refactor(backend): Make block fields consistently use SchemaField (#8360

)

autogpt_platform/backend/backend/blocks/__init__.py

@@ -69,6 +69,17 @@ def all_subclasses(clz):
             f"{block.name} `error` field in output_schema must be a string"
         )
 
+    # Make sure all fields in input_schema and output_schema are annotated and has a value
+    for field_name, field in [*input_schema.items(), *output_schema.items()]:
+        if field.annotation is None:
+            raise ValueError(
+                f"{block.name} has a field {field_name} that is not annotated"
+            )
+        if field.json_schema_extra is None:
+            raise ValueError(
+                f"{block.name} has a field {field_name} not defined as SchemaField"
+            )
+
     for field in block.input_schema.model_fields.values():
         if field.annotation is bool and field.default not in (True, False):
             raise ValueError(f"{block.name} has a boolean field with no default value")

autogpt_platform/backend/backend/blocks/ai_shortform_video_block.py

@@ -3,7 +3,6 @@
 from enum import Enum
 
 import requests
-from pydantic import Field
 
 from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
 from backend.data.model import BlockSecret, SchemaField, SecretField
@@ -129,9 +128,13 @@ class Input(BlockSchema):
             description="""1. Use short and punctuated sentences\n\n2. Use linebreaks to create a new clip\n\n3. Text outside of brackets is spoken by the AI, and [text between brackets] will be used to guide the visual generation. For example, [close-up of a cat] will show a close-up of a cat.""",
             placeholder="[close-up of a cat] Meow!",
         )
-        ratio: str = Field(description="Aspect ratio of the video", default="9 / 16")
-        resolution: str = Field(description="Resolution of the video", default="720p")
-        frame_rate: int = Field(description="Frame rate of the video", default=60)
+        ratio: str = SchemaField(
+            description="Aspect ratio of the video", default="9 / 16"
+        )
+        resolution: str = SchemaField(
+            description="Resolution of the video", default="720p"
+        )
+        frame_rate: int = SchemaField(description="Frame rate of the video", default=60)
         generation_preset: GenerationPreset = SchemaField(
             description="Generation preset for visual style - only effects AI generated visuals",
             default=GenerationPreset.LEONARDO,
@@ -154,8 +157,8 @@ class Input(BlockSchema):
         )
 
     class Output(BlockSchema):
-        video_url: str = Field(description="The URL of the created video")
-        error: str = Field(description="Error message if the request failed")
+        video_url: str = SchemaField(description="The URL of the created video")
+        error: str = SchemaField(description="Error message if the request failed")
 
     def __init__(self):
         super().__init__(

autogpt_platform/backend/backend/blocks/basic.py

@@ -2,7 +2,6 @@
 from typing import Any, List
 
 from jinja2 import BaseLoader, Environment
-from pydantic import Field
 
 from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema, BlockType
 from backend.data.model import SchemaField
@@ -19,18 +18,18 @@ class StoreValueBlock(Block):
     """
 
     class Input(BlockSchema):
-        input: Any = Field(
+        input: Any = SchemaField(
             description="Trigger the block to produce the output. "
             "The value is only used when `data` is None."
         )
-        data: Any = Field(
+        data: Any = SchemaField(
             description="The constant data to be retained in the block. "
             "This value is passed as `output`.",
             default=None,
         )
 
     class Output(BlockSchema):
-        output: Any
+        output: Any = SchemaField(description="The stored data retained in the block.")
 
     def __init__(self):
         super().__init__(
@@ -56,10 +55,10 @@ def run(self, input_data: Input, **kwargs) -> BlockOutput:
 
 class PrintToConsoleBlock(Block):
     class Input(BlockSchema):
-        text: str
+        text: str = SchemaField(description="The text to print to the console.")
 
     class Output(BlockSchema):
-        status: str
+        status: str = SchemaField(description="The status of the print operation.")
 
