Observability for CrewAI with Opik

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import os
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import getpass
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if "OPENAI_API_KEY" not in os.environ:
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    os.environ["OPENAI_API_KEY"] = getpass.getpass("Enter your OpenAI API key: ")

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from crewai import Agent, Crew, Task, Process
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class YourCrewName:
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    def agent_one(self) -> Agent:
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        return Agent(
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            role="Data Analyst",
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            goal="Analyze data trends in the market",
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            backstory="An experienced data analyst with a background in economics",
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            verbose=True,
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        )
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    def agent_two(self) -> Agent:
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        return Agent(
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            role="Market Researcher",
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            goal="Gather information on market dynamics",
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            backstory="A diligent researcher with a keen eye for detail",
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            verbose=True,
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        )
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    def task_one(self) -> Task:
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        return Task(
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            name="Collect Data Task",
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            description="Collect recent market data and identify trends.",
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            expected_output="A report summarizing key trends in the market.",
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            agent=self.agent_one(),
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        )
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    def task_two(self) -> Task:
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        return Task(
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            name="Market Research Task",
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            description="Research factors affecting market dynamics.",
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            expected_output="An analysis of factors influencing the market.",
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            agent=self.agent_two(),
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        )
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    def crew(self) -> Crew:
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        return Crew(
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            agents=[self.agent_one(), self.agent_two()],
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            tasks=[self.task_one(), self.task_two()],
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            process=Process.sequential,
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            verbose=True,
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        )

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from opik.integrations.crewai import track_crewai
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track_crewai(project_name="crewai-integration-demo")
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my_crew = YourCrewName().crew()
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result = my_crew.kickoff()
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print(result)

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from crewai.flow.flow import Flow, start, listen
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from opik.integrations.crewai import track_crewai
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track_crewai(project_name="crewai-integration-demo")
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class ExampleFlow(Flow):
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    model = "gpt-4o-mini"
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    @start()
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    def generate_city(self):
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        from litellm import completion
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        response = completion(
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            model=self.model,
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            messages=[{"role": "user", "content": "Return the name of a random city."}],
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        )
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        return response["choices"][0]["message"]["content"]
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    @listen(generate_city)
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    def generate_fun_fact(self, random_city):
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        from litellm import completion
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        response = completion(
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            model=self.model,
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            messages=[{"role": "user", "content": f"Tell me a fun fact about {random_city}"}],
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        )
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        return response["choices"][0]["message"]["content"]
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flow = ExampleFlow()
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result = flow.kickoff()