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@ -14,72 +14,72 @@ Follow these steps to create and test a new block:
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2. **Import necessary modules and create a class that inherits from `Block`**. Make sure to include all necessary imports for your block.
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Every block should contain the following:
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Every block should contain the following:
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```python
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from backend.data.block import Block, BlockSchema, BlockOutput
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```
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```python
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from backend.data.block import Block, BlockSchema, BlockOutput
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```
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Example for the Wikipedia summary block:
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Example for the Wikipedia summary block:
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```python
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from backend.data.block import Block, BlockSchema, BlockOutput
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from backend.utils.get_request import GetRequest
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import requests
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```python
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from backend.data.block import Block, BlockSchema, BlockOutput
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from backend.utils.get_request import GetRequest
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import requests
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class WikipediaSummaryBlock(Block, GetRequest):
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# Block implementation will go here
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```
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class WikipediaSummaryBlock(Block, GetRequest):
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# Block implementation will go here
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```
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3. **Define the input and output schemas** using `BlockSchema`. These schemas specify the data structure that the block expects to receive (input) and produce (output).
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- 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.
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- 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.
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Example:
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Example:
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```python
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class Input(BlockSchema):
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topic: str # The topic to get the Wikipedia summary for
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```python
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class Input(BlockSchema):
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topic: str # The topic to get the Wikipedia summary for
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class Output(BlockSchema):
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summary: str # The summary of the topic from Wikipedia
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error: str # Any error message if the request fails
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```
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class Output(BlockSchema):
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summary: str # The summary of the topic from Wikipedia
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error: str # Any error message if the request fails
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```
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4. **Implement the `__init__` method, including test data and mocks:**
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!!! important
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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())`
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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())`
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```python
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def __init__(self):
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super().__init__(
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# Unique ID for the block, used across users for templates
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# If you are an AI leave it as is or change to "generate-proper-uuid"
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id="xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx",
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input_schema=WikipediaSummaryBlock.Input, # Assign input schema
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output_schema=WikipediaSummaryBlock.Output, # Assign output schema
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```python
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def __init__(self):
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super().__init__(
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# Unique ID for the block, used across users for templates
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# If you are an AI leave it as is or change to "generate-proper-uuid"
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id="xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx",
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input_schema=WikipediaSummaryBlock.Input, # Assign input schema
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output_schema=WikipediaSummaryBlock.Output, # Assign output schema
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# Provide sample input, output and test mock for testing the block
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# Provide sample input, output and test mock for testing the block
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test_input={"topic": "Artificial Intelligence"},
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test_output=("summary", "summary content"),
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test_mock={"get_request": lambda url, json: {"extract": "summary content"}},
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)
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```
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test_input={"topic": "Artificial Intelligence"},
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test_output=("summary", "summary content"),
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test_mock={"get_request": lambda url, json: {"extract": "summary content"}},
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)
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```
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- `id`: A unique identifier for the block.
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- `id`: A unique identifier for the block.
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- `input_schema` and `output_schema`: Define the structure of the input and output data.
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- `input_schema` and `output_schema`: Define the structure of the input and output data.
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Let's break down the testing components:
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Let's break down the testing components:
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- `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.
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- `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.
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- `test_output`: This is the expected output when running the block with the `test_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.
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- `test_output`: This is the expected output when running the block with the `test_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.
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- `test_mock`: This is crucial for blocks that make network calls. It provides a mock function that replaces the actual network call during testing.
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- `test_mock`: This is crucial for blocks that make network calls. It provides a mock function that replaces the actual network call during testing.
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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.
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@ -105,7 +105,7 @@ Follow these steps to create and test a new block:
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- **Try block**: Contains the main logic to fetch and process the Wikipedia summary.
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- **API request**: Send a GET request to the Wikipedia API.
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- **Error handling**: Handle various exceptions that might occur during the API request and data processing.
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- **Yield**: Use `yield` to output the results.
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- **Yield**: Use `yield` to 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.
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### Blocks with authentication
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@ -115,6 +115,7 @@ for a service that we already have OAuth2 support for.
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Implementing the block itself is relatively simple. On top of the instructions above,
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you're going to add a `credentials` parameter to the `Input` model and the `run` method:
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```python
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from autogpt_libs.supabase_integration_credentials_store.types import (
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APIKeyCredentials,
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@ -129,10 +130,11 @@ from backend.data.model import CredentialsField
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# API Key auth:
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class BlockWithAPIKeyAuth(Block):
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class Input(BlockSchema):
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credentials = CredentialsField(
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# Note that the type hint below is require or you will get a type error.
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# The first argument is the provider name, the second is the credential type.
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credentials: CredentialsMetaInput[Literal['github'], Literal['api_key']] = CredentialsField(
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provider="github",
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supported_credential_types={"api_key"},
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required_scopes={"repo"},
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description="The GitHub integration can be used with "
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"any API key with sufficient permissions for the blocks it is used on.",
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)
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@ -151,7 +153,9 @@ class BlockWithAPIKeyAuth(Block):
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# OAuth:
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class BlockWithOAuth(Block):
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class Input(BlockSchema):
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credentials = CredentialsField(
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# Note that the type hint below is require or you will get a type error.
