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# Groupchat Example
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- Import required modules
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- Configure your agents first
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- Set your api keys for your model provider in the `.env` file such as `OPENAI_API_KEY="sk-"`
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- Conigure `GroupChat` with it's various settings
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## Install
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```bash
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pip install swarms
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```
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---------
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## Main Code
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```python
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from dotenv import load_dotenv
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import os
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from swarms import Agent, GroupChat
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if __name__ == "__main__":
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load_dotenv()
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# Get the OpenAI API key from the environment variable
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api_key = os.getenv("OPENAI_API_KEY")
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# Example agents
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agent1 = Agent(
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agent_name="Expense-Analysis-Agent",
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description="You are an accounting agent specializing in analyzing potential expenses.",
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model_name="gpt-4o-mini",
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max_loops=1,
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autosave=False,
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dashboard=False,
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verbose=True,
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dynamic_temperature_enabled=True,
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user_name="swarms_corp",
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retry_attempts=1,
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context_length=200000,
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output_type="string",
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streaming_on=False,
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max_tokens=15000,
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)
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agent2 = Agent(
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agent_name="Budget-Adviser-Agent",
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description="You are a budget adviser who provides insights on managing and optimizing expenses.",
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model_name="gpt-4o-mini",
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max_loops=1,
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autosave=False,
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dashboard=False,
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verbose=True,
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dynamic_temperature_enabled=True,
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user_name="swarms_corp",
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retry_attempts=1,
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context_length=200000,
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output_type="string",
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streaming_on=False,
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max_tokens=15000,
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)
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agents = [agent1, agent2]
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chat = GroupChat(
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name="Expense Advisory",
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description="Accounting group focused on discussing potential expenses",
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agents=agents,
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max_loops=1,
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output_type="all",
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)
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history = chat.run(
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"What potential expenses should we consider for the upcoming quarter? Please collaborate to outline a comprehensive list."
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)
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```
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@ -0,0 +1,65 @@
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# Swarms x Browser Use
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- Import required modules
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- Configure your agent first by making a new class
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- Set your api keys for your model provider in the `.env` file such as `OPENAI_API_KEY="sk-"`
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- Conigure your `ConcurrentWorkflow`
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## Install
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```bash
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pip install swarms browser-use langchain-openai
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```
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--------
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## Main
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```python
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import asyncio
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from browser_use import Agent
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from dotenv import load_dotenv
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from langchain_openai import ChatOpenAI
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from swarms import ConcurrentWorkflow
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load_dotenv()
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class BrowserAgent:
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def __init__(self, agent_name: str = "BrowserAgent"):
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self.agent_name = agent_name
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async def browser_agent_test(self, task: str):
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agent = Agent(
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task=task,
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llm=ChatOpenAI(model="gpt-4o"),
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)
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result = await agent.run()
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return result
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def run(self, task: str):
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return asyncio.run(self.browser_agent_test(task))
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swarm = ConcurrentWorkflow(
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agents=[BrowserAgent() for _ in range(3)],
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)
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swarm.run(
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"""
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Go to pump.fun.
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2. Make an account: use email: "test@test.com" and password: "test1234"
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3. Make a coin called and give it a cool description and etc. Fill in the form
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4. Sit back and watch the coin grow in value.
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"""
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)
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```
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