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build_flow

Compile and validate a flow's component graph, detecting configuration errors. Returns a job ID for asynchronous status monitoring.

Instructions

Compile and validate a flow, returning job ID for asynchronous status monitoring.

Purpose: Build and validate a flow's component graph, ensuring all nodes are properly configured and connected. Essential prerequisite for flow execution - detects configuration errors, validates component parameters, and prepares the flow for running. Returns job_id for tracking build progress asynchronously.

Parameters:

  • flow_id (required, UUID string): Flow identifier to build and validate

  • inputs (optional, object): Input values to use during build validation (key: input_name, value: test_data)

  • data (optional, object): Flow configuration override (use to build modified version without updating flow)

  • files (optional, array of strings): File paths to include in build context

  • stop_component_id (optional, string): Component ID where build should stop (useful for partial validation)

  • start_component_id (optional, string): Component ID where build should start (skip earlier components)

  • log_builds (optional, boolean, default: true): Enable detailed build logging for debugging

  • flow_name (optional, string): Override flow name during build (doesn't affect saved flow)

  • event_delivery (optional, string, default: "polling"): Delivery mode - "polling" (recommended), "streaming", or "direct"

Returns: BuildFlowResponse object containing:

  • job_id (UUID): Unique build job identifier for status polling via get_build_status

Usage Examples:

  1. Basic build: { flow_id: "550e8400-e29b-41d4-a716-446655440000" }

  2. Build with logging: { flow_id: "flow-uuid", log_builds: true }

  3. Build with test inputs: { flow_id: "flow-uuid", inputs: { "user_message": "test" } }

  4. Partial build: { flow_id: "flow-uuid", start_component_id: "node-1", stop_component_id: "node-5" }

  5. Streaming events: { flow_id: "flow-uuid", event_delivery: "streaming" }

Best Practices:

  • Always build flow before first execution to catch configuration errors early

  • Use polling event_delivery for reliable status tracking in production

  • Enable log_builds during development for detailed error diagnostics

  • Rebuild after any flow modifications (nodes, edges, parameters)

  • Monitor build status with get_build_status using returned job_id

  • Use partial builds (start/stop component) for faster validation of specific sections

  • Validate inputs during build to ensure flow accepts expected data format

  • Cache successful build status to avoid unnecessary rebuilds

Common Errors:

  • "Flow not found": flow_id doesn't exist (verify with list_flows or get_flow)

  • "Invalid flow configuration": Flow has disconnected nodes or missing required parameters

  • "Component validation failed": Node configuration is invalid (check component settings in Langflow UI)

  • "Missing required component parameters": Required fields not set on components

  • "Build timeout": Complex flow took too long; simplify or optimize component chain

  • "Invalid component ID": start_component_id or stop_component_id doesn't exist in flow

  • "Circular dependency detected": Flow has loop in node connections

Related Tools:

  • get_build_status: Poll build completion and retrieve validation results using job_id

  • run_flow: Execute flow after successful build

  • get_flow: Inspect flow structure before building

  • cancel_build: Stop long-running build job

  • update_flow: Fix configuration errors found during build

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataNoOptional flow data/configuration
filesNoOptional array of file paths
inputsNoOptional input values for the flow
flow_idYesFlow ID (UUID) to build
flow_nameNoOptional flow name override
log_buildsNoWhether to log build process (default: true)
event_deliveryNoEvent delivery mode: "polling", "streaming", or "direct" (default: "polling")
stop_component_idNoOptional component ID to stop at
start_component_idNoOptional component ID to start from
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description must fully disclose behavior. It explains that the tool returns a job_id for async monitoring, performs validation, and supports partial builds via start/stop_component_id. It also mentions potential build timeout. However, it does not explicitly state whether the operation is read-only or modifies state, though it seems to prepare the flow without permanent changes.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with clear sections: Purpose, Parameters, Returns, Usage Examples, Best Practices, Common Errors, Related Tools. The core purpose is stated upfront. While it is verbose and sometimes repeats schema information, each section contributes useful information and the organization is clear.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (9 parameters, nested objects, async behavior), the description is complete. It covers the purpose, each parameter's role, return value, examples, best practices, common errors, and related tools. Even without an output schema, it adequately describes the return object (job_id).

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the schema already documents each parameter. The description enriches this by explaining the purpose of each parameter (e.g., 'stop_component_id: Component ID where build should stop (useful for partial validation)') and provides usage examples that demonstrate parameter combinations. This adds value beyond the schema definitions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Compile and validate a flow, returning job ID for asynchronous status monitoring.' It uses specific verbs (compile, validate) and identifies the resource (flow) and output (job ID). This distinguishes it from sibling tools like run_flow and get_build_status.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly states it is an 'Essential prerequisite for flow execution' and provides a 'Best Practices' section with clear guidance (e.g., 'Always build flow before first execution'). Also includes 'Common Errors' to help avoid misuse and lists related tools like get_build_status and run_flow.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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