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AutoGPT/autogpt_platform/backend/backend/blocks/io.py
Toran Bruce Richards 11b846dd49 fix(blocks): rename placeholder_values to options on AgentDropdownInputBlock (#12595) 
## Summary

Resolves [REQ-78](https://linear.app/autogpt/issue/REQ-78): The
`placeholder_values` field on `AgentDropdownInputBlock` is misleadingly
named. In every major UI framework "placeholder" means non-binding hint
text that disappears on focus, but this field actually creates a
dropdown selector that restricts the user to only those values.

## Changes

### Core rename (`autogpt_platform/backend/backend/blocks/io.py`)
- Renamed `placeholder_values` → `options` on
`AgentDropdownInputBlock.Input`
- Added clear field description: *"If provided, renders the input as a
dropdown selector restricted to these values. Leave empty for free-text
input."*
- Updated class docstring to describe actual behavior
- Overrode `model_construct()` to remap legacy `placeholder_values` →
`options` for **backward compatibility** with existing persisted agent
JSON

### Tests (`autogpt_platform/backend/backend/blocks/test/test_block.py`)
- Updated existing tests to use canonical `options` field name
- Added 2 new backward-compat tests verifying legacy
`placeholder_values` still works through both `model_construct()` and
`Graph._generate_schema()` paths

### Documentation
- Updated
`autogpt_platform/backend/backend/copilot/sdk/agent_generation_guide.md`
— changed field name in CoPilot SDK guide
- Updated `docs/integrations/block-integrations/basic.md` — changed
field name and description in public docs

### Load tests
(`autogpt_platform/backend/load-tests/tests/api/graph-execution-test.js`)
- Removed spurious `placeholder_values: {}` from AgentInputBlock node
(this field never existed on AgentInputBlock)
- Fixed execution input to use `value` instead of `placeholder_values`

## Backward Compatibility

Existing agents with `placeholder_values` in their persisted
`input_default` JSON will continue to work — the `model_construct()`
override transparently remaps the old key to `options`. No database
migration needed since the field is stored inside a JSON blob, not as a
dedicated column.

## Testing

- All existing tests updated and passing
- 2 new backward-compat tests added
- No frontend changes needed (frontend reads `enum` from generated JSON
Schema, not the field name directly)

