Kiln CLI including project packager

.github/workflows/debug_detector.yml

@@ -17,7 +17,7 @@ jobs:
           found=0
 
           echo "Checking for python print statements"
-          prints=$(grep -nR --include='*.py' --exclude-dir=node_modules --exclude-dir=.venv --exclude-dir=.git --exclude-dir=.github --exclude-dir=build --exclude-dir=dist --exclude-dir=.svelte-kit -e 'print(' . || true)
+          prints=$(grep -nRP --include='*.py' --exclude-dir=node_modules --exclude-dir=.venv --exclude-dir=.git --exclude-dir=.github --exclude-dir=build --exclude-dir=dist --exclude-dir=.svelte-kit -e '(?<!\.)\bprint\(' . || true)
           if [ -n "$prints" ]; then
             echo "$prints"
             found=1

libs/core/README.md

@@ -107,9 +107,19 @@ for task in tasks:
 
 If you've already created a Kiln task and want to run it as part of a Python app you can follow this example.
 
+**Step 1: Export your Kiln task/project**
+
+You can run any Kiln task from code using it's project file/folder on disk. However, these folders can contain thousands of files relating to past runs and evals, which is more than you probably want to deploy to a service. Only a few of these files are needed for running the task: you can export a minimal project folder with on the necessary files to run a task by running our CLI:
+
+```bash
+uvx kiln_ai package_project "/path/to/your/project.kiln" -t TASK_ID_TO_EXPORT
+```
+
+**Step 2: Run Kiln Task from Code**
+
 Prerequisites:
 
-- Already have a Kiln Task created and saved to disk at `TASK_PATH`. It doesn't matter if you created it using the Kiln app or the library.
+- Already have a Kiln Task created and saved to disk at `TASK_PATH`. It doesn't matter if you created it using the Kiln app, the Kiln library, or exported it using the command above.
 - Set a default run configuration in the Kiln UI specifying how to run the task: model, AI provider, etc. Alternatively you can create a RunConfigProperties instance in code.
 - Set up any API keys required for the task. If running on the same machine as the Kiln app, these will already be saved in `~/.kiln_ai/settings.yaml` and will be loaded automatically. If running on a server, you can set the required environment variables (see `libs/core/kiln_ai/utils/config.py` for a list).
 - If your task uses RAG, ensure you have run search indexing on this machine with the Kiln UI or via the library.

libs/core/kiln_ai/cli/__init__.py

@@ -0,0 +1,3 @@
+from kiln_ai.cli.cli import app
+
+__all__ = ["app"]

libs/core/kiln_ai/cli/cli.py

@@ -0,0 +1,12 @@
+import typer
+
+from kiln_ai.cli.commands import package_project, projects, tasks
+
+app = typer.Typer(
+    help="Kiln AI CLI - Build AI systems with evals, data gen, fine-tuning, and more.",
+    no_args_is_help=True,
+)
+
+app.add_typer(projects.app, name="projects")
+app.add_typer(tasks.app, name="tasks")
+app.command(name="package_project")(package_project.package_project)