv(ENV_LLM_MAX_BACKOFF, str(DEFAULT_LLM_MAX_BACKOFF))),
|
|
llm_timeout=float(os.getenv(ENV_LLM_TIMEOUT, str(DEFAULT_LLM_TIMEOUT))),
|
|
llm_groq_service_tier=os.getenv(ENV_LLM_GROQ_SERVICE_TIER, DEFAULT_LLM_GROQ_SERVICE_TIER),
|
|
llm_openai_service_tier=os.getenv(ENV_LLM_OPENAI_SERVICE_TIER, DEFAULT_LLM_OPENAI_SERVICE_TIER),
|
|
# Vertex AI
|
|
llm_vertexai_project_id=os.getenv(ENV_LLM_VERTEXAI_PROJECT_ID) or DEFAULT_LLM_VERTEXAI_PROJECT_ID,
|
|
llm_vertexai_region=os.getenv(ENV_LLM_VERTEXAI_REGION, DEFAULT_LLM_VERTEXAI_REGION),
|
|
llm_vertexai_service_account_key=os.getenv(ENV_LLM_VERTEXAI_SERVICE_ACCOUNT_KEY)
|
|
or DEFAULT_LLM_VERTEXAI_SERVICE_ACCOUNT_KEY,
|
|
# Gemini safety settings (JSON-encoded list of {category, threshold} dicts)
|
|
llm_gemini_safety_settings=json.loads(os.getenv(ENV_LLM_GEMINI_SAFETY_SETTINGS, "null")),
|
|
# Per-operation LLM config (None = use default)
|
|
retain_llm_provider=os.getenv(ENV_RETAIN_LLM_PROVIDER) or None,
|
|
retain_llm_api_key=os.getenv(ENV_RETAIN_LLM_API_KEY) or None,
|
|
retain_llm_model=os.getenv(ENV_RETAIN_LLM_MODEL)
|
|
or (
|
|
_get_default_model_for_provider(os.getenv(ENV_RETAIN_LLM_PROVIDER))
|
|
if os.getenv(ENV_RETAIN_LLM_PROVIDER)
|
|
else None
|
|
),
|
|
retain_llm_base_url=os.getenv(ENV_RETAIN_LLM_BASE_URL) or None,
|
|
retain_llm_max_concurrent=int(os.getenv(ENV_RETAIN_LLM_MAX_CONCURRENT))
|
|
if os.getenv(ENV_RETAIN_LLM_MAX_CONCURRENT)
|
|
else None,
|
|
retain_llm_max_retries=int(os.getenv(ENV_RETAIN_LLM_MAX_RETRIES))
|
|
if os.getenv(ENV_RETAIN_LLM_MAX_RETRIES)
|
|
else None,
|
|
retain_llm_initial_backoff=float(os.getenv(ENV_RETAIN_LLM_INITIAL_BACKOFF))
|
|
if os.getenv(ENV_RETAIN_LLM_INITIAL_BACKOFF)
|
|
else None,
|
|
retain_llm_max_backoff=float(os.getenv(ENV_RETAIN_LLM_MAX_BACKOFF))
|
|
if os.getenv(ENV_RETAIN_LLM_MAX_BACKOFF)
|
|
else None,
|
|
retain_llm_timeout=float(os.getenv(ENV_RETAIN_LLM_TIMEOUT)) if os.getenv(ENV_RETAIN_LLM_TIMEOUT) else None,
|
|
reflect_llm_provider=os.getenv(ENV_REFLECT_LLM_PROVIDER) or None,
|
|
reflect_llm_api_key=os.getenv(ENV_REFLECT_LLM_API_KEY) or None,
|
|
reflect_llm_model=os.getenv(ENV_REFLECT_LLM_MODEL)
|
|
or (
|
|
_get_default_model_for_provider(os.getenv(ENV_REFLECT_LLM_PROVIDER))
|
|
if os.getenv(ENV_REFLECT_LLM_PROVIDER)
|
|
else None
|
|
),
|
|
reflect_llm_base_url=os.getenv(ENV_REFLECT_LLM_BASE_URL) or None,
|
|
reflect_llm_max_concurrent=int(os.getenv(ENV_REFLECT_LLM_MAX_CONCURRENT))
|
|
if os.getenv(ENV_REFLECT_LLM_MAX_CONCURRENT)
|
|
else None,
|
|
reflect_llm_max_retries=int(os.getenv(ENV_REFLECT_LLM_MAX_RETRIES))
|
|
if os.getenv(ENV_REFLECT_LLM_MAX_RETRIES)
|
|
else None,
|
|
reflect_llm_initial_backoff=float(os.getenv(ENV_REFLECT_LLM_INITIAL_BACKOFF))
