import openai
import gradio as gr
import os
import logging
import json

logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')

openai.api_key = os.environ['key']
initMsg = os.environ['init']
roleAns = os.environ['roleAns']
classAsk = os.environ['classAsk']
classAns = os.environ['classAns']
defaultMsg = os.environ['defaultMsg']

mod = 3;

def localVar(lv):
    lv = lv or {"race":"", "cls":""}
    return lv

def trimMessages(messages):
    # Assuming messages is an array of objects with "role" and "content" properties
    content = {}
    for message in messages:        
        if message["role"] == "assistant":
            if "Current Status:" in message["content"]:
                content = message["content"]
                start_index = message["content"].index("Current Status:") + len("Current Status:")
                end_index = message["content"].index("Wielding:")
                new_content = message["content"][:start_index] + message["content"][end_index:]
                message["content"] = new_content
    if content != {}:
        messages.append({"role": "assistant", "content": content})
    return messages

def getChooseRole(msg):
    start_index = msg.index("As a") + len("As a")
    if start_index >= 0:
        end_index = msg.index(",")
        str = trim(msg[start_index:] + msg[:end_index])
        if str.lower() == "dm":
            return ""
        else:
            return str
    else:
        return ""

def getChooseClass(msg):
    full = getChooseRole(msg)
    if full != "":
        start_index = full.index(" ") + len(" ")
        end_index = msg.index(",")
        return trim(full[start_index:] + full[:end_index])
    else:
        return ""

def chatbot(input, messages):
    messages = messages or [{"role": "system", "content": initMsg}]
    #if len(messages) == 1:
        
        #memory = trimMessages(messages)
        #logging.info("put memory:"+printMessages(memory))
        #chat = openai.ChatCompletion.create(
        #    model="gpt-3.5-turbo", messages=memory,
        #    max_tokens=1048,n=1,temperature=0.5,
        #)
        #logging.info("put memory return:"+chat.choices[0].message.content)

    if input:
        messages.append({"role": "user", "content": input})
        chat = openai.ChatCompletion.create(
            model="gpt-3.5-turbo", messages=messages[-2:],
            max_tokens=2048,n=1,temperature=0.5,
        )
        reply = chat.choices[0].message.content
        logging.info("AI Reply:"+reply)
        ans = ""
        if len(messages) == 2:
            lv.race = getChooseRole(reply)
            lv.cls = ""
            lv = localVar(lv)
            ans = "I choose "+ lv.race +" as my race." + classAsk
            logging.info("ChooseRole:"+ans)
        if len(messages) == 4:
            lv = localVar(lv)
            lv.cls = getChooseClass(reply)
            lv = localVar(lv)
            ans = "My Race is "+ lv.race +"，I choose "+ lv.cls +" as my class." + classAns
            logging.info("ChooseClass:"+ans)
        messages.append({"role": "assistant", "content": ans})
        return reply, printMessages(messages), messages

def printMessages(messages):
    delimiter = '\n'
    msg_string = delimiter.join([f"{obj['role']}:{obj['content']}" for obj in messages])
    logging.info("messages:"+msg_string)
    return msg_string

app = gr.Interface(fn=chatbot, inputs=[gr.Textbox(lines=7, label="You ask and answer questions below"), "state"], 
                   outputs=[gr.Textbox(label="DND Game Reply", placeholder=roleAns), gr.Textbox(label="History"), "state"], title="DND Game",#, gr.Textbox(label="History"), 
                   description="DND Game",theme="compact")
app.launch(share=False)