Copy of Contributing to AutoGPT Agent Server: Creating and Testing Blocks
This guide will walk you through the process of creating and testing a new block for the AutoGPT Agent Server, using the WikipediaSummaryBlock as an example.
New SDK-Based Approach
For a more comprehensive guide using the new SDK pattern with ProviderBuilder and advanced features like OAuth and webhooks, see the Block SDK Guide.
Understanding Blocks and Testing
Blocks are reusable components that can be connected to form a graph representing an agent's behavior. Each block has inputs, outputs, and a specific function. Proper testing is crucial to ensure blocks work correctly and consistently.
Creating and Testing a New Block
Follow these steps to create and test a new block:
Create a new Python file for your block in the
autogpt_platform/backend/backend/blocksdirectory. Name it descriptively and use snake_case. For example:get_wikipedia_summary.py.Import necessary modules and create a class that inherits from
Block. Make sure to include all necessary imports for your block.
Every block should contain the following:
from backend.data.block import Block, BlockSchemaInput, BlockSchemaOutput, BlockOutputExample for the Wikipedia summary block:
from backend.data.block import Block, BlockSchemaInput, BlockSchemaOutput, BlockOutput
from backend.utils.get_request import GetRequest
import requests
class WikipediaSummaryBlock(Block, GetRequest):
# Block implementation will go hereDefine the input and output schemas using
BlockSchema. These schemas specify the data structure that the block expects to receive (input) and produce (output).The input schema defines the structure of the data the block will process. Each field in the schema represents a required piece of input data.
The output schema defines the structure of the data the block will return after processing. Each field in the schema represents a piece of output data.
Example:
class Input(BlockSchemaInput):
topic: str # The topic to get the Wikipedia summary for
class Output(BlockSchemaOutput):
summary: str # The summary of the topic from WikipediaImplement the
__init__method, including test data and mocks:
!!! important Use UUID generator (e.g. https://www.uuidgenerator.net/) for every new block id and do not make up your own. Alternatively, you can run this python code to generate an uuid: print(__import__('uuid').uuid4())
def __init__(self):
super().__init__(
# Unique ID for the block, used across users for templates
# If you are an AI leave it as is or change to "generate-proper-uuid"
id="xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx",
input_schema=WikipediaSummaryBlock.Input, # Assign input schema
output_schema=WikipediaSummaryBlock.Output, # Assign output schema
# Provide sample input, output and test mock for testing the block
test_input={"topic": "Artificial Intelligence"},
test_output=("summary", "summary content"),
test_mock={"get_request": lambda url, json: {"extract": "summary content"}},
)id: A unique identifier for the block.input_schemaandoutput_schema: Define the structure of the input and output data.
Let's break down the testing components:
test_input: This is a sample input that will be used to test the block. It should be a valid input according to your Input schema.test_output: This is the expected output when running the block with thetest_input. It should match your Output schema. For non-deterministic outputs or when you only want to assert the type, you can use Python types instead of specific values. In this example,("summary", str)asserts that the output key is "summary" and its value is a string.test_mock: This is crucial for blocks that make network calls. It provides a mock function that replaces the actual network call during testing.
In this case, we're mocking the get_request method to always return a dictionary with an 'extract' key, simulating a successful API response. This allows us to test the block's logic without making actual network requests, which could be slow, unreliable, or rate-limited.
Implement the
runmethod with error handling. This should contain the main logic of the block:
def run(self, input_data: Input, **kwargs) -> BlockOutput:
try:
topic = input_data.topic
url = f"https://en.wikipedia.org/api/rest_v1/page/summary/{topic}"
response = self.get_request(url, json=True)
yield "summary", response['extract']
except requests.exceptions.HTTPError as http_err:
raise RuntimeError(f"HTTP error occurred: {http_err}")Try block: Contains the main logic to fetch and process the Wikipedia summary.
API request: Send a GET request to the Wikipedia API.
Error handling: Handle various exceptions that might occur during the API request and data processing. We don't need to catch all exceptions, only the ones we expect and can handle. The uncaught exceptions will be automatically yielded as
errorin the output. Any block that raises an exception (or yields anerroroutput) will be marked as failed. Prefer raising exceptions over yieldingerror, as it will stop the execution immediately.Yield: Use
yieldto output the results. Prefer to output one result object at a time. If you are calling a function that returns a list, you can yield each item in the list separately. You can also yield the whole list as well, but do both rather than yielding the list. For example: If you were writing a block that outputs emails, you'd yield each email as a separate result object, but you could also yield the whole list as an additional single result object. Yielding output namederrorwill break the execution right away and mark the block execution as failed.kwargs: The
kwargsparameter is used to pass additional arguments to the block. It is not used in the example above, but it is available to the block. You can also have args as inline signatures in the run method aladef run(self, input_data: Input, *, user_id: str, **kwargs) -> BlockOutput:. Available kwargs are:user_id: The ID of the user running the block.graph_id: The ID of the agent that is executing the block. This is the same for every version of the agentgraph_exec_id: The ID of the execution of the agent. This changes every time the agent has a new "run"node_exec_id: The ID of the execution of the node. This changes every time the node is executednode_id: The ID of the node that is being executed. It changes every version of the graph, but not every time the node is executed.
