Repository: gradio-app/gradio
Pull request: Dataframe support in Chatbot
## Description

Add Dataframe component support in chatbot. Test with `chatbot_core_components` demo.

![Screenshot 2024-12-18 at 7 16 52 PM](https://github.com/user-attachments/assets/177b334a-16d7-47a5-9470-f47a9b5e1b92)


Closes: #8657

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Problem statement:
gr.Chatbot cannot use gr.Markdown / gr.DataFrame while showing the results
- [y] I have searched to see if a similar issue already exists.

**Is your feature request related to a problem? Please describe.**  
I want to use gr.DataFrame in output of chatbot.

**Describe the solution you'd like**  
Show the result of gr.DataFrame as a table inside chatbot result.

**Additional context**  
`gradio.__version__: '4.37.1'`
Code: 
```python
import gradio as gr
import time

def html_works():
   history = []
   history.append(["",None])
   text_to_show_in_chatbot = '**testing** normal md <br> <table border="1" style="width:100%"><tr><th>Label</th><th>Value</th></tr><tr><th>x</th><th>y</th></tr>'
   response = [(text_to_show_in_chatbot, None)]

   for letter in response[0][0]:
      history[-1][0] += letter
      time.sleep(0.01)
      yield history
   
   return response

def dataframe_does_not_work():
   history = []
   history.append(["",None])
   df_to_show_in_chatbot = gr.DataFrame( # gr.Markdown neither work
                              headers=["name", "age", "gender"],
                              datatype=["str", "number", "str"],
                              col_count=(3, "fixed"),
                              type='array' 
                              ## returning as an array / list of lists also okay, I can convert it to normal markdown but I also don't get any output as a list
                           )
   print(f'{type(df_to_show_in_chatbot) = }')
   response = [(df_to_show_in_chatbot, None)]
   
   for letter in response[0][0]:
      history[-1][0] += letter
      time.sleep(0.01)
      yield history
   
   return response

with gr.Blocks() as demo:
   button = gr.Button()
   chatbot = gr.Chatbot(render_markdown=True)
   # button.click(html_works, outputs = chatbot)   
   button.click(dataframe_does_not_work, outputs = chatbot)   
   
demo.queue(default_concurrency_limit=None)
demo.launch()
```

Hints from issue discussion:
I believe `gr.Markdown` is supported but `gr.DataFrame` is not supported. @dawoodkhan82 can you confirm? Also we should have a helpful error if an unsupported component is used in the output. 
> I believe `gr.Markdown` is supported but `gr.DataFrame` is not supported. @dawoodkhan82 can you confirm? Also we should have a helpful error if an unsupported component is used in the output.

I get `TypeError: 'Markdown' object is not iterable`
@sglbl @abidlabs as of now `"gallery" | "plot" | "audio" | "video" | "image" | html ` are supported components in the chatbot. there's already progress on adding other components which will be supported soon. `markdown` and `dataframe` are on that list.
> Also we should have a helpful error if an unsupported component is used in the output.

I think we already have this, must not be working as expected.
`gr.Markdown` does not work but all text is treated as markdown and should be parsed appropriately.

