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requirements.txt

@@ -1,2 +1,2 @@
-gradio-client @ git+https://github.com/gradio-app/gradio@de997e67c9a7feb9e2eccebf92969366dbd67eba#subdirectory=client/python
-https://gradio-builds.s3.amazonaws.com/de997e67c9a7feb9e2eccebf92969366dbd67eba/gradio-4.39.0-py3-none-any.whl
+gradio-client @ git+https://github.com/gradio-app/gradio@9b42ba8f1006c05d60a62450d3036ce0d6784f86#subdirectory=client/python
+https://gradio-builds.s3.amazonaws.com/9b42ba8f1006c05d60a62450d3036ce0d6784f86/gradio-4.39.0-py3-none-any.whl

run.ipynb

@@ -1 +1 @@
-{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: chatinterface_system_prompt"]}, {"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 gradio as gr\n", "import time\n", "\n", "\n", "def echo(message, history, system_prompt, tokens):\n", "    response = f\"System prompt: {system_prompt}\\n Message: {message}.\"\n", "    for i in range(min(len(response), int(tokens))):\n", "        time.sleep(0.05)\n", "        yield response[: i + 1]\n", "\n", "\n", "demo = gr.ChatInterface(\n", "    echo,\n", "    additional_inputs=[\n", "        gr.Textbox(\"You are helpful AI.\", label=\"System Prompt\"),\n", "        gr.Slider(10, 100),\n", "    ],\n", ")\n", "\n", "if __name__ == \"__main__\":\n", "    demo.queue().launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}
+{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: chatinterface_system_prompt"]}, {"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 gradio as gr\n", "import time\n", "\n", "def echo(message, history, system_prompt, tokens):\n", "    response = f\"System prompt: {system_prompt}\\n Message: {message}.\"\n", "    for i in range(min(len(response), int(tokens))):\n", "        time.sleep(0.05)\n", "        yield response[: i + 1]\n", "\n", "demo = gr.ChatInterface(\n", "    echo,\n", "    additional_inputs=[\n", "        gr.Textbox(\"You are helpful AI.\", label=\"System Prompt\"),\n", "        gr.Slider(10, 100),\n", "    ],\n", ")\n", "\n", "if __name__ == \"__main__\":\n", "    demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}

run.py

@@ -1,14 +1,12 @@
 import gradio as gr
 import time
 
-
 def echo(message, history, system_prompt, tokens):
     response = f"System prompt: {system_prompt}\n Message: {message}."
     for i in range(min(len(response), int(tokens))):
         time.sleep(0.05)
         yield response[: i + 1]
 
-
 demo = gr.ChatInterface(
     echo,
     additional_inputs=[
@@ -18,4 +16,4 @@ demo = gr.ChatInterface(
 )
 
 if __name__ == "__main__":
-    demo.queue().launch()
+    demo.launch()