|
|
if os.getenv(ENV_REFLECT_LLM_INITIAL_BACKOFF)
|
|
else None,
|
|
reflect_llm_max_backoff=float(os.getenv(ENV_REFLECT_LLM_MAX_BACKOFF))
|
|
if os.getenv(ENV_REFLECT_LLM_MAX_BACKOFF)
|
|
else None,
|
|
reflect_llm_timeout=float(os.getenv(ENV_REFLECT_LLM_TIMEOUT))
|
|
if os.getenv(ENV_REFLECT_LLM_TIMEOUT)
|
|
else None,
|
|
consolidation_llm_provider=os.getenv(ENV_CONSOLIDATION_LLM_PROVIDER) or None,
|
|
consolidation_llm_api_key=os.getenv(ENV_CONSOLIDATION_LLM_API_KEY) or None,
|
|
consolidation_llm_model=os.getenv(ENV_CONSOLIDATION_LLM_MODEL)
|
|
or (
|
|
_get_default_model_for_provider(os.getenv(ENV_CONSOLIDATION_LLM_PROVIDER))
|
|
if os.getenv(ENV_CONSOLIDATION_LLM_PROVIDER)
|
|
else None
|
|
),
|
|
consolidation_llm_base_url=os.getenv(ENV_CONSOLIDATION_LLM_BASE_URL) or None,
|
|
consolidation_llm_max_concurrent=int(os.getenv(ENV_CONSOLIDATION_LLM_MAX_CONCURRENT))
|
|
if os.getenv(ENV_CONSOLIDATION_LLM_MAX_CONCURRENT)
|
|
else None,
|
|
consolidation_llm_max_retries=int(os.getenv(ENV_CONSOLIDATION_LLM_MAX_RETRIES))
|
|
if os.getenv(ENV_CONSOLIDATION_LLM_MAX_RETRIES)
|
|
else None,
|
|
consolidation_llm_initial_backoff=float(os.getenv(ENV_CONSOLIDATION_LLM_INITIAL_BACKOFF))
|
|
if os.getenv(ENV_CONSOLIDATION_LLM_INITIAL_BACKOFF)
|
|
else None,
|
|
consolidation_llm_max_backoff=float(os.getenv(ENV_CONSOLIDATION_LLM_MAX_BACKOFF))
|
|
if os.getenv(ENV_CONSOLIDATION_LLM_MAX_BACKOFF)
|
|
else None,
|
|
consolidation_llm_timeout=float(os.getenv(ENV_CONSOLIDATION_LLM_TIMEOUT))
|
|
if os.getenv(ENV_CONSOLIDATION_LLM_TIMEOUT)
|
|
else None,
|
|
# Embeddings
|
|
embeddings_provider=os.getenv(ENV_EMBEDDINGS_PROVIDER, DEFAULT_EMBEDDINGS_PROVIDER),
|
|
embeddings_local_model=os.getenv(ENV_EMBEDDINGS_LOCAL_MODEL, DEFAULT_EMBEDDINGS_LOCAL_MODEL),
|
|
embeddings_local_force_cpu=os.getenv(
|
|
ENV_EMBEDDINGS_LOCAL_FORCE_CPU, str(DEFAULT_EMBEDDINGS_LOCAL_FORCE_CPU)
|
|
).lower()
|
|
in ("true", "1"),
|
|
embeddings_local_trust_remote_code=os.getenv(
|
|
ENV_EMBEDDINGS_LOCAL_TRUST_REMOTE_CODE, str(DEFAULT_EMBEDDINGS_LOCAL_TRUST_REMOTE_CODE)
|
|
).lower()
|
|
in ("true", "1"),
|
|
embeddings_tei_url=os.getenv(ENV_EMBEDDINGS_TEI_URL),
|
|
embeddings_openai_base_url=os.getenv(ENV_EMBEDDINGS_OPENAI_BASE_URL) or None,
|
|
# Cohere embeddings (with backward-compatible fallback to shared API key)
|
|
embeddings_cohere_api_key=os.getenv(ENV_EMBEDDINGS_COHERE_API_KEY) or os.getenv(ENV_COHERE_API_KEY),
|
|
embeddings_cohere_model=os.getenv(ENV_EMBEDDINGS_COHERE_MODEL, DEFAULT_EMBEDDINGS_COHERE_MODEL),
|
|
embeddings_cohere_base_url=os.getenv(ENV_EMBEDDINGS_COHERE_BASE_URL) or None,
|
|
# LiteLLM embeddings (with backward-compatible fallback to shared config)
|
|
