promptfoo--promptfoo/site/docs/integrations/circle-ci.md

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CircleCI	Automate LLM testing in CircleCI pipelines with promptfoo. Configure caching, API keys, and evaluation workflows to validate prompts and models in CI/CD environments.

Setting up Promptfoo with CircleCI

This guide shows how to integrate promptfoo's LLM evaluation into your CircleCI pipeline. This allows you to automatically test your prompts and models whenever changes are made to your repository.

Prerequisites

• A CircleCI account connected to your repository
• Your LLM provider's API keys (e.g., OpenAI API key)
• Basic familiarity with CircleCI configuration

Configuration Steps

1. Create CircleCI Configuration

Create a .circleci/config.yml file in your repository. Here's a basic configuration that installs promptfoo and runs evaluations:

```yaml
version: 2.1
jobs:
  evaluate_prompts:
    docker:
      - image: cimg/node:lts
    steps:
      - checkout

      - restore_cache:
          keys:
            - promptfoo-cache-v1-{{ .Branch }}-{{ checksum "prompts/**/*" }}
            - promptfoo-cache-v1-{{ .Branch }}
            - promptfoo-cache-v1-

      - run:
          name: Install promptfoo
          command: npm install -g promptfoo

      - run:
          name: Run prompt evaluation
          command: promptfoo eval -c promptfooconfig.yaml --prompts prompts/**/*.json --share -o output.json
          environment:
            OPENAI_API_KEY: ${OPENAI_API_KEY}
            PROMPTFOO_CACHE_PATH: ~/.promptfoo/cache

      - save_cache:
          key: promptfoo-cache-v1-{{ .Branch }}-{{ checksum "prompts/**/*" }}
          paths:
            - ~/.promptfoo/cache

      - store_artifacts:
          path: output.json
          destination: evaluation-results

workflows:
  version: 2
  evaluate:
    jobs:
      - evaluate_prompts:
          filters:
            paths:
              - prompts/**/*
```

2. Set Up Environment Variables

1. Go to your project settings in CircleCI
2. Navigate to Environment Variables
3. Add your LLM provider's API keys:
   • e.g. Add OPENAI_API_KEY if you're using OpenAI

3. Configure Caching (Optional but Recommended)

The configuration above includes caching to save time and API costs. The cache:

• Stores LLM API responses
• Is keyed by branch and content hash
• Is saved in ~/.promptfoo/cache

4. Storing Results

The configuration stores the evaluation results as artifacts:

• Results are saved to output.json
• CircleCI makes these available in the Artifacts tab
• The --share flag creates a shareable web URL for results

Advanced Configuration

Adding Custom Test Steps

You can add custom steps to process the evaluation results:

```yaml
- run:
    name: Check evaluation results
    command: |
      if jq -e '.results.stats.failures > 0' output.json; then
        echo "Evaluation had failures"
        exit 1
      fi
```

Parallel Evaluation

For large test suites, you can parallelize evaluations:

```yaml
jobs:
  evaluate_prompts:
    parallelism: 3
    steps:
      - run:
          name: Split tests
          command: |
            prompts=$(find prompts -name "*.json" | circleci tests split)
            promptfoo eval -c promptfooconfig.yaml --prompts $prompts
```

Example Output

After the evaluation runs, you'll see:

• Test results in the CircleCI UI
• Artifacts containing the full evaluation data
• A shareable link to view results in the promptfoo web viewer
• Any test failures will cause the CircleCI job to fail

Troubleshooting

Common issues and solutions:

1. Cache not working:

   • Verify the cache key matches your configuration
   • Check that the cache path exists
   • Ensure file permissions are correct

2. API key errors:

   • Confirm environment variables are set in CircleCI
   • Check for typos in variable names
   • Verify API key permissions

3. Evaluation timeout:

   • Adjust the no_output_timeout setting in your job
   • Consider splitting tests into smaller batches

For more details on promptfoo configuration, see the configuration reference.