Workflow API Reference

Workflows provide the orchestration layer of BindAI. A workflow coordinates multiple operations into a larger execution process. Depending on the workflow design, those operations can involve agents, tools, conditions, loops, parallel execution, retries, timeouts, human tasks, scheduling, Knowledge, Memory, and external integrations. This page describes the current Workflow API at a conceptual and architectural level while avoiding assumptions about unverified workflow classes or methods.

Overview

A workflow defines how work should be organized and executed. Conceptually:

Workflow
   |
   +---- Agent
   |
   +---- Tool
   |
   +---- Condition
   |
   +---- Loop
   |
   +---- Parallel Work
   |
   +---- External Integration
   |
   v
Result

Workflows are useful when a task requires more than a single agent execution.

Workflow Construction

BindAI supports workflow construction as a structured orchestration capability. The exact workflow construction API should be taken from the current installed implementation. The workflow documentation intentionally does not assume a specific public WorkflowBuilder class or fluent method set unless those APIs are verified. Conceptually, workflow construction involves:

Defining the workflow.
Defining its operations.
Establishing execution order.
Configuring conditions and control flow.
Configuring error handling.
Validating the workflow.
Executing the workflow.

Workflow Components

A workflow can conceptually contain:

Workflow definition
Execution operations
Agents
Tools
Conditions
Loops
Parallel branches
Retry behavior
Timeout behavior
Human-task patterns
Scheduling
Knowledge operations
Memory operations
External integrations
Runtime state

Not every workflow requires all of these components.

Workflow Operations

Workflow operations represent individual units of work. An operation might:

Execute an agent.
Execute a tool.
Evaluate a condition.
Repeat work.
Process a collection.
Execute independent work in parallel.
Wait for human input.
Interact with an external system.

The exact representation of an operation depends on the workflow implementation.

Sequential Execution

The simplest workflow executes operations in sequence.

Operation A
     |
     v
Operation B
     |
     v
Operation C

Sequential execution is appropriate when later operations depend on the results of earlier operations. For example:

Retrieve Data
     |
     v
Process Data
     |
     v
Generate Result

Agent Execution

Agents can participate in workflows.

Workflow
    |
    v
Agent
    |
    v
Result

An agent operation can perform reasoning or generation as part of a larger process. This allows workflow orchestration to remain separate from the agent’s internal model behavior.

Tool Execution

Tools can also participate in workflow execution.

Workflow
    |
    v
Tool
    |
    v
Tool Result

Tools are useful when a workflow needs deterministic operations, external API calls, data processing, or other operations that should not be performed solely by a language model.

Conditions

Conditions allow a workflow to choose between different execution paths. Conceptually:

             Condition
             /       \
          True       False
           |           |
           v           v
        Branch A    Branch B

Conditions are useful for business rules, validation, approvals, routing, and state-dependent execution. The exact condition API depends on the current workflow implementation.

Loops

Loops allow workflow operations to execute repeatedly.

        Start
          |
          v
       Process
          |
          v
       Condition
        /     \
     Again    Done
      |         |
      +----<    v
             Complete

Common use cases include:

Processing collections
Pagination
Repeated validation
Polling
Iterative processing
Batch operations

Loops should always have a well-defined termination condition or execution limit.

Parallel Execution

Independent operations can be executed in parallel when their dependencies allow it.

             Workflow
                |
        +-------+-------+
        |       |       |
        v       v       v
      Task A  Task B  Task C
        |       |       |
        +-------+-------+
                |
                v
              Next

Parallel execution can reduce overall execution time when operations do not depend on one another. Dependent operations should remain sequential.

Workflow State

Workflow execution may require state to be passed between operations. Conceptually:

Input
  |
  v
Workflow State
  |
  +---- Operation A
  |
  +---- Operation B
  |
  +---- Operation C
  |
  v
Output

State can contain information required by later operations. Applications should distinguish temporary workflow execution state from persistent application state. Persistent information should generally use an appropriate Memory or storage provider.

Agent and Tool Results

Results from earlier operations can be used by later operations. For example:

Agent
  |
  v
Result
  |
  v
Condition
  |
  v
Next Operation

This allows workflows to use agent output as part of subsequent orchestration decisions. The exact result-passing mechanism depends on the workflow implementation.

Workflow Context

Workflow execution may require runtime context containing information relevant to the current execution. Conceptually:

Input
  |
  v
Runtime Context
  |
  +---- State
  +---- Execution Information
  +---- Operation Results
  |
  v
Workflow Operations

The exact context type and public API should not be assumed unless explicitly exposed by the current implementation.

