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49 lines
1.3 KiB
49 lines
1.3 KiB
import os
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from swarms import Agent
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from swarm_models import OpenAIChat
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from dotenv import load_dotenv
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# Load environment variables
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load_dotenv()
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# Retrieve the OpenAI API key from the environment variable
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api_key = os.getenv("GROQ_API_KEY")
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# Initialize the model for OpenAI Chat
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model = OpenAIChat(
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openai_api_base="https://api.groq.com/openai/v1",
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openai_api_key=api_key,
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model_name="llama-3.1-70b-versatile",
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temperature=0.1,
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)
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# Initialize the agent with automated prompt engineering enabled
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agent = Agent(
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agent_name="Financial-Analysis-Agent",
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system_prompt=None, # System prompt is dynamically generated
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agent_description=None,
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llm=model,
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max_loops=1,
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autosave=True,
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dashboard=False,
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verbose=False,
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dynamic_temperature_enabled=True,
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saved_state_path="finance_agent.json",
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user_name="Human:",
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return_step_meta=False,
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output_type="string",
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streaming_on=False,
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auto_generate_prompt=True, # Enable automated prompt engineering
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)
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# Run the agent with a task description and specify the device
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agent.run(
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"How can I establish a ROTH IRA to buy stocks and get a tax break? What are the criteria",
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## Will design a system prompt based on the task if description and system prompt are None
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device="cpu",
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)
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# Print the dynamically generated system prompt
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print(agent.system_prompt)
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