Commit message: add changeset

Patch to review:
diff --git a/.changeset/long-months-wave.md b/.changeset/long-months-wave.md
new file mode 100644
index 0000000000..adfcda1fe6
--- /dev/null
+++ b/.changeset/long-months-wave.md
@@ -0,0 +1,6 @@
+---
+"@gradio/chatbot": minor
+"gradio": minor
+---
+
+feat:Dataframe support in Chatbot
diff --git a/demo/chatbot_core_components/run.ipynb b/demo/chatbot_core_components/run.ipynb
index 9d07bae9c2..5abdfb0cbf 100644
--- a/demo/chatbot_core_components/run.ipynb
+++ b/demo/chatbot_core_components/run.ipynb
@@ -1 +1 @@
-{"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 plotly numpy pandas matplotlib "]}, {"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": ["# type: ignore\n", "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", "txt = \"\"\"\n", "Absolutely! The mycorrhizal network, often referred to as the \"Wood Wide Web,\" is a symbiotic association between fungi and the roots of most plant species. Here\u2019s a deeper dive into how it works and its implications:\n", "\n", "### How It Works\n", "\n", "1. **Symbiosis**: Mycorrhizal fungi attach to plant roots, extending far into the soil. The plant provides the fungi with carbohydrates produced via photosynthesis. In return, the fungi help the plant absorb water and essential nutrients like phosphorus and nitrogen from the soil.\n", "\n", "2. **Network Formation**: The fungal hyphae (thread-like structures) connect individual plants, creating an extensive underground network. This network can link many plants together, sometimes spanning entire forests.\n", "\n", "3. **Communication**: Trees and plants use this network to communicate and share resources. For example, a tree under attack by pests can send chemical signals through the mycorrhizal network to warn neighboring trees. These trees can then produce defensive chemicals to prepare for the impending threat.\n", "\n", "### Benefits and Functions\n", "\n", "1. **Resource Sharing**: The network allows for the redistribution of resources among plants. For instance, a large, established tree might share excess nutrients and water with smaller, younger trees, promoting overall forest health.\n", "\n", "2. **Defense Mechanism**: The ability to share information about pests and diseases enhances the resilience of plant communities. This early warning system helps plants activate their defenses before they are directly affected.\n", "\n", "3. **Support for Seedlings**: Young seedlings, which have limited root systems, benefit immensely from the mycorrhizal network. They receive nutrients and water from larger plants, increasing their chances of survival and growth.\n", "\n", "### Ecological Impact\n", "\n", "1. **Biodiversity**: The mycorrhizal network supports biodiversity by fostering a cooperative environment. Plants of different species can coexist and thrive because of the shared resources and information.\n", "\n", "2. **Forest Health**: The network enhances the overall health of forests. By enabling efficient nutrient cycling and supporting plant defenses, it contributes to the stability and longevity of forest ecosystems.\n", "\n", "3. **Climate Change Mitigation**: Healthy forests act as significant carbon sinks, absorbing carbon dioxide from the atmosphere. The mycorrhizal network plays a critical role in maintaining forest health and, consequently, in mitigating climate change.\n", "\n", "### Research and Discoveries\n", "\n", "1. **Suzanne Simard's Work**: Ecologist Suzanne Simard\u2019s research has been pivotal in uncovering the complexities of the mycorrhizal network. She demonstrated that trees of different species can share resources and that \"mother trees\" (large, older trees) play a crucial role in nurturing younger plants.\n", "\n", "2. **Implications for Conservation**: Understanding the mycorrhizal network has significant implications for conservation efforts. It highlights the importance of preserving not just individual trees but entire ecosystems, including the fungal networks that sustain them.\n", "\n", "### Practical Applications\n", "\n", "1. **Agriculture**: Farmers and horticulturists are exploring the use of mycorrhizal fungi to improve crop yields and soil health. By incorporating these fungi into agricultural practices, they can reduce the need for chemical fertilizers and enhance plant resilience.\n", "\n", "2. **Reforestation**: In reforestation projects, introducing mycorrhizal fungi can accelerate the recovery of degraded lands. The fungi help establish healthy plant communities, ensuring the success of newly planted trees.