> ## Documentation Index
> Fetch the complete documentation index at: https://docs.gaussia.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Regulatory

> Evaluate AI response compliance against a regulatory document corpus

## Overview

The **Regulatory** metric evaluates whether AI responses comply with a regulatory corpus (laws, policies, guidelines). It uses a RAG-based pipeline to:

1. Retrieve relevant regulatory chunks for each interaction
2. Check for contradictions between the response and the retrieved chunks
3. Score compliance per interaction and aggregate per session

## Verdicts

| Verdict         | Meaning                                      |
| --------------- | -------------------------------------------- |
| `COMPLIANT`     | Response supports regulatory requirements    |
| `NON_COMPLIANT` | Response contradicts regulatory requirements |
| `IRRELEVANT`    | No relevant regulatory content found         |

## Usage

```python theme={null}
from gaussia.metrics.regulatory import Regulatory
from gaussia.connectors import MyCorpusConnector
from gaussia.embedders import SentenceTransformerEmbedder
from gaussia.rerankers import MyReranker

embedder = SentenceTransformerEmbedder(model="all-mpnet-base-v2")
reranker = MyReranker()
corpus = MyCorpusConnector(path="./regulations/")

results = Regulatory.run(
    MyRetriever,
    corpus_connector=corpus,
    embedder=embedder,
    reranker=reranker,
)

for r in results:
    print(f"Compliance: {r.compliance_score:.2f} ({r.verdict})")
    print(f"Supporting: {r.total_supporting_chunks}, Contradicting: {r.total_contradicting_chunks}")
```

## Parameters

| Parameter                 | Type              | Default             | Description                             |
| ------------------------- | ----------------- | ------------------- | --------------------------------------- |
| `retriever`               | `type[Retriever]` | *required*          | Retriever class                         |
| `corpus_connector`        | `CorpusConnector` | *required*          | Loader for regulatory documents         |
| `embedder`                | `Embedder`        | *required*          | Text embedder for retrieval             |
| `reranker`                | `Reranker`        | *required*          | Reranker for contradiction detection    |
| `statistical_mode`        | `StatisticalMode` | `FrequentistMode()` | Statistical computation mode            |
| `chunk_size`              | `int`             | `1000`              | Characters per chunk                    |
| `chunk_overlap`           | `int`             | `100`               | Overlap between chunks                  |
| `top_k`                   | `int`             | `10`                | Max chunks to retrieve                  |
| `similarity_threshold`    | `float`           | `0.3`               | Minimum cosine similarity for retrieval |
| `contradiction_threshold` | `float`           | `0.6`               | Score below which a chunk contradicts   |
| `compliance_threshold`    | `float`           | `0.5`               | Minimum score for COMPLIANT verdict     |

## Output schema

### RegulatoryMetric

| Field                        | Type                          | Description                  |
| ---------------------------- | ----------------------------- | ---------------------------- |
| `session_id`                 | `str`                         | Session identifier           |
| `assistant_id`               | `str`                         | Assistant identifier         |
| `n_interactions`             | `int`                         | Interactions evaluated       |
| `compliance_score`           | `float`                       | Aggregated compliance score  |
| `compliance_score_ci_low`    | `float \| None`               | Lower CI (Bayesian only)     |
| `compliance_score_ci_high`   | `float \| None`               | Upper CI (Bayesian only)     |
| `verdict`                    | `str`                         | Session-level verdict        |
| `total_supporting_chunks`    | `int`                         | Total supporting evidence    |
| `total_contradicting_chunks` | `int`                         | Total contradicting evidence |
| `interactions`               | `list[RegulatoryInteraction]` | Per-interaction breakdown    |

<Note>
  Requires the `regulatory` extra: `pip install "gaussia[regulatory]"`.
</Note>