import logging
from pathlib import Path
from dotenv import load_dotenv
from livekit.agents import JobContext, WorkerOptions, cli
from livekit.agents.voice import Agent, AgentSession
from livekit.plugins import openai, deepgram, silero

load_dotenv(dotenv_path=Path(__file__).parent.parent / '.env')

logger = logging.getLogger("context-variables")
logger.setLevel(logging.INFO)

class ContextAgent(Agent):
    def __init__(self, context_vars=None) -> None:
        instructions = """
            You are a helpful agent. The user's name is {name}.
            They are {age} years old and live in {city}.
        """
        
        if context_vars:
            instructions = instructions.format(**context_vars)
            
        super().__init__(
            instructions=instructions,
            stt=deepgram.STT(),
            llm=openai.LLM(model="gpt-4o"),
            tts=openai.TTS(),
            vad=silero.VAD.load()
        )
    
    async def on_enter(self):
        self.session.generate_reply()

async def entrypoint(ctx: JobContext):
    await ctx.connect()

    context_variables = {
        "name": "Shayne",
        "age": 35,
        "city": "Toronto"
    }

    session = AgentSession()

    await session.start(
        agent=ContextAgent(context_vars=context_variables),
        room=ctx.room
    )

if __name__ == "__main__":
    cli.run_app(WorkerOptions(entrypoint_fnc=entrypoint))