from swarms import Agent, SequentialWorkflow
# import litellm

# litellm._turn_on_debug()


# Initialize market research agent
market_researcher = Agent(
    agent_name="Market-Researcher",
    system_prompt="""You are a market research specialist. Your tasks include:
    1. Analyzing market trends and patterns
    2. Identifying market opportunities and threats
    3. Evaluating competitor strategies
    4. Assessing customer needs and preferences
    5. Providing actionable market insights""",
    model_name="claude-3-sonnet-20240229",
    max_loops=1,
    temperature=0.7,
    streaming_on=True,
)

# Initialize financial analyst agent
financial_analyst = Agent(
    agent_name="Financial-Analyst",
    system_prompt="""You are a financial analysis expert. Your responsibilities include:
    1. Analyzing financial statements
    2. Evaluating investment opportunities
    3. Assessing risk factors
    4. Providing financial forecasts
    5. Recommending financial strategies""",
    model_name="claude-3-sonnet-20240229",
    max_loops=1,
    streaming_on=True,
    temperature=0.7,
)

# Initialize technical analyst agent
technical_analyst = Agent(
    agent_name="Technical-Analyst",
    system_prompt="""You are a technical analysis specialist. Your focus areas include:
    1. Analyzing price patterns and trends
    2. Evaluating technical indicators
    3. Identifying support and resistance levels
    4. Assessing market momentum
    5. Providing trading recommendations""",
    model_name="claude-3-sonnet-20240229",
    max_loops=1,
    temperature=0.7,
    streaming_on=True,
)

# Create list of agents
agents = [market_researcher, financial_analyst, technical_analyst]

# # Initialize the concurrent workflow
# workflow = ConcurrentWorkflow(
#     name="market-analysis-workflow",
#     agents=agents,
#     max_loops=1,
# )

# # Run the workflow
# result = workflow.run(
#     "Analyze Tesla (TSLA) stock from market, financial, and technical perspectives"
# )
router = SequentialWorkflow(
    name="market-analysis-router",
    agents=agents,
    max_loops=1,
    # output_type="all",
)

result = router.run(
    "Analyze Tesla (TSLA) stock from market, financial, and technical perspectives"
)

print(result)