\n", "\n", "The \"Wood Wide Web\" exemplifies the intricate and often hidden connections that sustain life on Earth. It\u2019s a reminder of the profound interdependence within natural systems and the importance of preserving these delicate relationships.\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", "color_map = {\n", "    \"harmful\": \"crimson\",\n", "    \"neutral\": \"gray\",\n", "    \"beneficial\": \"green\",\n", "}\n", "\n", "def html_src(harm_level):\n", "    return f\"\"\"\n", "<div style=\"display: flex; gap: 5px;\">\n", "  <div style=\"background-color: {color_map[harm_level]}; padding: 2px; border-radius: 5px;\">\n", "  {harm_level}\n", "  </div>\n", "</div>\n", "\"\"\"\n", "\n", "def print_like_dislike(x: gr.LikeData):\n", "    print(x.index, x.value, x.liked)\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\n", "\n", "    classes = 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", "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", "def add_message(history, message):\n", "    for x in message[\"files\"]:\n", "        history.append({\"role\": \"user\", \"content\": {\"path\": x}})\n", "    if message[\"text\"] is not None:\n", "        history.append({\"role\": \"user\", \"content\": message[\"text\"]})\n", "    return history, gr.MultimodalTextbox(value=None, interactive=False)\n", "\n", "def bot(history, response_type):\n", "    msg = {\"role\": \"assistant\", \"content\": \"\"}\n", "    if response_type == \"plot\":\n", "        content = gr.Plot(random_plot())\n", "    elif response_type == \"bokeh_plot\":\n", "        content = gr.Plot(random_bokeh_plot())\n", "    elif response_type == \"matplotlib_plot\":\n", "        content =  gr.Plot(random_matplotlib_plot())\n", "    elif response_type == \"gallery\":\n", "        content = gr.Gallery(\n", "            [os.path.join(\"files\", \"avatar.png\"), os.path.join(\"files\", \"avatar.png\")]\n", "        )\n", "    elif response_type == \"image\":\n", "       content = gr.Image(os.path.join(\"files\", \"avatar.png\"))\n", "    elif response_type == \"video\":\n", "       content = gr.Video(os.path.join(\"files\", \"world.mp4\"))\n", "    elif response_type == \"audio\":\n", "        content = gr.Audio(os.path.join(\"files\", \"audio.wav\"))\n", "    elif response_type == \"audio_file\":\n", "        content = {\"path\": os.path.join(\"files\", \"audio.wav\"), \"alt_text\": \"description\"}\n", "    elif response_type == \"image_file\":\n", "        content = {\"path\": os.path.join(\"files\", \"avatar.png\"), \"alt_text\": \"description\"}\n", "    elif response_type == \"video_file\":\n", "        content = {\"path\": os.path.join(\"files\", \"world.mp4\"), \"alt_text\": \"description\"}\n", "    elif response_type == \"txt_file\":\n", "        content = {\"path\": os.path.join(\"files\", \"sample.txt\"), \"alt_text\": \"description\"}\n", "    elif response_type == \"html\":\n", "        content = gr.HTML(\n", "            html_src(random.choice([\"harmful\", \"neutral\", \"beneficial\"]))\n", "        )\n", "    else:\n", "        content = txt\n", "    msg[\"content\"] = content # type: ignore\n", "    history.append(msg)\n", "    return history\n", "\n", "fig = random_plot()\n", "\n", "with gr.Blocks(fill_height=True) as demo:\n", "    chatbot = gr.Chatbot(\n", "        elem_id=\"chatbot\",\n", "        type=\"messages\",\n", "        bubble_full_width=False,\n", "        scale=1,\n", "        show_copy_button=True,\n", "        avatar_images=(\n", "            None,  # os.path.join(\"files\", \"avatar.png\"),\n", "            os.path.join(\"files\", \"avatar.png\"),\n", "        ),\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", "if __name__ == \"__main__\":\n", "    demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}
\ No newline at end of file