embeddings_litellm_api_base=os.getenv(ENV_EMBEDDINGS_LITELLM_API_BASE)
|
|
or os.getenv(ENV_LITELLM_API_BASE, DEFAULT_LITELLM_API_BASE),
|
|
embeddings_litellm_api_key=os.getenv(ENV_EMBEDDINGS_LITELLM_API_KEY) or os.getenv(ENV_LITELLM_API_KEY),
|
|
embeddings_litellm_model=os.getenv(ENV_EMBEDDINGS_LITELLM_MODEL, DEFAULT_EMBEDDINGS_LITELLM_MODEL),
|
|
# LiteLLM SDK embeddings (direct API access)
|
|
embeddings_litellm_sdk_api_key=os.getenv(ENV_EMBEDDINGS_LITELLM_SDK_API_KEY),
|
|
embeddings_litellm_sdk_model=os.getenv(
|
|
ENV_EMBEDDINGS_LITELLM_SDK_MODEL, DEFAULT_EMBEDDINGS_LITELLM_SDK_MODEL
|
|
),
|
|
embeddings_litellm_sdk_api_base=os.getenv(ENV_EMBEDDINGS_LITELLM_SDK_API_BASE) or None,
|
|
# Reranker
|
|
reranker_provider=os.getenv(ENV_RERANKER_PROVIDER, DEFAULT_RERANKER_PROVIDER),
|
|
reranker_local_model=os.getenv(ENV_RERANKER_LOCAL_MODEL, DEFAULT_RERANKER_LOCAL_MODEL),
|
|
reranker_local_force_cpu=os.getenv(
|
|
ENV_RERANKER_LOCAL_FORCE_CPU, str(DEFAULT_RERANKER_LOCAL_FORCE_CPU)
|
|
).lower()
|
|
in ("true", "1"),
|
|
reranker_local_max_concurrent=int(
|
|
os.getenv(ENV_RERANKER_LOCAL_MAX_CONCURRENT, str(DEFAULT_RERANKER_LOCAL_MAX_CONCURRENT))
|
|
),
|
|
reranker_local_trust_remote_code=os.getenv(
|
|
ENV_RERANKER_LOCAL_TRUST_REMOTE_CODE, str(DEFAULT_RERANKER_LOCAL_TRUST_REMOTE_CODE)
|
|
).lower()
|
|
in ("true", "1"),
|
|
reranker_local_fp16=os.getenv(ENV_RERANKER_LOCAL_FP16, str(DEFAULT_RERANKER_LOCAL_FP16)).lower()
|
|
in ("true", "1"),
|
|
reranker_local_bucket_batching=os.getenv(
|
|
ENV_RERANKER_LOCAL_BUCKET_BATCHING, str(DEFAULT_RERANKER_LOCAL_BUCKET_BATCHING)
|
|
).lower()
|
|
in ("true", "1"),
|
|
reranker_local_batch_size=int(
|
|
os.getenv(ENV_RERANKER_LOCAL_BATCH_SIZE, str(DEFAULT_RERANKER_LOCAL_BATCH_SIZE))
|
|
),
|
|
reranker_tei_url=os.getenv(ENV_RERANKER_TEI_URL),
|
|
reranker_tei_batch_size=int(os.getenv(ENV_RERANKER_TEI_BATCH_SIZE, str(DEFAULT_RERANKER_TEI_BATCH_SIZE))),
|
|
reranker_tei_max_concurrent=int(
|
|
os.getenv(ENV_RERANKER_TEI_MAX_CONCURRENT, str(DEFAULT_RERANKER_TEI_MAX_CONCURRENT))
|
|
),
|
|
reranker_max_candidates=int(os.getenv(ENV_RERANKER_MAX_CANDIDATES, str(DEFAULT_RERANKER_MAX_CANDIDATES))),
|
|
# Cohere reranker (with backward-compatible fallback to shared API key)
|
|
reranker_cohere_api_key=os.getenv(ENV_RERANKER_COHERE_API_KEY) or os.getenv(ENV_COHERE_API_KEY),
|
|
reranker_cohere_model=os.getenv(ENV_RERANKER_COHERE_MODEL, DEFAULT_RERANKER_COHERE_MODEL),
|
|
reranker_cohere_base_url=os.getenv(ENV_RERANKER_COHERE_BASE_URL) or None,
|
|
# LiteLLM reranker (with backward-compatible fallback to shared config)
|
|
reranker_litellm_api_base=os.getenv(ENV_RERANKER_LITELLM_API_BASE)
|
|
or os.getenv(ENV_LITELLM_API_BASE, DEFAULT_LITELLM_API_BASE),
