verifily 1.4.2

ML data quality gate — ingest, validate, and ship datasets with confidence.

Verifily

ML data quality gate. Ingest, validate, and ship datasets with confidence.

Verifily catches contamination, PII leaks, SQL template leakage, contract violations, and metric regressions before they reach production. It runs locally — no network, no GPU, no external services.

One command gates your CI pipeline. Exit 0 means ship.

Install

pip install -e .

For integrations (HuggingFace, W&B, MLflow) and API server:

pip install -e ".[all]"

60-Second Quick Start

# 1. Scaffold a project
verifily quickstart my_project

# 2. Ingest raw data (JSONL, CSV, Parquet, or HuggingFace)
verifily ingest --in my_project/data/raw/sample.csv \
                --out my_project/data/artifact \
                --schema sft

# 3. Run the CI gate
verifily pipeline --config my_project/verifily.yaml --ci
# Exit 0 = SHIP, 1 = DONT_SHIP, 2 = INVESTIGATE

Or run the full demo end-to-end:

bash scripts/demo_quickstart_ci.sh

What Verifily Prevents

Risk	How Verifily catches it
Train/eval data leakage	Exact-match + Jaccard contamination detection via MinHash LSH
SQL template leakage	Three-tier NL2SQL gate: exact SQL, template fingerprint, question near-dup
PII in training data	Regex-based PII scan with configurable thresholds and redaction
Missing or corrupt artifacts	Run contract validation (hashes, configs, eval results)
Metric regressions	Threshold checks against baselines with delta tracking
Ambiguous ship decisions	Deterministic gate: blockers always block, no silent passes
Dataset drift	Privacy-safe fingerprinting and diff without raw data exposure

Supported Schemas

8 canonical dataset types, auto-detected from field names:

Schema	Required fields	Use case
sft	instruction, output	Supervised fine-tuning
qa	question, answer	Question answering
classification	text, label	Text classification
chat	messages	Multi-turn conversations
summarization	document, summary	Summarization tasks
translation	source, target	Translation pairs
rm_pairwise	prompt, chosen, rejected	Reward model training
nl2sql	question, sql, schema	Natural language to SQL

CLI Commands

Command	Purpose
verifily quickstart <path>	Scaffold a working project
verifily ingest	Normalize raw data to artifact format (JSONL, CSV, Parquet, hf://)
verifily pipeline --ci	Run full quality gate (CI mode)
verifily report	Dataset quality report with PII scan
verifily contamination	Detect train/eval overlap
verifily contract-check	Validate run artifacts
verifily fingerprint	Privacy-safe dataset summary
verifily diff-datasets	Compare two datasets
verifily ci-init	Generate GitHub/GitLab CI config
verifily serve	Start API server
verifily version	Show version, Python, platform

NL2SQL Commands

Command	Purpose
verifily nl2sql validate	Validate NL2SQL dataset structure
verifily nl2sql fingerprint	SQL normalization + template fingerprinting
verifily nl2sql split	Leakage-resistant train/eval splitting
verifily nl2sql gate	Three-tier contamination gate for NL2SQL

Integrations

All opt-in with lazy imports. No hard dependencies.

Integration	What it does
HuggingFace Datasets	Load datasets via hf:// URIs
Weights & Biases	Log decisions, metrics, and artifacts
MLflow	Track runs with model registry integration
GitHub Actions	Pre-built action + CI workflow generator

# HuggingFace
verifily ingest --in "hf://squad" --out datasets/squad --schema qa

# W&B + MLflow
verifily pipeline --config pipeline.yaml --wandb --mlflow

CI Exit Codes

Code	Label	Meaning
0	SHIP	All quality gates passed
1	DONT_SHIP	One or more blockers failed
2	INVESTIGATE	Risk flags present, no hard blockers
3	CONTRACT_FAIL	Run contract invalid
4	TOOL_ERROR	Invalid config or unexpected error

Documentation

• Product Overview
• Quick Install
• 3-Minute Quickstart
• Decision Gate
• Dataset Fingerprints
• CI Init
• API & Jobs
• Monitor
• Versioning & Stability
• Changelog

Versioning

Verifily follows Semantic Versioning. See VERSIONING.md.

Current version: 1.4.1

Stability Guarantees

• Deterministic outputs — fixed seed produces identical results across runs
• Stable contracts — run_contract_v1 schema is frozen within the v1.x line
• Stable exit codes — 0/1/2/3/4 semantics are frozen
• Backward compatibility within MAJOR version — artifacts from any v1.x release are accepted
• 1,300+ tests — all deterministic, no network, no GPU

License

Business Source License 1.1 (BSL-1.1). See LICENSE for details.

You may use Verifily for any purpose except offering it as a commercial data quality or ML pipeline gating service to third parties. On 2030-02-16, the license converts to Apache 2.0.