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90 lines
2.4 KiB
90 lines
2.4 KiB
5 months ago
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from swarms import OpenAIChat, AgentRearrange, Agent
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from swarms.prompts.finance_agent_sys_prompt import (
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FINANCIAL_AGENT_SYS_PROMPT,
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)
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from swarms.utils.data_to_text import data_to_text
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model = OpenAIChat(max_tokens=3000)
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# Initialize the agent
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receipt_analyzer_agent = Agent(
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agent_name="Receipt Analyzer",
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system_prompt=FINANCIAL_AGENT_SYS_PROMPT,
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llm=model,
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max_loops=1,
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autosave=True,
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# dynamic_temperature_enabled=True,
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dashboard=False,
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verbose=True,
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streaming_on=True,
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# interactive=True, # Set to False to disable interactive mode
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dynamic_temperature_enabled=True,
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saved_state_path="finance_agent.json",
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# tools=[Add your functions here# ],
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# stopping_token="Stop!",
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# interactive=True,
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# docs_folder="docs", # Enter your folder name
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# pdf_path="docs/finance_agent.pdf",
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# sop="Calculate the profit for a company.",
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# sop_list=["Calculate the profit for a company."],
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user_name="swarms_corp",
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# # docs=
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# # docs_folder="docs",
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retry_attempts=3,
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# tool_schema = dict
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# agent_ops_on=True,
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# long_term_memory=ChromaDB(docs_folder="artifacts"),
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# multi_modal=True
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)
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# 2nd agent
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analyst_agent = Agent(
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agent_name="Analyst_Agent",
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system_prompt=FINANCIAL_AGENT_SYS_PROMPT,
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llm=model,
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max_loops=1,
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autosave=True,
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# dynamic_temperature_enabled=True,
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dashboard=False,
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verbose=True,
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streaming_on=True,
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# interactive=True, # Set to False to disable interactive mode
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dynamic_temperature_enabled=True,
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saved_state_path="finance_agent.json",
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# tools=[Add your functions here# ],
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# stopping_token="Stop!",
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# interactive=True,
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# docs_folder="docs", # Enter your folder name
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# pdf_path="docs/finance_agent.pdf",
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# sop="Calculate the profit for a company.",
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# sop_list=["Calculate the profit for a company."],
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user_name="swarms_corp",
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# # docs=
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# # docs_folder="docs",
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retry_attempts=3,
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# tool_schema = dict
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# agent_ops_on=True,
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# long_term_memory=ChromaDB(docs_folder="artifacts"),
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# multi_modal=True,
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)
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# sWARM
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agents = [receipt_analyzer_agent, analyst_agent]
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# Flow
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flow = f"{receipt_analyzer_agent.agent_name} -> {analyst_agent.agent_name} -> H"
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pdf = data_to_text("receipt.pdf")
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# Swarm
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swarm = AgentRearrange(
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agents=agents,
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flow=flow,
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)
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# Run the swarm
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swarm.run(
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f"Analyze this PDF: {pdf} and return a summary of the expense and if it's necessary"
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)
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