Field Types
oneOf fields
oneOf allows you to specify that a field must be exactly one of several possible options. This is useful when you want your block to accept different types of inputs that are mutually exclusive.
Example:
attachment: Union[Media, DeepLink, Poll, Place, Quote] = SchemaField(
discriminator='discriminator',
description="Attach either media, deep link, poll, place or quote - only one can be used"
)The discriminator parameter tells AutoGPT which field to look at in the input to determine which type it is.
In each model, you need to define the discriminator value:
class Media(BaseModel):
discriminator: Literal['media']
media_ids: List[str]
class DeepLink(BaseModel):
discriminator: Literal['deep_link']
direct_message_deep_link: strOptionalOneOf fields
OptionalOneOf is similar to oneOf but allows the field to be optional (None). This means the field can be either one of the specified types or None.
Example:
attachment: Union[Media, DeepLink, Poll, Place, Quote] | None = SchemaField(
discriminator='discriminator',
description="Optional attachment - can be media, deep link, poll, place, quote or None"
)The key difference is the | None which makes the entire field optional.
Blocks with authentication
Our system supports auth offloading for API keys and OAuth2 authorization flows. Adding a block with API key authentication is straight-forward, as is adding a block for a service that we already have OAuth2 support for.
Implementing the block itself is relatively simple. On top of the instructions above, you're going to add a credentials parameter to the Input model and the run method:
from backend.data.model import (
APIKeyCredentials,
OAuth2Credentials,
Credentials,
)
from backend.data.block import Block, BlockOutput, BlockSchemaInput, BlockSchemaOutput
from backend.data.model import CredentialsField
from backend.integrations.providers import ProviderName
# API Key auth:
class BlockWithAPIKeyAuth(Block):
class Input(BlockSchemaInput):
# Note that the type hint below is require or you will get a type error.
# The first argument is the provider name, the second is the credential type.
credentials: CredentialsMetaInput[
Literal[ProviderName.GITHUB], Literal["api_key"]
] = CredentialsField(
description="The GitHub integration can be used with "
"any API key with sufficient permissions for the blocks it is used on.",
)
# ...
def run(
self,
input_data: Input,
*,
credentials: APIKeyCredentials,
**kwargs,
) -> BlockOutput:
...
# OAuth:
class BlockWithOAuth(Block):
class Input(BlockSchemaInput):
# Note that the type hint below is require or you will get a type error.
# The first argument is the provider name, the second is the credential type.
credentials: CredentialsMetaInput[
Literal[ProviderName.GITHUB], Literal["oauth2"]
] = CredentialsField(
required_scopes={"repo"},
description="The GitHub integration can be used with OAuth.",
)
# ...
def run(
self,
input_data: Input,
*,
credentials: OAuth2Credentials,
**kwargs,
) -> BlockOutput:
...
# API Key auth + OAuth:
class BlockWithAPIKeyAndOAuth(Block):
class Input(BlockSchemaInput):
# Note that the type hint below is require or you will get a type error.
# The first argument is the provider name, the second is the credential type.
credentials: CredentialsMetaInput[
Literal[ProviderName.GITHUB], Literal["api_key", "oauth2"]
] = CredentialsField(
required_scopes={"repo"},
description="The GitHub integration can be used with OAuth, "
"or any API key with sufficient permissions for the blocks it is used on.",
)
# ...
def run(
self,
input_data: Input,
*,
credentials: Credentials,
**kwargs,
) -> BlockOutput:
...The credentials will be automagically injected by the executor in the back end.
The APIKeyCredentials and OAuth2Credentials models are defined here. To use them in e.g. an API request, you can either access the token directly:
# credentials: APIKeyCredentials
response = requests.post(
url,
headers={
"Authorization": f"Bearer {credentials.api_key.get_secret_value()})",
},
)
# credentials: OAuth2Credentials
response = requests.post(
url,
headers={
"Authorization": f"Bearer {credentials.access_token.get_secret_value()})",
},
)or use the shortcut credentials.auth_header():
# credentials: APIKeyCredentials | OAuth2Credentials
response = requests.post(
url,
headers={"Authorization": credentials.auth_header()},
)The ProviderName enum is the single source of truth for which providers exist in our system. Naturally, to add an authenticated block for a new provider, you'll have to add it here too.