|
|
reranker_litellm_api_key=os.getenv(ENV_RERANKER_LITELLM_API_KEY) or os.getenv(ENV_LITELLM_API_KEY),
|
|
reranker_litellm_model=os.getenv(ENV_RERANKER_LITELLM_MODEL, DEFAULT_RERANKER_LITELLM_MODEL),
|
|
reranker_litellm_max_tokens_per_doc=int(v)
|
|
if (v := os.getenv(ENV_RERANKER_LITELLM_MAX_TOKENS_PER_DOC))
|
|
else DEFAULT_RERANKER_LITELLM_MAX_TOKENS_PER_DOC,
|
|
# LiteLLM SDK reranker (direct API access)
|
|
reranker_litellm_sdk_api_key=os.getenv(ENV_RERANKER_LITELLM_SDK_API_KEY),
|
|
reranker_litellm_sdk_model=os.getenv(ENV_RERANKER_LITELLM_SDK_MODEL, DEFAULT_RERANKER_LITELLM_SDK_MODEL),
|
|
reranker_litellm_sdk_api_base=os.getenv(ENV_RERANKER_LITELLM_SDK_API_BASE) or None,
|
|
# ZeroEntropy reranker
|
|
reranker_zeroentropy_api_key=os.getenv(ENV_RERANKER_ZEROENTROPY_API_KEY),
|
|
reranker_zeroentropy_model=os.getenv(ENV_RERANKER_ZEROENTROPY_MODEL, DEFAULT_RERANKER_ZEROENTROPY_MODEL),
|
|
# Server
|
|
host=os.getenv(ENV_HOST, DEFAULT_HOST),
|
|
port=int(os.getenv(ENV_PORT, DEFAULT_PORT)),
|
|
base_path=os.getenv(ENV_BASE_PATH, DEFAULT_BASE_PATH),
|
|
log_level=os.getenv(ENV_LOG_LEVEL, DEFAULT_LOG_LEVEL),
|
|
log_format=os.getenv(ENV_LOG_FORMAT, DEFAULT_LOG_FORMAT).lower(),
|
|
mcp_enabled=os.getenv(ENV_MCP_ENABLED, str(DEFAULT_MCP_ENABLED)).lower() == "true",
|
|
mcp_enabled_tools=[t.strip() for t in os.getenv(ENV_MCP_ENABLED_TOOLS).split(",") if t.strip()]
|
|
if os.getenv(ENV_MCP_ENABLED_TOOLS)
|
|
else DEFAULT_MCP_ENABLED_TOOLS,
|
|
enable_bank_config_api=os.getenv(ENV_ENABLE_BANK_CONFIG_API, str(DEFAULT_ENABLE_BANK_CONFIG_API)).lower()
|
|
== "true",
|
|
# Recall
|
|
graph_retriever=os.getenv(ENV_GRAPH_RETRIEVER, DEFAULT_GRAPH_RETRIEVER),
|
|
mpfp_top_k_neighbors=int(os.getenv(ENV_MPFP_TOP_K_NEIGHBORS, str(DEFAULT_MPFP_TOP_K_NEIGHBORS))),
|
|
recall_max_concurrent=int(os.getenv(ENV_RECALL_MAX_CONCURRENT, str(DEFAULT_RECALL_MAX_CONCURRENT))),
|
|
recall_connection_budget=int(
|
|
os.getenv(ENV_RECALL_CONNECTION_BUDGET, str(DEFAULT_RECALL_CONNECTION_BUDGET))
|
|
),
|
|
recall_max_query_tokens=int(os.getenv(ENV_RECALL_MAX_QUERY_TOKENS, str(DEFAULT_RECALL_MAX_QUERY_TOKENS))),
|
|
mental_model_refresh_concurrency=int(
|
|
os.getenv(ENV_MENTAL_MODEL_REFRESH_CONCURRENCY, str(DEFAULT_MENTAL_MODEL_REFRESH_CONCURRENCY))
|
|
),
|
|
# Optimization flags
|
|
skip_llm_verification=os.getenv(ENV_SKIP_LLM_VERIFICATION, "false").lower() == "true",
|
|
lazy_reranker=os.getenv(ENV_LAZY_RERANKER, "false").lower() == "true",
|
|
# Retain settings
|
|
retain_max_completion_tokens=int(
|
|
os.getenv(ENV_RETAIN_MAX_COMPLETION_TOKENS, str(DEFAULT_RETAIN_MAX_COMPLETION_TOKENS))
|
|
),
|
|
retain_chunk_size=int(os.getenv(ENV_RETAIN_CHUNK_SIZE, str(DEFAULT_RETAIN_CHUNK_SIZE))),
