CLI Reference
Documents 7 CLI commands for evaluating retrieval systems, managing baselines, and detecting drift.
What this file does
Documents 7 CLI commands for evaluating retrieval systems, managing baselines, and detecting drift.
When to use it
- You need to run evaluation on pre-computed retrieval results
- You want to compare two evaluation runs side by side
- You need to detect regression from a stored baseline
- You want to validate a golden set structure
Assumes this stack
CLI Reference
ir-eval provides a Typer-based CLI with 7 commands for evaluation, baseline management, and drift detection.
Global Usage
ir-eval [COMMAND] [OPTIONS]
Commands
evaluate — Evaluate pre-computed results
Primary evaluation path. Takes pre-computed retrieval results and evaluates against a golden set.
ir-eval evaluate RESULTS_FILE [OPTIONS]
| Option | Type | Default | Description |
|---|---|---|---|
--golden | PATH | required | Path to golden set JSON |
--top-k | INT | 10 | Cutoff for @k metrics |
--output | PATH | — | Save EvalRun to JSON |
--format | STR | console | Output: console, markdown, json |
Example:
ir-eval evaluate results.json --golden golden.json --format markdown --output run.json
run — Live evaluation via adapter
Evaluate a running retrieval system using an adapter registered via entry points.
ir-eval run GOLDEN_SET [OPTIONS]
| Option | Type | Default | Description |
|---|---|---|---|
--adapter | STR | required | Entry point name of adapter |
--top-k | INT | 10 | Results to retrieve per query |
--output | PATH | — | Save EvalRun to JSON |
--format | STR | console | Output format |
Example:
ir-eval run golden.json --adapter research-kb --top-k 10
baseline set — Pin a baseline
Pin an evaluation run as the baseline for drift detection.
ir-eval baseline set RUN_FILE [OPTIONS]
| Option | Type | Default | Description |
|---|---|---|---|
--notes | STR | — | Notes about this baseline |
--store-dir | PATH | .ir-eval/baselines | Storage directory |
baseline show — View current baseline
ir-eval baseline show GOLDEN_SET_NAME [OPTIONS]
| Option | Type | Default | Description |
|---|---|---|---|
--store-dir | PATH | .ir-eval/baselines | Storage directory |
compare — Compare two runs
Side-by-side comparison of two evaluation runs.
ir-eval compare RUN_A RUN_B [OPTIONS]
| Option | Type | Default | Description |
|---|---|---|---|
--format | STR | console | Output format |
Example:
ir-eval compare baseline.json current.json --format markdown
drift — Detect regression from baseline
Run evaluation and compare against stored baseline with statistical tests.
ir-eval drift GOLDEN_SET [OPTIONS]
| Option | Type | Default | Description |
|---|---|---|---|
--adapter | STR | required | Adapter name |
--top-k | INT | 10 | Results per query |
--exit-code | BOOL | false | Exit 1 on CRITICAL drift |
--ci | BOOL | false | Show confidence intervals |
--format | STR | console | Output format |
--store-dir | PATH | .ir-eval/baselines | Baseline storage |
validate — Validate golden set
Check golden set structure and show distribution summary.
ir-eval validate GOLDEN_SET
history — Baseline history
Show baseline change history for a golden set.
ir-eval history GOLDEN_SET_NAME [OPTIONS]
| Option | Type | Default | Description |
|---|---|---|---|
--store-dir | PATH | .ir-eval/baselines | Storage directory |
What's inside
7 commands with options tables, 6 code examples, and global usage syntax.
Change this for your project
- Replace
ir-evalwith your own CLI entry point name - Replace
.ir-eval/baselineswith your preferred baseline storage path
Where it goes
Keep alongside your test suite. Used to define and score model evaluations.
Worth borrowing
- Separates pre-computed evaluation from live adapter evaluation
- Uses a baseline set/show/drift workflow for regression detection
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