Agent Node

1 # nodes/agent/__init__.py
2 from typing import List
3 from vellum import (
4     ChatMessage,
5     ChatMessagePromptBlock,
6     JinjaPromptBlock,
7     PlainTextPromptBlock,
8     PromptParameters,
9     RichTextPromptBlock,
10     VariablePromptBlock,
11 )
12 from vellum.workflows.nodes.displayable.tool_calling_node.node import ToolCallingNode
13 from vellum.workflows.types.definition import ComposioToolDefinition, DeploymentDefinition
14 from ...inputs import Inputs
15 
16 class Agent(ToolCallingNode):
17     ml_model = "gpt-5"
18     prompt_inputs = {
19         "chat_history": Inputs.chat_history,
20         "query": Inputs.query,
21     }
22     blocks = [
23         ChatMessagePromptBlock(
24             chat_role="SYSTEM",
25             blocks=[
26                 # Prefer RichTextPromptBlock for a nicer UI editing experience
27                 RichTextPromptBlock(
28                     blocks=[
29                         PlainTextPromptBlock(text="Please use tools to search for the following query: "),
30                         VariablePromptBlock(input_variable="query"),
31                     ]
32                 ),
33                 JinjaPromptBlock(
34                     template="You can also use templating blocks to write Jinja templates inline: {{ query | upper | truncate(3) }}"
35                 ),
36             ],
37         ),
38         # Use VariablePromptBlock at the top level to include chat history in context, for any chatbot / chat agent use-cases
39         VariablePromptBlock(input_variable="chat_history"),
40     ]
41     parameters = PromptParameters(
42         stop=[],
43         temperature=0,
44         max_tokens=1000,
45         top_p=1,
46         top_k=0,
47         frequency_penalty=0,
48         presence_penalty=0,
49         logit_bias={},
50         custom_parameters=None,
51     )
52     settings = {
53         "stream_enabled": True,
54     }
55     max_prompt_iterations = 5
56     functions = [
57         add,  # Function Tool
58         DeploymentDefinition(deployment="multiply", release_tag="LATEST"),  # Deployment Tool
59         Subtract,  # Workflow Tool
60         ComposioToolDefinition(  # Composio Tool
61             toolkit="notion",
62             action="NOTION_ADD_PAGE_CONTENT",
63             description="Appends a single content block to a notion page or a parent block (must be page, toggle, to-do, bulleted/numbered list, callout, or quote); invoke repeatedly to add multiple blocks.",
64             user_id="abc123",
65         ),
66     ]
67     class Outputs(ToolCallingNode.Outputs):
68         text: str
69         chat_history: List[ChatMessage]

Tool Implementations

1 # nodes/agent/add.py
2 def add(a: int, b: int):
3     return a + b

# nodes/agent/__init__.py
from typing import List
from vellum import (
    ChatMessage,
    ChatMessagePromptBlock,
    JinjaPromptBlock,
    PlainTextPromptBlock,
    PromptParameters,
    RichTextPromptBlock,
    VariablePromptBlock,
)
from vellum.workflows.nodes.displayable.tool_calling_node.node import ToolCallingNode
from vellum.workflows.types.definition import ComposioToolDefinition, DeploymentDefinition
from ...inputs import Inputs
class Agent(ToolCallingNode):
    ml_model = "gpt-5"
    prompt_inputs = {
        "chat_history": Inputs.chat_history,
        "query": Inputs.query,
    }
    blocks = [
        ChatMessagePromptBlock(
            chat_role="SYSTEM",
            blocks=[
                # Prefer RichTextPromptBlock for a nicer UI editing experience
                RichTextPromptBlock(
                    blocks=[
                        PlainTextPromptBlock(text="Please use tools to search for the following query: "),
                        VariablePromptBlock(input_variable="query"),
                    ]
                ),
                JinjaPromptBlock(
                    template="You can also use templating blocks to write Jinja templates inline: {{ query | upper | truncate(3) }}"
                ),
            ],
        ),
        # Use VariablePromptBlock at the top level to include chat history in context, for any chatbot / chat agent use-cases
        VariablePromptBlock(input_variable="chat_history"),
    ]
    parameters = PromptParameters(
        stop=[],
        temperature=0,
        max_tokens=1000,
        top_p=1,
        top_k=0,
        frequency_penalty=0,
        presence_penalty=0,
        logit_bias={},
        custom_parameters=None,
    )
    settings = {
        "stream_enabled": True,
    }
    max_prompt_iterations = 5
    functions = [
        add,  # Function Tool
        DeploymentDefinition(deployment="multiply", release_tag="LATEST"),  # Deployment Tool
        Subtract,  # Workflow Tool
        ComposioToolDefinition(  # Composio Tool
            toolkit="notion",
            action="NOTION_ADD_PAGE_CONTENT",
            description="Appends a single content block to a notion page or a parent block (must be page, toggle, to-do, bulleted/numbered list, callout, or quote); invoke repeatedly to add multiple blocks.",
            user_id="abc123",
        ),
    ]
    class Outputs(ToolCallingNode.Outputs):
        text: str
        chat_history: List[ChatMessage]