Multiple credentials inputs
Multiple credentials inputs are supported, under the following conditions:
The name of each of the credentials input fields must end with
_credentials.The names of the credentials input fields must match the names of the corresponding parameters on the
run(..)method of the block.If more than one of the credentials parameters are required,
test_credentialsis adict[str, Credentials], with for each required credentials input the parameter name as the key and suitable test credentials as the value.
Adding an OAuth2 service integration
To add support for a new OAuth2-authenticated service, you'll need to add an OAuthHandler. All our existing handlers and the base class can be found here.
Every handler must implement the following parts of the [BaseOAuthHandler] interface:
backend/integrations/oauth/base.py
PROVIDER_NAME: ClassVar[ProviderName | str]
DEFAULT_SCOPES: ClassVar[list[str]] = []
def __init__(self, client_id: str, client_secret: str, redirect_uri: str): ...
def get_login_url(
self, scopes: list[str], state: str, code_challenge: Optional[str]
) -> str:
async def exchange_code_for_tokens(
self, code: str, scopes: list[str], code_verifier: Optional[str]
) -> OAuth2Credentials:
async def _refresh_tokens(
self, credentials: OAuth2Credentials
) -> OAuth2Credentials:
async def revoke_tokens(self, credentials: OAuth2Credentials) -> bool:As you can see, this is modeled after the standard OAuth2 flow.
Aside from implementing the OAuthHandler itself, adding a handler into the system requires two more things:
Adding the handler class to
HANDLERS_BY_NAMEunderintegrations/oauth/__init__.py
backend/integrations/oauth/__init__.py
# Build handlers dict with string keys for compatibility with SDK auto-registration
_ORIGINAL_HANDLERS = [
DiscordOAuthHandler,
GitHubOAuthHandler,
GoogleOAuthHandler,
NotionOAuthHandler,
TwitterOAuthHandler,
TodoistOAuthHandler,
]
# Start with original handlers
_handlers_dict = {
(
handler.PROVIDER_NAME.value
if hasattr(handler.PROVIDER_NAME, "value")
else str(handler.PROVIDER_NAME)
): handler
for handler in _ORIGINAL_HANDLERS
}
class SDKAwareCredentials(BaseModel):
"""OAuth credentials configuration."""
use_secrets: bool = True
client_id_env_var: Optional[str] = None
client_secret_env_var: Optional[str] = None
_credentials_by_provider = {}
# Add default credentials for original handlers
for handler in _ORIGINAL_HANDLERS:
provider_name = (
handler.PROVIDER_NAME.value
if hasattr(handler.PROVIDER_NAME, "value")
else str(handler.PROVIDER_NAME)
)
_credentials_by_provider[provider_name] = SDKAwareCredentials(
use_secrets=True, client_id_env_var=None, client_secret_env_var=None
)
# Create a custom dict class that includes SDK handlers
class SDKAwareHandlersDict(dict):
"""Dictionary that automatically includes SDK-registered OAuth handlers."""
def __getitem__(self, key):
# First try the original handlers
if key in _handlers_dict:
return _handlers_dict[key]
# Then try SDK handlers
try:
from backend.sdk import AutoRegistry
sdk_handlers = AutoRegistry.get_oauth_handlers()
if key in sdk_handlers:
return sdk_handlers[key]
except ImportError:
pass
# If not found, raise KeyError
raise KeyError(key)
def get(self, key, default=None):
try:
return self[key]
except KeyError:
return default
def __contains__(self, key):
if key in _handlers_dict:
return True
try:
from backend.sdk import AutoRegistry
sdk_handlers = AutoRegistry.get_oauth_handlers()
return key in sdk_handlers
except ImportError:
return False
def keys(self):
# Combine all keys into a single dict and return its keys view
combined = dict(_handlers_dict)
try:
from backend.sdk import AutoRegistry
sdk_handlers = AutoRegistry.get_oauth_handlers()
combined.update(sdk_handlers)
except ImportError:
pass
return combined.keys()
def values(self):
combined = dict(_handlers_dict)
try:
from backend.sdk import AutoRegistry
sdk_handlers = AutoRegistry.get_oauth_handlers()
combined.update(sdk_handlers)
except ImportError:
pass
return combined.values()
def items(self):
combined = dict(_handlers_dict)
try:
from backend.sdk import AutoRegistry
sdk_handlers = AutoRegistry.get_oauth_handlers()
combined.update(sdk_handlers)
except ImportError:
pass
return combined.items()
class SDKAwareCredentialsDict(dict):
"""Dictionary that automatically includes SDK-registered OAuth credentials."""
