{ "cells": [ { "cell_type": "markdown", "id": "8b0e11f2-9ea4-48c2-b8d2-d0a4ba967827", "metadata": {}, "source": [ "# Gradio Day!\n", "\n", "Today we will build User Interfaces using the outrageously simple Gradio framework.\n", "\n", "Prepare for joy!\n", "\n", "Please note: your Gradio screens may appear in 'dark mode' or 'light mode' depending on your computer settings." ] }, { "cell_type": "code", "execution_count": null, "id": "c44c5494-950d-4d2f-8d4f-b87b57c5b330", "metadata": {}, "outputs": [], "source": [ "# imports\n", "\n", "import os\n", "import requests\n", "from bs4 import BeautifulSoup\n", "from typing import List\n", "from dotenv import load_dotenv\n", "from openai import OpenAI\n", "import google.generativeai\n", "import anthropic" ] }, { "cell_type": "code", "execution_count": null, "id": "d1715421-cead-400b-99af-986388a97aff", "metadata": {}, "outputs": [], "source": [ "import gradio as gr # oh yeah!" ] }, { "cell_type": "code", "execution_count": null, "id": "337d5dfc-0181-4e3b-8ab9-e78e0c3f657b", "metadata": {}, "outputs": [], "source": [ "# Load environment variables in a file called .env\n", "# Print the key prefixes to help with any debugging\n", "\n", "load_dotenv()\n", "openai_api_key = os.getenv('OPENAI_API_KEY')\n", "anthropic_api_key = os.getenv('ANTHROPIC_API_KEY')\n", "google_api_key = os.getenv('GOOGLE_API_KEY')\n", "\n", "if openai_api_key:\n", " print(f\"OpenAI API Key exists and begins {openai_api_key[:8]}\")\n", "else:\n", " print(\"OpenAI API Key not set\")\n", " \n", "if anthropic_api_key:\n", " print(f\"Anthropic API Key exists and begins {anthropic_api_key[:7]}\")\n", "else:\n", " print(\"Anthropic API Key not set\")\n", "\n", "if google_api_key:\n", " print(f\"Google API Key exists and begins {google_api_key[:8]}\")\n", "else:\n", " print(\"Google API Key not set\")" ] }, { "cell_type": "code", "execution_count": null, "id": "22586021-1795-4929-8079-63f5bb4edd4c", "metadata": {}, "outputs": [], "source": [ "# Connect to OpenAI, Anthropic and Google; comment out the Claude or Google lines if you're not using them\n", "\n", "openai = OpenAI()\n", "\n", "claude = anthropic.Anthropic()\n", "\n", "google.generativeai.configure()" ] }, { "cell_type": "code", "execution_count": null, "id": "b16e6021-6dc4-4397-985a-6679d6c8ffd5", "metadata": {}, "outputs": [], "source": [ "# A generic system message - no more snarky adversarial AIs!\n", "\n", "system_message = \"You are a helpful assistant\"" ] }, { "cell_type": "code", "execution_count": null, "id": "02ef9b69-ef31-427d-86d0-b8c799e1c1b1", "metadata": {}, "outputs": [], "source": [ "# Let's wrap a call to GPT-4o-mini in a simple function\n", "\n", "def message_gpt(prompt):\n", " messages = [\n", " {\"role\": \"system\", \"content\": system_message},\n", " {\"role\": \"user\", \"content\": prompt}\n", " ]\n", " completion = openai.chat.completions.create(\n", " model='gpt-4o-mini',\n", " messages=messages,\n", " )\n", " return completion.choices[0].message.content" ] }, { "cell_type": "code", "execution_count": null, "id": "aef7d314-2b13-436b-b02d-8de3b72b193f", "metadata": {}, "outputs": [], "source": [ "message_gpt(\"What is today's date?\")" ] }, { "cell_type": "markdown", "id": "f94013d1-4f27-4329-97e8-8c58db93636a", "metadata": {}, "source": [ "## User Interface time!" ] }, { "cell_type": "code", "execution_count": null, "id": "bc664b7a-c01d-4fea-a1de-ae22cdd5141a", "metadata": {}, "outputs": [], "source": [ "# here's a simple function\n", "\n", "def shout(text):\n", " print(f\"Shout has been called with input {text}\")\n", " return text.upper()" ] }, { "cell_type": "code", "execution_count": null, "id": "083ea451-d3a0-4d13-b599-93ed49b975e4", "metadata": {}, "outputs": [], "source": [ "shout(\"hello\")" ] }, { "cell_type": "code", "execution_count": null, "id": "08f1f15a-122e-4502-b112-6ee2817dda32", "metadata": {}, "outputs": [], "source": [ "# The simplicty of gradio. This might appear in \"light mode\" - I'll show you how to make this in dark mode later.