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# The first argument is the provider name, the second is the credential type.
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credentials: CredentialsMetaInput[Literal['github'], Literal['oauth2']] = CredentialsField(
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provider="github",
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supported_credential_types={"oauth2"},
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required_scopes={"repo"},
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@ -172,7 +176,9 @@ class BlockWithOAuth(Block):
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# API Key auth + OAuth:
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class BlockWithAPIKeyAndOAuth(Block):
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class Input(BlockSchema):
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credentials = CredentialsField(
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# Note that the type hint below is require or you will get a type error.
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# The first argument is the provider name, the second is the credential type.
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credentials: CredentialsMetaInput[Literal['github'], Literal['api_key', 'oauth2']] = CredentialsField(
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provider="github",
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supported_credential_types={"api_key", "oauth2"},
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required_scopes={"repo"},
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@ -191,10 +197,12 @@ class BlockWithAPIKeyAndOAuth(Block):
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) -> BlockOutput:
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...
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```
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The credentials will be automagically injected by the executor in the back end.
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The `APIKeyCredentials` and `OAuth2Credentials` models are defined [here](https://github.com/Significant-Gravitas/AutoGPT/blob/master/rnd/autogpt_libs/autogpt_libs/supabase_integration_credentials_store/types.py).
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To use them in e.g. an API request, you can either access the token directly:
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```python
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# credentials: APIKeyCredentials
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response = requests.post(
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@ -212,7 +220,9 @@ response = requests.post(
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},
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)
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```
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or use the shortcut `credentials.bearer()`:
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```python
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# credentials: APIKeyCredentials | OAuth2Credentials
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response = requests.post(
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@ -227,25 +237,84 @@ To add support for a new OAuth2-authenticated service, you'll need to add an `OA
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All our existing handlers and the base class can be found [here][OAuth2 handlers].
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Every handler must implement the following parts of the [`BaseOAuthHandler`] interface:
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- `PROVIDER_NAME`
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- `__init__(client_id, client_secret, redirect_uri)`
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- `get_login_url(scopes, state)`
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- `exchange_code_for_tokens(code)`
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- `_refresh_tokens(credentials)`
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```python title="autogpt_platform/backend/backend/integrations/oauth/base.py"
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--8<-- "autogpt_platform/backend/backend/integrations/oauth/base.py:BaseOAuthHandler1"
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--8<-- "autogpt_platform/backend/backend/integrations/oauth/base.py:BaseOAuthHandler2"
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--8<-- "autogpt_platform/backend/backend/integrations/oauth/base.py:BaseOAuthHandler3"
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--8<-- "autogpt_platform/backend/backend/integrations/oauth/base.py:BaseOAuthHandler4"
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--8<-- "autogpt_platform/backend/backend/integrations/oauth/base.py:BaseOAuthHandler5"
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```
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As you can see, this is modeled after the standard OAuth2 flow.
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Aside from implementing the `OAuthHandler` itself, adding a handler into the system requires two more things:
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- Adding the handler class to `HANDLERS_BY_NAME` [here](https://github.com/Significant-Gravitas/AutoGPT/blob/master/autogpt_platform/backend/backend/integrations/oauth/__init__.py)
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- Adding `{provider}_client_id` and `{provider}_client_secret` to the application's `Secrets` [here](https://github.com/Significant-Gravitas/AutoGPT/blob/e3f35d79c7e9fc6ee0cabefcb73e0fad15a0ce2d/autogpt_platform/backend/backend/util/settings.py#L132)
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- Adding the handler class to `HANDLERS_BY_NAME` under [`integrations/oauth/__init__.py`](https://github.com/Significant-Gravitas/AutoGPT/blob/master/autogpt_platform/backend/backend/integrations/oauth/__init__.py)
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```python title="autogpt_platform/backend/backend/integrations/oauth/__init__.py"
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--8<-- "autogpt_platform/backend/backend/integrations/oauth/__init__.py:HANDLERS_BY_NAMEExample"
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```
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- Adding `{provider}_client_id` and `{provider}_client_secret` to the application's `Secrets` under [`util/settings.py`](https://github.com/Significant-Gravitas/AutoGPT/blob/master/autogpt_platform/backend/backend/util/settings.py)
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```python title="autogpt_platform/backend/backend/util/settings.py"
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--8<-- "autogpt_platform/backend/backend/util/settings.py:OAuthServerCredentialsExample"
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```
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[OAuth2 handlers]: https://github.com/Significant-Gravitas/AutoGPT/tree/master/autogpt_platform/backend/backend/integrations/oauth
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[`BaseOAuthHandler`]: https://github.com/Significant-Gravitas/AutoGPT/blob/master/autogpt_platform/backend/backend/integrations/oauth/base.py
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#### Adding to the frontend
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You will need to add the provider (api or oauth) to the `CredentialsInput` component in [`frontend/src/components/integrations/credentials-input.tsx`](https://github.com/Significant-Gravitas/AutoGPT/blob/master/autogpt_platform/frontend/src/components/integrations/credentials-input.tsx).