def __getitem__(self, key):
# First try the original handlers
if key in _credentials_by_provider:
return _credentials_by_provider[key]
# Then try SDK credentials
try:
from backend.sdk import AutoRegistry
sdk_credentials = AutoRegistry.get_oauth_credentials()
if key in sdk_credentials:
# Convert from SDKOAuthCredentials to SDKAwareCredentials
sdk_cred = sdk_credentials[key]
return SDKAwareCredentials(
use_secrets=sdk_cred.use_secrets,
client_id_env_var=sdk_cred.client_id_env_var,
client_secret_env_var=sdk_cred.client_secret_env_var,
)
except ImportError:
pass
# If not found, raise KeyError
raise KeyError(key)
def get(self, key, default=None):
try:
return self[key]
except KeyError:
return default
def __contains__(self, key):
if key in _credentials_by_provider:
return True
try:
from backend.sdk import AutoRegistry
sdk_credentials = AutoRegistry.get_oauth_credentials()
return key in sdk_credentials
except ImportError:
return False
def keys(self):
# Combine all keys into a single dict and return its keys view
combined = dict(_credentials_by_provider)
try:
from backend.sdk import AutoRegistry
sdk_credentials = AutoRegistry.get_oauth_credentials()
combined.update(sdk_credentials)
except ImportError:
pass
return combined.keys()
def values(self):
combined = dict(_credentials_by_provider)
try:
from backend.sdk import AutoRegistry
sdk_credentials = AutoRegistry.get_oauth_credentials()
# Convert SDK credentials to SDKAwareCredentials
for key, sdk_cred in sdk_credentials.items():
combined[key] = SDKAwareCredentials(
use_secrets=sdk_cred.use_secrets,
client_id_env_var=sdk_cred.client_id_env_var,
client_secret_env_var=sdk_cred.client_secret_env_var,
)
except ImportError:
pass
return combined.values()
def items(self):
combined = dict(_credentials_by_provider)
try:
from backend.sdk import AutoRegistry
sdk_credentials = AutoRegistry.get_oauth_credentials()
# Convert SDK credentials to SDKAwareCredentials
for key, sdk_cred in sdk_credentials.items():
combined[key] = SDKAwareCredentials(
use_secrets=sdk_cred.use_secrets,
client_id_env_var=sdk_cred.client_id_env_var,
client_secret_env_var=sdk_cred.client_secret_env_var,
)
except ImportError:
pass
return combined.items()
HANDLERS_BY_NAME: dict[str, type["BaseOAuthHandler"]] = SDKAwareHandlersDict()
CREDENTIALS_BY_PROVIDER: dict[str, SDKAwareCredentials] = SDKAwareCredentialsDict()Adding
{provider}_client_idand{provider}_client_secretto the application'sSecretsunderutil/settings.py
backend/util/settings.py
github_client_id: str = Field(default="", description="GitHub OAuth client ID")
github_client_secret: str = Field(
default="", description="GitHub OAuth client secret"
)Adding to the frontend
You will need to add the provider (api or oauth) to the CredentialsInput component in /frontend/src/app/(platform)/library/agents/[id]/components/AgentRunsView/components/CredentialsInputs/CredentialsInputs.tsx.
frontend/src/components/integrations/credentials-input.tsx
--8 <
--"autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/AgentRunsView/components/CredentialsInputs/CredentialsInputs.tsx:ProviderIconsEmbed";You will also need to add the provider to the credentials provider list in frontend/src/components/integrations/helper.ts.
frontend/src/components/integrations/helper.ts
--8 <
--"autogpt_platform/frontend/src/components/integrations/helper.ts:CredentialsProviderNames";Finally you will need to add the provider to the CredentialsType enum in frontend/src/lib/autogpt-server-api/types.ts.
