{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "9f74e899-4d57-4778-a2fc-c9484279080c",
   "metadata": {},
   "outputs": [],
   "source": [
    "import gradio as gr\n",
    "import random\n",
    "import openai\n",
    "import os\n",
    "from dotenv import load_dotenv, find_dotenv\n",
    "\n",
    "_ = load_dotenv(find_dotenv())\n",
    "\n",
    "openai.api_key  = os.getenv('OPENAI_API_KEY')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "8660af3a-7d7c-4f89-a127-6eb6942a4dda",
   "metadata": {},
   "outputs": [],
   "source": [
    "class Conversation:\n",
    "    def __init__(self, prompt, num_of_round):\n",
    "        self.prompt = prompt\n",
    "        self.num_of_round = num_of_round\n",
    "        self.messages = []\n",
    "        self.messages.append({\"role\": \"system\", \"content\": self.prompt})\n",
    "\n",
    "    def ask(self, question):\n",
    "        try:\n",
    "            self.messages.append( {\"role\": \"user\", \"content\": question})\n",
    "            response = openai.ChatCompletion.create(\n",
    "                model=\"gpt-3.5-turbo\",\n",
    "                messages=self.messages,\n",
    "                temperature=0.5,\n",
    "                max_tokens=300,\n",
    "                top_p=1,\n",
    "            )\n",
    "        except Exception as e:\n",
    "            print(e)\n",
    "            return e\n",
    "\n",
    "        message = response[\"choices\"][0][\"message\"][\"content\"]\n",
    "        self.messages.append({\"role\": \"assistant\", \"content\": message})\n",
    "        \n",
    "        if len(self.messages) > self.num_of_round*2 + 1:\n",
    "            del self.messages[1:3]\n",
    "        return message"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "47d1dd3e-b84e-4713-9a20-0b5029d548a5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running on local URL:  http://127.0.0.1:7860\n",
      "\n",
      "To create a public link, set `share=True` in `launch()`.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div><iframe src=\"http://127.0.0.1:7860/\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": []
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "with open('chatbot_03_prompt.md', 'r') as file:\n",
    "    prompt = file.read()\n",
    "\n",
    "prompt = '\"\"\"\\n' + prompt + '\\n\"\"\"'\n",
    "\n",
    "conv = Conversation(prompt, 5)\n",
    "\n",
    "def respond(message, chat_history):\n",
    "    # bot_message = random.choice([\"How are you?\", \"I love you\", \"I'm very hungry\"])\n",
    "    bot_message = conv.ask(message)\n",
    "    chat_history.append((message, bot_message))\n",
    "    return \"\", chat_history\n",
    "\n",
    "    \n",
    "init_conversation = [(None, \"欢迎来到我们的 Chatbot! 请问有什么可以帮助你的吗?\")]\n",
    "\n",
    "with gr.Blocks(css=\"#chatbot{height:900px} .overflow-y-auto{height:1200px}\") as demo:\n",
    "    chatbot = gr.Chatbot(elem_id=\"chatbot\", value=init_conversation, height=\"900px\")\n",
    "    msg = gr.Textbox()\n",
    "    msg.submit(respond, [msg, chatbot], [msg, chatbot])\n",
    "\n",
    "demo.launch()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2414bf0a-ae3c-490c-bbc5-d6d0fac36490",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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