Add LLMOps basic template

contrib/templates/llmops-basic/README.md

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+# LLMOps basic template
+
+This template introduces a base structure for organizing LLMOps projects
+using DABs, Unity Catalog and MLflow.
+
+Install it using
+
+```
+databricks bundle init https://github.com/databricks/bundle-examples --template-dir contrib/templates/llmops-basic
+```

contrib/templates/llmops-basic/databricks_template_schema.json

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+{
+  "properties": {
+    "project_name": {
+      "type": "string",
+      "default": "llmops_basic",
+      "description": "Name of the LLMOps project (use underscores, no hyphens)",
+      "order": 1
+    },
+    "catalog_name_dev": {
+      "type": "string",
+      "default": "dev_catalog",
+      "description": "Name of the Unity Catalog for development environment",
+      "order": 2
+    },
+    "catalog_name_prod": {
+      "type": "string",
+      "default": "prod_catalog",
+      "description": "Name of the Unity Catalog for production environment",
+      "order": 3
+    },
+    "workspace_host_dev": {
+      "type": "string",
+      "default": "https://your-workspace.azuredatabricks.net/",
+      "description": "Databricks workspace URL for development",
+      "order": 4
+    },
+    "workspace_host_prod": {
+      "type": "string",
+      "default": "https://your-workspace.azuredatabricks.net/",
+      "description": "Databricks workspace URL for production",
+      "order": 5
+    }
+  }
+}
+

contrib/templates/llmops-basic/template/{{.project_name}}/.gitignore

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+.databricks/
+.bundle/
+__pycache__/
+*.py[cod]
+*$py.class
+*.so
+.Python
+venv/
+env/
+ENV/
+.ipynb_checkpoints/
+*.ipynb_checkpoints
+.vscode/
+.idea/
+*.swp
+*.swo
+*~
+.DS_Store
+Thumbs.db
+mlruns/
+*.log
+

contrib/templates/llmops-basic/template/{{.project_name}}/README.md.tmpl

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+# {{.project_name}}
+
+End-to-end LLMOps project for sentiment analysis of reviews using Databricks.
+
+## Overview
+
+This example demonstrates a complete LLMOps pipeline for building, evaluating, and deploying a sentiment analysis model.
+
+**Pipeline stages:**
+- Data preparation
+- Model build and evaluation with MLflow
+- Model deployment to serving endpoint
+- Batch inference
+
+## Requirements
+
+- Databricks CLI (v0.218.0+)
+- Unity Catalog enabled
+- Required permissions on the catalog:
+  - `USE CATALOG` - to access the catalog
+  - `CREATE SCHEMA` - to create schemas
+
+## Quick Start
+
+**Deploy:**
+```bash
+databricks bundle deploy -t dev
+```
+
+**Run pipeline:**
+```bash
+databricks bundle run model_preprocessing -t dev
+databricks bundle run model_build_evaluation -t dev
+databricks bundle run model_endpoint_deploy -t dev
+databricks bundle run model_inference -t dev
+```
+
+## Configuration
+
+- **Dev Catalog**: `{{.catalog_name_dev}}`
+- **Prod Catalog**: `{{.catalog_name_prod}}`
+
+Edit `databricks.yml` to customize catalog names, schema name, model name, and experiment settings.
+

contrib/templates/llmops-basic/template/{{.project_name}}/databricks.yml.tmpl

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+# This is a Databricks Asset Bundle for {{.project_name}}.
+bundle:
+  name: "{{.project_name}}"
+
+variables:
+  catalog_name:
+    description: "Name of the UC catalog to use"
+    default: "default_catalog"
+  schema_name:
+    description: "Name of the UC schema to use"
+    default: "sentiment_agent_project"
+  model_name:
+    description: "Name of the UC model to use"
+    default: "sentiment_agent"
+  experiment_name:
+    description: "Name of experiment"
+    default: "/Users/${workspace.current_user.userName}/${bundle.target}_sentiment_agent"
+
+include:
+  - resources/*.yml
+
+targets:
+  dev:
+    mode: development
+    default: true
+    workspace:
+      host: {{.workspace_host_dev}}
+    variables:
+      catalog_name: {{.catalog_name_dev}}
+
+  prod:
+    mode: production
+    workspace:
+      host: {{.workspace_host_prod}}
+      root_path: /Shared/.bundle/prod/${bundle.name}
+    variables:
+      catalog_name: {{.catalog_name_prod}}
+    {{- if not is_service_principal}}
+    run_as:
+      # This runs as {{user_name}} in production. Alternatively,
+      # a service principal could be used here using service_principal_name
+      # (see Databricks documentation).
+      user_name: {{user_name}}
+    {{end -}}