|
|
retain_extract_causal_links=os.getenv(
|
|
ENV_RETAIN_EXTRACT_CAUSAL_LINKS, str(DEFAULT_RETAIN_EXTRACT_CAUSAL_LINKS)
|
|
).lower()
|
|
== "true",
|
|
retain_extraction_mode=_validate_extraction_mode(
|
|
os.getenv(ENV_RETAIN_EXTRACTION_MODE, DEFAULT_RETAIN_EXTRACTION_MODE)
|
|
),
|
|
retain_mission=os.getenv(ENV_RETAIN_MISSION) or DEFAULT_RETAIN_MISSION,
|
|
retain_custom_instructions=os.getenv(ENV_RETAIN_CUSTOM_INSTRUCTIONS) or DEFAULT_RETAIN_CUSTOM_INSTRUCTIONS,
|
|
retain_default_strategy=os.getenv(ENV_RETAIN_DEFAULT_STRATEGY) or DEFAULT_RETAIN_DEFAULT_STRATEGY,
|
|
retain_strategies=DEFAULT_RETAIN_STRATEGIES,
|
|
retain_batch_tokens=int(os.getenv(ENV_RETAIN_BATCH_TOKENS, str(DEFAULT_RETAIN_BATCH_TOKENS))),
|
|
retain_entity_lookup=os.getenv(ENV_RETAIN_ENTITY_LOOKUP, DEFAULT_RETAIN_ENTITY_LOOKUP),
|
|
retain_batch_enabled=os.getenv(ENV_RETAIN_BATCH_ENABLED, str(DEFAULT_RETAIN_BATCH_ENABLED)).lower()
|
|
== "true",
|
|
retain_batch_poll_interval_seconds=int(
|
|
os.getenv(ENV_RETAIN_BATCH_POLL_INTERVAL_SECONDS, str(DEFAULT_RETAIN_BATCH_POLL_INTERVAL_SECONDS))
|
|
),
|
|
# File storage
|
|
file_storage_type=os.getenv(ENV_FILE_STORAGE_TYPE, DEFAULT_FILE_STORAGE_TYPE),
|
|
file_storage_s3_bucket=os.getenv(ENV_FILE_STORAGE_S3_BUCKET) or None,
|
|
file_storage_s3_region=os.getenv(ENV_FILE_STORAGE_S3_REGION) or None,
|
|
file_storage_s3_endpoint=os.getenv(ENV_FILE_STORAGE_S3_ENDPOINT) or None,
|
|
file_storage_s3_access_key_id=os.getenv(ENV_FILE_STORAGE_S3_ACCESS_KEY_ID) or None,
|
|
file_storage_s3_secret_access_key=os.getenv(ENV_FILE_STORAGE_S3_SECRET_ACCESS_KEY) or None,
|
|
file_storage_gcs_bucket=os.getenv(ENV_FILE_STORAGE_GCS_BUCKET) or None,
|
|
file_storage_gcs_service_account_key=os.getenv(ENV_FILE_STORAGE_GCS_SERVICE_ACCOUNT_KEY) or None,
|
|
file_storage_azure_container=os.getenv(ENV_FILE_STORAGE_AZURE_CONTAINER) or None,
|
|
file_storage_azure_account_name=os.getenv(ENV_FILE_STORAGE_AZURE_ACCOUNT_NAME) or None,
|
|
file_storage_azure_account_key=os.getenv(ENV_FILE_STORAGE_AZURE_ACCOUNT_KEY) or None,
|
|
file_parser=_parse_str_list(os.getenv(ENV_FILE_PARSER, DEFAULT_FILE_PARSER)),
|
|
file_parser_allowlist=_parse_str_list(os.getenv(ENV_FILE_PARSER_ALLOWLIST))
|
|
if os.getenv(ENV_FILE_PARSER_ALLOWLIST)
|
|
else None,
|
|
file_parser_iris_token=os.getenv(ENV_FILE_PARSER_IRIS_TOKEN) or None,
|
|
file_parser_iris_org_id=os.getenv(ENV_FILE_PARSER_IRIS_ORG_ID) or None,
|
|
file_conversion_max_batch_size_mb=int(
|
|
os.getenv(ENV_FILE_CONVERSION_MAX_BATCH_SIZE_MB, str(DEFAULT_FILE_CONVERSION_MAX_BATCH_SIZE_MB))
|
|
),
|
|
file_conversion_max_batch_size=int(
|
|
os.getenv(ENV_FILE_CONVERSION_MAX_BATCH_SIZE, str(DEFAULT_FILE_CONVERSION_MAX_BATCH_SIZE))
|
|
),
|
