chore: import upstream snapshot with attribution
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This commit is contained in:
wehub-resource-sync
2026-07-13 13:24:08 +08:00
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# config-csv-metadata (CSV Metadata Example)
You can run this example with:
```bash
npx promptfoo@latest init --example config-csv-metadata
cd config-csv-metadata
```
## Usage
This example demonstrates how to use metadata columns in CSV and Excel test files to organize and filter your test cases. You can see more details on how to build test cases from CSV in the [Promptfoo docs](https://www.promptfoo.dev/docs/configuration/test-cases/#csv-format)
### Files
- `promptfooconfig.yaml`: Configuration file with a simple prompt and provider setup
- `tests.csv`: Test cases with metadata columns for categorization and filtering
- `tests.xlsx`: Same test cases in Excel format (optional - requires `npm install read-excel-file`)
### Metadata Columns
The CSV/Excel file includes two types of metadata columns:
1. `__metadata:category` - Single value metadata for broad categorization
2. `__metadata:tags[]` - Array metadata for multiple tags, with comma separation and escape support
### Running the Example
Basic evaluation:
```bash
promptfoo eval
```
To use Excel file instead of CSV:
```bash
# First install the read-excel-file package
npm install read-excel-file
# Then run with Excel file
promptfoo eval -c promptfooconfig.yaml -t file://tests.xlsx
```
Filter by category:
```bash
promptfoo eval --filter-metadata category=technology
```
Filter by tags:
```bash
promptfoo eval --filter-metadata tags=ai
```
Note that array metadata values (tags) support escaped commas. For example, "global\,warming" is treated as a single tag.
### Expected Output
The example includes basic assertions using the `__expected` column to verify outputs contain relevant keywords.
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# yaml-language-server: $schema=https://promptfoo.dev/config-schema.json
description: Loading test cases and metadata from CSV files
prompts:
- 'Tell me about {{topic}}'
providers:
- id: openai:gpt-4
config:
temperature: 0.7
tests: file://tests.csv
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topic,__expected1,__expected2,__metadata:category,__metadata:tags[],__config:__expected:threshold,__config:__expected2:threshold
"machine learning","contains: algorithm","llm-rubric:Does this describe {{topic}} accurately?","technology","ai,data science,algorithms",0.9,0.8
"quantum physics","contains: quantum","llm-rubric:Does this describe {{topic}} accurately?","science","physics,advanced\,theory,quantum",0.85,0.75
"climate change","contains: temperature","llm-rubric:Does this describe {{topic}} inaccurately?","environment","science,global\,warming,research",0.7,0.675
1 topic __expected1 __expected2 __metadata:category __metadata:tags[] __config:__expected:threshold __config:__expected2:threshold
2 machine learning contains: algorithm llm-rubric:Does this describe {{topic}} accurately? technology ai,data science,algorithms 0.9 0.8
3 quantum physics contains: quantum llm-rubric:Does this describe {{topic}} accurately? science physics,advanced\,theory,quantum 0.85 0.75
4 climate change contains: temperature llm-rubric:Does this describe {{topic}} inaccurately? environment science,global\,warming,research 0.7 0.675
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