\n", "\n", "gr.Interface(fn=shout, inputs=\"textbox\", outputs=\"textbox\").launch()" ] }, { "cell_type": "code", "execution_count": null, "id": "c9a359a4-685c-4c99-891c-bb4d1cb7f426", "metadata": {}, "outputs": [], "source": [ "# Adding share=True means that it can be accessed publically\n", "# A more permanent hosting is available using a platform called Spaces from HuggingFace, which we will touch on next week\n", "\n", "gr.Interface(fn=shout, inputs=\"textbox\", outputs=\"textbox\", flagging_mode=\"never\").launch(share=True)" ] }, { "cell_type": "code", "execution_count": null, "id": "cd87533a-ff3a-4188-8998-5bedd5ba2da3", "metadata": {}, "outputs": [], "source": [ "# Adding inbrowser=True opens up a new browser window automatically\n", "\n", "gr.Interface(fn=shout, inputs=\"textbox\", outputs=\"textbox\", flagging_mode=\"never\").launch(inbrowser=True)" ] }, { "cell_type": "markdown", "id": "b42ec007-0314-48bf-84a4-a65943649215", "metadata": {}, "source": [ "## Forcing dark mode\n", "\n", "Gradio appears in light mode or dark mode depending on the settings of the browser and computer. There is a way to force gradio to appear in dark mode, but Gradio recommends against this as it should be a user preference (particularly for accessibility reasons). But if you wish to force dark mode for your screens, below is how to do it." ] }, { "cell_type": "code", "execution_count": null, "id": "e8129afa-532b-4b15-b93c-aa9cca23a546", "metadata": {}, "outputs": [], "source": [ "# Define this variable and then pass js=force_dark_mode when creating the Interface\n", "\n", "force_dark_mode = \"\"\"\n", "function refresh() {\n", " const url = new URL(window.location);\n", " if (url.searchParams.get('__theme') !== 'dark') {\n", " url.searchParams.set('__theme', 'dark');\n", " window.location.href = url.href;\n", " }\n", "}\n", "\"\"\"\n", "gr.Interface(fn=shout, inputs=\"textbox\", outputs=\"textbox\", flagging_mode=\"never\", js=force_dark_mode).launch()" ] }, { "cell_type": "code", "execution_count": null, "id": "3cc67b26-dd5f-406d-88f6-2306ee2950c0", "metadata": {}, "outputs": [], "source": [ "# Inputs and Outputs\n", "\n", "view = gr.Interface(\n", " fn=shout,\n", " inputs=[gr.Textbox(label=\"Your message:\", lines=6)],\n", " outputs=[gr.Textbox(label=\"Response:\", lines=8)],\n", " flagging_mode=\"never\"\n", ")\n", "view.launch()" ] }, { "cell_type": "code", "execution_count": null, "id": "f235288e-63a2-4341-935b-1441f9be969b", "metadata": {}, "outputs": [], "source": [ "# And now - changing the function from \"shout\" to \"message_gpt\"\n", "\n", "view = gr.Interface(\n", " fn=message_gpt,\n", " inputs=[gr.Textbox(label=\"Your message:\", lines=6)],\n", " outputs=[gr.Textbox(label=\"Response:\", lines=8)],\n", " flagging_mode=\"never\"\n", ")\n", "view.launch()" ] }, { "cell_type": "code", "execution_count": null, "id": "af9a3262-e626-4e4b-80b0-aca152405e63", "metadata": {}, "outputs": [], "source": [ "# Let's use Markdown\n", "# Are you wondering why it makes any difference to set system_message when it's not referred to in the code below it?\n", "# I'm taking advantage of system_message being a global variable, used back in the message_gpt function (go take a look)\n", "# Not a great software engineering practice, but quite sommon during Jupyter Lab R&D!\n", "\n", "system_message = \"You are a helpful assistant that responds in markdown\"\n", "\n", "view = gr.Interface(\n", " fn=message_gpt,\n", " inputs=[gr.Textbox(label=\"Your message:\")],\n", " outputs=[gr.Markdown(label=\"Response:\")],\n", " flagging_mode=\"never\"\n", ")\n", "view.launch()" ] }, { "cell_type": "code", "execution_count": null, "id": "88c04ebf-0671-4fea-95c9-bc1565d4bb4f", "metadata": {}, "outputs": [], "source": [ "# Let's create a call that streams back results\n", "# If you'd like a refresher on Generators (the \"yield\" keyword),\n", "# Please take a look at the Intermediate Python notebook in week1 folder.