|
enable_file_upload_api=os.getenv(ENV_ENABLE_FILE_UPLOAD_API, str(DEFAULT_ENABLE_FILE_UPLOAD_API)).lower()
|
|
== "true",
|
|
file_delete_after_retain=os.getenv(
|
|
ENV_FILE_DELETE_AFTER_RETAIN, str(DEFAULT_FILE_DELETE_AFTER_RETAIN)
|
|
).lower()
|
|
== "true",
|
|
# Observations settings (consolidated knowledge from facts)
|
|
enable_observations=os.getenv(ENV_ENABLE_OBSERVATIONS, str(DEFAULT_ENABLE_OBSERVATIONS)).lower() == "true",
|
|
enable_observation_history=os.getenv(
|
|
ENV_ENABLE_OBSERVATION_HISTORY, str(DEFAULT_ENABLE_OBSERVATION_HISTORY)
|
|
).lower()
|
|
== "true",
|
|
enable_mental_model_history=os.getenv(
|
|
ENV_ENABLE_MENTAL_MODEL_HISTORY, str(DEFAULT_ENABLE_MENTAL_MODEL_HISTORY)
|
|
).lower()
|
|
== "true",
|
|
consolidation_batch_size=int(
|
|
os.getenv(ENV_CONSOLIDATION_BATCH_SIZE, str(DEFAULT_CONSOLIDATION_BATCH_SIZE))
|
|
),
|
|
consolidation_llm_batch_size=int(
|
|
os.getenv(ENV_CONSOLIDATION_LLM_BATCH_SIZE, str(DEFAULT_CONSOLIDATION_LLM_BATCH_SIZE))
|
|
),
|
|
consolidation_max_tokens=int(
|
|
os.getenv(ENV_CONSOLIDATION_MAX_TOKENS, str(DEFAULT_CONSOLIDATION_MAX_TOKENS))
|
|
),
|
|
consolidation_source_facts_max_tokens=int(
|
|
os.getenv(ENV_CONSOLIDATION_SOURCE_FACTS_MAX_TOKENS, str(DEFAULT_CONSOLIDATION_SOURCE_FACTS_MAX_TOKENS))
|
|
),
|
|
consolidation_source_facts_max_tokens_per_observation=int(
|
|
os.getenv(
|
|
ENV_CONSOLIDATION_SOURCE_FACTS_MAX_TOKENS_PER_OBSERVATION,
|
|
str(DEFAULT_CONSOLIDATION_SOURCE_FACTS_MAX_TOKENS_PER_OBSERVATION),
|
|
)
|
|
),
|
|
observations_mission=os.getenv(ENV_OBSERVATIONS_MISSION) or DEFAULT_OBSERVATIONS_MISSION,
|
|
entity_labels=None,
|
|
entities_allow_free_form=True,
|
|
# Database migrations
|
|
run_migrations_on_startup=os.getenv(ENV_RUN_MIGRATIONS_ON_STARTUP, "true").lower() == "true",
|
|
# Database connection pool
|
|
db_pool_min_size=int(os.getenv(ENV_DB_POOL_MIN_SIZE, str(DEFAULT_DB_POOL_MIN_SIZE))),
|
|
db_pool_max_size=int(os.getenv(ENV_DB_POOL_MAX_SIZE, str(DEFAULT_DB_POOL_MAX_SIZE))),
|
|
db_command_timeout=int(os.getenv(ENV_DB_COMMAND_TIMEOUT, str(DEFAULT_DB_COMMAND_TIMEOUT))),
|
|
db_acquire_timeout=int(os.getenv(ENV_DB_ACQUIRE_TIMEOUT, str(DEFAULT_DB_ACQUIRE_TIMEOUT))),
|
|
# Worker configuration
|
|
worker_enabled=os.getenv(ENV_WORKER_ENABLED, str(DEFAULT_WORKER_ENABLED)).lower() == "true",
|
|
worker_id=os.getenv(ENV_WORKER_ID) or DEFAULT_WORKER_ID,
|
|
worker_poll_interval_ms=int(os.getenv(ENV_WORKER_POLL_INTERVAL_MS, str(DEFAULT_WORKER_POLL_INTERVAL_MS))),
|
|
worker_max_retries=int(os.getenv(ENV_WORKER_MAX_RETRIES, str(DEFAULT_WORKER_MAX_RETRIES))),
|
|
worker_http_port=int(os.getenv(ENV_WORKER_HTTP_PORT, str(DEFAULT_WORKER_HTTP_PORT))),
|
|