     def __init__(self):
         super().__init__(
@@ -79,12 +78,14 @@ def run(self, input_data: Input, **kwargs) -> BlockOutput:
 
 class FindInDictionaryBlock(Block):
     class Input(BlockSchema):
-        input: Any = Field(description="Dictionary to lookup from")
-        key: str | int = Field(description="Key to lookup in the dictionary")
+        input: Any = SchemaField(description="Dictionary to lookup from")
+        key: str | int = SchemaField(description="Key to lookup in the dictionary")
 
     class Output(BlockSchema):
-        output: Any = Field(description="Value found for the given key")
-        missing: Any = Field(description="Value of the input that missing the key")
+        output: Any = SchemaField(description="Value found for the given key")
+        missing: Any = SchemaField(
+            description="Value of the input that missing the key"
+        )
 
     def __init__(self):
         super().__init__(

autogpt_platform/backend/backend/blocks/block.py

@@ -3,6 +3,7 @@
 from typing import Type
 
 from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
+from backend.data.model import SchemaField
 
 
 class BlockInstallationBlock(Block):
@@ -15,11 +16,17 @@ class BlockInstallationBlock(Block):
     """
 
     class Input(BlockSchema):
-        code: str
+        code: str = SchemaField(
+            description="Python code of the block to be installed",
+        )
 
     class Output(BlockSchema):
-        success: str
-        error: str
+        success: str = SchemaField(
+            description="Success message if the block is installed successfully",
+        )
+        error: str = SchemaField(
+            description="Error message if the block installation fails",
+        )
 
     def __init__(self):
         super().__init__(

autogpt_platform/backend/backend/blocks/csv.py

@@ -1,21 +1,49 @@
 from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
-from backend.data.model import ContributorDetails
+from backend.data.model import ContributorDetails, SchemaField
 
 
 class ReadCsvBlock(Block):
     class Input(BlockSchema):
-        contents: str
-        delimiter: str = ","
-        quotechar: str = '"'
-        escapechar: str = "\\"
-        has_header: bool = True
-        skip_rows: int = 0
-        strip: bool = True
-        skip_columns: list[str] = []
+        contents: str = SchemaField(
+            description="The contents of the CSV file to read",
+            placeholder="a, b, c\n1,2,3\n4,5,6",
+        )
+        delimiter: str = SchemaField(
+            description="The delimiter used in the CSV file",
+            default=",",
+        )
+        quotechar: str = SchemaField(
+            description="The character used to quote fields",
+            default='"',
+        )
+        escapechar: str = SchemaField(
+            description="The character used to escape the delimiter",
+            default="\\",
+        )
+        has_header: bool = SchemaField(
+            description="Whether the CSV file has a header row",
+            default=True,
+        )
+        skip_rows: int = SchemaField(
+            description="The number of rows to skip from the start of the file",
+            default=0,
+        )
+        strip: bool = SchemaField(
+            description="Whether to strip whitespace from the values",
+            default=True,
+        )
+        skip_columns: list[str] = SchemaField(
+            description="The columns to skip from the start of the row",
+            default=[],
+        )
 
     class Output(BlockSchema):
-        row: dict[str, str]
-        all_data: list[dict[str, str]]
+        row: dict[str, str] = SchemaField(
+            description="The data produced from each row in the CSV file"
+        )
+        all_data: list[dict[str, str]] = SchemaField(
+            description="All the data in the CSV file as a list of rows"
+        )
 
     def __init__(self):
         super().__init__(

autogpt_platform/backend/backend/blocks/discord.py

@@ -2,27 +2,28 @@
 
 import aiohttp
 import discord
-from pydantic import Field
 
 from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
-from backend.data.model import BlockSecret, SecretField
+from backend.data.model import BlockSecret, SchemaField, SecretField
 
 
 class ReadDiscordMessagesBlock(Block):
     class Input(BlockSchema):
         discord_bot_token: BlockSecret = SecretField(
             key="discord_bot_token", description="Discord bot token"
         )
-        continuous_read: bool = Field(
+        continuous_read: bool = SchemaField(
             description="Whether to continuously read messages", default=True
         )
 
     class Output(BlockSchema):
-        message_content: str = Field(description="The content of the message received")
-        channel_name: str = Field(
+        message_content: str = SchemaField(
+            description="The content of the message received"
+        )
+        channel_name: str = SchemaField(
             description="The name of the channel the message was received from"
         )
-        username: str = Field(
+        username: str = SchemaField(
             description="The username of the user who sent the message"
         )
 
