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"gradio": minor | ||
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feat:Lazy-import altair |
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"gradio": patch | ||
"gradio_client": patch | ||
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feat:Small fix to client.view_api() in the case of default file values |
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"gradio": patch | ||
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feat:Decrease latency: do not run pre and postprocess in threadpool |
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"gradio": patch | ||
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fix:Fix root url resolution from `x_forwarded_host` headers |
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"gradio": patch | ||
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fix:Adds trigger_mode to gr.on. Use it to set trigger_model="always_last" for live interfaces. |
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"gradio": minor | ||
"website": minor | ||
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feat:Convert Docs Demos to Lite |
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"@gradio/wasm": patch | ||
"gradio": patch | ||
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feat:Remove the aiohttp mock from the Wasm worker as it's removed in https://github.com/gradio-app/gradio/pull/5244 |
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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 "]}, {"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\n", "!wget -q -O files/lion.jpg https://github.com/gradio-app/gradio/raw/main/demo/chatbot_multimodal/files/lion.jpg"]}, {"cell_type": "code", "execution_count": null, "id": "44380577570523278879349135829904343037", "metadata": {}, "outputs": [], "source": ["import gradio as gr\n", "import os\n", "import time\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 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", " response = \"**That's cool!**\"\n", " history[-1][1] = \"\"\n", " for character in response:\n", " history[-1][1] += character\n", " time.sleep(0.05)\n", " yield history\n", "\n", "\n", "with gr.Blocks() as demo:\n", " chatbot = gr.Chatbot(\n", " [],\n", " elem_id=\"chatbot\",\n", " bubble_full_width=False,\n", " avatar_images=(None, (os.path.join(os.path.abspath(''), \"files/avatar.png\"))),\n", " )\n", "\n", " chat_input = gr.MultimodalTextbox(interactive=True, file_types=[\"image\"], 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} | ||
{"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 "]}, {"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\n", "!wget -q -O files/lion.jpg https://github.com/gradio-app/gradio/raw/main/demo/chatbot_multimodal/files/lion.jpg"]}, {"cell_type": "code", "execution_count": null, "id": "44380577570523278879349135829904343037", "metadata": {}, "outputs": [], "source": ["import gradio as gr\n", "import os\n", "import time\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 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", " response = \"**That's cool!**\"\n", " history[-1][1] = \"\"\n", " for character in response:\n", " history[-1][1] += character\n", " time.sleep(0.05)\n", " yield history\n", "\n", "\n", "with gr.Blocks() as demo:\n", " chatbot = gr.Chatbot(\n", " [],\n", " elem_id=\"chatbot\",\n", " bubble_full_width=False,\n", " )\n", "\n", " chat_input = gr.MultimodalTextbox(interactive=True, file_types=[\"image\"], 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: color_picker"]}, {"cell_type": "code", "execution_count": null, "id": "272996653310673477252411125948039410165", "metadata": {}, "outputs": [], "source": ["!pip install -q gradio