worker_max_slots=int(os.getenv(ENV_WORKER_MAX_SLOTS, str(DEFAULT_WORKER_MAX_SLOTS))),
|
|
worker_consolidation_max_slots=int(
|
|
os.getenv(ENV_WORKER_CONSOLIDATION_MAX_SLOTS, str(DEFAULT_WORKER_CONSOLIDATION_MAX_SLOTS))
|
|
),
|
|
# Reflect agent settings
|
|
reflect_max_iterations=int(os.getenv(ENV_REFLECT_MAX_ITERATIONS, str(DEFAULT_REFLECT_MAX_ITERATIONS))),
|
|
reflect_max_context_tokens=int(
|
|
os.getenv(ENV_REFLECT_MAX_CONTEXT_TOKENS, str(DEFAULT_REFLECT_MAX_CONTEXT_TOKENS))
|
|
),
|
|
reflect_mission=os.getenv(ENV_REFLECT_MISSION) or None,
|
|
# Disposition settings (None = fall back to DB value)
|
|
disposition_skepticism=int(os.getenv(ENV_DISPOSITION_SKEPTICISM))
|
|
if os.getenv(ENV_DISPOSITION_SKEPTICISM)
|
|
else DEFAULT_DISPOSITION_SKEPTICISM,
|
|
disposition_literalism=int(os.getenv(ENV_DISPOSITION_LITERALISM))
|
|
if os.getenv(ENV_DISPOSITION_LITERALISM)
|
|
else DEFAULT_DISPOSITION_LITERALISM,
|
|
disposition_empathy=int(os.getenv(ENV_DISPOSITION_EMPATHY))
|
|
if os.getenv(ENV_DISPOSITION_EMPATHY)
|
|
else DEFAULT_DISPOSITION_EMPATHY,
|
|
# OpenTelemetry tracing configuration
|
|
otel_traces_enabled=os.getenv(ENV_OTEL_TRACES_ENABLED, str(DEFAULT_OTEL_TRACES_ENABLED)).lower()
|
|
in ("true", "1", "yes"),
|
|
otel_exporter_otlp_endpoint=os.getenv(ENV_OTEL_EXPORTER_OTLP_ENDPOINT) or None,
|
|
otel_exporter_otlp_headers=os.getenv(ENV_OTEL_EXPORTER_OTLP_HEADERS) or None,
|
|
otel_service_name=os.getenv(ENV_OTEL_SERVICE_NAME, DEFAULT_OTEL_SERVICE_NAME),
|
|
otel_deployment_environment=os.getenv(ENV_OTEL_DEPLOYMENT_ENVIRONMENT, DEFAULT_OTEL_DEPLOYMENT_ENVIRONMENT),
|
|
# Webhook configuration (static, server-level only)
|
|
webhook_url=os.getenv(ENV_WEBHOOK_URL) or DEFAULT_WEBHOOK_URL,
|
|
webhook_secret=os.getenv(ENV_WEBHOOK_SECRET) or DEFAULT_WEBHOOK_SECRET,
|
|
webhook_event_types=[
|
|
t.strip()
|
|
for t in os.getenv(ENV_WEBHOOK_EVENT_TYPES, DEFAULT_WEBHOOK_EVENT_TYPES).split(",")
|
|
if t.strip()
|
|
],
|
|
webhook_delivery_poll_interval_seconds=int(
|
|
os.getenv(
|
|
ENV_WEBHOOK_DELIVERY_POLL_INTERVAL_SECONDS,
|
|
str(DEFAULT_WEBHOOK_DELIVERY_POLL_INTERVAL_SECONDS),
|
|
)
|
|
),
|
|
)
|
|
config.validate()
|
|
return config
|
|
|
|
def get_llm_base_url(self) -> str:
|
|
"""Get the LLM base URL, with provider-specific defaults."""
|
|
if self.llm_base_url:
|
|
return self.llm_base_url
|
|
|
|
provider = self.llm_provider.lower()
|
|
if provider == "groq":
|
|
return "https://api.groq.com/openai/v1"
|
|
elif provider == "ollama":
|
|
return "http://localhost:11434/v1"
|
|
elif provider == "lmstudio":
|
|
return "http://localhost:1234/v1"
|
|
else:
|
|
return ""
|
|
|
|
def get_python_log_level(self) -> int:
|
|
"""Get the Python logging level from the configured log level string."""
