bl run

bl run resource-type resource-name [flags]

  # Run agent with inline data
  bl run agent my-agent --data '{"inputs": "Summarize this text"}'

  # Run agent with file input
  bl run agent my-agent --file request.json

  # Run job with batch file
  bl run job my-job --file batches/process-users.json

  # Run job locally for testing (requires 'bl serve' in another terminal)
  bl run job my-job --local --file batch.json

  # Run job locally with 4 concurrent workers
  bl run job my-job --local --file batch.json --concurrent 4

  # Run model with custom endpoint
  bl run model my-model --path /v1/chat/completions --data '{"messages": [...]}'

  # Run with query parameters
  bl run agent my-agent --data '{}' --params "stream=true" --params "max_tokens=100"

  # Run with custom headers
  bl run agent my-agent --data '{}' --header "X-User-ID: 123"

  # Debug mode (see full request/response details)
  bl run agent my-agent --data '{}' --debug

  # Execute a command in a sandbox
  bl run sandbox my-sandbox --path /process --data '{"command": "echo hello"}'

  # Execute a command and wait for it to complete (returns stdout/stderr in response)
  bl run sandbox my-sandbox --path /process --data '{"command": "ls -al /app", "waitForCompletion": true}'

  # Execute a command with a working directory and a process name
  bl run sandbox my-sandbox --path /process --data '{"command": "npm install", "name": "install-deps", "workingDir": "/app"}'

  # Execute a long-running command with keep-alive (prevents sandbox auto-standby)
  bl run sandbox my-sandbox --path /process --data '{"command": "npm run dev -- --port 3000", "name": "dev-server", "keepAlive": true}'

  # You can also use the 'sbx' shorthand
  bl run sbx my-sandbox --path /process --data '{"command": "python script.py", "waitForCompletion": true}'

  -c, --concurrent int       Number of concurrent workers for local job execution (default 1)
  -d, --data string          JSON body data for the inference request
      --debug                Debug mode
      --directory string     Directory to run the command from
  -e, --env-file strings     Environment file to load (default [.env])
  -f, --file string          Input from a file
      --header stringArray   Request headers in 'Key: Value' format. Can be specified multiple times
  -h, --help                 help for run
      --local                Run locally
      --method string        HTTP method for the inference request (default "POST")
  -o, --output string        Output format: json, yaml
      --params strings       Query params sent to the inference request
      --path string          path for the inference request
  -s, --secrets strings      Secrets to pass to the execution
      --upload-file string   This transfers the specified local file to the remote URL

      --skip-version-warning   Skip version warning
  -u, --utc                    Enable UTC timezone
  -v, --verbose                Enable verbose output
  -w, --workspace string       Specify the workspace name