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```ts title="frontend/src/components/integrations/credentials-input.tsx"
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--8<-- "autogpt_platform/frontend/src/components/integrations/credentials-input.tsx:ProviderIconsEmbed"
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```
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You will also need to add the provider to the `CredentialsProvider` component in [`frontend/src/components/integrations/credentials-provider.tsx`](https://github.com/Significant-Gravitas/AutoGPT/blob/master/autogpt_platform/frontend/src/components/integrations/credentials-provider.tsx).
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```ts title="frontend/src/components/integrations/credentials-provider.tsx"
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--8<-- "autogpt_platform/frontend/src/components/integrations/credentials-provider.tsx:CredentialsProviderNames"
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```
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Finally you will need to add the provider to the `CredentialsType` enum in [`frontend/src/lib/autogpt-server-api/types.ts`](https://github.com/Significant-Gravitas/AutoGPT/blob/master/autogpt_platform/frontend/src/lib/autogpt-server-api/types.ts).
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```ts title="frontend/src/lib/autogpt-server-api/types.ts"
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--8<-- "autogpt_platform/frontend/src/lib/autogpt-server-api/types.ts:BlockIOCredentialsSubSchema"
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```
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#### Example: GitHub integration
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- GitHub blocks with API key + OAuth2 support: [`blocks/github`](https://github.com/Significant-Gravitas/AutoGPT/tree/master/autogpt_platform/backend/backend/blocks/github/)
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```python title="blocks/github/issues.py"
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--8<-- "autogpt_platform/backend/backend/blocks/github/issues.py:GithubCommentBlockExample"
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```
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- GitHub OAuth2 handler: [`integrations/oauth/github.py`](https://github.com/Significant-Gravitas/AutoGPT/blob/master/autogpt_platform/backend/backend/integrations/oauth/github.py)
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```python title="blocks/github/github.py"
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--8<-- "autogpt_platform/backend/backend/integrations/oauth/github.py:GithubOAuthHandlerExample"
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```
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#### Example: Google integration
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- Google OAuth2 handler: [`integrations/oauth/google.py`](https://github.com/Significant-Gravitas/AutoGPT/blob/master/autogpt_platform/backend/backend/integrations/oauth/google.py)
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```python title="integrations/oauth/google.py"
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--8<-- "autogpt_platform/backend/backend/integrations/oauth/google.py:GoogleOAuthHandlerExample"
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```
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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.
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```python title="blocks/google/_auth.py"
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--8<-- "autogpt_platform/backend/backend/blocks/google/_auth.py:GoogleOAuthIsConfigured"
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```
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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.
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## Key Points to Remember
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- **Unique ID**: Give your block a unique ID in the **init** method.
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@ -275,7 +344,8 @@ This approach allows us to test the block's logic comprehensively without relyin
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1. **Provide realistic test_input**: Ensure your test input covers typical use cases.
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2. **Define appropriate test_output**:
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2. **Define appropriate test_output**:
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- For deterministic outputs, use specific expected values.
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- For non-deterministic outputs or when only the type matters, use Python types (e.g., `str`, `int`, `dict`).
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- You can mix specific values and types, e.g., `("key1", str), ("key2", 42)`.
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@ -292,14 +362,14 @@ By following these steps, you can create new blocks that extend the functionalit
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## Blocks we want to see
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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 suggest your own by editing [docs/content/server/new_blocks.md](https://github.com/Significant-Gravitas/AutoGPT/edit/master/docs/content/server/new_blocks.md) and opening a pull request.
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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.
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If you would like to implement one of these blocks, open a pull request and we will start the review process.
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### Consumer Services/Platforms
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- Google sheets - Read/Append [Read in Progress](https://github.com/Significant-Gravitas/AutoGPT/pull/7521)
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- Email - Read/Send with Gmail, Outlook, Yahoo, Proton, etc
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- Google sheets - [~~Read/Append~~](https://github.com/Significant-Gravitas/AutoGPT/pull/8236)
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- Email - Read/Send with [~~Gmail~~](https://github.com/Significant-Gravitas/AutoGPT/pull/8236), Outlook, Yahoo, Proton, etc
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- Calendar - Read/Write with Google Calendar, Outlook Calendar, etc
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- Home Assistant - Call Service, Get Status
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- Dominos - Order Pizza, Track Order
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@ -346,7 +416,6 @@ If you would like to implement one of these blocks, open a pull request and we w
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## Agent Templates we want to see
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### Data/Information
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- Summarize top news of today, of this week, this month via Apple News or other large media outlets BBC, TechCrunch, hackernews, etc
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@ -358,9 +427,9 @@ If you would like to implement one of these blocks, open a pull request and we w
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- Get dates for specific shows across all streaming services
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- Suggest/Recommend/Get most watched shows in a given month, year, etc across all streaming platforms
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- Data analysis from xlsx data set
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- 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)
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- 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)
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- Tiktok video search and download
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### Marketing
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### Marketing
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- Portfolio site design and enhancements
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Nicholas Tindle
GitHub