frontend/src/lib/autogpt-server-api/types.ts
--8 <
--"autogpt_platform/frontend/src/lib/autogpt-server-api/types.ts:BlockIOCredentialsSubSchema";Example: GitHub integration¶
GitHub blocks with API key + OAuth2 support:
blocks/github
backend/blocks/github/issues.py
class GithubCommentBlock(Block):
class Input(BlockSchemaInput):
credentials: GithubCredentialsInput = GithubCredentialsField("repo")
issue_url: str = SchemaField(
description="URL of the GitHub issue or pull request",
placeholder="https://github.com/owner/repo/issues/1",
)
comment: str = SchemaField(
description="Comment to post on the issue or pull request",
placeholder="Enter your comment",
)
class Output(BlockSchemaOutput):
id: int = SchemaField(description="ID of the created comment")
url: str = SchemaField(description="URL to the comment on GitHub")
error: str = SchemaField(
description="Error message if the comment posting failed"
)
def __init__(self):
super().__init__(
id="a8db4d8d-db1c-4a25-a1b0-416a8c33602b",
description="This block posts a comment on a specified GitHub issue or pull request.",
categories={BlockCategory.DEVELOPER_TOOLS},
input_schema=GithubCommentBlock.Input,
output_schema=GithubCommentBlock.Output,
test_input=[
{
"issue_url": "https://github.com/owner/repo/issues/1",
"comment": "This is a test comment.",
"credentials": TEST_CREDENTIALS_INPUT,
},
{
"issue_url": "https://github.com/owner/repo/pull/1",
"comment": "This is a test comment.",
"credentials": TEST_CREDENTIALS_INPUT,
},
],
test_credentials=TEST_CREDENTIALS,
test_output=[
("id", 1337),
("url", "https://github.com/owner/repo/issues/1#issuecomment-1337"),
("id", 1337),
(
"url",
"https://github.com/owner/repo/issues/1#issuecomment-1337",
),
],
test_mock={
"post_comment": lambda *args, **kwargs: (
1337,
"https://github.com/owner/repo/issues/1#issuecomment-1337",
)
},
)
@staticmethod
async def post_comment(
credentials: GithubCredentials, issue_url: str, body_text: str
) -> tuple[int, str]:
api = get_api(credentials)
data = {"body": body_text}
if "pull" in issue_url:
issue_url = issue_url.replace("pull", "issues")
comments_url = issue_url + "/comments"
response = await api.post(comments_url, json=data)
comment = response.json()
return comment["id"], comment["html_url"]
async def run(
self,
input_data: Input,
*,
credentials: GithubCredentials,
**kwargs,
) -> BlockOutput:
id, url = await self.post_comment(
credentials,
input_data.issue_url,
input_data.comment,
)
yield "id", id
yield "url", urlGitHub OAuth2 handler:
integrations/oauth/github.py
backend/integrations/oauth/github.py
class GitHubOAuthHandler(BaseOAuthHandler):
"""
Based on the documentation at:
- [Authorizing OAuth apps - GitHub Docs](https://docs.github.com/en/apps/oauth-apps/building-oauth-apps/authorizing-oauth-apps)
- [Refreshing user access tokens - GitHub Docs](https://docs.github.com/en/apps/creating-github-apps/authenticating-with-a-github-app/refreshing-user-access-tokens)
Notes:
- By default, token expiration is disabled on GitHub Apps. This means the access
token doesn't expire and no refresh token is returned by the authorization flow.
- When token expiration gets enabled, any existing tokens will remain non-expiring.
- When token expiration gets disabled, token refreshes will return a non-expiring
access token *with no refresh token*.
""" # noqa
PROVIDER_NAME = ProviderName.GITHUB
def __init__(self, client_id: str, client_secret: str, redirect_uri: str):
self.client_id = client_id
self.client_secret = client_secret
self.redirect_uri = redirect_uri
self.auth_base_url = "https://github.com/login/oauth/authorize"
self.token_url = "https://github.com/login/oauth/access_token"
self.revoke_url = "https://api.github.com/applications/{client_id}/token"
def get_login_url(
self, scopes: list[str], state: str, code_challenge: Optional[str]
) -> str:
params = {
"client_id": self.client_id,
"redirect_uri": self.redirect_uri,
"scope": " ".join(scopes),
"state": state,
}
return f"{self.auth_base_url}?{urlencode(params)}"
async def exchange_code_for_tokens(
self, code: str, scopes: list[str], code_verifier: Optional[str]
) -> OAuth2Credentials:
return await self._request_tokens(
{"code": code, "redirect_uri": self.redirect_uri}
)
async def revoke_tokens(self, credentials: OAuth2Credentials) -> bool:
if not credentials.access_token:
raise ValueError("No access token to revoke")
headers = {
"Accept": "application/vnd.github+json",
"X-GitHub-Api-Version": "2022-11-28",
}
await Requests().delete(
url=self.revoke_url.format(client_id=self.client_id),
auth=(self.client_id, self.client_secret),
headers=headers,
json={"access_token": credentials.access_token.get_secret_value()},
)
return True
async def _refresh_tokens(
self, credentials: OAuth2Credentials
) -> OAuth2Credentials:
if not credentials.refresh_token:
return credentials
return await self._request_tokens(
{
"refresh_token": credentials.refresh_token.get_secret_value(),
"grant_type": "refresh_token",
}
)
async def _request_tokens(
self,
params: dict[str, str],
current_credentials: Optional[OAuth2Credentials] = None,
) -> OAuth2Credentials:
request_body = {
"client_id": self.client_id,
"client_secret": self.client_secret,
**params,
}
headers = {"Accept": "application/json"}
response = await Requests().post(
self.token_url, data=request_body, headers=headers
)
token_data: dict = response.json()
username = await self._request_username(token_data["access_token"])
now = int(time.time())