Pillow"]}, {"cell_type": "code", "execution_count": null, "id": "288918539441861185822528903084949547379", "metadata": {}, "outputs": [], "source": ["# Downloading files from the demo repo\n", "import os\n", "!wget -q https://github.com/gradio-app/gradio/raw/main/demo/color_picker/rabbit.png"]}, {"cell_type": "code", "execution_count": null, "id": "44380577570523278879349135829904343037", "metadata": {}, "outputs": [], "source": ["import gradio as gr\n", "import numpy as np\n", "import os\n", "from PIL import Image, ImageColor\n", "\n", "\n", "def change_color(icon, color):\n", "\n", " \"\"\"\n", " Function that given an icon in .png format changes its color\n", " Args:\n", " icon: Icon whose color needs to be changed.\n", " color: Chosen color with which to edit the input icon.\n", " Returns:\n", " edited_image: Edited icon.\n", " \"\"\"\n", " img = icon.convert(\"LA\")\n", " img = img.convert(\"RGBA\")\n", " image_np = np.array(icon)\n", " _, _, _, alpha = image_np.T\n", " mask = alpha > 0\n", " image_np[..., :-1][mask.T] = ImageColor.getcolor(color, \"RGB\")\n", " edited_image = Image.fromarray(image_np)\n", " return edited_image\n", "\n", "\n", "inputs = [\n", " gr.Image(label=\"icon\", type=\"pil\", image_mode=\"RGBA\"),\n", " gr.ColorPicker(label=\"color\"),\n", "]\n", "outputs = gr.Image(label=\"colored icon\")\n", "\n", "demo = gr.Interface(\n", " fn=change_color,\n", " inputs=inputs,\n", " outputs=outputs,\n", " examples=[\n", " [os.path.join(os.path.abspath(''), \"rabbit.png\"), \"#ff0000\"],\n", " [os.path.join(os.path.abspath(''), \"rabbit.png\"), \"#0000FF\"],\n", " ],\n", ")\n", "\n", "if __name__ == \"__main__\":\n", " demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5} | ||
{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: color_picker"]}, {"cell_type": "code", "execution_count": null, "id": "272996653310673477252411125948039410165", "metadata": {}, "outputs": [], "source": ["!pip install -q gradio Pillow"]}, {"cell_type": "code", "execution_count": null, "id": "288918539441861185822528903084949547379", "metadata": {}, "outputs": [], "source": ["# Downloading files from the demo repo\n", "import os\n", "!wget -q https://github.com/gradio-app/gradio/raw/main/demo/color_picker/rabbit.png"]}, {"cell_type": "code", "execution_count": null, "id": "44380577570523278879349135829904343037", "metadata": {}, "outputs": [], "source": ["import gradio as gr\n", "import numpy as np\n", "import os\n", "from PIL import Image, ImageColor\n", "\n", "\n", "def change_color(icon, color):\n", "\n", " \"\"\"\n", " Function that given an icon in .png format changes its color\n", " Args:\n", " icon: Icon whose color needs to be changed.\n", " color: Chosen color with which to edit the input icon.\n", " Returns:\n", " edited_image: Edited icon.\n", " \"\"\"\n", " img = icon.convert(\"LA\")\n", " img = img.convert(\"RGBA\")\n", " image_np = np.array(icon)\n", " _, _, _, alpha = image_np.T\n", " mask = alpha > 0\n", " image_np[..., :-1][mask.T] = ImageColor.getcolor(color, \"RGB\")\n", " edited_image = Image.fromarray(image_np)\n", " return edited_image\n", "\n", "\n", "inputs = [\n", " gr.Image(label=\"icon\", type=\"pil\", image_mode=\"RGBA\"),\n", " gr.ColorPicker(label=\"color\"),\n", "]\n", "outputs = gr.Image(label=\"colored icon\")\n", "\n", "demo = gr.Interface(\n", " fn=change_color,\n", " inputs=inputs,\n", " outputs=outputs\n", ")\n", "\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: reverse_audio"]}, {"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('audio')\n", "!wget -q -O audio/cantina.wav https://github.com/gradio-app/gradio/raw/main/demo/reverse_audio/audio/cantina.wav\n", "!wget -q -O audio/recording1.wav https://github.com/gradio-app/gradio/raw/main/demo/reverse_audio/audio/recording1.wav"]}, {"cell_type": "code", "execution_count": null, "id": "44380577570523278879349135829904343037", "metadata": {}, "outputs": [], "source": ["import