@ -53,14 +53,33 @@ Voila! You’re now ready to summon your Worker.
Here’s a simple way to invoke the Worker and give it a task:
```python
from swarms.models import OpenAIChat
from swarms import Worker
node = Worker(ai_name="Optimus Prime")
llm = OpenAIChat(
#enter your api key
openai_api_key="",
temperature=0.5,
)
node = Worker(
llm=llm,
ai_name="Optimus Prime",
openai_api_key="",
ai_role="Worker in a swarm",
external_tools=None,
human_in_the_loop=False,
temperature=0.5,
)
task = "What were the winning boston marathon times for the past 5 years (ending in 2022)? Generate a table of the year, name, country of origin, and times."
response = node.run(task)
print(response)
```
The result? An agent with elegantly integrated tools and long term memories
task = "What were the winning boston marathon times for the past 5 years (ending in 2022)? Generate a table of the year, name, country of origin, and times."
response = node.run(task)
print(response)
```
### **Example 2**: Usage with custom tools:
```python
from swarms import Worker, MyCustomTool
import os
import interpreter
from swarms.agents.hf_agents import HFAgent
from swarms.agents.omni_modal_agent import OmniModalAgent
from swarms.models import OpenAIChat
from swarms.tools.autogpt import tool
from swarms.workers import Worker
# Initialize API Key
api_key = ""
# Initialize the language model,
# This model can be swapped out with Anthropic, ETC, Huggingface Models like Mistral, ETC
llm = OpenAIChat(
openai_api_key=api_key,
temperature=0.5,
)
# wrap a function with the tool decorator to make it a tool, then add docstrings for tool documentation
@tool
def hf_agent(task: str = None):
"""
An tool that uses an openai model to call and respond to a task by search for a model on huggingface
It first downloads the model then uses it.
Rules: Don't call this model for simple tasks like generating a summary, only call this tool for multi modal tasks like generating images, videos, speech, etc
response = agent.run(task, text="¡Este es un API muy agradable!")
return response
# wrap a function with the tool decorator to make it a tool
@tool
def omni_agent(task: str = None):
"""
An tool that uses an openai Model to utilize and call huggingface models and guide them to perform a task.
Rules: Don't call this model for simple tasks like generating a summary, only call this tool for multi modal tasks like generating images, videos, speech
The following tasks are what this tool should be used for:
Tasks omni agent is good for:
--------------
document-question-answering
image-captioning
image-question-answering
image-segmentation
speech-to-text
summarization
text-classification
text-question-answering
translation
huggingface-tools/text-to-image
huggingface-tools/text-to-video
text-to-speech
huggingface-tools/text-download
huggingface-tools/image-transformation
"""
agent = OmniModalAgent(llm)
response = agent.run(task)
return response
# Code Interpreter
@tool
def compile(task: str):
"""
Open Interpreter lets LLMs run code (Python, Javascript, Shell, and more) locally.
You can chat with Open Interpreter through a ChatGPT-like interface in your terminal
by running $ interpreter after installing.
This provides a natural-language interface to your computer's general-purpose capabilities:
Create and edit photos, videos, PDFs, etc.
Control a Chrome browser to perform research
Plot, clean, and analyze large datasets
...etc.
⚠️ Note: You'll be asked to approve code before it's run.
Rules: Only use when given to generate code or an application of some kind
# Initialize a single Worker node with previously defined tools in addition to it's
# predefined tools
node = Worker(
llm=llm,
ai_name="Optimus Prime",
openai_api_key=api_key,
ai_role="Worker in a swarm",
external_tools=tools,
human_in_the_loop=False,
temperature=0.5,
)
# Specify task
task = "What were the winning boston marathon times for the past 5 years (ending in 2022)? Generate a table of the year, name, country of origin, and times."
result = worker.run("Translate this complex document, and ask for help if needed.")
llm = OpenAIChat(
#enter your api key
openai_api_key="",
temperature=0.5,
)
node = Worker(
llm=llm,
ai_name="Optimus Prime",
openai_api_key="",
ai_role="Worker in a swarm",
external_tools=None,
human_in_the_loop=True,
temperature=0.5,
)
task = "What were the winning boston marathon times for the past 5 years (ending in 2022)? Generate a table of the year, name, country of origin, and times."
Kye
1 year ago