Flow Node Reference

Agent Flow provides 10 nodes organized into 4 categories that you can drag and drop on the canvas. Drag from the Node Palette on the left and place on the canvas.

Category	Nodes
General	Start, Output
AI	Agent, Model
Logic & Data	Condition, Router, Merge, Transform
Workspace	Guardrail, Glossary

General

Start

Flow entry point. Receives user input as the input State key and passes it to the next node. Required in every flow. You can define flow Variables.

Output

Flow exit point. Returns the previous node’s result to the user. Choose Action Type: Passthrough / Response (prompt-based final answer) / Error.

AI

Agent

Runs a registered agent. KBSphere (enhanced RAG) and DBSphere (database) mode agents are supported.

Model

Calls an LLM directly without an agent. Suited for simple text processing (summarize, translate, classify).

Logic & Data

Condition

Branch True / False based on a condition. 6 condition types supported.

Router

Multi-path routing. Define multiple Routes and branch by LLM intent or by condition.

Merge

Combine multiple parallel outputs into one. 3 modes: concat / template / json.

Transform

Transform data. Modes: Extract Field (pull a specific value) or Format Text (template-based generation).

Workspace

Guardrail

Apply a guardrail and branch Pass / Block. Use Block Action to control behavior on block.

Glossary

Find glossary terms in the input text and append definitions to the body. Matched terms are referenceable by downstream nodes.

Node Settings — Details

Start node

Flow entry point. The user message arrives as the input State key.

Setting	Description
Label	Node display name
Variables	Define variables used across the flow (name, type, default)

Variable types: String, Number, Boolean, Array, Object

Output node

Flow exit point. Returns the previous node’s result to the user.

Setting	Description
Label	Node display name
Action Type	`Passthrough` (return result as-is), `Response` (generate prompt-based final answer), `Error` (return error message)

In Response mode, additionally configure Final Response Prompt and Model for Response. The prompt can reference {input}, {output}, {sources}, and State Key variables.

The UI label is shown as “Output”. The internal type name is flowOutput.

Agent node

Runs a registered agent. KBSphere / DBSphere agents supported.

Setting	Description
Agent	Agent to run
User Prompt	User prompt passed to the agent. Can reference `{input}`, `{state_key}`, etc.

With KBSphere agents, retrieved document sources are returned alongside
With DBSphere agents, SQL execution results are included

The Agent node inherits all Knowledge Base, Tool, and Guardrail settings of the connected agent.

Model node

Calls an LLM directly without an agent.

Setting	Description
Model	LLM model to use
System Prompt	System instructions to the model
User Prompt	User prompt. Can reference `{input}`, `{state_key}`, etc.
Output Fields	Define JSON-structured output fields (name, type, description)

Defining Output Fields produces a JSON-structured response. Without them, plain text is returned.

Condition node

Branches the flow on a condition. Has two output handles at the bottom: True and False.

Setting	Description
State Key	Target for evaluation (`input` or upstream State Key)
Condition Type	Pick one of 6 condition types
Value	Comparison value

Supported condition types (6):

Condition	Internal Code	Description
`Contains`	`contains`	Whether the text is contained
`Does not contain`	`not_contains`	Whether the text is absent
`Equals`	`equals`	Exact match
`Starts with`	`starts_with`	Whether it starts with the text
`Ends with`	`ends_with`	Whether it ends with the text
`Regex match`	`regex`	Regex pattern match

Numeric comparisons (Greater than / Less than) and empty checks (Is empty) have no dedicated operators. If needed, transform with a Transform node and check via equals / regex.

Router node

Multi-path routing. Define at least 2 Routes and set a branching condition for each.

Setting	Description
Routing Type	`llm` (LLM picks the route via intent classification) or `condition` (per-route condition evaluation)
State Key	Evaluation target for condition routing
Routes	Set Label, Branch Key, Condition for each route
Default Route	Fallback when no condition matches

When using Condition Routing, each route’s condition supports the same 6 types as the Condition node.

Merge node

Combines multiple parallel outputs into one.

Setting	Description
Merge Type	`concat` (text concatenation, default) / `template` (Jinja2) / `json` (JSON object)
Source Keys	List of State Keys to merge. If empty, auto-collected
Separator	Separator for concat mode (default `\n\n`)
Template	Jinja2 template for template mode (`{{ input }}`, `{{ variables.x }}`, etc.)

