import gradio as gr
import openai
import os
from openai import OpenAI

client = OpenAI()

# Load your OpenAI API key from the environment variable
openai.api_key = os.getenv("OPENAI_API_KEY")

# Read the static CV file
def load_cv():
    with open("templated_CV.txt", 'r') as file:
        return file.read()

# Extract information from the CV
cv_text = load_cv()

# Initialize a history list to keep track of the conversation
history = []

def chat_with_ai(user_input):  
    global history
    
    # Append user message to history
    history.append({"role": "user", "content": user_input})

    # Limit history to the last 20 messages
    if len(history) > 20:
        history = history[-20:]

    # Prepare the messages for the API call, including the CV text
    messages = [
        {"role": "system", "content": "You are Karthik Raja, and the following details are your academic and research achievements and industry experiences."},
        {"role": "system", "content": cv_text}
    ] + history

    # Make the API call
    completion = client.chat.completions.create(
        model="gpt-3.5-turbo",
        messages=messages
    )
    
    assistant_message = completion.choices[0].message
    # Append assistant message to history
    history.append(assistant_message)

    return assistant_message['content']

def main(user_input):
    response = chat_with_ai(user_input)
    return response

iface = gr.Interface(
    fn=main,
    inputs=gr.Textbox(label="Ask a question, that you would like to ask Karthik"),
    outputs="text",
    title="AI Clone",
    description="Interact with an AI clone for recruiting or for fun :)"
)

iface.launch()