import whisper
from langchain.llms import OpenAI
from langchain.agents import initialize_agent
from langchain.agents.agent_toolkits import ZapierToolkit
from langchain.utilities.zapier import ZapierNLAWrapper
import os

# Set up API keys
os.environ["OPENAI_API_KEY"] = "sk-proj-j70hae3tYEWKJxprAgQTT3BlbkFJwjjY9VyVZPm2hKrBt82c"
os.environ["ZAPIER_NLA_API_KEY"] = "sk-ak-ACaspkBllFPiU0EHUtqXi6FiEU"

def transcribe_audio(uploaded_file):
    # Load Whisper model
    model = whisper.load_model("base")

    # Save uploaded file to a temporary file
    with open("temp_audio.mp3", "wb") as f:
        f.write(uploaded_file.getbuffer())

    # Transcribe audio file
    result = model.transcribe("temp_audio.mp3")
    transcribed_text = result["text"]
    print(transcribed_text)

    # Return transcribed text
    return transcribed_text

def send_summary_email(transcribed_text):
    # Initialize the large language model
    llm = OpenAI(temperature=0)

    # Initialize Zapier
    zapier = ZapierNLAWrapper()
    toolkit = ZapierToolkit(zapier_nla_wrapper=zapier)

    # Get tools from the toolkit
    tools = toolkit.get_tools()

    if not tools:
        raise ValueError("No tools available for the agent to use.")

    # Initialize the agent with the tools
    agent = initialize_agent(
        tools=tools,
        llm=llm,
        agent="zero-shot-react-description",
        verbose=True
    )

    # Send email using Zapier
    summary = f"Send an Email to mehrdaddjavadi@gmail.com via gmail summarizing the following text provided below: {transcribed_text}"
    agent.run(summary)

    return summary