Workflow Validation

Workflow definitions should be validated before production execution. Validation can identify problems such as:

Invalid configuration
Missing required operations
Invalid references
Impossible execution paths
Incorrect dependencies
Invalid control-flow configuration

Validation reduces the likelihood of discovering structural problems only after deployment. The exact validation API depends on the current workflow implementation.

Workflow Results

Workflow execution produces results representing the outcome of the workflow. Depending on the implementation, a workflow result may contain information such as:

Success or failure
Output
Operation results
Error information
Execution metadata

Applications should inspect the actual result type provided by the installed BindAI version. The Workflow API should not be assumed to use the same result object as Agent.run() unless explicitly implemented that way.

Error Handling

Workflow failures can originate from many components. Examples include:

Agent execution
Model providers
Tool execution
Knowledge retrieval
Memory providers
Conditions
External integrations
Workflow configuration
Runtime operations

Conceptually:

Workflow
    |
    v
Operation
    |
    +---- Success ---> Continue
    |
    +---- Failure ---> Error Handling

A workflow should define appropriate behavior for expected failure modes.

Retries

Retries can be used when an operation may fail temporarily.

Operation
    |
    +---- Success ---> Continue
    |
    +---- Failure
             |
             v
           Retry

Retries are particularly useful for transient failures such as some provider or network errors. They should be used carefully for operations that produce external side effects. The current BindAI retry implementation is intentionally simple and should not be interpreted as a complete distributed retry system.

Timeouts

Timeouts limit how long an operation or execution is allowed to continue. Conceptually:

Start
  |
  v
Operation
  |
  +---- Completes ---> Continue
  |
  +---- Timeout ----> Error Handling

Timeout behavior depends on the configured execution mechanism. A timeout should not automatically be assumed to cancel every underlying thread, task, network request, or external operation.

Human Tasks

Human-in-the-loop execution can be represented as a workflow pattern.

Workflow
   |
   v
Human Decision
   |
   v
Continue Workflow

A human task may require an external interface, task store, authentication system, and persistence mechanism. BindAI’s workflow documentation should not assume that every workflow automatically provides a complete task-management system. The exact pause, resume, assignment, and persistence behavior depends on the current implementation.

Scheduling

Workflows can be combined with scheduling for recurring automation. Conceptually:

Schedule
   |
   v
Workflow
   |
   v
Result

Scheduling is a separate concern from workflow orchestration. The scheduler, persistence model, timezone handling, and deployment behavior depend on the scheduling implementation and surrounding application infrastructure.

Knowledge Integration

Workflows can coordinate Knowledge operations. For example:

Documents / Knowledge
        |
        v
Retrieval
        |
        v
Agent
        |
        v
Workflow Result

Knowledge can provide retrieved information to agents or other workflow operations. This is useful for document-processing, research, retrieval-augmented generation, and domain-specific automation.

Memory Integration

Workflows can also work alongside Memory.

Workflow
   |
   +---- Read Memory
   |
   +---- Execute Agent
   |
   +---- Update Memory

Memory is appropriate for persistent or reusable application information. Temporary workflow state should not automatically be treated as persistent Memory.

External Integrations

Workflows can coordinate external services through tools and Connections.

Workflow
   |
   v
Tool
   |
   v
Connection
   |
   v
External Service

Current Connections include integrations such as:

Webhooks
GitHub
Slack
Notion
Jira
Discord
Resend
Vercel
Netlify

This allows workflows to participate in larger application and automation systems.

Multi-Agent Workflows

Workflows can coordinate multiple agents.

Workflow
    |
    +---- Research Agent
    |
    +---- Analysis Agent
    |
    +---- Communication Agent
    |
    v
Final Result

This is useful when different stages require different agent responsibilities. Multi-agent delegation and team execution provide additional orchestration patterns beyond simple sequential agent execution.

Workflow Composition

Larger workflows can be organized into smaller logical operations. Conceptually:

Main Workflow
      |
      +---- Data Processing
      |
      +---- AI Analysis
      |
      +---- Validation
      |
      +---- Notification

Breaking complex processes into smaller units improves:

Testing
Maintainability
Debugging
Reuse
Observability

The exact composition mechanism depends on the current workflow API.

Workflow and Project

Projects provide a higher-level organizational concept around application components. A workflow can be part of a larger application architecture containing:

Agents
Tools
Knowledge
Memory
Connections
Other workflows

The Project API should not be assumed to provide automatic workflow registration or deployment unless those features are explicitly implemented.

Workflow and Agent

Agents and workflows have different responsibilities.