@@ -134,13 +135,15 @@ class Input(BlockSchema):
         discord_bot_token: BlockSecret = SecretField(
             key="discord_bot_token", description="Discord bot token"
         )
-        message_content: str = Field(description="The content of the message received")
-        channel_name: str = Field(
+        message_content: str = SchemaField(
+            description="The content of the message received"
+        )
+        channel_name: str = SchemaField(
             description="The name of the channel the message was received from"
         )
 
     class Output(BlockSchema):
-        status: str = Field(
+        status: str = SchemaField(
             description="The status of the operation (e.g., 'Message sent', 'Error')"
         )
 

autogpt_platform/backend/backend/blocks/email_block.py

@@ -2,17 +2,17 @@
 from email.mime.multipart import MIMEMultipart
 from email.mime.text import MIMEText
 
-from pydantic import BaseModel, ConfigDict, Field
+from pydantic import BaseModel, ConfigDict
 
 from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
 from backend.data.model import BlockSecret, SchemaField, SecretField
 
 
 class EmailCredentials(BaseModel):
-    smtp_server: str = Field(
+    smtp_server: str = SchemaField(
         default="smtp.gmail.com", description="SMTP server address"
     )
-    smtp_port: int = Field(default=25, description="SMTP port number")
+    smtp_port: int = SchemaField(default=25, description="SMTP port number")
     smtp_username: BlockSecret = SecretField(key="smtp_username")
     smtp_password: BlockSecret = SecretField(key="smtp_password")
 
@@ -30,7 +30,7 @@ class Input(BlockSchema):
         body: str = SchemaField(
             description="Body of the email", placeholder="Enter the email body"
         )
-        creds: EmailCredentials = Field(
+        creds: EmailCredentials = SchemaField(
             description="SMTP credentials",
             default=EmailCredentials(),
         )

autogpt_platform/backend/backend/blocks/http.py

@@ -4,6 +4,7 @@
 import requests
 
 from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
+from backend.data.model import SchemaField
 
 
 class HttpMethod(Enum):
@@ -18,15 +19,27 @@ class HttpMethod(Enum):
 
 class SendWebRequestBlock(Block):
     class Input(BlockSchema):
-        url: str
-        method: HttpMethod = HttpMethod.POST
-        headers: dict[str, str] = {}
-        body: object = {}
+        url: str = SchemaField(
+            description="The URL to send the request to",
+            placeholder="https://api.example.com",
+        )
+        method: HttpMethod = SchemaField(
+            description="The HTTP method to use for the request",
+            default=HttpMethod.POST,
+        )
+        headers: dict[str, str] = SchemaField(
+            description="The headers to include in the request",
+            default={},
+        )
+        body: object = SchemaField(
+            description="The body of the request",
+            default={},
+        )
 
     class Output(BlockSchema):
-        response: object
-        client_error: object
-        server_error: object
+        response: object = SchemaField(description="The response from the server")
+        client_error: object = SchemaField(description="The error on 4xx status codes")
+        server_error: object = SchemaField(description="The error on 5xx status codes")
 
     def __init__(self):
         super().__init__(

autogpt_platform/backend/backend/blocks/ideogram.py

@@ -75,28 +75,24 @@ class Input(BlockSchema):
             description="The name of the Image Generation Model, e.g., V_2",
             default=IdeogramModelName.V2,
             title="Image Generation Model",
-            enum=IdeogramModelName,
             advanced=False,
         )
         aspect_ratio: AspectRatio = SchemaField(
             description="Aspect ratio for the generated image",
             default=AspectRatio.ASPECT_1_1,
             title="Aspect Ratio",
-            enum=AspectRatio,
             advanced=False,
         )
         upscale: UpscaleOption = SchemaField(
             description="Upscale the generated image",
             default=UpscaleOption.NO_UPSCALE,
             title="Upscale Image",
-            enum=UpscaleOption,
             advanced=False,
         )
         magic_prompt_option: MagicPromptOption = SchemaField(
             description="Whether to use MagicPrompt for enhancing the request",
             default=MagicPromptOption.AUTO,
             title="Magic Prompt Option",
-            enum=MagicPromptOption,
             advanced=True,
         )
         seed: Optional[int] = SchemaField(
@@ -109,7 +105,6 @@ class Input(BlockSchema):
             description="Style type to apply, applicable for V_2 and above",
             default=StyleType.AUTO,
             title="Style Type",
-            enum=StyleType,
             advanced=True,
         )
         negative_prompt: Optional[str] = SchemaField(
@@ -122,7 +117,6 @@ class Input(BlockSchema):
             description="Color palette preset name, choose 'None' to skip",
             default=ColorPalettePreset.NONE,
             title="Color Palette Preset",
-            enum=ColorPalettePreset,
             advanced=True,
         )