---------

Co-authored-by: Zamil Majdy <zamil.majdy@agpt.co>
2026-04-02 05:56:17 +00:00

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import copy
from datetime import date, time
from typing import Any, Optional
from pydantic import AliasChoices, Field
from backend.blocks._base import (
Block,
BlockCategory,
BlockOutput,
BlockSchema,
BlockSchemaInput,
BlockType,
)
# Import for Google Drive file input block
from backend.blocks.google._drive import AttachmentView, GoogleDriveFile
from backend.data.execution import ExecutionContext
from backend.data.model import SchemaField
from backend.util.file import store_media_file
from backend.util.mock import MockObject
from backend.util.settings import Config
from backend.util.text import TextFormatter
from backend.util.type import LongTextType, MediaFileType, ShortTextType
config = Config()
class AgentInputBlock(Block):
"""
This block is used to provide input to the graph.
It takes in a value, name, and description.
It outputs the value passed as input.
"""
class Input(BlockSchemaInput):
name: str = SchemaField(description="The name of the input.")
value: Any = SchemaField(
description="The value to be passed as input.",
default=None,
)
title: str | None = SchemaField(
description="The title of the input.", default=None, advanced=True
)
description: str | None = SchemaField(
description="The description of the input.",
default=None,
advanced=True,
)
advanced: bool = SchemaField(
description="Whether to show the input in the advanced section, if the field is not required.",
default=False,
advanced=True,
)
secret: bool = SchemaField(
description="Whether the input should be treated as a secret.",
default=False,
advanced=True,
)
def generate_schema(self):
return copy.deepcopy(self.get_field_schema("value"))
class Output(BlockSchema):
# Use BlockSchema to avoid automatic error field for interface definition
result: Any = SchemaField(description="The value passed as input.")
def __init__(self, **kwargs):
super().__init__(
**{
"id": "c0a8e994-ebf1-4a9c-a4d8-89d09c86741b",
"description": "A block that accepts and processes user input values within a workflow, supporting various input types and validation.",
"input_schema": AgentInputBlock.Input,
"output_schema": AgentInputBlock.Output,
"test_input": [
{
"value": "Hello, World!",
"name": "input_1",
"description": "Example test input.",
},
{
"value": 42,
"name": "input_2",
"description": "Example numeric input.",
},
],
"test_output": [
("result", "Hello, World!"),
("result", 42),
],
"categories": {BlockCategory.INPUT, BlockCategory.BASIC},
"block_type": BlockType.INPUT,
"static_output": True,
**kwargs,
}
)
async def run(self, input_data: Input, *args, **kwargs) -> BlockOutput:
if input_data.value is not None:
yield "result", input_data.value
class AgentOutputBlock(Block):
"""
Records the output of the graph for users to see.
Behavior:
If `format` is provided and the `value` is of a type that can be formatted,
the block attempts to format the recorded_value using the `format`.
If formatting fails or no `format` is provided, the raw `value` is output.
"""
class Input(BlockSchemaInput):
value: Any = SchemaField(
description="The value to be recorded as output.",
default=None,
advanced=False,
)
name: str = SchemaField(description="The name of the output.")
title: str | None = SchemaField(
description="The title of the output.",
default=None,
advanced=True,
)
description: str | None = SchemaField(
description="The description of the output.",
default=None,
advanced=True,
)
format: str = SchemaField(
description="The format string to be used to format the recorded_value. Use Jinja2 syntax.",
default="",
advanced=True,
)
escape_html: bool = SchemaField(
default=False,
advanced=True,
description="Whether to escape special characters in the inserted values to be HTML-safe. Enable for HTML output, disable for plain text.",
)
advanced: bool = SchemaField(
description="Whether to treat the output as advanced.",
default=False,
advanced=True,
)
secret: bool = SchemaField(
description="Whether the output should be treated as a secret.",
