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README.md

@@ -5,7 +5,7 @@ emoji: 🔥
 colorFrom: indigo
 colorTo: indigo
 sdk: gradio
-sdk_version: 5.49.1
+sdk_version: 6.0.0
 app_file: run.py
 pinned: false
 hf_oauth: true

run.ipynb

@@ -1 +1 @@
-{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: chatinterface_deep_link"]}, {"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": ["import time\n", "import gradio as gr\n", "\n", "def slow_echo(message, history):\n", "    for i in range(len(message[\"text\"])):\n", "        time.sleep(0.05)\n", "        yield \"You typed: \" + message[\"text\"][: i + 1]\n", "\n", "chat = gr.ChatInterface(\n", "    slow_echo,\n", "    type=\"messages\",\n", "    flagging_mode=\"manual\",\n", "    flagging_options=[\"Like\", \"Spam\", \"Inappropriate\", \"Other\"],\n", "    save_history=False,\n", "    multimodal=True,\n", ")\n", "\n", "with gr.Blocks() as demo:\n", "\n", "        chat.render()\n", "        gr.DeepLinkButton()\n", "\n", "with demo.route(\"cached_examples\"):\n", "        gr.Interface(lambda x, y: f\"{y}: {x}\",\n", "                     inputs=[gr.Textbox(label=\"name\"),\n", "                             gr.Radio(label=\"Salutation\", choices=[\"Hello\", \"Greetings\"])\n", "                     ],\n", "                     outputs=gr.Textbox(label=\"Output\"),\n", "                     examples=[[\"Freddy\", \"Hello\"]],\n", "                     cache_examples=True,\n", "                     deep_link=True)\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: chatinterface_deep_link"]}, {"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": ["import time\n", "import gradio as gr\n", "\n", "def slow_echo(message, history):\n", "    for i in range(len(message[\"text\"])):\n", "        time.sleep(0.05)\n", "        yield \"You typed: \" + message[\"text\"][: i + 1]\n", "\n", "chat = gr.ChatInterface(\n", "    slow_echo,\n", "    flagging_mode=\"manual\",\n", "    flagging_options=[\"Like\", \"Spam\", \"Inappropriate\", \"Other\"],\n", "    save_history=False,\n", "    multimodal=True,\n", "    api_name=\"chat\"\n", ")\n", "\n", "with gr.Blocks() as demo:\n", "\n", "        chat.render()\n", "        gr.DeepLinkButton()\n", "\n", "with demo.route(\"cached_examples\"):\n", "        gr.Interface(lambda x, y: f\"{y}: {x}\",\n", "                     inputs=[gr.Textbox(label=\"name\"),\n", "                             gr.Radio(label=\"Salutation\", choices=[\"Hello\", \"Greetings\"])\n", "                     ],\n", "                     outputs=gr.Textbox(label=\"Output\"),\n", "                     examples=[[\"Freddy\", \"Hello\"]],\n", "                     cache_examples=True,\n", "                     api_name=\"predict\",\n", "                     deep_link=True)\n", "\n", "\n", "if __name__ == \"__main__\":\n", "    demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}

run.py

@@ -8,11 +8,11 @@ def slow_echo(message, history):
 
 chat = gr.ChatInterface(
     slow_echo,
-    type="messages",
     flagging_mode="manual",
     flagging_options=["Like", "Spam", "Inappropriate", "Other"],
     save_history=False,
     multimodal=True,
+    api_name="chat"
 )
 
 with gr.Blocks() as demo:
@@ -28,9 +28,9 @@ with demo.route("cached_examples"):
                      outputs=gr.Textbox(label="Output"),
                      examples=[["Freddy", "Hello"]],
                      cache_examples=True,
+                     api_name="predict",
                      deep_link=True)
 
 
-
 if __name__ == "__main__":
     demo.launch()