+{"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 plotly numpy pandas matplotlib "]}, {"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": ["# type: ignore\n", "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", "txt = \"\"\"\n", "Absolutely! The mycorrhizal network, often referred to as the \"Wood Wide Web,\" is a symbiotic association between fungi and the roots of most plant species. Here\u2019s a deeper dive into how it works and its implications:\n", "\n", "### How It Works\n", "\n", "1. **Symbiosis**: Mycorrhizal fungi attach to plant roots, extending far into the soil. The plant provides the fungi with carbohydrates produced via photosynthesis. In return, the fungi help the plant absorb water and essential nutrients like phosphorus and nitrogen from the soil.\n", "\n", "2. **Network Formation**: The fungal hyphae (thread-like structures) connect individual plants, creating an extensive underground network. This network can link many plants together, sometimes spanning entire forests.\n", "\n", "3. **Communication**: Trees and plants use this network to communicate and share resources. For example, a tree under attack by pests can send chemical signals through the mycorrhizal network to warn neighboring trees. These trees can then produce defensive chemicals to prepare for the impending threat.\n", "\n", "### Benefits and Functions\n", "\n", "1. **Resource Sharing**: The network allows for the redistribution of resources among plants. For instance, a large, established tree might share excess nutrients and water with smaller, younger trees, promoting overall forest health.\n", "\n", "2. **Defense Mechanism**: The ability to share information about pests and diseases enhances the resilience of plant communities. This early warning system helps plants activate their defenses before they are directly affected.\n", "\n", "3. **Support for Seedlings**: Young seedlings, which have limited root systems, benefit immensely from the mycorrhizal network. They receive nutrients and water from larger plants, increasing their chances of survival and growth.\n", "\n", "### Ecological Impact\n", "\n", "1. **Biodiversity**: The mycorrhizal network supports biodiversity by fostering a cooperative environment. Plants of different species can coexist and thrive because of the shared resources and information.\n", "\n", "2. **Forest Health**: The network enhances the overall health of forests. By enabling efficient nutrient cycling and supporting plant defenses, it contributes to the stability and longevity of forest ecosystems.\n", "\n", "3. **Climate Change Mitigation**: Healthy forests act as significant carbon sinks, absorbing carbon dioxide from the atmosphere. The mycorrhizal network plays a critical role in maintaining forest health and, consequently, in mitigating climate change.\n", "\n", "### Research and Discoveries\n", "\n", "1. **Suzanne Simard's Work**: Ecologist Suzanne Simard\u2019s research has been pivotal in uncovering the complexities of the mycorrhizal network. She demonstrated that trees of different species can share resources and that \"mother trees\" (large, older trees) play a crucial role in nurturing younger plants.\n", "\n", "2. **Implications for Conservation**: Understanding the mycorrhizal network has significant implications for conservation efforts. It highlights the importance of preserving not just individual trees but entire ecosystems, including the fungal networks that sustain them.\n", "\n", "### Practical Applications\n", "\n", "1. **Agriculture**: Farmers and horticulturists are exploring the use of mycorrhizal fungi to improve crop yields and soil health. By incorporating these fungi into agricultural practices, they can reduce the need for chemical fertilizers and enhance plant resilience.\n", "\n", "2. **Reforestation**: In reforestation projects, introducing mycorrhizal fungi can accelerate the recovery of degraded lands. The fungi help establish healthy plant communities, ensuring the success of newly planted trees.\n", "\n", "The \"Wood Wide Web\" exemplifies the intricate and often hidden connections that sustain life on Earth. It\u2019s a reminder of the profound interdependence within natural systems and the importance of preserving these delicate relationships.\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", "color_map = {\n", "    \"harmful\": \"crimson\",\n", "    \"neutral\": \"gray\",\n", "    \"beneficial\": \"green\",\n", "}\n", "\n", "def html_src(harm_level):\n", "    return f\"\"\"\n", "<div style=\"display: flex; gap: 5px;\">\n", "  <div style=\"background-color: {color_map[harm_level]}; padding: 2px; border-radius: 5px;\">\n", "  {harm_level}\n", "  </div>\n", "</div>\n", "\"\"\"\n", "\n", "def print_like_dislike(x: gr.LikeData):\n", "    print(x.index, x.value, x.liked)\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\n", "\n", "    classes = 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", "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", "def add_message(history, message):\n", "    for x in message[\"files\"]:\n", "        history.append({\"role\": \"user\", \"content\": {\"path\": x}})\n", "    if message[\"text\"] is not None:\n", "        