+{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: chatbot_core_components"]}, {"cell_type": "code", "execution_count": null, "id": "272996653310673477252411125948039410165", "metadata": {}, "outputs": [], "source": ["!pip install -q gradio "]}, {"cell_type": "code", "execution_count": null, "id": "288918539441861185822528903084949547379", "metadata": {}, "outputs": [], "source": ["# Downloading files from the demo repo\n", "import os\n", "os.mkdir('files')\n", "!wget -q -O files/audio.wav https://github.com/gradio-app/gradio/raw/main/demo/chatbot_core_components/files/audio.wav\n", "!wget -q -O files/avatar.png https://github.com/gradio-app/gradio/raw/main/demo/chatbot_core_components/files/avatar.png\n", "!wget -q -O files/sample.txt https://github.com/gradio-app/gradio/raw/main/demo/chatbot_core_components/files/sample.txt\n", "!wget -q -O files/world.mp4 https://github.com/gradio-app/gradio/raw/main/demo/chatbot_core_components/files/world.mp4"]}, {"cell_type": "code", "execution_count": null, "id": "44380577570523278879349135829904343037", "metadata": {}, "outputs": [], "source": ["import gradio as gr\n", "import os\n", "import plotly.express as px\n", "import random\n", "\n", "# Chatbot demo with multimodal input (text, markdown, LaTeX, code blocks, image, audio, & video). Plus shows support for streaming text.\n", "\n", "\n", "def random_plot():\n", " df = px.data.iris()\n", " fig = px.scatter(\n", " df,\n", " x=\"sepal_width\",\n", " y=\"sepal_length\",\n", " color=\"species\",\n", " size=\"petal_length\",\n", " hover_data=[\"petal_width\"],\n", " )\n", " return fig\n", "\n", "\n", "color_map = {\n", " \"harmful\": \"crimson\",\n", " \"neutral\": \"gray\",\n", " \"beneficial\": \"green\",\n", "}\n", "\n", "\n", "def html_src(harm_level):\n", " return f\"\"\"\n", "<div style=\"display: flex; gap: 5px;padding: 2px 4px;margin-top: -40px\">\n", " <div style=\"background-color: {color_map[harm_level]}; padding: 2px; border-radius: 5px;\">\n", " {harm_level}\n", " </div>\n", "</div>\n", "\"\"\"\n", "\n", "\n", "def print_like_dislike(x: gr.LikeData):\n", " print(x.index, x.value, x.liked)\n", "\n", "\n", "def random_bokeh_plot():\n", " from bokeh.models import ColumnDataSource, Whisker\n", " from bokeh.plotting import figure\n", " from bokeh.sampledata.autompg2 import autompg2 as df\n", " from bokeh.transform import factor_cmap, jitter, factor_mark\n", "\n", " classes = list(sorted(df[\"class\"].unique()))\n", "\n", " p = figure(\n", " height=400,\n", " x_range=classes,\n", " background_fill_color=\"#efefef\",\n", " title=\"Car class vs HWY mpg with quintile ranges\",\n", " )\n", " p.xgrid.grid_line_color = None\n", "\n", " g = df.groupby(\"class\")\n", " upper = g.hwy.quantile(0.80)\n", " lower = g.hwy.quantile(0.20)\n", " source = ColumnDataSource(data=dict(base=classes, upper=upper, lower=lower))\n", "\n", " error = Whisker(\n", " base=\"base\",\n", " upper=\"upper\",\n", " lower=\"lower\",\n", " source=source,\n", " level=\"annotation\",\n", " line_width=2,\n", " )\n", " error.upper_head.size = 20\n", " error.lower_head.size = 20\n", " p.add_layout(error)\n", "\n", " p.circle(\n", " jitter(\"class\", 0.3, range=p.x_range),\n", " \"hwy\",\n", " source=df,\n", " alpha=0.5,\n", " size=13,\n", " line_color=\"white\",\n", " color=factor_cmap(\"class\", \"Light6\", classes),\n", " )\n", " return p\n", "\n", "\n", "def random_matplotlib_plot():\n", " import numpy as np\n", " import pandas as pd\n", " import matplotlib.pyplot as plt\n", "\n", " countries = [\"USA\", \"Canada\", \"Mexico\", \"UK\"]\n", " months = [\"January\", \"February\", \"March\", \"April\", \"May\"]\n", " m = months.index(\"January\")\n", " r = 3.2\n", " start_day = 30 * m\n", " final_day = 30 * (m + 1)\n", " x = np.arange(start_day, final_day + 1)\n", " pop_count = {\"USA\": 350, \"Canada\": 40, \"Mexico\": 300, \"UK\": 120}\n", " df = pd.DataFrame({\"day\": x})\n", " for country in countries:\n", " df[country] = x ** (r) * (pop_count[country] + 1)\n", "\n", " fig = plt.figure()\n", " plt.plot(df[\"day\"], df[countries].to_numpy())\n", " plt.title(\"Outbreak in \" + \"January\")\n", " plt.ylabel(\"Cases\")\n", " plt.xlabel(\"Days since Day 0\")\n", " plt.legend(countries)\n", " return fig\n", "\n", "\n", "def add_message(history, message):\n", " for x in message[\"files\"]:\n", " history.append(((x,), None))\n", " if message[\"text\"] is not None:\n", " history.append((message[\"text\"], None))\n", " return history, gr.MultimodalTextbox(value=None, interactive=False)\n", "\n", "\n", "def bot(history, response_type):\n", " if response_type == \"plot\":\n", " history[-1][1] = gr.Plot(random_plot())\n", " elif response_type == \"bokeh_plot\":\n", " history[-1][1] = gr.Plot(random_bokeh_plot())\n", " elif response_type == \"matplotlib_plot\":\n", " history[-1][1] = gr.Plot(random_matplotlib_plot())\n", " elif response_type == \"gallery\":\n", " history[-1][1] = gr.Gallery(\n", " [os.path.join(\"files\", \"avatar.png\"), os.path.join(\"files\", \"avatar.png\")]\n", " )\n", " elif response_type == \"image\":\n", " history[-1][1] = gr.Image(os.path.join(\"files\", \"avatar.png\"))\n", " elif response_type == \"video\":\n", " history[-1][1] = gr.Video(os.path.join(\"files\", \"world.mp4\"))\n", " elif response_type == \"audio\":\n", " history[-1][1] = gr.Audio(os.path.join(\"files\", \"audio.wav\"))\n", " elif response_type == \"audio_file\":\n", " history[-1][1] = (os.path.join(\"files\", \"audio.wav\"), \"description\")\n", " elif response_type == \"image_file\":\n", " history[-1][1] = (os.path.join(\"files\", \"avatar.png\"), \"description\")\n", " elif response_type == \"video_file\":\n", " history[-1][1] = (os.path.join(\"files\", \"world.mp4\"), \"description\")\n", " elif response_type == \"txt_file\":\n", " history[-1][1] = (os.path.join(\"files\", \"sample.txt\"), \"description\")\n", " elif response_type == \"html\":\n", " history[-1][1] = gr.HTML(\n", " html_src(random.choice([\"harmful\", \"neutral\", \"beneficial\"]))\n", " )\n", " else:\n", " history[-1][1] = \"Cool!\"\n", " return history\n", "\n", "\n", "fig = random_plot()\n", "\n", "with gr.Blocks(fill_height=True) as demo:\n", " chatbot = gr.Chatbot(\n", " elem_id=\"chatbot\",\n", " bubble_full_width=False,\n", " scale=1,\n", " )\n", " response_type = gr.Radio(\n", " [\n", " \"audio_file\",\n", " \"image_file\",\n", " \"video_file\",\n", " \"txt_file\",\n", " \"plot\",\n", " \"matplotlib_plot\",\n", " \"bokeh_plot\",\n", " \"image\",\n", " \"text\",\n", " \"gallery\",\n", " \"video\",\n", " \"audio\",\n", " \"html\",\n", " ],\n", " value=\"text\",\n", " label=\"Response Type\",\n", " )\n", "\n", " chat_input = gr.MultimodalTextbox(\n", " interactive=True,\n", " placeholder=\"Enter message or upload file...\",\n", " show_label=False,\n", " )\n", "\n", " chat_msg = chat_input.submit(\n", " add_message, [chatbot, chat_input], [chatbot, chat_input]\n", " )\n", " bot_msg = chat_msg.then(\n", " bot, [chatbot, response_type], chatbot, api_name=\"bot_response\"\n", " )\n", " bot_msg.then(lambda: gr.MultimodalTextbox(interactive=True), None, [chat_input])\n", "\n", " chatbot.like(print_like_dislike, None, None)\n", "\n", "demo.queue()\n", "if __name__ == \"__main__\":\n", " demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}
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