\n", "\n", "def stream_gpt(prompt):\n", " messages = [\n", " {\"role\": \"system\", \"content\": system_message},\n", " {\"role\": \"user\", \"content\": prompt}\n", " ]\n", " stream = openai.chat.completions.create(\n", " model='gpt-4o-mini',\n", " messages=messages,\n", " stream=True\n", " )\n", " result = \"\"\n", " for chunk in stream:\n", " result += chunk.choices[0].delta.content or \"\"\n", " yield result" ] }, { "cell_type": "code", "execution_count": null, "id": "0bb1f789-ff11-4cba-ac67-11b815e29d09", "metadata": {}, "outputs": [], "source": [ "view = gr.Interface(\n", " fn=stream_gpt,\n", " inputs=[gr.Textbox(label=\"Your message:\")],\n", " outputs=[gr.Markdown(label=\"Response:\")],\n", " flagging_mode=\"never\"\n", ")\n", "view.launch()" ] }, { "cell_type": "code", "execution_count": null, "id": "bbc8e930-ba2a-4194-8f7c-044659150626", "metadata": {}, "outputs": [], "source": [ "def stream_claude(prompt):\n", " result = claude.messages.stream(\n", " model=\"claude-3-haiku-20240307\",\n", " max_tokens=1000,\n", " temperature=0.7,\n", " system=system_message,\n", " messages=[\n", " {\"role\": \"user\", \"content\": prompt},\n", " ],\n", " )\n", " response = \"\"\n", " with result as stream:\n", " for text in stream.text_stream:\n", " response += text or \"\"\n", " yield response" ] }, { "cell_type": "code", "execution_count": null, "id": "a0066ffd-196e-4eaf-ad1e-d492958b62af", "metadata": {}, "outputs": [], "source": [ "view = gr.Interface(\n", " fn=stream_claude,\n", " inputs=[gr.Textbox(label=\"Your message:\")],\n", " outputs=[gr.Markdown(label=\"Response:\")],\n", " flagging_mode=\"never\"\n", ")\n", "view.launch()" ] }, { "cell_type": "markdown", "id": "bc5a70b9-2afe-4a7c-9bed-2429229e021b", "metadata": {}, "source": [ "## Minor improvement\n", "\n", "I've made a small improvement to this code.\n", "\n", "Previously, it had these lines:\n", "\n", "```\n", "for chunk in result:\n", " yield chunk\n", "```\n", "\n", "There's actually a more elegant way to achieve this (which Python people might call more 'Pythonic'):\n", "\n", "`yield from result`\n", "\n", "I cover this in more detail in the Intermediate Python notebook in the week1 folder - take a look if you'd like more." ] }, { "cell_type": "code", "execution_count": null, "id": "0087623a-4e31-470b-b2e6-d8d16fc7bcf5", "metadata": {}, "outputs": [], "source": [ "def stream_model(prompt, model):\n", " if model==\"GPT\":\n", " result = stream_gpt(prompt)\n", " elif model==\"Claude\":\n", " result = stream_claude(prompt)\n", " else:\n", " raise ValueError(\"Unknown model\")\n", " yield from result" ] }, { "cell_type": "code", "execution_count": null, "id": "8d8ce810-997c-4b6a-bc4f-1fc847ac8855", "metadata": {}, "outputs": [], "source": [ "view = gr.Interface(\n", " fn=stream_model,\n", " inputs=[gr.Textbox(label=\"Your message:\"), gr.Dropdown([\"GPT\", \"Claude\"], label=\"Select model\", value=\"GPT\")],\n", " outputs=[gr.Markdown(label=\"Response:\")],\n", " flagging_mode=\"never\"\n", ")\n", "view.launch()" ] }, { "cell_type": "markdown", "id": "d933865b-654c-4b92-aa45-cf389f1eda3d", "metadata": {}, "source": [ "# Building a company brochure generator\n", "\n", "Now you know how - it's simple!" ] }, { "cell_type": "markdown", "id": "92d7c49b-2e0e-45b3-92ce-93ca9f962ef4", "metadata": {}, "source": [ "
\n",
" ![]() | \n",
" \n",
" Before you read the next few cells\n", " \n", " Try to do this yourself - go back to the company brochure in week1, day5 and add a Gradio UI to the end. Then come and look at the solution.\n", " \n", " | \n",
"