umbrela-quickstart

name	umbrela-quickstart
description	Use when working with umbrela CLI commands (judge, evaluate), backend selection (gpt, gemini, hf, os, ensemble), qrel handling (dl19-passage, dl20-passage, etc.), relevance labels (0–3), or introspection (doctor, describe, schema, validate). Covers all entry points, flags, and evaluation workflows.

Umbrela Quickstart

Reference for the umbrela CLI — the tool for LLM-based relevance assessment of query-passage pairs, reproducing the Bing BRELA methodology with 4-class labels (0–3).

CLI Entry Point

umbrela <command> [options]

Primary Commands

Command	Purpose
judge	Run a single backend on direct JSON or batch JSONL input
evaluate	Generate modified qrels and compute nDCG@10 from a result file

Introspection Commands

Command	Purpose
doctor	Check Python version, API keys, backend readiness
describe <cmd>	Machine-readable command contract
schema <name>	Print JSON Schema for inputs/outputs
validate <target>	Validate inputs without running models
prompt list|show|render	Inspect and render prompt templates
view <path>	Inspect existing artifact files

Quick Workflow

# 1. Check environment
umbrela doctor

# 2. Judge query-passage pairs
umbrela judge --backend gpt --model gpt-4o \
  --input-file pairs.jsonl --output-file judgments.jsonl

# 3. Evaluate against standard qrels
umbrela evaluate --backend gpt --model gpt-4o \
  --qrel dl19-passage --result-file run.trec

Reference Files

Read these on demand for details:

• references/cli-examples.md — Common invocations for each command
• references/input-output-examples.md — JSONL format examples and judgment output
• references/backends.md — Backend selection guide and provider configuration
• references/qrel-handling.md — Standard qrels, label meanings, and evaluation workflow

Key Concepts

• Labels 0–3: 0=irrelevant, 1=related but doesn't answer, 2=partially answers, 3=perfectly answers
• Backends: gpt (OpenAI/Azure/OpenRouter), gemini (Vertex AI), hf (HuggingFace), os (FastChat), ensemble (majority voting, evaluate only)
• Prompt types: bing (BRELA-style, default) or basic
• Modified qrels: LLM judgments merged into standard qrels to fill "holes" (unjudged pairs)

Gotchas

• --backend ensemble is only valid for evaluate, not judge.
• --execution-mode async is only supported for GPT backend.
• The evaluate command requires pyserini for qrel loading and passage retrieval. Install with uv sync --extra pyserini.
• evaluate writes two artifacts: a modified qrel file in modified_qrels/ and a confusion matrix PNG in conf_matrix/.
• --judge-cat controls which relevance categories to evaluate. Default 0,1,2,3 judges all pairs. Use 2,3 to focus on relevant documents only.
• --min-judgment on judge filters output — pairs below the threshold go to --filtered-output-file.
• --few-shot-count controls few-shot examples in the prompt. Examples are drawn from the qrel dataset. Default is 0 (zero-shot).
• Config file (.umbrela.toml or ~/.config/umbrela/config.toml) can set defaults.