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import os | |
from dotenv import load_dotenv | |
from swarm_models import OpenAIChat | |
from swarms import Agent, GroupChat, expertise_based | |
if __name__ == "__main__": | |
load_dotenv() | |
# Get the OpenAI API key from the environment variable | |
api_key = os.getenv("GROQ_API_KEY") | |
# Model | |
model = OpenAIChat( | |
openai_api_base="https://api.groq.com/openai/v1", | |
openai_api_key=api_key, | |
model_name="llama-3.1-70b-versatile", | |
temperature=0.1, | |
) | |
# Example agents | |
agent1 = Agent( | |
agent_name="Crypto-Tax-Optimization-Agent", | |
system_prompt="You are a friendly tax expert specializing in cryptocurrency investments. Provide approachable insights on optimizing tax savings for crypto transactions.", | |
llm=model, | |
max_loops=1, | |
dynamic_temperature_enabled=True, | |
user_name="User", | |
output_type="string", | |
streaming_on=True, | |
) | |
agent2 = Agent( | |
agent_name="Crypto-Investment-Strategies-Agent", | |
system_prompt="You are a conversational financial analyst focused on cryptocurrency investments. Offer debatable advice on investment strategies that minimize tax liabilities.", | |
llm=model, | |
max_loops=1, | |
dynamic_temperature_enabled=True, | |
user_name="User", | |
output_type="string", | |
streaming_on=True, | |
) | |
agents = [agent1, agent2] | |
chat = GroupChat( | |
name="Crypto Tax Optimization Debate", | |
description="Debate on optimizing tax savings for cryptocurrency transactions and investments", | |
agents=agents, | |
speaker_fn=expertise_based, | |
) | |
history = chat.run( | |
"How can one optimize tax savings for cryptocurrency transactions and investments? I bought some Bitcoin and Ethereum last year and want to minimize my tax liabilities this year." | |
) | |
print(history.model_dump_json(indent=2)) | |