Basic Advisor

class BasicAdvisorCapability(MatchingCapability):
    worker: AgentWorker = None
    capability_worker: CapabilityWorker = None

    @classmethod
    def register_capability(cls) -> "MatchingCapability":
        with open(
            os.path.join(os.path.dirname(os.path.abspath(__file__)), "config.json")
        ) as file:
            data = json.load(file)
        return cls(
            unique_name=data["unique_name"],
            matching_hotwords=data["matching_hotwords"],
        )

async def give_advice(self):
    # Introduce the advisor and ask for the user's problem
    await self.capability_worker.speak(INTRO_PROMPT)

    # Wait for the user to describe their problem
    user_problem = await self.capability_worker.user_response()

    # Generate a solution using the LLM
    solution_prompt = (
        f"The user has the following problem: {user_problem}. "
        "Provide a helpful solution in just 1 or 2 sentences."
    )
    solution = self.capability_worker.text_to_text_response(solution_prompt)

    # Speak the solution and ask for feedback
    user_feedback = await self.capability_worker.run_io_loop(
        solution + FEEDBACK_PROMPT
    )

    # Thank the user and exit
    await self.capability_worker.speak(FINAL_PROMPT)
    self.capability_worker.resume_normal_flow()

INTRO_PROMPT = "Hi! I'm your daily life advisor. Tell me about a problem you're facing."
FEEDBACK_PROMPT = " Are you satisfied with the advice?"
FINAL_PROMPT = "Thank you for using the daily life advisor. Goodbye!"

User: "Give me advice"

AI: "Hi! I'm your daily life advisor. Tell me about a problem you're facing."

User: "I can't sleep at night"

AI: "Try establishing a consistent bedtime routine and avoid screens an hour 
     before sleep. Are you satisfied with the advice?"

User: "Yes, thanks"

AI: "Thank you for using the daily life advisor. Goodbye!"