DirectorConfig

Dataclass-based configuration with environment variable, YAML file, and named profile loaders. All fields have sensible defaults.

Loading Configuration

Environment VariablesYAML FileNamed Profile

from director_ai.core.config import DirectorConfig

config = DirectorConfig.from_env()

All fields map to DIRECTOR_<FIELD> env vars:

DIRECTOR_COHERENCE_THRESHOLD=0.6
DIRECTOR_HARD_LIMIT=0.5
DIRECTOR_USE_NLI=true
DIRECTOR_NLI_MODEL=lytang/MiniCheck-DeBERTa-L
DIRECTOR_LLM_PROVIDER=openai
DIRECTOR_VECTOR_BACKEND=chroma
DIRECTOR_METRICS_ENABLED=true

config = DirectorConfig.from_yaml("config.yaml")

coherence_threshold: 0.6
hard_limit: 0.5
use_nli: true
nli_model: "lytang/MiniCheck-DeBERTa-L"
vector_backend: chroma
chroma_persist_dir: "./data/chroma"
metrics_enabled: true

config = DirectorConfig.from_profile("thorough")

Profiles

Profile	NLI	Threshold	Candidates	Metrics	Use Case
fast	Off	0.5	1	Off	Development, prototyping
thorough	On	0.6	3	On	Production default
research	On	0.7	5	On	Evaluation, benchmarking
medical	On	0.30	3	On	Healthcare (measured on PubMedQA)
finance	On	0.30	3	On	Financial services (measured on FinanceBench)
legal	On	0.30	3	On	Legal document review
creative	Off	0.40	3	Off	Creative writing (low halt rate)
customer_support	Off	0.55	3	Off	Support agents
summarization	On	0.15	3	On	Document summarization
lite	Off	0.50	1	Off	Zero-dependency fast path

Building Components from Config

config = DirectorConfig.from_profile("thorough")

# Build a scorer with all config settings applied
scorer = config.build_scorer(store=my_store)

# Build a vector store from config
store = config.build_store()

Field Reference

Scoring

Field	Type	Default	Description
coherence_threshold	float	0.6	Minimum coherence to approve
hard_limit	float	0.5	Safety kernel emergency stop
soft_limit	float	0.6	Warning zone threshold
use_nli	bool	False	Enable DeBERTa NLI model
nli_model	str	"yaxili96/FactCG-DeBERTa-v3-Large"	HuggingFace model ID
max_candidates	int	3	LLM candidates to generate
history_window	int	5	Rolling history size
scorer_backend	str	"deberta"	deberta, onnx, minicheck, hybrid, lite, rust

LLM Provider

Field	Type	Default	Description
llm_provider	str	"mock"	mock, openai, anthropic, huggingface, local
llm_api_url	str	""	API endpoint (for local provider)
llm_api_key	str	""	API key (for cloud providers)
llm_model	str	""	Model name
llm_temperature	float	0.8	Sampling temperature
llm_max_tokens	int	512	Maximum tokens per response

LLM-as-Judge

Privacy

When enabled, user prompts and responses are sent to the configured external LLM. Do not enable in privacy-sensitive deployments without user consent.

Field	Type	Default	Description
llm_judge_enabled	bool	False	Enable LLM escalation
llm_judge_confidence_threshold	float	0.3	Softmax margin for escalation
llm_judge_provider	str	""	"openai", "anthropic", or "local"
llm_judge_model	str	""	Model name for judge
privacy_mode	bool	False	Redact PII before sending

Vector Store

Field	Type	Default	Description
vector_backend	str	"memory"	"memory" or "chroma"
embedding_model	str	"BAAI/bge-large-en-v1.5"	Embedding model ID
chroma_collection	str	"director_ai"	ChromaDB collection name
chroma_persist_dir	str	""	Persistence directory (empty = in-memory)
reranker_enabled	bool	True	Enable cross-encoder reranking
reranker_model	str	"cross-encoder/ms-marco-MiniLM-L-6-v2"	Reranker model

Server

Field	Type	Default	Description
server_host	str	"0.0.0.0"	Bind address
server_port	int	8080	Port
server_workers	int	1	Uvicorn worker count
cors_origins	str	""	CORS allowed origins
metrics_enabled	bool	True	Enable Prometheus metrics
log_level	str	"INFO"	Logging level
log_json	bool	False	Structured JSON logging

Caching

Field	Type	Default	Description
cache_size	int	1024	LRU cache max entries
cache_ttl	float	300.0	Cache entry TTL (seconds)
redis_url	str	""	Redis URL for distributed caching