Per-mode behavior:

Mode	Result	Use Case
`concat`	Single text in `[key]\nvalue\n\n[key]\nvalue` form	Merge multiple agent outputs into one answer
`template`	Jinja2 rendering result	Format outputs into a specific format (email/report)
`json`	JSON string (key: value mapping)	Pass structured data to a downstream system

Options like “Sum / Use first only / Custom” mentioned in older docs are not currently implemented. The 3 modes above are all that exist.

Transform node

Transforms data. Two modes: Extract Field and Format Text.

Setting	Description
Transform Type	`Extract Field` or `Format Text`
Output Key	State Key name for the transform result (default: `transformed`)

Extract Field mode — Pass through one of the upstream State Keys as-is.

Setting	Description
State Key	State Key to extract (`input` or upstream output)

Format Text mode — Compose new text using {state_key} syntax.

Setting	Description
Output Template	Text template containing `{state_key}` placeholders

Analysis result: {guardrail_type} - {guardrail_reason}

Jinja2 templates are not used in default mode. Enable “Use Jinja2 Template” in Advanced Settings to use Jinja2 with {'{{ state.key }}'} syntax.

Guardrail node

Applies a guardrail to validate input. Two output handles: Pass and Block.

Setting	Description
Guardrail	Guardrail to apply
Block Action	`Stop` (immediate exit) / `Message` (show message and exit) / `Continue` (proceed via Block output)
Blocked Message	Message shown when Block Action is `Message`

Output handles:

Pass (green, bottom left) — proceed to next node when passed
Block (red, bottom right) — only active when Block Action is Continue

The Block output includes guardrail_type (block category) and guardrail_reason (block reason) fields in the State.

Glossary node

Finds matches between the input text and the specified glossary’s terms/synonyms, and appends the definitions to the body.

Setting	Description
Glossary	Glossary to match

Behavior:

Check whether the input text (current_output or input) contains a glossary entry’s term or synonyms (case-insensitive)

Collect matched terms and append to the end of the body like:

[Original text]

[Term reference]
• Term1: Definition1
• Term2: Definition2

The downstream LLM node generates a more accurate response using the definitions

Output State keys:

current_output — enriched text with appended definitions
{node}.matched — array of matched term objects (term, matched_form, definition)

For chatbots that frequently use internal abbreviations and specialized terminology, placing a Glossary node before an Agent node ensures the LLM understands term meanings before generating an answer.

Additional Nodes (code-only)

The following node components exist in the codebase but are not exposed in the current Node Palette. Users can’t add them directly on the canvas — they may be enabled in future releases:

Aggregator, Human Input, Subflow, Error Handler, Notification, Knowledge, Tool

If you need these nodes, use the AI Builder (natural-language flow generation) on the Agent Flow page, or wait for the next release.

Inter-node Data Flow (State)

A flow uses a shared State object to pass data between nodes.

State Key	Description
`input`	User message (filled by Start node)
`current_output`	Output of the previous node (updated through the chain)
`variables.{name}`	Flow variables defined in the Start node
`{node_id}.{field}`	Each node’s output fields (e.g., `{model_node}.response`)

Each node writes its output to current_output and {node_id}.<field> keys. Downstream nodes’ prompts/conditions can reference them with {state_key} or Jinja2 {'{{ variables.x }}'}.

When debugging complex flows, place a Transform (Format Text) node right after Start to print all State keys — useful for seeing what’s currently alive in State.

Workspace

AI Agents

Knowledge & Data

Safety

Customization

General

Start

Output

AI

Agent

Model

Logic & Data

Condition

Router

Merge

Transform

Workspace

Guardrail

Glossary

Node Settings — Details

Additional Nodes (code-only)

Inter-node Data Flow (State)

​General

Start

Output

​AI

Agent

Model

​Logic & Data

Condition

Router

Merge

Transform

​Workspace

Guardrail

Glossary

​Node Settings — Details

​Additional Nodes (code-only)

​Inter-node Data Flow (State)

General

AI

Logic & Data

Workspace

Node Settings — Details

Additional Nodes (code-only)

Inter-node Data Flow (State)