aliabd HF staff commited on
Commit
d4d9dfb
1 Parent(s): 811dda3

Upload folder using huggingface_hub

Browse files
Files changed (3) hide show
  1. README.md +1 -1
  2. run.ipynb +1 -1
  3. run.py +3 -1
README.md CHANGED
@@ -5,7 +5,7 @@ emoji: 🔥
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  colorFrom: indigo
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  colorTo: indigo
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  sdk: gradio
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- sdk_version: 4.37.1
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  app_file: run.py
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  pinned: false
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  hf_oauth: true
 
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  colorFrom: indigo
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  colorTo: indigo
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  sdk: gradio
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+ sdk_version: 4.37.2
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  app_file: run.py
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  pinned: false
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  hf_oauth: true
run.ipynb CHANGED
@@ -1 +1 @@
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- {"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: chatbot_multimodal"]}, {"cell_type": "code", "execution_count": null, "id": "272996653310673477252411125948039410165", "metadata": {}, "outputs": [], "source": ["!pip install -q gradio plotly"]}, {"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/avatar.png https://github.com/gradio-app/gradio/raw/main/demo/chatbot_multimodal/files/avatar.png"]}, {"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", "\n", "# Chatbot demo with multimodal input (text, markdown, LaTeX, code blocks, image, audio, & video). Plus shows support for streaming text.\n", "\n", "def random_plot():\n", " df = px.data.iris()\n", " fig = px.scatter(df, x=\"sepal_width\", y=\"sepal_length\", color=\"species\",\n", " size='petal_length', hover_data=['petal_width'])\n", " return fig\n", "\n", "def print_like_dislike(x: gr.LikeData):\n", " print(x.index, x.value, x.liked)\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", "def bot(history):\n", " history[-1][1] = \"Cool!\"\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", " bubble_full_width=False,\n", " scale=1,\n", " )\n", "\n", " chat_input = gr.MultimodalTextbox(interactive=True, placeholder=\"Enter message or upload file...\", show_label=False)\n", "\n", " chat_msg = chat_input.submit(add_message, [chatbot, chat_input], [chatbot, chat_input])\n", " bot_msg = chat_msg.then(bot, chatbot, chatbot, api_name=\"bot_response\")\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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+ {"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: chatbot_multimodal"]}, {"cell_type": "code", "execution_count": null, "id": "272996653310673477252411125948039410165", "metadata": {}, "outputs": [], "source": ["!pip install -q gradio plotly"]}, {"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/avatar.png https://github.com/gradio-app/gradio/raw/main/demo/chatbot_multimodal/files/avatar.png"]}, {"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", "\n", "# Chatbot demo with multimodal input (text, markdown, LaTeX, code blocks, image, audio, & video). Plus shows support for streaming text.\n", "\n", "def random_plot():\n", " df = px.data.iris()\n", " fig = px.scatter(df, x=\"sepal_width\", y=\"sepal_length\", color=\"species\",\n", " size='petal_length', hover_data=['petal_width'])\n", " return fig\n", "\n", "def print_like_dislike(x: gr.LikeData):\n", " print(x.index, x.value, x.liked)\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", "def bot(history):\n", " history[-1][1] = \"Cool!\"\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", " bubble_full_width=False,\n", " scale=1,\n", " )\n", "\n", " chat_input = gr.MultimodalTextbox(interactive=True,\n", " file_count=\"multiple\",\n", " placeholder=\"Enter message or upload file...\", show_label=False)\n", "\n", " chat_msg = chat_input.submit(add_message, [chatbot, chat_input], [chatbot, chat_input])\n", " bot_msg = chat_msg.then(bot, chatbot, chatbot, api_name=\"bot_response\")\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}
run.py CHANGED
@@ -33,7 +33,9 @@ with gr.Blocks(fill_height=True) as demo:
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  scale=1,
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  )
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- chat_input = gr.MultimodalTextbox(interactive=True, placeholder="Enter message or upload file...", show_label=False)
 
 
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  chat_msg = chat_input.submit(add_message, [chatbot, chat_input], [chatbot, chat_input])
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  bot_msg = chat_msg.then(bot, chatbot, chatbot, api_name="bot_response")
 
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  scale=1,
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  )
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+ chat_input = gr.MultimodalTextbox(interactive=True,
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+ file_count="multiple",
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+ placeholder="Enter message or upload file...", show_label=False)
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  chat_msg = chat_input.submit(add_message, [chatbot, chat_input], [chatbot, chat_input])
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  bot_msg = chat_msg.then(bot, chatbot, chatbot, api_name="bot_response")