> ## Documentation Index > Fetch the complete documentation index at: https://docs.budecosystem.com/llms.txt > Use this file to discover all available pages before exploring further. # Actions Reference > Complete reference for all pipeline actions ## Overview Actions are the building blocks of pipelines. Each action performs a specific operation and can be configured with parameters, outputs, and conditions. ## Control Flow Actions ### Log Write messages to execution logs for debugging and monitoring. **Parameters:** * `message` (string, required): The message to log * `level` (string): Log level - `info`, `warning`, `error`, `debug` **Example:** ```python theme={null} { "action": "log", "params": { "message": "Starting deployment process", "level": "info" } } ``` ### Conditional Branch Execute different paths based on conditions. **Parameters:** * `condition` (string, required): Boolean expression to evaluate * `branches` (object): Named branches with their conditions **Example:** ```python theme={null} { "action": "conditional", "params": { "condition": "steps.health_check.output.status == 'healthy'" } } ``` ### Transform Modify or transform data between steps. **Parameters:** * `operation` (string, required): Transformation type * `input` (any): Input data to transform * `template` (string): Jinja2 template for transformation ### Aggregate Combine outputs from multiple parallel actions. **Parameters:** * `sources` (array, required): List of step IDs to aggregate * `strategy` (string): Aggregation strategy - `merge`, `concat`, `first` ### Set Output Define pipeline-level outputs. **Parameters:** * `key` (string, required): Output variable name * `value` (any, required): Output value **Example:** ```python theme={null} { "action": "set_output", "params": { "key": "endpoint_url", "value": "{{steps.deploy.output.endpoint_url}}" } } ``` ### Wait Until Pause execution until a condition is met. **Parameters:** * `condition` (string, required): Condition to wait for * `timeout_seconds` (integer): Maximum wait time * `poll_interval_seconds` (integer): Check interval ### Fail Explicitly fail the pipeline with a message. **Parameters:** * `message` (string, required): Failure message * `error_code` (string): Error code for categorization *** ## Deployment Actions ### Deploy Model Create a model deployment endpoint. **Parameters:** * `model_id` (string, required): Model to deploy * `cluster_id` (string, required): Target cluster * `deployment_name` (string, required): Deployment identifier * `replicas` (integer): Initial replica count * `auto_scaling` (object): Autoscaling configuration **Outputs:** * `deployment_id`: Created deployment ID * `endpoint_url`: Inference endpoint URL * `status`: Deployment status **Example:** ```python theme={null} { "action": "deployment_create", "params": { "model_id": "{{steps.add_model.output.model_id}}", "cluster_id": "cluster_prod", "deployment_name": "llama-inference", "replicas": 2 } } ``` ### Scale Deployment Adjust the number of replicas for a deployment. **Parameters:** * `deployment_id` (string, required): Deployment to scale * `replicas` (integer, required): Target replica count **Outputs:** * `previous_replicas`: Replica count before scaling * `current_replicas`: New replica count ### Configure Rate Limiting Set rate limits for a deployment endpoint. **Parameters:** * `deployment_id` (string, required): Target deployment * `rate_limit` (integer, required): Requests per time window * `time_window` (string): Time window - `second`, `minute`, `hour` * `algorithm` (string): Algorithm - `token_bucket`, `fixed_window` ### Delete Deployment Remove a deployment and release resources. **Parameters:** * `deployment_id` (string, required): Deployment to delete *** ## Model Operations Actions ### Add Model Add a model from HuggingFace or URL to the registry. **Parameters:** * `model_uri` (string, required): Model identifier or URL * `model_name` (string, required): Display name * `model_source` (string, required): Source - `hugging_face`, `url`, `local` * `max_wait_seconds` (integer): Maximum download wait time **Outputs:** * `model_id`: Created model ID * `model_name`: Model name * `size_bytes`: Model size **Example:** ```python theme={null} { "action": "model_add", "params": { "model_uri": "meta-llama/Llama-3.2-1B-Instruct", "model_name": "Llama-3.2-1B-Instruct", "model_source": "hugging_face" } } ``` ### Add Cloud Model Add a cloud-hosted model (OpenAI, Anthropic, etc.). **Parameters:** * `provider` (string, required): Cloud provider * `model_id` (string, required): Provider's model ID * `api_key` (string): API key (use secrets) ### Model Benchmark Run performance benchmarks on a model. **Parameters:** * `model_id` (string, required): Model to benchmark * `test_prompts` (array): List of test prompts * `metrics` (array): Metrics to measure **Outputs:** * `latency_p50`: 50th percentile latency * `latency_p99`: 99th percentile latency * `throughput`: Requests per second ### Delete Model Remove a model from the registry. **Parameters:** * `model_id` (string, required): Model to delete *** ## Cluster Actions ### Cluster Health Check Verify cluster status and readiness. **Parameters:** * `cluster_id` (string, required): Cluster to check * `timeout_seconds` (integer): Health check timeout **Outputs:** * `status`: Cluster status - `healthy`, `degraded`, `unhealthy` * `node_count`: Number of active nodes * `available_resources`: Available CPU/GPU/memory **Example:** ```python theme={null} { "action": "cluster_health", "params": { "cluster_id": "cluster_prod", "timeout_seconds": 30 } } ``` *** ## Integration Actions ### HTTP Request Make external API calls. **Parameters:** * `url` (string, required): Request URL * `method` (string): HTTP method - `GET`, `POST`, `PUT`, `DELETE` * `headers` (object): Request headers * `body` (object): Request body * `timeout_seconds` (integer): Request timeout **Outputs:** * `status_code`: HTTP status code * `response_body`: Response data * `headers`: Response headers **Example:** ```python theme={null} { "action": "http_request", "params": { "url": "https://api.example.com/webhook", "method": "POST", "headers": { "Content-Type": "application/json" }, "body": { "event": "deployment_complete", "deployment_id": "{{steps.deploy.output.deployment_id}}" } } } ``` ### Send Notification Send alerts via email, Slack, or Teams. **Parameters:** * `message` (string, required): Notification message * `channel` (string, required): Channel type - `email`, `slack`, `teams` * `recipients` (array): List of recipients * `priority` (string): Priority level **Example:** ```python theme={null} { "action": "notification", "params": { "message": "Deployment {{steps.deploy.output.deployment_name}} completed successfully", "channel": "slack", "priority": "normal" } } ``` *** ## Common Patterns ### Referencing Step Outputs Access outputs from previous steps: ``` {{steps.step_id.output.field_name}} ``` ### Conditional Execution All actions support conditional execution: ```python theme={null} { "action": "notification", "condition": "steps.deploy.output.status == 'active'", "params": {...} } ``` ### Error Handling Configure retry behavior: ```python theme={null} { "action": "deployment_create", "retry": { "max_attempts": 3, "backoff_multiplier": 2 }, "params": {...} } ``` ## Next Steps Learn about DAGs and workflows Build your first pipeline