Domain Presets¶

DirectorConfig.from_profile(name) loads a preset parameter set for common use cases. These are starting points based on domain heuristics, not validated against domain-specific benchmarks.

Profile Reference¶

Profile	Threshold	Hard Limit	Soft Limit	NLI	Reranker	W_Logic	W_Fact
`fast`	0.50	default	default	no	no	default	default
`thorough`	0.60	default	default	yes	no	default	default
`research`	0.70	default	default	yes	no	default	default
`medical`	0.30	0.20	0.35	yes	yes	0.5	0.5
`finance`	0.30	0.20	0.35	yes	yes	0.4	0.6
`legal`	0.30	0.20	0.35	yes	no	0.6	0.4
`creative`	0.40	0.30	0.45	no	no	0.7	0.3
`customer_support`	0.55	0.40	0.60	no	no	0.5	0.5

"default" means the field inherits the DirectorConfig dataclass default (hard_limit=0.5, soft_limit=0.6, w_logic/w_fact=0.0 which defers to CoherenceScorer class defaults).

Profile Rationale¶

fast — Heuristic scoring only, no model loading. Sub-millisecond latency for dev loops and high-throughput pipelines where approximate filtering is acceptable.

thorough — Adds NLI inference (FactCG-DeBERTa) to catch logical contradictions that heuristics miss. Standard production baseline.

research — Higher threshold (0.70) for academic and analytical workloads where factual precision matters more than recall.

medical — Equal logic/fact weighting reflects the need for both clinical reasoning and factual accuracy. Reranker enabled for precise KB retrieval. Measured on PubMedQA (500 samples, 2026-03-20): CoherenceScorer scores cluster 0.25–0.35; threshold=0.30 yields best F1 (59.9%) with 77.3% catch rate and 66.2% FPR.

finance — Fact-weighted (0.6) because numerical claims and regulatory data dominate. Reranker sharpens retrieval against financial KB documents. Measured on FinanceBench (150 known-good SEC filing answers, 2026-03-20): scores cluster 0.30–0.55; threshold ≤0.30 achieves 0% FPR on correct answers.

legal — Logic-weighted (0.6) because legal reasoning chains (statute + precedent + application) matter more than isolated facts. No reranker; legal KBs tend to be smaller and well-structured. Not yet validated on domain data (CUAD OOM on 6GB VRAM).

creative — Permissive thresholds (0.40/0.30/0.45) allow divergent generation. NLI disabled to avoid penalising metaphor and fiction. Logic-weighted (0.7) because internal narrative consistency matters more than factual grounding.

customer_support — Moderate thresholds balance helpfulness with accuracy. NLI disabled for latency (support bots need fast responses). Equal weights suit mixed queries (policy facts + troubleshooting logic).

Usage¶

from director_ai import DirectorConfig

config = DirectorConfig.from_profile("medical")

Load via CLI:

director-ai quickstart --profile medical

Load via environment variable:

export DIRECTOR_PROFILE=finance

Customising a Profile¶

from_profile returns a regular DirectorConfig dataclass. Override fields after loading:

from dataclasses import replace
from director_ai import DirectorConfig

base = DirectorConfig.from_profile("medical")
config = replace(base, hard_limit=0.60, nli_model="lytang/MiniCheck-DeBERTa-L")

Or override via environment variables (env vars take precedence when using from_env after profile):

config = DirectorConfig.from_profile("finance")
config.coherence_threshold = 0.72
config.reranker_top_k_multiplier = 5

Profile + YAML¶

Combine a profile base with a YAML overlay:

# config.yaml
coherence_threshold: 0.72
chroma_persist_dir: /data/chroma
audit_log_path: /var/log/director/audit.jsonl

from director_ai import DirectorConfig

config = DirectorConfig.from_profile("finance")
yaml_overrides = DirectorConfig.from_yaml("config.yaml")

# Merge: YAML values override profile values
for field_name in DirectorConfig.__dataclass_fields__:
    yaml_val = getattr(yaml_overrides, field_name)
    default_val = DirectorConfig.__dataclass_fields__[field_name].default
    if yaml_val != default_val:
        setattr(config, field_name, yaml_val)

Adding Custom Profiles¶

For organisation-specific profiles, subclass or wrap:

from director_ai import DirectorConfig

INTERNAL_PROFILES = {
    "compliance": {
        "coherence_threshold": 0.80,
        "hard_limit": 0.60,
        "soft_limit": 0.80,
        "use_nli": True,
        "reranker_enabled": True,
        "w_logic": 0.5,
        "w_fact": 0.5,
    },
}

def load_profile(name: str) -> DirectorConfig:
    if name in INTERNAL_PROFILES:
        return DirectorConfig(**INTERNAL_PROFILES[name], profile=name)
    return DirectorConfig.from_profile(name)