new_credentials = OAuth2Credentials(
provider=self.PROVIDER_NAME,
title=current_credentials.title if current_credentials else None,
username=username,
access_token=token_data["access_token"],
# Token refresh responses have an empty `scope` property (see docs),
# so we have to get the scope from the existing credentials object.
scopes=(
token_data.get("scope", "").split(",")
or (current_credentials.scopes if current_credentials else [])
),
# Refresh token and expiration intervals are only given if token expiration
# is enabled in the GitHub App's settings.
refresh_token=token_data.get("refresh_token"),
access_token_expires_at=(
now + expires_in
if (expires_in := token_data.get("expires_in", None))
else None
),
refresh_token_expires_at=(
now + expires_in
if (expires_in := token_data.get("refresh_token_expires_in", None))
else None
),
)
if current_credentials:
new_credentials.id = current_credentials.id
return new_credentials
async def _request_username(self, access_token: str) -> str | None:
url = "https://api.github.com/user"
headers = {
"Accept": "application/vnd.github+json",
"Authorization": f"Bearer {access_token}",
"X-GitHub-Api-Version": "2022-11-28",
}
response = await Requests().get(url, headers=headers)
if not response.ok:
return None
# Get the login (username)
resp = response.json()
return resp.get("login")Example: Google integration
Google OAuth2 handler:
integrations/oauth/google.py
backend/integrations/oauth/google.py
class GoogleOAuthHandler(BaseOAuthHandler):
"""
Based on the documentation at https://developers.google.com/identity/protocols/oauth2/web-server
""" # noqa
PROVIDER_NAME = ProviderName.GOOGLE
EMAIL_ENDPOINT = "https://www.googleapis.com/oauth2/v2/userinfo"
DEFAULT_SCOPES = [
"https://www.googleapis.com/auth/userinfo.email",
"https://www.googleapis.com/auth/userinfo.profile",
"openid",
]You can see that google has defined a DEFAULT_SCOPES variable, this is used to set the scopes that are requested no matter what the user asks for.
backend/blocks/google/_auth.py
secrets = Secrets()
GOOGLE_OAUTH_IS_CONFIGURED = bool(
secrets.google_client_id and secrets.google_client_secret
)You can also see that GOOGLE_OAUTH_IS_CONFIGURED is used to disable the blocks that require OAuth if the oauth is not configured. This is in the __init__ method of each block. This is because there is no api key fallback for google blocks so we need to make sure that the oauth is configured before we allow the user to use the blocks.
Webhook-triggered Blocks
Webhook-triggered blocks allow your agent to respond to external events in real-time. These blocks are triggered by incoming webhooks from third-party services rather than being executed manually.
Creating and running a webhook-triggered block involves three main components:
The block itself, which specifies:
Inputs for the user to select a resource and events to subscribe to
A
credentialsinput with the scopes needed to manage webhooksLogic to turn the webhook payload into outputs for the webhook block
The
WebhooksManagerfor the corresponding webhook service provider, which handles:(De)registering webhooks with the provider
Parsing and validating incoming webhook payloads
The credentials system for the corresponding service provider, which may include an
OAuthHandler
There is more going on under the hood, e.g. to store and retrieve webhooks and their links to nodes, but to add a webhook-triggered block you shouldn't need to make changes to those parts of the system.
Creating a Webhook-triggered Block
To create a webhook-triggered block, follow these additional steps on top of the basic block creation process:
Define
webhook_configin your block's__init__method.
Define event filter input in your block's Input schema. This allows the user to select which specific types of events will trigger the block in their agent.
The name of the input field (
eventsin this case) must matchwebhook_config.event_filter_input.The event filter itself must be a Pydantic model with only boolean fields.
Include payload field in your block's Input schema.
Define
credentialsinput in your block's Input schema.Its scopes must be sufficient to manage a user's webhooks through the provider's API
See Blocks with authentication for further details
Process webhook payload and output relevant parts of it in your block's
runmethod.
Adding a Webhooks Manager¶
To add support for a new webhook provider, you'll need to create a WebhooksManager that implements the BaseWebhooksManager interface:
backend/integrations/webhooks/_base.py
PROVIDER_NAME: ClassVar[ProviderName]
@abstractmethod
async def _register_webhook(
self,
credentials: Credentials,
webhook_type: WT,
resource: str,
events: list[str],
ingress_url: str,
secret: str,
) -> tuple[str, dict]:
"""
Registers a new webhook with the provider.
Params:
credentials: The credentials with which to create the webhook
webhook_type: The provider-specific webhook type to create
resource: The resource to receive events for
events: The events to subscribe to
ingress_url: The ingress URL for webhook payloads
secret: Secret used to verify webhook payloads
Returns:
str: Webhook ID assigned by the provider
config: Provider-specific configuration for the webhook
"""
...
@classmethod
@abstractmethod
async def validate_payload(
cls,
webhook: integrations.Webhook,
request: Request,
credentials: Credentials | None,
) -> tuple[dict, str]:
"""
Validates an incoming webhook request and returns its payload and type.