history.append({\"role\": \"user\", \"content\": message[\"text\"]})\n", "    return history, gr.MultimodalTextbox(value=None, interactive=False)\n", "\n", "def bot(history, response_type):\n", "    msg = {\"role\": \"assistant\", \"content\": \"\"}\n", "    if response_type == \"plot\":\n", "        content = gr.Plot(random_plot())\n", "    elif response_type == \"bokeh_plot\":\n", "        content = gr.Plot(random_bokeh_plot())\n", "    elif response_type == \"matplotlib_plot\":\n", "        content =  gr.Plot(random_matplotlib_plot())\n", "    elif response_type == \"gallery\":\n", "        content = gr.Gallery(\n", "            [os.path.join(\"files\", \"avatar.png\"), os.path.join(\"files\", \"avatar.png\")]\n", "        )\n", "    elif response_type == \"dataframe\":\n", "        content = gr.Dataframe(\n", "            interactive=True,\n", "            headers=[\"One\", \"Two\", \"Three\"],\n", "            col_count=(3, \"fixed\"),\n", "            row_count=(3, \"fixed\"),\n", "            value=[[1, 2, 3], [4, 5, 6], [7, 8, 9]],\n", "            label=\"Dataframe\",\n", "        )\n", "    elif response_type == \"image\":\n", "       content = gr.Image(os.path.join(\"files\", \"avatar.png\"))\n", "    elif response_type == \"video\":\n", "       content = gr.Video(os.path.join(\"files\", \"world.mp4\"))\n", "    elif response_type == \"audio\":\n", "        content = gr.Audio(os.path.join(\"files\", \"audio.wav\"))\n", "    elif response_type == \"audio_file\":\n", "        content = {\"path\": os.path.join(\"files\", \"audio.wav\"), \"alt_text\": \"description\"}\n", "    elif response_type == \"image_file\":\n", "        content = {\"path\": os.path.join(\"files\", \"avatar.png\"), \"alt_text\": \"description\"}\n", "    elif response_type == \"video_file\":\n", "        content = {\"path\": os.path.join(\"files\", \"world.mp4\"), \"alt_text\": \"description\"}\n", "    elif response_type == \"txt_file\":\n", "        content = {\"path\": os.path.join(\"files\", \"sample.txt\"), \"alt_text\": \"description\"}\n", "    elif response_type == \"html\":\n", "        content = gr.HTML(\n", "            html_src(random.choice([\"harmful\", \"neutral\", \"beneficial\"]))\n", "        )\n", "    else:\n", "        content = txt\n", "    msg[\"content\"] = content # type: ignore\n", "    history.append(msg)\n", "    return history\n", "\n", "fig = random_plot()\n", "\n", "with gr.Blocks(fill_height=True) as demo:\n", "    chatbot = gr.Chatbot(\n", "        elem_id=\"chatbot\",\n", "        type=\"messages\",\n", "        bubble_full_width=False,\n", "        scale=1,\n", "        show_copy_button=True,\n", "        avatar_images=(\n", "            None,  # os.path.join(\"files\", \"avatar.png\"),\n", "            os.path.join(\"files\", \"avatar.png\"),\n", "        ),\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", "            \"dataframe\",\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", "if __name__ == \"__main__\":\n", "    demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}
\ No newline at end of file
diff --git a/demo/chatbot_core_components/run.py b/demo/chatbot_core_components/run.py
index 57f1282caa..0ef50965f0 100644
--- a/demo/chatbot_core_components/run.py
+++ b/demo/chatbot_core_components/run.py
@@ -166,6 +166,15 @@ def bot(history, response_type):
         content = gr.Gallery(
             [os.path.join("files", "avatar.png"), os.path.join("files", "avatar.png")]
         )
+    elif response_type == "dataframe":
+        content = gr.Dataframe(
+            interactive=True,
+            headers=["One", "Two", "Three"],
+            col_count=(3, "fixed"),
+            row_count=(3, "fixed"),
+            value=[[1, 2, 3], [4, 5, 6], [7, 8, 9]],
+            label="Dataframe",
+        )
     elif response_type == "image":
        content = gr.Image(os.path.join("files", "avatar.png"))
     elif response_type == "video":
@@ -216,6 +225,7 @@ def bot(history, response_type):
             "image",
             "text",
             "gallery",
+            "dataframe",
             "video",
             "audio",
             "html",
diff --git a/js/chatbot/shared/ChatBot.svelte b/js/chatbot/shared/ChatBot.svelte
index f28343416f..b91ed3d2b6 100644
--- a/js/chatbot/shared/ChatBot.svelte
+++ b/js/chatbot/shared/ChatBot.svelte
@@ -11,7 +11,6 @@
 	import { copy } from "@gradio/utils";
 	import type { CopyData } from "@gradio/utils";
 	import Message from "./Message.svelte";
-	import { DownloadLink } from "@gradio/wasm/svelte";
 
