from swarms import Agent, HuggingfaceLLM
from swarms.prompts.finance_agent_sys_prompt import (
    FINANCIAL_AGENT_SYS_PROMPT,
)

model = HuggingfaceLLM(
    model_id="meta-llama/Meta-Llama-3.1-8B",
    max_tokens=4000,
    temperature=0.1,
)

# Initialize the agent
agent = Agent(
    agent_name="Financial-Analysis-Agent",
    system_prompt=FINANCIAL_AGENT_SYS_PROMPT,
    llm=model,
    max_loops=1,
    autosave=True,
    # dynamic_temperature_enabled=True,
    dashboard=False,
    verbose=True,
    streaming_on=True,
    # interactive=True, # Set to False to disable interactive mode
    dynamic_temperature_enabled=True,
    saved_state_path="finance_agent.json",
    # tools=[Add your functions here# ],
    # stopping_token="Stop!",
    # interactive=True,
    # docs_folder="docs", # Enter your folder name
    # pdf_path="docs/finance_agent.pdf",
    # sop="Calculate the profit for a company.",
    # sop_list=["Calculate the profit for a company."],
    user_name="swarms_corp",
    # # docs=
    # # docs_folder="docs",
    retry_attempts=3,
    # context_length=1000,
    # tool_schema = dict
    context_length=200000,
    # tool_schema=
    # tools
    # agent_ops_on=True,
    # long_term_memory=ChromaDB(docs_folder="artifacts"),
)


agent.run(
    "What are the components of a startups stock incentive equity plan"
)