Params:
webhook: Object representing the configured webhook and its properties in our system.
request: Incoming FastAPI `Request`
Returns:
dict: The validated payload
str: The event type associated with the payload
"""
@abstractmethod
async def _deregister_webhook(
self, webhook: integrations.Webhook, credentials: Credentials
) -> None: ...
async def trigger_ping(
self, webhook: integrations.Webhook, credentials: Credentials | None
) -> None:
"""
Triggers a ping to the given webhook.
Raises:
NotImplementedError: if the provider doesn't support pinging
"""And add a reference to your WebhooksManager class in load_webhook_managers:
backend/integrations/webhooks/__init__.py
@cached(ttl_seconds=3600)
def load_webhook_managers() -> dict["ProviderName", type["BaseWebhooksManager"]]:
webhook_managers = {}
from .compass import CompassWebhookManager
from .github import GithubWebhooksManager
from .slant3d import Slant3DWebhooksManager
webhook_managers.update(
{
handler.PROVIDER_NAME: handler
for handler in [
CompassWebhookManager,
GithubWebhooksManager,
Slant3DWebhooksManager,
]
}
)
return webhook_managersExample: GitHub Webhook Integration¶
Key Points to Remember
Unique ID: Give your block a unique ID in the init method.
Input and Output Schemas: Define clear input and output schemas.
Error Handling: Implement error handling in the
runmethod.Output Results: Use
yieldto output results in therunmethod.Testing: Provide test input and output in the init method for automatic testing.
Understanding the Testing Process
The testing of blocks is handled by test_block.py, which does the following:
It calls the block with the provided
test_input. If the block has acredentialsfield,test_credentialsis passed in as well.If a
test_mockis provided, it temporarily replaces the specified methods with the mock functions.It then asserts that the output matches the
test_output.
For the WikipediaSummaryBlock:
The test will call the block with the topic "Artificial Intelligence".
Instead of making a real API call, it will use the mock function, which returns
{"extract": "summary content"}.It will then check if the output key is "summary" and its value is a string.
This approach allows us to test the block's logic comprehensively without relying on external services, while also accommodating non-deterministic outputs.
Security Best Practices for SSRF Prevention
When creating blocks that handle external URL inputs or make network requests, it's crucial to use the platform's built-in SSRF protection mechanisms. The backend.util.request module provides a secure Requests wrapper class that should be used for all HTTP requests.
Using the Secure Requests Wrapper
from backend.util.request import requests
class MyNetworkBlock(Block):
def run(self, input_data: Input, **kwargs) -> BlockOutput:
try:
# The requests wrapper automatically validates URLs and blocks dangerous requests
response = requests.get(input_data.url)
yield "result", response.text
except ValueError as e:
# URL validation failed
raise RuntimeError(f"Invalid URL provided: {e}")
except requests.exceptions.RequestException as e:
# Request failed
raise RuntimeError(f"Request failed: {e}")The Requests wrapper provides these security features:
URL Validation:
Blocks requests to private IP ranges (RFC 1918)
Validates URL format and protocol
Resolves DNS and checks IP addresses
Supports whitelisting trusted origins
Secure Defaults:
Disables redirects by default
Raises exceptions for non-200 status codes
Supports custom headers and validators
Protected IP Ranges: The wrapper denies requests to these networks:
backend/util/request.py
# IPv4 Ranges
ipaddress.ip_network("0.0.0.0/8"), # "This" Network
ipaddress.ip_network("10.0.0.0/8"), # Private-Use
ipaddress.ip_network("127.0.0.0/8"), # Loopback
ipaddress.ip_network("169.254.0.0/16"), # Link Local
ipaddress.ip_network("172.16.0.0/12"), # Private-Use
ipaddress.ip_network("192.168.0.0/16"), # Private-Use
ipaddress.ip_network("224.0.0.0/4"), # Multicast
ipaddress.ip_network("240.0.0.0/4"), # Reserved for Future Use
# IPv6 Ranges
ipaddress.ip_network("::1/128"), # Loopback
ipaddress.ip_network("fc00::/7"), # Unique local addresses (ULA)
ipaddress.ip_network("fe80::/10"), # Link-local
ipaddress.ip_network("ff00::/8"), # MulticastCustom Request Configuration
If you need to customize the request behavior:
from backend.util.request import Requests
# Create a custom requests instance with specific trusted origins
custom_requests = Requests(
trusted_origins=["api.trusted-service.com"],
raise_for_status=True,
extra_headers={"User-Agent": "MyBlock/1.0"}
)Tips for Effective Block Testing
Provide realistic test_input: Ensure your test input covers typical use cases.
Define appropriate test_output:
For deterministic outputs, use specific expected values.
For non-deterministic outputs or when only the type matters, use Python types (e.g.,
str,int,dict).You can mix specific values and types, e.g.,
("key1", str), ("key2", 42).Use test_mock for network calls: This prevents tests from failing due to network issues or API changes.