Agent	Workflow
Performs AI reasoning	Orchestrates execution
Uses a model provider	Coordinates multiple operations
Can invoke tools	Controls sequencing and branching
Can use Knowledge	Can coordinate Knowledge operations
Can use Memory	Can coordinate persistent state

A useful architecture is:

Workflow
    |
    v
Agent
    |
    v
Model

The workflow decides what happens next. The agent decides how to perform its AI task.

Workflow and Tools

Tools are usually focused on individual operations. Workflows coordinate those operations.

Workflow
   |
   +---- Tool A
   |
   +---- Tool B
   |
   +---- Tool C

This separation keeps deterministic operations separate from orchestration logic.

Workflow Execution

The execution mechanism depends on the installed BindAI workflow implementation. Conceptually:

Workflow Definition
        |
        v
Execution
        |
        +---- Operation
        |
        +---- Condition
        |
        +---- Loop
        |
        +---- Parallel Work
        |
        v
Workflow Outcome

Applications should use the public execution API exposed by their installed BindAI version rather than relying on undocumented executor internals.

Serialization

Workflow persistence or transport may require serialization. However, a specific public serialization API should not be assumed unless it is implemented. This documentation therefore does not prescribe methods such as:

workflow.to_dict()
workflow.load_dict(...)
workflow.to_json()
workflow.from_json(...)

unless those methods are explicitly provided by the current implementation.

API Accuracy

This page intentionally avoids presenting unverified classes and methods as public API. In particular, applications should not assume the existence of:

WorkflowBuilder(...)
WorkflowNode(...)
AgentNode(...)
ToolNode(...)
ConditionNode(...)
LoopNode(...)
ParallelNode(...)
JoinNode(...)
HumanTaskNode(...)

workflow.executor.run(...)
workflow.add_node(...)
workflow.connect(...)
workflow.validate(...)
workflow.to_dict(...)
workflow.load_dict(...)

unless those APIs are explicitly implemented by the installed BindAI version. Workflow concepts such as agents, tools, conditions, loops, parallel execution, retries, timeouts, human tasks, and scheduling describe supported orchestration capabilities; they do not necessarily correspond one-to-one with public Python classes.

Best Practices

Keep workflows focused on orchestration.
Keep agent reasoning inside agents.
Keep deterministic operations inside tools.
Keep external-service communication behind Connections where appropriate.
Validate workflow behavior before production use.
Keep conditions explicit.
Give loops clear termination conditions.
Parallelize only independent operations.
Use retries for appropriate transient failures.
Use timeouts to protect long-running operations.
Treat external side effects carefully.
Keep persistent state in appropriate storage.
Test failure paths as well as successful paths.

Testing

Workflow tests should cover:

Sequential execution
Conditions
Loops
Parallel execution
Agent operations
Tool operations
Error handling
Retries
Timeouts
Knowledge integration
Memory integration
External integrations
Multi-agent behavior
Human-task flows where applicable
Scheduling where applicable

Tests should verify both successful execution and expected failure behavior.

The Workflow API works closely with:

Agent
AgentResult
Tools
Knowledge
Memory
Connections
Multi-agent execution
Scheduling
Retry behavior
Timeout behavior
Project architecture

Together these components provide BindAI’s broader orchestration capabilities.

Summary

Workflows provide BindAI’s orchestration layer. A workflow can conceptually coordinate:

Workflow
   |
   +---- Agents
   +---- Tools
   +---- Conditions
   +---- Loops
   +---- Parallel Work
   +---- Retries
   +---- Timeouts
   +---- Human Tasks
   +---- Knowledge
   +---- Memory
   +---- Connections
   |
   v
Workflow Outcome

The current documentation deliberately separates workflow capabilities from assumptions about specific implementation classes. This keeps the API reference accurate while the workflow subsystem continues to evolve.

​Workflow API Reference

​Overview

​Workflow Construction

​Workflow Components

​Workflow Operations

​Sequential Execution

​Agent Execution

​Tool Execution

​Conditions

​Loops

​Parallel Execution

​Workflow State

​Agent and Tool Results

​Workflow Context

​Workflow Validation

​Workflow Results

​Error Handling

​Retries

​Timeouts

​Human Tasks

​Scheduling

​Knowledge Integration

​Memory Integration

​External Integrations

​Multi-Agent Workflows

​Workflow Composition

​Workflow and Project

​Workflow and Agent

​Workflow and Tools

​Workflow Execution

​Serialization

​API Accuracy

​Best Practices

​Testing

​Related APIs

​Summary