os\n", "\n", "import numpy as np\n", "\n", "import gradio as gr\n", "\n", "\n", "def reverse_audio(audio):\n", " sr, data = audio\n", " return (sr, np.flipud(data))\n", "\n", "\n", "input_audio = gr.Audio(\n", " sources=[\"microphone\"],\n", " waveform_options=gr.WaveformOptions(\n", " waveform_color=\"#01C6FF\",\n", " waveform_progress_color=\"#0066B4\",\n", " skip_length=2,\n", " show_controls=False,\n", " ),\n", ")\n", "demo = gr.Interface(\n", " fn=reverse_audio,\n", " inputs=input_audio,\n", " outputs=\"audio\",\n", " examples=[\n", " \"https://samplelib.com/lib/preview/mp3/sample-3s.mp3\",\n", " os.path.join(os.path.abspath(''), \"audio/recording1.wav\"),\n", " ],\n", " cache_examples=True,\n", ")\n", "\n", "if __name__ == \"__main__\":\n", " demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5} | ||
{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: reverse_audio"]}, {"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('audio')\n", "!wget -q -O audio/cantina.wav https://github.com/gradio-app/gradio/raw/main/demo/reverse_audio/audio/cantina.wav\n", "!wget -q -O audio/recording1.wav https://github.com/gradio-app/gradio/raw/main/demo/reverse_audio/audio/recording1.wav"]}, {"cell_type": "code", "execution_count": null, "id": "44380577570523278879349135829904343037", "metadata": {}, "outputs": [], "source": ["import os\n", "\n", "import numpy as np\n", "\n", "import gradio as gr\n", "\n", "\n", "def reverse_audio(audio):\n", " sr, data = audio\n", " return (sr, np.flipud(data))\n", "\n", "\n", "input_audio = gr.Audio(\n", " sources=[\"microphone\"],\n", " waveform_options=gr.WaveformOptions(\n", " waveform_color=\"#01C6FF\",\n", " waveform_progress_color=\"#0066B4\",\n", " skip_length=2,\n", " show_controls=False,\n", " ),\n", ")\n", "demo = gr.Interface(\n", " fn=reverse_audio,\n", " inputs=input_audio,\n", " outputs=\"audio\"\n", ")\n", "\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: sort_records"]}, {"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", "!wget -q https://github.com/gradio-app/gradio/raw/main/demo/sort_records/polars_sort.csv"]}, {"cell_type": "code", "execution_count": null, "id": "44380577570523278879349135829904343037", "metadata": {}, "outputs": [], "source": ["import gradio as gr\n", "import os\n", "\n", "def sort_records(records):\n", " return records.sort(\"Quantity\")\n", "\n", "demo = gr.Interface(\n", " sort_records,\n", " gr.Dataframe(\n", " headers=[\"Item\", \"Quantity\"],\n", " datatype=[\"str\", \"number\"],\n", " row_count=3,\n", " col_count=(2, \"fixed\"),\n", " type=\"polars\"\n", " ),\n", " \"dataframe\",\n", " description=\"Sort by Quantity\",\n", " examples=[\n", " [os.path.join(os.path.abspath(''), \"polars_sort.csv\")],\n", " ],\n", ")\n", "\n", "if __name__ == \"__main__\":\n", " demo.launch()"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5} | ||
{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: sort_records"]}, {"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", "!wget -q https://github.com/gradio-app/gradio/raw/main/demo/sort_records/polars_sort.csv"]}, {"cell_type": "code", "execution_count": null, "id": "44380577570523278879349135829904343037", "metadata": {}, "outputs": [], "source": ["import gradio as gr\n", "import os\n", "\n", "def sort_records(records):\n", " return records.sort(\"Quantity\")\n", "\n", "demo = gr.Interface(\n", " sort_records,\n", " gr.Dataframe(\n", " headers=[\"Item\", \"Quantity\"],\n", " datatype=[\"str\", \"number\"],\n", " row_count=3,\n", " col_count=(2, \"fixed\"),\n", " type=\"polars\"\n", " ),\n", " \"dataframe\",\n", " description=\"Sort by Quantity\"\n", ")\n", "\n", "if __name__ == \"__main__\":\n", " demo.launch()"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5} |
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