default=False,
advanced=True,
)
def generate_schema(self):
return self.get_field_schema("value")
class Output(BlockSchema):
# Use BlockSchema to avoid automatic error field for interface definition
output: Any = SchemaField(description="The value recorded as output.")
name: Any = SchemaField(description="The name of the value recorded as output.")
def __init__(self):
super().__init__(
id="363ae599-353e-4804-937e-b2ee3cef3da4",
description="A block that records and formats workflow results for display to users, with optional Jinja2 template formatting support.",
input_schema=AgentOutputBlock.Input,
output_schema=AgentOutputBlock.Output,
test_input=[
{
"value": "Hello, World!",
"name": "output_1",
"description": "This is a test output.",
"format": "{{ output_1 }}!!",
},
{
"value": "42",
"name": "output_2",
"description": "This is another test output.",
"format": "{{ output_2 }}",
},
{
"value": MockObject(value="!!", key="key"),
"name": "output_3",
"description": "This is a test output with a mock object.",
"format": "{{ output_3 }}",
},
],
test_output=[
("output", "Hello, World!!!"),
("output", "42"),
("output", MockObject(value="!!", key="key")),
],
categories={BlockCategory.OUTPUT, BlockCategory.BASIC},
block_type=BlockType.OUTPUT,
static_output=True,
)
async def run(self, input_data: Input, *args, **kwargs) -> BlockOutput:
"""
Attempts to format the recorded_value using the fmt_string if provided.
If formatting fails or no fmt_string is given, returns the original recorded_value.
"""
if input_data.format:
try:
formatter = TextFormatter(autoescape=input_data.escape_html)
yield "output", await formatter.format_string(
input_data.format, {input_data.name: input_data.value}
)
except Exception as e:
yield "output", f"Error: {e}, {input_data.value}"
else:
yield "output", input_data.value
yield "name", input_data.name
class AgentShortTextInputBlock(AgentInputBlock):
class Input(AgentInputBlock.Input):
value: Optional[ShortTextType] = SchemaField(
description="Short text input.",
default=None,
advanced=False,
title="Default Value",
)
class Output(AgentInputBlock.Output):
result: str = SchemaField(description="Short text result.")
def __init__(self):
super().__init__(
id="7fcd3bcb-8e1b-4e69-903d-32d3d4a92158",
description="Block for short text input (single-line).",
disabled=not config.enable_agent_input_subtype_blocks,
input_schema=AgentShortTextInputBlock.Input,
output_schema=AgentShortTextInputBlock.Output,
test_input=[
{
"value": "Hello",
"name": "short_text_1",
"description": "Short text example 1",
},
{
"value": "Quick test",
"name": "short_text_2",
"description": "Short text example 2",
},
],
test_output=[
("result", "Hello"),
("result", "Quick test"),
],
)
class AgentLongTextInputBlock(AgentInputBlock):
class Input(AgentInputBlock.Input):
value: Optional[LongTextType] = SchemaField(
description="Long text input (potentially multi-line).",
default=None,
advanced=False,
title="Default Value",
)
class Output(AgentInputBlock.Output):
result: str = SchemaField(description="Long text result.")
def __init__(self):
super().__init__(
id="90a56ffb-7024-4b2b-ab50-e26c5e5ab8ba",
description="Block for long text input (multi-line).",
disabled=not config.enable_agent_input_subtype_blocks,
input_schema=AgentLongTextInputBlock.Input,
output_schema=AgentLongTextInputBlock.Output,
test_input=[
{
"value": "Lorem ipsum dolor sit amet...",
"name": "long_text_1",
"description": "Long text example 1",
},
{
"value": "Another multiline text input.",
"name": "long_text_2",
"description": "Long text example 2",
},
],
test_output=[
("result", "Lorem ipsum dolor sit amet..."),
("result", "Another multiline text input."),
],
)
class AgentNumberInputBlock(AgentInputBlock):
class Input(AgentInputBlock.Input):
value: Optional[int] = SchemaField(
description="Number input.",
default=None,
advanced=False,
title="Default Value",
)
class Output(AgentInputBlock.Output):
result: int = SchemaField(description="Number result.")
def __init__(self):
super().__init__(
id="96dae2bb-97a2-41c2-bd2f-13a3b5a8ea98",
description="Block for number input.",