Full API

director_ai.core.config.DirectorConfig dataclass

DirectorConfig(mode: str = 'auto', coherence_threshold: float = 0.6, hard_limit: float = 0.5, soft_limit: float = 0.6, use_nli: bool = False, nli_model: str = 'yaxili96/FactCG-DeBERTa-v3-Large', nli_max_length: int = 512, max_candidates: int = 3, history_window: int = 5, llm_provider: str = 'mock', llm_api_url: str = '', llm_api_key: str = '', llm_model: str = '', llm_temperature: float = 0.8, llm_max_tokens: int = 512, llm_judge_enabled: bool = False, llm_judge_confidence_threshold: float = 0.3, llm_judge_provider: str = '', llm_judge_model: str = '', llm_judge_local_model: str = '', privacy_mode: bool = False, scorer_backend: str = 'deberta', nli_devices: str = '', vector_backend: str = 'memory', embedding_model: str = 'BAAI/bge-large-en-v1.5', chroma_collection: str = 'director_ai', chroma_persist_dir: str = '', hybrid_retrieval: bool = True, reranker_enabled: bool = True, reranker_model: str = 'cross-encoder/ms-marco-MiniLM-L-6-v2', reranker_top_k_multiplier: int = 3, retrieval_abstention_threshold: float = 0.3, redis_url: str = '', redis_prefix: str = 'dai:', cache_size: int = 1024, cache_ttl: float = 300.0, server_host: str = '0.0.0.0', server_port: int = 8080, server_workers: int = 1, cors_origins: str = '', onnx_path: str = '', onnx_batch_size: int = 16, onnx_flush_timeout_ms: float = 10.0, batch_max_concurrency: int = 4, review_queue_enabled: bool = False, review_queue_max_batch: int = 32, review_queue_flush_timeout_ms: float = 10.0, metrics_enabled: bool = True, log_level: str = 'INFO', log_json: bool = False, otel_enabled: bool = False, audit_log_path: str = '', audit_postgres_url: str = '', tenant_routing: bool = False, rate_limit_enabled: bool = False, sanitize_inputs: bool = True, sanitizer_block_threshold: float = 0.8, redact_pii: bool = False, w_logic: float = 0.0, w_fact: float = 0.0, metrics_require_auth: bool = True, rate_limit_rpm: int = 0, rate_limit_strict: bool = False, api_keys: list[str] = list(), api_key_tenant_map: str = '', stats_backend: str = 'prometheus', stats_db_path: str = '~/.director-ai/stats.db', source_endpoint_enabled: bool = True, source_repository_url: str = 'https://github.com/anulum/director-ai', license_key: str = '', license_file: str = '', nli_fact_inner_agg: str = 'max', nli_fact_outer_agg: str = 'max', nli_logic_inner_agg: str = 'max', nli_logic_outer_agg: str = 'max', nli_premise_ratio: float = 0.4, nli_fact_retrieval_top_k: int = 3, nli_use_prompt_as_premise: bool = False, nli_summarization_baseline: float = 0.2, nli_claim_coverage_enabled: bool = True, nli_claim_support_threshold: float = 0.6, nli_claim_coverage_alpha: float = 0.4, adaptive_threshold_enabled: bool = True, threshold_summarization: float = 0.72, threshold_qa: float = 0.69, threshold_fact_check: float = 0.56, threshold_rag: float = 0.78, threshold_dialogue: float = 0.68, nli_chunk_overlap_ratio: float = 0.5, nli_qa_premise_ratio: float = 0.7, nli_confidence_weighted_agg: bool = True, lora_adapter_path: str = '', meta_classifier_path: str = '', grpc_max_message_mb: int = 4, grpc_deadline_seconds: float = 30.0, profile: str = 'default', extra: dict[str, str] = dict(), _REDACTED_FIELDS: frozenset[str] = frozenset({'llm_api_key', 'api_keys', 'api_key_tenant_map', 'audit_postgres_url', 'redis_url'}))

Central configuration for Director-Class AI.

Parameters:

Name	Type	Description	Default
coherence_threshold	float — minimum coherence to approve (0.0-1.0).		0.6
hard_limit	float — safety kernel emergency stop threshold.		0.5
use_nli	bool — enable DeBERTa NLI model for logical divergence.		False
nli_model	str — HuggingFace model ID for NLI.		'yaxili96/FactCG-DeBERTa-v3-Large'
max_candidates	int — number of LLM candidates to generate.		3
history_window	int — scorer rolling history size.		5
llm_provider	str — LLM backend: mock, openai, anthropic,	huggingface, or local.	'mock'
llm_api_url	str — API endpoint URL (for "local" provider).		''
llm_api_key	str — API key (for cloud providers).		''
llm_model	str — model name for cloud providers.		''
llm_temperature	float — sampling temperature.		0.8
llm_max_tokens	int — maximum tokens per response.		512
vector_backend	str — "memory" or "chroma".		'memory'
chroma_collection	str — ChromaDB collection name.		'director_ai'
chroma_persist_dir	str — ChromaDB persistence directory (None=in-memory).		''
onnx_path	str — directory with exported ONNX model (for scorer_backend="onnx").		''
server_host	str — FastAPI server bind address.		'0.0.0.0'
server_port	int — FastAPI server port.		8080
server_workers	int — Uvicorn worker count.		1
batch_max_concurrency	int — max concurrent batch requests.		4
metrics_enabled	bool — enable Prometheus-style metrics collection.		True
log_level	str — logging level.		'INFO'
log_json	bool — structured JSON logging.		False

from_env classmethod

from_env(prefix: str = 'DIRECTOR_') -> DirectorConfig

Load configuration from environment variables.

Reads DIRECTOR_<FIELD> env vars (case-insensitive field matching). Example: DIRECTOR_COHERENCE_THRESHOLD=0.7

from_yaml classmethod

from_yaml(path: str) -> DirectorConfig

Load configuration from a YAML file.

Falls back to JSON parsing if PyYAML is not installed.

from_profile classmethod

from_profile(name: str) -> DirectorConfig

Load a predefined profile.

Profiles

• "fast" — heuristic scoring only, no NLI model, low latency.
• "thorough" — NLI + RAG scoring, higher accuracy.
• "research" — NLI + RAG + reranker, all scoring modules enabled.

configure_logging

configure_logging() -> None

Apply log_level and log_json settings to the DirectorAI logger hierarchy.

build_store

build_store()

Construct a VectorGroundTruthStore from config fields.

In general mode, returns a bare GroundTruthStore (no vector backend). In grounded and auto modes, builds the full vector pipeline.

build_scorer

build_scorer(store=None)

Construct a CoherenceScorer wired to all relevant config fields.

to_dict

to_dict() -> dict

Serialize to a plain dict (safe for JSON/API responses).