> For the complete documentation index, see [llms.txt](https://stackpi-intelligent.gitbook.io/stackpi-intelligent/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://stackpi-intelligent.gitbook.io/stackpi-intelligent/stackpi-intelligent-cover/setup/cli.md).

# CLI

StackPi Intelligent

**Setup** StackPi Intelligent **Cover in the CLI**

**Requirements**

Before you begin, make sure you have the following:

* `OPENAI_API_KEY` set in your environment variables, which is required for calling the OpenAI API.
* Code Coverage tool: A Cobertura XML code coverage report is required for the tool to function correctly.
  * For example, in Python one could use `pytest-cov`. Add the `--cov-report=xml` option when running Pytest.
  * Note: We are actively working on adding more coverage types but please feel free to open a PR and contribute to `cover_agent/CoverageProcessor.py`

If running directly from the repository you will also need:

* Python installed on your system.
* Poetry installed for managing Python package dependencies. Installation instructions for Poetry can be found at <https://python-poetry.org/docs/>.

**Standalone Runtime**

StackPi Intelligent Cover can be installed as a Python Pip package or run as a standalone executable.

**Python Pip**

To install the Python Pip package directly via GitHub run the following command:

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```
pip install git+https://github.com/StackPiIntelligent-ai/StackPiIntelligent-cover.git
```

**Binary**

The binary can be run without any Python environment installed on your system (e.g. within a Docker container that does not contain Python). You can download the release for your system by navigating to the project's release page.

**Repository Setup**

Run the following command to install all the dependencies and run the project from source:

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```
poetry install
```

**Running the Code**

After downloading the executable or installing the Pip package you can run the Cover Agent to generate and validate unit tests. Execute it from the command line by using the following command:

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```
cover-agent \
  --source-file-path "<path_to_source_file>" \
  --test-file-path "<path_to_test_file>" \
  --project-root "<path_to_project_root>" \
  --code-coverage-report-path "<path_to_coverage_report>" \
  --test-command "<test_command_to_run>" \
  --test-command-dir "<directory_to_run_test_command>" \
  --coverage-type "<type_of_coverage_report>" \
  --desired-coverage <desired_coverage_between_0_and_100> \
  --max-iterations <max_number_of_llm_iterations> \
  --included-files "<optional_list_of_files_to_include>"
```

You can use the example code below to try out the Cover Agent. (Note that the usage\_examples file provides more elaborate examples of how to use the Cover Agent)

**Python**

Follow the steps in the README.md file located in the `templated_tests/python_fastapi/` directory to setup an environment, then return to the root of the repository, and run the following command to add tests to the **python fastapi** example:

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```
cover-agent \
  --source-file-path "templated_tests/python_fastapi/app.py" \
  --test-file-path "templated_tests/python_fastapi/test_app.py" \
  --project-root "templated_tests/python_fastapi" \
  --code-coverage-report-path "templated_tests/python_fastapi/coverage.xml" \
  --test-command "pytest --cov=. --cov-report=xml --cov-report=term" \
  --test-command-dir "templated_tests/python_fastapi" \
  --coverage-type "cobertura" \
  --desired-coverage 70 \
  --max-iterations 10
```

**Go**

For an example using **go** `cd` into `templated_tests/go_webservice`, set up the project following the `README.md`. To work with coverage reporting, you need to install `gocov` and `gocov-xml`. Run the following commands to install these tools:

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```
go install github.com/axw/gocov/gocov@v1.1.0
go install github.com/AlekSi/gocov-xml@v1.1.0
```

and then run the following command:

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```
cover-agent \
  --source-file-path "app.go" \
  --test-file-path "app_test.go" \
  --code-coverage-report-path "coverage.xml" \
  --test-command "go test -coverprofile=coverage.out && gocov convert coverage.out | gocov-xml > coverage.xml" \
  --test-command-dir $(pwd) \
  --coverage-type "cobertura" \
  --desired-coverage 70 \
  --max-iterations 1
```

**Java**

For an example using **java** `cd` into `templated_tests/java_gradle`, set up the project following the README.md. To work with jacoco coverage reporting, follow the README.md Requirements section: and then run the following command:

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```
cover-agent \
  --source-file-path="src/main/java/com/davidparry/cover/SimpleMathOperations.java" \
  --test-file-path="src/test/groovy/com/davidparry/cover/SimpleMathOperationsSpec.groovy" \
  --code-coverage-report-path="build/reports/jacoco/test/jacocoTestReport.csv" \
  --test-command="./gradlew clean test jacocoTestReport" \
  --test-command-dir=$(pwd) \
  --coverage-type="jacoco" \
  --desired-coverage=70 \
  --max-iterations=1
```

**Outputs**

A few debug files will be outputted locally within the repository (that are part of the `.gitignore`)

* `run.log`: A copy of the logger that gets dumped to your `stdout`
* `test_results.html`: A results table that contains the following for each generated test:
  * Test status
  * Failure reason (if applicable)
  * Exit code,
  * `stderr`
  * `stdout`
  * Generated test

**Additional logging**

If you set an environment variable `WANDB_API_KEY`, the prompts, responses, and additional information will be logged to [Weights and Biases](https://wandb.ai/).

**Using other LLMs**

This project uses LiteLLM to communicate with OpenAI and other hosted LLMs (supporting 100+ LLMs to date). To use a different model other than the OpenAI default you'll need to:

1. Export any environment variables needed by the supported LLM [following the LiteLLM instructions](https://litellm.vercel.app/docs/proxy/quick_start#supported-llms).
2. Call the name of the model using the `--model` option when calling Cover Agent.

For example (as found in the [LiteLLM Quick Start guide](https://litellm.vercel.app/docs/proxy/quick_start#supported-llms)):

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```
export VERTEX_PROJECT="hardy-project"
export VERTEX_LOCATION="us-west"

cover-agent \
  ...
  --model "vertex_ai/gemini-pro"
```

**OpenAI Compatible Endpoint**

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```
export OPENAI_API_KEY="<your api key>" # If <your-api-base> requires an API KEY, set this value.

cover-agent \
  ...
  --model "openai/<your model name>" \
  --api-base "<your-api-base>"
```

**Azure OpenAI Compatible Endpoint**

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```
export AZURE_API_BASE="<your api base>" # azure api base
export AZURE_API_VERSION="<your api version>" # azure api version (optional)
export AZURE_API_KEY="<your api key>" # azure api key

cover-agent \
  ...
  --model "azure/<your deployment name>"
```