disabled=not config.enable_agent_input_subtype_blocks,
input_schema=AgentNumberInputBlock.Input,
output_schema=AgentNumberInputBlock.Output,
test_input=[
{
"value": 42,
"name": "number_input_1",
"description": "Number example 1",
},
{
"value": 314,
"name": "number_input_2",
"description": "Number example 2",
},
],
test_output=[
("result", 42),
("result", 314),
],
)
class AgentDateInputBlock(AgentInputBlock):
class Input(AgentInputBlock.Input):
value: Optional[date] = SchemaField(
description="Date input (YYYY-MM-DD).",
default=None,
advanced=False,
title="Default Value",
)
class Output(AgentInputBlock.Output):
result: date = SchemaField(description="Date result.")
def __init__(self):
super().__init__(
id="7e198b09-4994-47db-8b4d-952d98241817",
description="Block for date input.",
disabled=not config.enable_agent_input_subtype_blocks,
input_schema=AgentDateInputBlock.Input,
output_schema=AgentDateInputBlock.Output,
test_input=[
{
# If your system can parse JSON date strings to date objects
"value": str(date(2025, 3, 19)),
"name": "date_input_1",
"description": "Example date input 1",
},
{
"value": str(date(2023, 12, 31)),
"name": "date_input_2",
"description": "Example date input 2",
},
],
test_output=[
("result", date(2025, 3, 19)),
("result", date(2023, 12, 31)),
],
)
class AgentTimeInputBlock(AgentInputBlock):
class Input(AgentInputBlock.Input):
value: Optional[time] = SchemaField(
description="Time input (HH:MM:SS).",
default=None,
advanced=False,
title="Default Value",
)
class Output(AgentInputBlock.Output):
result: time = SchemaField(description="Time result.")
def __init__(self):
super().__init__(
id="2a1c757e-86cf-4c7e-aacf-060dc382e434",
description="Block for time input.",
disabled=not config.enable_agent_input_subtype_blocks,
input_schema=AgentTimeInputBlock.Input,
output_schema=AgentTimeInputBlock.Output,
test_input=[
{
"value": str(time(9, 30, 0)),
"name": "time_input_1",
"description": "Time example 1",
},
{
"value": str(time(23, 59, 59)),
"name": "time_input_2",
"description": "Time example 2",
},
],
test_output=[
("result", time(9, 30, 0)),
("result", time(23, 59, 59)),
],
)
class AgentFileInputBlock(AgentInputBlock):
"""
A simplified file-upload block. In real usage, you might have a custom
file type or handle binary data. Here, we'll store a string path as the example.
"""
class Input(AgentInputBlock.Input):
value: Optional[MediaFileType] = SchemaField(
description="Path or reference to an uploaded file.",
default=None,
advanced=False,
title="Default Value",
)
base_64: bool = SchemaField(
description="Whether produce an output in base64 format (not recommended, you can pass the string path just fine accross blocks).",
default=False,
advanced=True,
title="Produce Base64 Output",
)
class Output(AgentInputBlock.Output):
result: str = SchemaField(description="File reference/path result.")
def __init__(self):
super().__init__(
id="95ead23f-8283-4654-aef3-10c053b74a31",
description="Block for file upload input (string path for example).",
disabled=not config.enable_agent_input_subtype_blocks,
input_schema=AgentFileInputBlock.Input,
output_schema=AgentFileInputBlock.Output,
test_input=[
{
"value": "data:image/png;base64,MQ==",
"name": "file_upload_1",
"description": "Example file upload 1",
},
],
test_output=[
("result", str),
],
)
async def run(
self,
input_data: Input,
*,
execution_context: ExecutionContext,
**kwargs,
) -> BlockOutput:
if not input_data.value:
return
# Determine return format based on user preference
# for_external_api: always returns data URI (base64) - honors "Produce Base64 Output"
# for_block_output: smart format - workspace:// in CoPilot, data URI in graphs
return_format = "for_external_api" if input_data.base_64 else "for_block_output"
yield "result", await store_media_file(
file=input_data.value,
execution_context=execution_context,
return_format=return_format,
)
class AgentDropdownInputBlock(AgentInputBlock):
"""
A specialized text input block that presents a dropdown selector
restricted to a fixed set of values.
"""
class Input(AgentInputBlock.Input):