 	import { dequal } from "dequal/lite";
 	import {
diff --git a/js/chatbot/shared/Component.svelte b/js/chatbot/shared/Component.svelte
index 12c1f48d19..aa33132ccb 100644
--- a/js/chatbot/shared/Component.svelte
+++ b/js/chatbot/shared/Component.svelte
@@ -1,5 +1,12 @@
 <script lang="ts">
-	export let type: "gallery" | "plot" | "audio" | "video" | "image" | string;
+	export let type:
+		| "gallery"
+		| "plot"
+		| "audio"
+		| "video"
+		| "image"
+		| "dataframe"
+		| string;
 	export let components;
 	export let value;
 	export let target;
@@ -27,6 +34,27 @@
 		fixed_height={1}
 		on:load
 	/>
+{:else if type === "dataframe"}
+	<svelte:component
+		this={components[type]}
+		{value}
+		show_label={false}
+		{i18n}
+		label=""
+		{_fetch}
+		allow_preview={false}
+		interactive={false}
+		mode="minimal"
+		fixed_height={1}
+		line_breaks={true}
+		wrap={true}
+		root=""
+		gradio={{ dispatch: () => {} }}
+		latex_delimiters={props.latex_delimiters}
+		col_count={props.col_count}
+		row_count={props.row_count}
+		on:load
+	/>
 {:else if type === "plot"}
 	<svelte:component
 		this={components[type]}
diff --git a/js/chatbot/shared/utils.ts b/js/chatbot/shared/utils.ts
index e2fea9d548..b6b1747083 100644
--- a/js/chatbot/shared/utils.ts
+++ b/js/chatbot/shared/utils.ts
@@ -223,13 +223,12 @@ export async function load_components(
 		if (_components[component_name] || component_name === "file") {
 			return;
 		}
-
-		const { name, component } = load_component(component_name, "base");
+		const variant = component_name === "dataframe" ? "component" : "base";
+		const { name, component } = load_component(component_name, variant);
 		names.push(name);
 		components.push(component);
 		component_name;
 	});
-
 	const loaded_components: LoadedComponent[] = await Promise.all(components);
 	loaded_components.forEach((component, i) => {
 		_components[names[i]] = component.default;


Code review comments:
diff_hunk: @@ -27,6 +34,27 @@
 		fixed_height={1}
 		on:load
 	/>
+{:else if type === "dataframe"}
+	<svelte:component
+		this={components[type]}
+		{value}
+		show_label={false}
+		{i18n}
+		label=""
+		{_fetch}
+		allow_preview={false}
+		interactive={false}
+		mode="minimal"
+		fixed_height={1}
+		line_breaks={true}
path: js/chatbot/shared/Component.svelte
text: @user1:
I'm curious why why we force certain parameters like `line_break={true}` instead of doing:
```suggestion
		line_breaks={props.line_breaks}
```