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tweak(docs): Replace all instances of "Node" with "Block". (#7416)
Replace all instances of "Node" with "Block" in the doccumentation.
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Toran Bruce Richards
GitHub
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@ -1,172 +1,172 @@
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# Contributing to AutoGPT Agent Server: Creating Nodes!
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This guide will walk you through the process of creating a new node (also called a block) for the AutoGPT Agent Server. We'll use the GetWikipediaSummary node as an example.
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## Understanding Nodes
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Nodes are reusable components that can be connected to form a graph representing an agent's behavior. Each node has inputs, outputs, and a specific function it performs.
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## Creating a New Node
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To create a new node, follow these steps:
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1. **Create a new Python file** in the `autogpt_server/blocks` directory. Name it descriptively and use snake_case. For example: `get_wikipedia_summary.py`.
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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 node. Every node should contain:
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```python
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from autogpt_server.data.block import Block, BlockSchema, BlockOutput
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```
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Example for the Wikipedia summary node:
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```python
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import requests
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from autogpt_server.data.block import Block, BlockSchema, BlockOutput
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class GetWikipediaSummary(Block):
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# Node 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 node expects to receive (input) and produce (output).
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- The input schema defines the structure of the data the node 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 node will return after processing. Each field in the schema represents a piece of output data.
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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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class Output(BlockSchema):
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summary: str # The summary of the topic from Wikipedia
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```
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4. **Implement the `__init__` method**:
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```python
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def __init__(self):
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super().__init__(
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id="h5e7f8g9-1b2c-3d4e-5f6g-7h8i9j0k1l2m", # Unique ID for the node
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input_schema=GetWikipediaSummary.Input, # Assign input schema
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output_schema=GetWikipediaSummary.Output, # Assign output schema
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# Provide sample input and output for testing the node
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test_input={"topic": "Artificial Intelligence"},
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test_output={"summary": "Artificial intelligence (AI) is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and animals."},
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)
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```
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- `id`: A unique identifier for the node.
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- `input_schema` and `output_schema`: Define the structure of the input and output data.
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- `test_input` and `test_output`: Provide sample input and output data for testing the node.
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5. **Implement the `run` method**, which contains the main logic of the node:
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```python
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def run(self, input_data: Input) -> BlockOutput:
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try:
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# Make the request to Wikipedia API
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response = requests.get(f"https://en.wikipedia.org/api/rest_v1/page/summary/{input_data.topic}")
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response.raise_for_status()
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summary_data = response.json()
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# Output the summary
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yield "summary", summary_data['extract']
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except requests.exceptions.HTTPError as http_err:
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raise ValueError(f"HTTP error occurred: {http_err}")
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except requests.RequestException as e:
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raise ValueError(f"Request to Wikipedia API failed: {e}")
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except KeyError as e:
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raise ValueError(f"Error processing Wikipedia data: {e}")
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```
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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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6. **Register the new node** by adding it to the `__init__.py` file in the `autogpt_server/blocks` directory. This step makes your new node available to the rest of the server.
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- Open the `__init__.py` file in the `autogpt_server/blocks` directory.
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- Add an import statement for your new node at the top of the file.
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- Add the new node to the `AVAILABLE_BLOCKS` and `__all__` lists.
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Example:
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```python
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from autogpt_server.blocks import sample, reddit, text, ai, wikipedia, discord, get_wikipedia_summary # Import your new node
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from autogpt_server.data.block import Block
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AVAILABLE_BLOCKS = {
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block.id: block
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for block in [v() for v in Block.__subclasses__()]
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}
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__all__ = ["ai", "sample", "reddit", "text", "AVAILABLE_BLOCKS", "wikipedia", "discord", "get_wikipedia_summary"]
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```
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- The import statement ensures your new node is included in the module.
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- The `AVAILABLE_BLOCKS` dictionary includes all blocks by their ID.
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- The `__all__` list specifies all public objects that the module exports.
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### Full Code example
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Here is the complete implementation of the `GetWikipediaSummary` nodes:
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```python
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import requests
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from autogpt_server.data.block import Block, BlockSchema, BlockOutput
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class GetWikipediaSummary(Block):
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# Define the input schema with the required field 'topic'
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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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# Define the output schema with the field 'summary'
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class Output(BlockSchema):
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summary: str # The summary of the topic from Wikipedia
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def __init__(self):
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super().__init__(
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id="h5e7f8g9-1b2c-3d4e-5f6g-7h8i9j0k1l2m", # Unique ID for the node
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input_schema=GetWikipediaSummary.Input, # Assign input schema
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output_schema=GetWikipediaSummary.Output, # Assign output schema
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# Provide sample input and output for testing the node
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test_input={"topic": "Artificial Intelligence"},
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test_output={"summary": "Artificial intelligence (AI) is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and animals."},
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)
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def run(self, input_data: Input) -> BlockOutput:
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try:
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# Make the request to Wikipedia API
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response = requests.get(f"https://en.wikipedia.org/api/rest_v1/page/summary/{input_data.topic}")
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response.raise_for_status()
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summary_data = response.json()
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# Output the summary
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yield "summary", summary_data['extract']
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except requests.exceptions.HTTPError as http_err:
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raise ValueError(f"HTTP error occurred: {http_err}")
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except requests.RequestException as e:
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raise ValueError(f"Request to Wikipedia API failed: {e}")
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except KeyError as e:
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raise ValueError(f"Error processing Wikipedia data: {e}")
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```
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## Key Points to Remember
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- **Unique ID**: Give your node a unique ID in the `__init__` method.
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- **Input and Output Schemas**: Define clear input and output schemas.
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- **Error Handling**: Implement error handling in the `run` method.
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- **Output Results**: Use `yield` to output results in the `run` method.