Consider omitting test_mock for blocks without external dependencies: If your block doesn't make network calls or use external resources, you might not need a mock.
Consider edge cases: Include tests for potential error conditions in your
runmethod.Update tests when changing block behavior: If you modify your block, ensure the tests are updated accordingly.
By following these steps, you can create new blocks that extend the functionality of the AutoGPT Agent Server.
Blocks we want to see
Below is a list of blocks that we would like to see implemented in the AutoGPT Agent Server. If you're interested in contributing, feel free to pick one of these blocks or chose your own.
If you would like to implement one of these blocks, open a pull request and we will start the review process.
Consumer Services/Platforms
Google sheets -
Read/AppendEmail - Read/Send with
Gmail, Outlook, Yahoo, Proton, etcCalendar - Read/Write with Google Calendar, Outlook Calendar, etc
Home Assistant - Call Service, Get Status
Dominos - Order Pizza, Track Order
Uber - Book Ride, Track Ride
Notion - Create/Read Page, Create/Append/Read DB
Google drive - read/write/overwrite file/folder
Social Media
Twitter - Post, Reply, Get Replies, Get Comments, Get Followers, Get Following, Get Tweets, Get Mentions
Instagram - Post, Reply, Get Comments, Get Followers, Get Following, Get Posts, Get Mentions, Get Trending Posts
TikTok - Post, Reply, Get Comments, Get Followers, Get Following, Get Videos, Get Mentions, Get Trending Videos
LinkedIn - Post, Reply, Get Comments, Get Followers, Get Following, Get Posts, Get Mentions, Get Trending Posts
YouTube - Transcribe Videos/Shorts, Post Videos/Shorts, Read/Reply/React to Comments, Update Thumbnails, Update Description, Update Tags, Update Titles, Get Views, Get Likes, Get Dislikes, Get Subscribers, Get Comments, Get Shares, Get Watch Time, Get Revenue, Get Trending Videos, Get Top Videos, Get Top Channels
Reddit - Post, Reply, Get Comments, Get Followers, Get Following, Get Posts, Get Mentions, Get Trending Posts
Treatwell (and related Platforms) - Book, Cancel, Review, Get Recommendations
Substack - Read/Subscribe/Unsubscribe, Post/Reply, Get Recommendations
Discord - Read/Post/Reply, Moderation actions
GoodReads - Read/Post/Reply, Get Recommendations
E-commerce
Airbnb - Book, Cancel, Review, Get Recommendations
Amazon - Order, Track Order, Return, Review, Get Recommendations
eBay - Order, Track Order, Return, Review, Get Recommendations
Upwork - Post Jobs, Hire Freelancer, Review Freelancer, Fire Freelancer
Business Tools
External Agents - Call other agents similar to AutoGPT
Trello - Create/Read/Update/Delete Cards, Lists, Boards
Jira - Create/Read/Update/Delete Issues, Projects, Boards
Linear - Create/Read/Update/Delete Issues, Projects, Boards
Excel - Read/Write/Update/Delete Rows, Columns, Sheets
Slack - Read/Post/Reply to Messages, Create Channels, Invite Users
ERPNext - Create/Read/Update/Delete Invoices, Orders, Customers, Products
Salesforce - Create/Read/Update/Delete Leads, Opportunities, Accounts
HubSpot - Create/Read/Update/Delete Contacts, Deals, Companies
Zendesk - Create/Read/Update/Delete Tickets, Users, Organizations
Odoo - Create/Read/Update/Delete Sales Orders, Invoices, Customers
Shopify - Create/Read/Update/Delete Products, Orders, Customers
WooCommerce - Create/Read/Update/Delete Products, Orders, Customers
Squarespace - Create/Read/Update/Delete Pages, Products, Orders
Agent Templates we want to see
Data/Information
Summarize top news of today, of this week, this month via Apple News or other large media outlets BBC, TechCrunch, hackernews, etc
Create, read, and summarize substack newsletters or any newsletters (blog writer vs blog reader)
Get/read/summarize the most viral Twitter, Instagram, TikTok (general social media accounts) of the day, week, month
Get/Read any LinkedIn posts or profile that mention AI Agents
Read/Summarize discord (might not be able to do this because you need access)
Read / Get most read books in a given month, year, etc from GoodReads or Amazon Books, etc
Get dates for specific shows across all streaming services
Suggest/Recommend/Get most watched shows in a given month, year, etc across all streaming platforms
Data analysis from xlsx data set
Gather via Excel or Google Sheets data > Sample the data randomly (sample block takes top X, bottom X, randomly, etc) > pass that to LLM Block to generate a script for analysis of the full data > Python block to run the script> making a loop back through LLM Fix Block on error > create chart/visualization (potentially in the code block?) > show the image as output (this may require frontend changes to show)
Tiktok video search and download
Marketing
Portfolio site design and enhancements
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