{
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  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "---\n",
    "description: Gradio app.py\n",
    "output-file: app.html\n",
    "title: app\n",
    "\n",
    "---\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<!-- WARNING: THIS FILE WAS AUTOGENERATED! DO NOT EDIT! -->"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "language": "python"
   },
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     "data": {
      "text/plain": [
       "True"
      ]
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     "execution_count": null,
     "metadata": {},
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   ],
   "source": [
    "#: eval: false\n",
    "load_dotenv()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Put the chat backend pieces together"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "language": "python"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "skip\n"
     ]
    }
   ],
   "source": [
    "def create_demo(bot: ConversationBot):\n",
    "    sample_images = []\n",
    "    all_imgs = [f\"{SAMPLE_IMG_DIR}/{img}\" for img in os.listdir(SAMPLE_IMG_DIR)]\n",
    "    for i, img in enumerate(all_imgs):\n",
    "        if i in [\n",
    "            1,\n",
    "            2,\n",
    "            3,\n",
    "        ]:\n",
    "            sample_images.append(img)\n",
    "    with gr.Blocks() as demo:\n",
    "        gr_img = gr.Image(type=\"filepath\")\n",
    "        btn = gr.Button(value=\"Submit image\")\n",
    "        ingredients_msg = gr.Text(label=\"Ingredients from image\")\n",
    "        btn.click(bot.run_img, inputs=[gr_img], outputs=[ingredients_msg])\n",
    "        gr.Examples(\n",
    "            examples=sample_images,\n",
    "            inputs=gr_img,\n",
    "        )\n",
    "\n",
    "        chatbot = gr.Chatbot(\n",
    "            value=[(None, bot.ai_prompt_questions[\"ingredients\"].prompt.template)]\n",
    "        )\n",
    "\n",
    "        msg = gr.Textbox()\n",
    "        # clear = gr.Button(\"Clear\")\n",
    "        gr.Markdown(\n",
    "            \"\"\"\n",
    "        **🔃Refresh the page to start from scratch🔃**  \n",
    "        \n",
    "        Recipe search tool powered by the [Edamam API](https://www.edamam.com/)  \n",
    "        \n",
    "        ![Edamam Logo](https://www.edamam.com/assets/img/small-logo.png)\n",
    "        \"\"\"\n",
    "        )\n",
    "        msg.submit(\n",
    "            fn=bot.respond, inputs=[msg, chatbot], outputs=[msg, chatbot], queue=False\n",
    "        )\n",
    "        # clear.click(lambda: None, None, chatbot, queue=False).then(bot.reset)\n",
    "        return demo"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "language": "python"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Closing server running on port: 7860\n",
      "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": null,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#| eval: false\n",
    "if \"demo\" in globals():\n",
    "    demo.close()\n",
    "\n",
    "demo = create_demo(\n",
    "    ConversationBot(\n",
    "        vegan_ingred_finder=vegan_ingred_finder, img_cap=img_cap, verbose=True\n",
    "    )\n",
    ")\n",
    "demo.launch()"
   ]
  }
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