|
|
log_level_map = {
|
|
"critical": logging.CRITICAL,
|
|
"error": logging.ERROR,
|
|
"warning": logging.WARNING,
|
|
"info": logging.INFO,
|
|
"debug": logging.DEBUG,
|
|
"trace": logging.DEBUG, # Python doesn't have TRACE, use DEBUG
|
|
}
|
|
return log_level_map.get(self.log_level.lower(), logging.INFO)
|
|
|
|
def configure_logging(self) -> None:
|
|
"""Configure Python logging based on the log level and format.
|
|
|
|
When log_format is "json", outputs structured JSON logs with a severity
|
|
field that GCP Cloud Logging can parse for proper log level categorization.
|
|
"""
|
|
root_logger = logging.getLogger()
|
|
root_logger.setLevel(self.get_python_log_level())
|
|
|
|
# Remove existing handlers
|
|
for handler in root_logger.handlers[:]:
|
|
root_logger.removeHandler(handler)
|
|
|
|
# Create handler writing to stdout (GCP treats stderr as ERROR)
|
|
handler = logging.StreamHandler(sys.stdout)
|
|
handler.setLevel(self.get_python_log_level())
|
|
|
|
if self.log_format == "json":
|
|
handler.setFormatter(JsonFormatter())
|
|
else:
|
|
handler.setFormatter(logging.Formatter("%(asctime)s - %(levelname)s - %(name)s - %(message)s"))
|
|
|
|
root_logger.addHandler(handler)
|
|
|
|
def log_config(self) -> None:
|
|
"""Log the current configuration (without sensitive values)."""
|
|
logger.info(f"Database: {self.database_url} (schema: {self.database_schema})")
|
|
logger.info(f"LLM: provider={self.llm_provider}, model={self.llm_model}")
|
|
if self.retain_llm_provider or self.retain_llm_model:
|
|
retain_provider = self.retain_llm_provider or self.llm_provider
|
|
retain_model = self.retain_llm_model or self.llm_model
|
|
logger.info(f"LLM (retain): provider={retain_provider}, model={retain_model}")
|
|
if self.reflect_llm_provider or self.reflect_llm_model:
|
|
reflect_provider = self.reflect_llm_provider or self.llm_provider
|
|
reflect_model = self.reflect_llm_model or self.llm_model
|
|
logger.info(f"LLM (reflect): provider={reflect_provider}, model={reflect_model}")
|
|
if self.consolidation_llm_provider or self.consolidation_llm_model:
|
|
consolidation_provider = self.consolidation_llm_provider or self.llm_provider
|
|
consolidation_model = self.consolidation_llm_model or self.llm_model
|
|
logger.info(f"LLM (consolidation): provider={consolidation_provider}, model={consolidation_model}")
|
|
logger.info(f"Embeddings: provider={self.embeddings_provider}")
|
|
logger.info(f"Reranker: provider={self.reranker_provider}")
|
|
logger.info(f"Graph retriever: {self.graph_retriever}")
|
|
|
|
|
|
# Cached config instance
|
|
_config_cache: HindsightConfig | None = None
|
|
|
|
|
|
def get_config() -> StaticConfigProxy:
|
|
"""
|
|
Get global configuration with ONLY static (non-configurable) fields accessible.
|
|
|
|
This returns a proxy that prevents access to bank-configurable fields
|
|
(like enable_observations, retain_chunk_size, etc.).
|
|
|
|
For bank-specific configuration, use:
|
|
config_resolver.resolve_full_config(bank_id, context)
|
|
|
|
This design prevents accidentally using global defaults when bank-specific
|
|
overrides exist.
|
|
|
|
Returns:
|
|
StaticConfigProxy that only exposes static infrastructure fields
|
|
|
|
Raises:
|
|
ConfigFieldAccessError: If you try to access a bank-configurable field
|
|
"""
|
|
return StaticConfigProxy(_get_raw_config())
|
|
|
|
|
|
def _get_raw_config() -> HindsightConfig:
|
|
"""
|
|
Get raw config (internal use only).
|
|
|
|
INTERNAL USE ONLY. Do not use this directly in application code.
|
|
Use get_config() for static fields or ConfigResolver.resolve_full_config() for bank-specific config.
|
|
"""
|
|
global _config_cache
|
|
if _config_cache is None:
|
|
_config_cache = HindsightConfig.from_env()
|
|
return _config_cache
|
|
|
|
|
|
def clear_config_cache() -> None:
|
|
"""Clear the config cache. Useful for testing or reloading config."""
|
|
global _config_cache
|
|
_config_cache = None
|