使用方法
- 复制安装命令，在自己的智能体环境安装前先检查源码包。
- 从原始文档核对所需工具、凭据和支持的宿主。
- 说明输入材料与期望交付物，并对照来源检查输出。
npx skills add https://github.com/cheaper-inference/omniroute --skill cli-eval开始前需了解
- 安装不包含模型订阅、API 额度或访问文件的权限。
- 仓库星数和安装量反映活跃情况，不等于独立质量或安全测试。
按源仓库内容呈现，保留标题、案例、代码、表格、链接以及原文引用的演示图片。
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Overview
Create and run evaluation suites, watch live benchmark progress, view scorecards, compare model performance, and integrate eval runs with CI workflows from the CLI.
Quick install
npm install -g omniroute # or: npx omniroute
omniroute --versionSubcommands
eval
Example:
omniroute evaleval suites
Example:
omniroute eval suiteseval list
Example:
omniroute eval listeval get <suiteId>
Example:
omniroute eval get <suiteId>eval create
Flags:
--file <path>
Example:
omniroute eval createeval run <suiteId>
Flags:
-m, --model <id>--combo <name>--concurrency <n>--tag <tag>--watch
Example:
omniroute eval run <suiteId>eval list
Flags:
--suite <id>--status <s>--since <ts>--limit <n>
Example:
omniroute eval listeval get <runId>
Example:
omniroute eval get <runId>eval results <runId>
Flags:
--failed
Example:
omniroute eval results <runId>eval cancel <runId>
Flags:
--yes
Example:
omniroute eval cancel <runId>eval scorecard <runId>
Example:
omniroute eval scorecard <runId>simulate [prompt]
Flags:
--file <path>-m, --model <id>--combo <name>--reasoning-effort <level>--thinking-budget <n>--explain
Example:
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OmniRoute — CLI Evals
Requires the omniroute CLI. See CLI entry-point skill for install + global flags.
What are evals?
Evals are automated test suites that score LLM outputs against expected answers or rubrics. OmniRoute stores suites and run results in its local database.
Eval suites
omniroute eval suites list # List all eval suites
omniroute eval suites list --json # JSON output
omniroute eval suites get <suiteId> # Full suite definitionCreate a suite
omniroute eval suites create \
--name "code-quality" \
--rubric "exact-match" \
--samples-file ./samples.jsonl # JSONL: {input, expected_output}Rubric options: exact-match, contains, llm-judge, regex.
--samples-file format (one JSON object per line):
{"input": "What is 2+2?", "expected_output": "4"}
{"input": "Translate 'hello' to Spanish", "expected_output": "hola"}Run an eval
omniroute eval suites run <suiteId> \
--model claude-sonnet-4-6 # Run suite against a specific model
omniroute eval suites run <suiteId> \
--model gpt-4o \
--watch # Live TUI progress (EvalWatch)The run is asynchronous. Use --watch for a live terminal dashboard or poll manually:
RUN_ID=$(omniroute eval suites run <suiteId> --model claude-sonnet-4-6 --output json | jq -r '.id')
omniroute eval get $RUN_IDManage runs
omniroute eval list # List all eval runs
omniroute eval list --json
omniroute eval get <runId> # Run details (status, model, score)
omniroute eval results <runId> # Per-sample results
omniroute eval scorecard <runId> # Full scorecard with pass/fail per sample
omniroute eval cancel <runId> # Cancel a running evalScorecard output
omniroute eval scorecard <runId> --output jsonResponse fields per sample:
{
"id": "sample-1",
"score": 0.95,
"passed": true,
"input": "What is 2+2?",
"output": "4",
"expected": "4"
}Comparing models
Run the same suite against multiple models and compare:
for MODEL in claude-sonnet-4-6 gpt-4o gemini-2.0-flash; do
omniroute eval suites run $SUITE_ID --model $MODEL --output json | jq '{model: .model, score: .score}'
doneCI integration
# Run and fail CI if score drops below threshold
SCORE=$(omniroute eval suites run $SUITE_ID --model claude-sonnet-4-6 --output json | jq -r '.score')
python3 -c "import sys; score=float('$SCORE'); sys.exit(0 if score >= 0.90 else 1)"Errors
suites createfails withinvalid rubric→ use one of:exact-match,contains,llm-judge,regexsuites runreturnsmodel not found→ verify model ID withomniroute models --search <name>eval getshowsstatus: failed→ checkomniroute logs --search evalfor error detailsscorecardreturns empty results → the run may still berunning; pollomniroute eval get <runId>untilstatusiscompleted
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