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- **Register the Node**: Add your new node to the `__init__.py` file to make it available to the server.
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- **Testing**: Provide test input and output in the `__init__` method for automatic testing.
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By following these steps, you can create new nodes that extend the functionality of the AutoGPT Agent Server.
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# Contributing to AutoGPT Agent Server: Creating Blocks!
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This guide will walk you through the process of creating a new block for the AutoGPT Agent Server. We'll use the GetWikipediaSummary block as an example.
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## Understanding Blocks
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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 it performs.
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## Creating a New Block
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To create a new block, follow these steps:
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1. **Create a new Python file** in the `autogpt_server/blocks` directory. Name it descriptively and use snake_case. For example: `get_wikipedia_summary.py`.
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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. Every block should contain:
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```python
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from autogpt_server.data.block import Block, BlockSchema, BlockOutput
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```
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Example for the Wikipedia summary block:
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```python
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import requests
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from autogpt_server.data.block import Block, BlockSchema, BlockOutput
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class GetWikipediaSummary(Block):
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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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```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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```
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4. **Implement the `__init__` method**:
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```python
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def __init__(self):
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super().__init__(
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id="h5e7f8g9-1b2c-3d4e-5f6g-7h8i9j0k1l2m", # Unique ID for the block
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input_schema=GetWikipediaSummary.Input, # Assign input schema
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output_schema=GetWikipediaSummary.Output, # Assign output schema
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# Provide sample input and output for testing the block
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test_input={"topic": "Artificial Intelligence"},
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test_output={"summary": "Artificial intelligence (AI) is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and animals."},
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)
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```
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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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- `test_input` and `test_output`: Provide sample input and output data for testing the block.
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5. **Implement the `run` method**, which contains the main logic of the block:
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```python
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def run(self, input_data: Input) -> BlockOutput:
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try:
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# Make the request to Wikipedia API
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response = requests.get(f"https://en.wikipedia.org/api/rest_v1/page/summary/{input_data.topic}")
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response.raise_for_status()
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summary_data = response.json()
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# Output the summary
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yield "summary", summary_data['extract']
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except requests.exceptions.HTTPError as http_err:
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raise ValueError(f"HTTP error occurred: {http_err}")
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except requests.RequestException as e:
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raise ValueError(f"Request to Wikipedia API failed: {e}")
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except KeyError as e:
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raise ValueError(f"Error processing Wikipedia data: {e}")
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```
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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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6. **Register the new block** by adding it to the `__init__.py` file in the `autogpt_server/blocks` directory. This step makes your new block available to the rest of the server.
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- Open the `__init__.py` file in the `autogpt_server/blocks` directory.
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- Add an import statement for your new block at the top of the file.
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- Add the new block to the `AVAILABLE_BLOCKS` and `__all__` lists.
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Example:
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```python
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from autogpt_server.blocks import sample, reddit, text, ai, wikipedia, discord, get_wikipedia_summary # Import your new block
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from autogpt_server.data.block import Block
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AVAILABLE_BLOCKS = {
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block.id: block
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for block in [v() for v in Block.__subclasses__()]
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}
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__all__ = ["ai", "sample", "reddit", "text", "AVAILABLE_BLOCKS", "wikipedia", "discord", "get_wikipedia_summary"]
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```
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- The import statement ensures your new block is included in the module.
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- The `AVAILABLE_BLOCKS` dictionary includes all blocks by their ID.
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- The `__all__` list specifies all public objects that the module exports.
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### Full Code example
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Here is the complete implementation of the `GetWikipediaSummary` blocks:
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```python
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import requests
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from autogpt_server.data.block import Block, BlockSchema, BlockOutput
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class GetWikipediaSummary(Block):
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# Define the input schema with the required field 'topic'
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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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# Define the output schema with the field 'summary'
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class Output(BlockSchema):
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summary: str # The summary of the topic from Wikipedia
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def __init__(self):
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super().__init__(
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id="h5e7f8g9-1b2c-3d4e-5f6g-7h8i9j0k1l2m", # Unique ID for the block
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input_schema=GetWikipediaSummary.Input, # Assign input schema
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output_schema=GetWikipediaSummary.Output, # Assign output schema
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# Provide sample input and output for testing the block
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test_input={"topic": "Artificial Intelligence"},
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test_output={"summary": "Artificial intelligence (AI) is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and animals."},
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)
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def run(self, input_data: Input) -> BlockOutput:
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try:
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# Make the request to Wikipedia API
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response = requests.get(f"https://en.wikipedia.org/api/rest_v1/page/summary/{input_data.topic}")
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response.raise_for_status()
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summary_data = response.json()
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# Output the summary
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yield "summary", summary_data['extract']
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except requests.exceptions.HTTPError as http_err:
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raise ValueError(f"HTTP error occurred: {http_err}")
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except requests.RequestException as e:
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raise ValueError(f"Request to Wikipedia API failed: {e}")
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except KeyError as e:
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raise ValueError(f"Error processing Wikipedia data: {e}")
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```
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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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- **Input and Output Schemas**: Define clear input and output schemas.
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- **Error Handling**: Implement error handling in the `run` method.
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- **Output Results**: Use `yield` to output results in the `run` method.
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- **Register the Block**: Add your new block to the `__init__.py` file to make it available to the server.
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- **Testing**: Provide test input and output in the `__init__` method for automatic testing.
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By following these steps, you can create new blocks that extend the functionality of the AutoGPT Agent Server.
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@ -6,7 +6,7 @@ nav:
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- Home: index.md
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- The AutoGPT Server 🆕:
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- Build your own Node: server/new_nodes.md
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- Build your own Blocks: server/new_blocks.md
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- AutoGPT Agent:
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- Introduction: AutoGPT/index.md
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