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We should treat this as the first step towards building a robust eval story for BQ tools. PiperOrigin-RevId: 807247053
Instructions
Run Evaluation
- Set environment variables in your terminal:
export GOOGLE_GENAI_USE_VERTEXAI=FALSE
export GOOGLE_API_KEY=<your_api_key>
export GOOGLE_CLOUD_PROJECT=<your_bigquery_project>
- Change to the current directory:
cd third_party/py/google/adk/tests/integration/fixture/bigquery_agent/
- Customize the evaluation dataset to the environment
GOOGLE_CLOUD_PROJECTby replacing the placeholder to the real project set in your environment:
sed -e "s:\${GOOGLE_CLOUD_PROJECT}:${GOOGLE_CLOUD_PROJECT}:g" simple.test.json -i
- Run the following command as per https://google.github.io/adk-docs/evaluate/#3-adk-eval-run-evaluations-via-the-cli:
adk eval . simple.test.json --config_file_path=test_config.json
If it fails, re-run with --print_detailed_results flag to see more details
on turn-by-turn evaluation.
Generate Evaluation dataset
- Set environment variables in your terminal:
export GOOGLE_GENAI_USE_VERTEXAI=FALSE
export GOOGLE_API_KEY=<your_api_key>
export GOOGLE_CLOUD_PROJECT=<your_bigquery_project>
- Set up google application default credentials on your machine.
gcloud auth application-default login
- Change to the directory containing agent folder:
cd third_party/py/google/adk/tests/integration/fixture/
- Run the following command to start the ADK web app:
adk web
- Open the ADK web UI in your browser http://127.0.0.1:8000/dev-ui/?app=bigquery_agent.
- Create an evaluation dataset by following these steps.
This would generate file
bigquery_agent/simple.evalset.json. - Note that this evaluation data would be tied to the agent interaction in the
GOOGLE_CLOUD_PROJECTset in your environment. To normalize it by replacing the real project set in your environment to a placeholder, let's run the following command:
sed -e "s:${GOOGLE_CLOUD_PROJECT}:\${GOOGLE_CLOUD_PROJECT}:g" bigquery_agent/simple.evalset.json > bigquery_agent/simple.test.json