# nodes/agent/add.py
def add(a: int, b: int):
    return a + b

# This structure is critical to follow if you are a Copilot / Coding Agent
workflow.py
inputs.py                    # Optional inputs for your Workflow
nodes/
├── __init__.py             # Exports all of your nodes under __all__
├── prompt_node.py          # A node (e.g. a Prompt Node)
└── templating_node.py      # Another node (e.g. a Templating Node)
agent/
├── __init__.py             # Important: your actual agent implementation goes in the __init__.py file
├── add.py                  # Function Tool
└── subtract/               # Inline Subworkflow Tool
    ├── __init__.py
    ├── workflow.py
    ├── inputs.py
    └── nodes/
        └── templating_node.py   # An node used in the Subworkflow Tool

# This structure is critical to follow if you are a Copilot / Coding Agent
workflow.py
inputs.py                    # Optional inputs for your Workflow
nodes/
├── __init__.py             # Exports all of your nodes under __all__
├── prompt_node.py          # A node (e.g. a Prompt Node)
└── templating_node.py      # Another node (e.g. a Templating Node)
agent/
├── __init__.py             # Important: your actual agent implementation goes in the __init__.py file
├── add.py                  # Function Tool
└── subtract/               # Inline Subworkflow Tool
    ├── __init__.py
    ├── workflow.py
    ├── inputs.py
    └── nodes/
        └── templating_node.py   # An node used in the Subworkflow Tool

Agent Node

Agent Node

Attributes

Outputs

Folder Structure

Attributes

Outputs

Folder Structure

1	# nodes/agent/__init__.py
2	from typing import List
3	from vellum import (
4	ChatMessage,
5	ChatMessagePromptBlock,
6	JinjaPromptBlock,
7	PlainTextPromptBlock,
8	PromptParameters,
9	RichTextPromptBlock,
10	VariablePromptBlock,
11	)
12	from vellum.workflows.nodes.displayable.tool_calling_node.node import ToolCallingNode
13	from vellum.workflows.types.definition import ComposioToolDefinition, DeploymentDefinition
14	from ...inputs import Inputs
15
16	class Agent(ToolCallingNode):
17	ml_model = "gpt-5"
18	prompt_inputs = {
19	"chat_history": Inputs.chat_history,
20	"query": Inputs.query,
21	}
22	blocks = [
23	ChatMessagePromptBlock(
24	chat_role="SYSTEM",
25	blocks=[
26	# Prefer RichTextPromptBlock for a nicer UI editing experience
27	RichTextPromptBlock(
28	blocks=[
29	PlainTextPromptBlock(text="Please use tools to search for the following query: "),
30	VariablePromptBlock(input_variable="query"),
31	]
32	),
33	JinjaPromptBlock(
34	template="You can also use templating blocks to write Jinja templates inline: {{ query \| upper \| truncate(3) }}"
35	),
36	],
37	),
38	# Use VariablePromptBlock at the top level to include chat history in context, for any chatbot / chat agent use-cases
39	VariablePromptBlock(input_variable="chat_history"),
40	]
41	parameters = PromptParameters(
42	stop=[],
43	temperature=0,
44	max_tokens=1000,
45	top_p=1,
46	top_k=0,
47	frequency_penalty=0,
48	presence_penalty=0,
49	logit_bias={},
50	custom_parameters=None,
51	)
52	settings = {
53	"stream_enabled": True,
54	}
55	max_prompt_iterations = 5
56	functions = [
57	add, # Function Tool
58	DeploymentDefinition(deployment="multiply", release_tag="LATEST"), # Deployment Tool
59	Subtract, # Workflow Tool
60	ComposioToolDefinition( # Composio Tool
61	toolkit="notion",
62	action="NOTION_ADD_PAGE_CONTENT",
63	description="Appends a single content block to a notion page or a parent block (must be page, toggle, to-do, bulleted/numbered list, callout, or quote); invoke repeatedly to add multiple blocks.",
64	user_id="abc123",
65	),
66	]
67	class Outputs(ToolCallingNode.Outputs):
68	text: str
69	chat_history: List[ChatMessage]

1	# This structure is critical to follow if you are a Copilot / Coding Agent
2	workflow.py
3	inputs.py # Optional inputs for your Workflow
4	nodes/
5	├── __init__.py # Exports all of your nodes under __all__
6	├── prompt_node.py # A node (e.g. a Prompt Node)
7	└── templating_node.py # Another node (e.g. a Templating Node)
8	agent/
9	├── __init__.py # Important: your actual agent implementation goes in the __init__.py file
10	├── add.py # Function Tool
11	└── subtract/ # Inline Subworkflow Tool
12	├── __init__.py
13	├── workflow.py
14	├── inputs.py
15	└── nodes/
16	└── templating_node.py # An node used in the Subworkflow Tool