value: Optional[str] = SchemaField(
description="Text selected from a dropdown.",
default=None,
advanced=False,
title="Default Value",
)
# Use Field() directly (not SchemaField) to pass validation_alias,
# which handles backward compat for legacy "placeholder_values" across
# all construction paths (model_construct, __init__, model_validate).
options: list = Field(
default_factory=list,
title="Dropdown Options",
description=(
"If provided, renders the input as a dropdown selector "
"restricted to these values. Leave empty for free-text input."
),
validation_alias=AliasChoices("options", "placeholder_values"),
json_schema_extra={"advanced": False, "secret": False},
)
def generate_schema(self):
schema = super().generate_schema()
if possible_values := self.options:
schema["enum"] = possible_values
return schema
class Output(AgentInputBlock.Output):
result: str = SchemaField(description="Selected dropdown value.")
def __init__(self):
super().__init__(
id="655d6fdf-a334-421c-b733-520549c07cd1",
description="Block for dropdown text selection.",
disabled=not config.enable_agent_input_subtype_blocks,
input_schema=AgentDropdownInputBlock.Input,
output_schema=AgentDropdownInputBlock.Output,
test_input=[
{
"value": "Option A",
"name": "dropdown_1",
"options": ["Option A", "Option B", "Option C"],
"description": "Dropdown example 1",
},
{
"value": "Option C",
"name": "dropdown_2",
"options": ["Option A", "Option B", "Option C"],
"description": "Dropdown example 2",
},
],
test_output=[
("result", "Option A"),
("result", "Option C"),
],
)
class AgentToggleInputBlock(AgentInputBlock):
class Input(AgentInputBlock.Input):
value: bool = SchemaField(
description="Boolean toggle input.",
default=False,
advanced=False,
title="Default Value",
)
class Output(AgentInputBlock.Output):
result: bool = SchemaField(description="Boolean toggle result.")
def __init__(self):
super().__init__(
id="cbf36ab5-df4a-43b6-8a7f-f7ed8652116e",
description="Block for boolean toggle input.",
disabled=not config.enable_agent_input_subtype_blocks,
input_schema=AgentToggleInputBlock.Input,
output_schema=AgentToggleInputBlock.Output,
test_input=[
{
"value": True,
"name": "toggle_1",
"description": "Toggle example 1",
},
{
"value": False,
"name": "toggle_2",
"description": "Toggle example 2",
},
],
test_output=[
("result", True),
("result", False),
],
)
class AgentTableInputBlock(AgentInputBlock):
"""
This block allows users to input data in a table format.
Configure the table columns at build time, then users can input
rows of data at runtime. Each row is output as a dictionary
with column names as keys.
"""
class Input(AgentInputBlock.Input):
value: Optional[list[dict[str, Any]]] = SchemaField(
description="The table data as a list of dictionaries.",
default=None,
advanced=False,
title="Default Value",
)
column_headers: list[str] = SchemaField(
description="Column headers for the table.",
default_factory=lambda: ["Column 1", "Column 2", "Column 3"],
advanced=False,
title="Column Headers",
)
def generate_schema(self):
"""Generate schema for the value field with table format."""
schema = super().generate_schema()
schema["type"] = "array"
schema["format"] = "table"
schema["items"] = {
"type": "object",
"properties": {
header: {"type": "string"}
for header in (
self.column_headers or ["Column 1", "Column 2", "Column 3"]
)
},
}
if self.value is not None:
schema["default"] = self.value
return schema
class Output(AgentInputBlock.Output):
result: list[dict[str, Any]] = SchemaField(
description="The table data as a list of dictionaries with headers as keys."
)
def __init__(self):
super().__init__(
id="5603b273-f41e-4020-af7d-fbc9c6a8d928",
description="Block for table data input with customizable headers.",
disabled=not config.enable_agent_input_subtype_blocks,
input_schema=AgentTableInputBlock.Input,
output_schema=AgentTableInputBlock.Output,
test_input=[
{
"name": "test_table",
"column_headers": ["Name", "Age", "City"],
"value": [
{"Name": "John", "Age": "30", "City": "New York"},
{"Name": "Jane", "Age": "25", "City": "London"},
],
"description": "Example table input",
}
