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Swarms Documentation
====================
Worker Node
-----------
The `WorkerNode` class is a powerful component of the Swarms framework. It is designed to spawn an autonomous agent instance as a worker to accomplish complex tasks. It can search the internet, spawn child multi-modality models to process and generate images, text, audio, and so on.
### WorkerNodeInitializer
The `WorkerNodeInitializer` class is used to initialize a worker node.
#### Initialization
```
WorkerNodeInitializer(openai_api_key: str,
llm: Optional[Union[InMemoryDocstore, ChatOpenAI]] = None,
tools: Optional[List[Tool]] = None,
worker_name: Optional[str] = "Swarm Worker AI Assistant",
worker_role: Optional[str] = "Assistant",
human_in_the_loop: Optional[bool] = False,
search_kwargs: dict = {},
verbose: Optional[bool] = False,
chat_history_file: str = "chat_history.txt")
```
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##### Parameters
- `openai_api_key` (str): The OpenAI API key.
- `llm` (Union[InMemoryDocstore, ChatOpenAI], optional): The language model to use. Default is `ChatOpenAI`.
- `tools` (List[Tool], optional): The tools to use.
- `worker_name` (str, optional): The name of the worker. Default is "Swarm Worker AI Assistant".
- `worker_role` (str, optional): The role of the worker. Default is "Assistant".
- `human_in_the_loop` (bool, optional): Whether to include a human in the loop. Default is False.
- `search_kwargs` (dict, optional): The keyword arguments for the search.
- `verbose` (bool, optional): Whether to print verbose output. Default is False.
- `chat_history_file` (str, optional): The file to store the chat history. Default is "chat_history.txt".
##### Example
```
from swarms.tools.autogpt import DuckDuckGoSearchRun
worker_node_initializer = WorkerNodeInitializer(openai_api_key="your_openai_api_key",
tools=[DuckDuckGoSearchRun()],
worker_name="My Worker",
worker_role="Assistant",
human_in_the_loop=True)
```
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### WorkerNode
The `WorkerNode` class is used to create a worker node.
#### Initialization
```
WorkerNode(openai_api_key: str,
temperature: int,
llm: Optional[Union[InMemoryDocstore, ChatOpenAI]] = None,
tools: Optional[List[Tool]] = None,
worker_name: Optional[str] = "Swarm Worker AI Assistant",
worker_role: Optional[str] = "Assistant",
human_in_the_loop: Optional[bool] = False,
search_kwargs: dict = {},
verbose: Optional[bool] = False,
chat_history_file: str = "chat_history.txt")
```
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##### Parameters
- `openai_api_key` (str): The OpenAI API key.
- `temperature` (int): The temperature for the language model.
- `llm` (Union[InMemoryDocstore, ChatOpenAI], optional): The language model to use. Default is `ChatOpenAI`.
- `tools` (List[Tool], optional): The tools to use.
- `worker_name` (str, optional): The name of the worker. Default is "Swarm Worker AI Assistant".
- `worker_role` (str, optional): The role of the worker. Default is "Assistant".
- `human_in_the_loop` (bool, optional): Whether to include a human in the loop. Default is False.
- `search_kwargs` (dict, optional): The keyword arguments for the search.
- `verbose` (bool, optional): Whether to print verbose output. Default is False.
- `chat_history_file` (str, optional): The file to store the chat history. Default is "chat_history.txt".
##### Example
```
worker_node = WorkerNode(openai_api_key="your_openai_api_key",
temperature=0.8,
tools=[DuckDuckGoSearchRun()],
worker_name="My Worker",
worker_role="As```
tools=[DuckDuckGoSearchRun()],
worker_name="My Worker",
worker_role="Assistant",
human_in_the_loop=True)
# Create a worker node
worker_node = WorkerNode(openai_api_key="your_openai_api_key",
temperature=0.8,
tools=[DuckDuckGoSearchRun()],
worker_name="My Worker",
worker_role="Assistant",
human_in_the_loop=True)
# Add a tool to the worker node
worker_node_initializer.add_tool(DuckDuckGoSearchRun())
# Initialize the language model and tools for the worker node
worker_node.initialize_llm(ChatOpenAI, temperature=0.8)
worker_node.initialize_tools(ChatOpenAI)
# Create the worker node
worker_node.create_worker_node(worker_name="My Worker Node",
worker_role="Assistant",
human_in_the_loop=True,
llm_class=ChatOpenAI,
search_kwargs={})
# Run the worker node
`worker_node.run("Hello, world!")`
In this example, we first initialize a `WorkerNodeInitializer` and a `WorkerNode`. We then add a tool to the `WorkerNodeInitializer` and initialize the language model and tools for the `WorkerNode`. Finally, we create the worker node and run it with a given prompt.
This example shows how you can use the `WorkerNode` and `WorkerNodeInitializer` classes to create a worker node, add tools to it, initialize its language model and tools, and run it with a given prompt. The parameters of these classes can be customized to suit your specific needs.
Thanks for becoming an alpha build user, email [email protected] with all complaintssistant",
human_in_the_loop=True)
```
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### Full Example
Here is a full example of how to use the `WorkerNode` and `WorkerNodeInitializer` classes:
```python
from swarms.tools.autogpt import DuckDuckGoSearchRun
from swarms.worker_node import WorkerNode, WorkerNodeInitializer
# Initialize a worker node
worker_node_initializer = WorkerNodeInitializer(openai_api_key="your_openai_api_key",
tools=[DuckDuckGoSearchRun()],
worker_name="My Worker",
worker_role="Assistant",
human_in_the_loop=True)
# Create a worker node
worker_node = WorkerNode(openai_api_key="your_openai_api_key",
temperature=0.8,
tools=[DuckDuckGoSearchRun()],
worker_name="My Worker",
worker_role="Assistant",
human_in_the_loop=True)
# Add a tool to the worker node
worker_node_initializer.add_tool(DuckDuckGoSearchRun())
# Initialize the language model and tools for the worker node
worker_node.initialize_llm(ChatOpenAI, temperature=0.8)
worker_node.initialize_tools(ChatOpenAI)
# Create the worker node
worker_node.create_worker_node(worker_name="My Worker Node",
worker_role="Assistant",
human_in_the_loop=True,
llm_class=ChatOpenAI,
search_kwargs={})
# Run the worker node
worker_node.run("Hello, world!")
```
In this example, we first initialize a `WorkerNodeInitializer` and a `WorkerNode`. We then add a tool to the `WorkerNodeInitializer` and initialize the language model and tools for the `WorkerNode`. Finally, we create the worker node and run it with a given prompt.
This example shows how you can use the `WorkerNode` and `WorkerNodeInitializer` classes to create a worker node, add tools to it, initialize its language model and tools, and run it with a given prompt. The parameters of these classes can be customized to suit your specific needs. |