test_prompts = [
    {
        "title": "documentary about good video games that push the boundary of game design"
    },
]
synopsis_chain.apply(test_prompts)
mlflow_callback.flush_tracker(synopsis_chain)
from langchain.agents import initialize_agent, load_tools
from langchain.agents import AgentType
# SCENARIO 3 - Agent with Tools
tools = load_tools(["serpapi", "llm-math"], llm=llm, callbacks=[mlflow_callback])
agent = initialize_agent(
    tools,
    llm,
    agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION,
    callbacks=[mlflow_callback],
    verbose=True,
)
agent.run(
    "Who is Leo DiCaprio's girlfriend? What is her current age raised to the 0.43 power?"
)
mlflow_callback.flush_tracker(agent, finish=True)
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By Harrison Chase
    
      © Copyright 2023, Harrison Chase.
      
  Last updated on Jun 16, 2023.
rtdocs_stable/api.python.langchain.com/en/stable/integrations/mlflow_tracking.html