],
test_output=[
(
"result",
[
{"Name": "John", "Age": "30", "City": "New York"},
{"Name": "Jane", "Age": "25", "City": "London"},
],
)
],
)
async def run(self, input_data: Input, *args, **kwargs) -> BlockOutput:
"""
Yields the table data as a list of dictionaries.
"""
# Pass through the value, defaulting to empty list if None
yield "result", input_data.value if input_data.value is not None else []
class AgentGoogleDriveFileInputBlock(AgentInputBlock):
"""
This block allows users to select a file from Google Drive.
It provides a Google Drive file picker UI that handles both authentication
and file selection. The selected file information (ID, name, URL, etc.)
is output for use by other blocks like Google Sheets Read.
"""
class Input(AgentInputBlock.Input):
value: Optional[GoogleDriveFile] = SchemaField(
description="The selected Google Drive file.",
default=None,
advanced=False,
title="Selected File",
)
allowed_views: list[AttachmentView] = SchemaField(
description="Which views to show in the file picker (DOCS, SPREADSHEETS, PRESENTATIONS, etc.).",
default_factory=lambda: ["DOCS", "SPREADSHEETS", "PRESENTATIONS"],
advanced=False,
title="Allowed Views",
)
allow_folder_selection: bool = SchemaField(
description="Whether to allow selecting folders.",
default=False,
advanced=True,
title="Allow Folder Selection",
)
def generate_schema(self):
"""Generate schema for the value field with Google Drive picker format."""
schema = super().generate_schema()
# Default scopes for drive.file access
scopes = ["https://www.googleapis.com/auth/drive.file"]
# Build picker configuration
picker_config = {
"multiselect": False, # Single file selection only for now
"allow_folder_selection": self.allow_folder_selection,
"allowed_views": (
list(self.allowed_views) if self.allowed_views else ["DOCS"]
),
"scopes": scopes,
# Auto-credentials config tells frontend to include _credentials_id in output
"auto_credentials": {
"provider": "google",
"type": "oauth2",
"scopes": scopes,
"kwarg_name": "credentials",
},
}
# Set format and config for frontend to render Google Drive picker
schema["format"] = "google-drive-picker"
schema["google_drive_picker_config"] = picker_config
# Also keep auto_credentials at top level for backend detection
schema["auto_credentials"] = {
"provider": "google",
"type": "oauth2",
"scopes": scopes,
"kwarg_name": "credentials",
}
if self.value is not None:
schema["default"] = self.value.model_dump()
return schema
class Output(AgentInputBlock.Output):
result: GoogleDriveFile = SchemaField(
description="The selected Google Drive file with ID, name, URL, and other metadata."
)
def __init__(self):
test_file = GoogleDriveFile.model_validate(
{
"id": "test-file-id",
"name": "Test Spreadsheet",
"mimeType": "application/vnd.google-apps.spreadsheet",
"url": "https://docs.google.com/spreadsheets/d/test-file-id",
}
)
super().__init__(
id="d3b32f15-6fd7-40e3-be52-e083f51b19a2",
description="Block for selecting a file from Google Drive.",
disabled=not config.enable_agent_input_subtype_blocks,
input_schema=AgentGoogleDriveFileInputBlock.Input,
output_schema=AgentGoogleDriveFileInputBlock.Output,
test_input=[
{
"name": "spreadsheet_input",
"description": "Select a spreadsheet from Google Drive",
"allowed_views": ["SPREADSHEETS"],
"value": {
"id": "test-file-id",
"name": "Test Spreadsheet",
"mimeType": "application/vnd.google-apps.spreadsheet",
"url": "https://docs.google.com/spreadsheets/d/test-file-id",
},
}
],
test_output=[("result", test_file)],
)
async def run(self, input_data: Input, *args, **kwargs) -> BlockOutput:
"""
Yields the selected Google Drive file.
"""
if input_data.value is not None:
yield "result", input_data.value
IO_BLOCK_IDs = [
AgentInputBlock().id,
AgentOutputBlock().id,
AgentShortTextInputBlock().id,
AgentLongTextInputBlock().id,
AgentNumberInputBlock().id,
AgentDateInputBlock().id,
AgentTimeInputBlock().id,
AgentFileInputBlock().id,
AgentDropdownInputBlock().id,
AgentToggleInputBlock().id,
AgentTableInputBlock().id,
AgentGoogleDriveFileInputBlock().id,
]
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