From the uDemy course on LLM engineering.
https://www.udemy.com/course/llm-engineering-master-ai-and-large-language-models
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580 lines
16 KiB
580 lines
16 KiB
{ |
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"cells": [ |
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{ |
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"cell_type": "markdown", |
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"id": "8b0e11f2-9ea4-48c2-b8d2-d0a4ba967827", |
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"metadata": {}, |
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"source": [ |
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"# Gradio Day!\n", |
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"\n", |
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"Today we will build User Interfaces using the outrageously simple Gradio framework.\n", |
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"\n", |
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"Prepare for joy!" |
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] |
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}, |
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{ |
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"cell_type": "code", |
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"execution_count": null, |
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"id": "c44c5494-950d-4d2f-8d4f-b87b57c5b330", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"# imports\n", |
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"\n", |
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"import os\n", |
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"import requests\n", |
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"from bs4 import BeautifulSoup\n", |
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"from typing import List\n", |
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"from dotenv import load_dotenv\n", |
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"from openai import OpenAI\n", |
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"import google.generativeai\n", |
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"import anthropic" |
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] |
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}, |
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{ |
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"cell_type": "code", |
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"execution_count": null, |
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"id": "d1715421-cead-400b-99af-986388a97aff", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"import gradio as gr # oh yeah!" |
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] |
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}, |
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{ |
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"cell_type": "code", |
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"execution_count": null, |
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"id": "337d5dfc-0181-4e3b-8ab9-e78e0c3f657b", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"# Load environment variables in a file called .env\n", |
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"\n", |
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"load_dotenv()\n", |
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"os.environ['OPENAI_API_KEY'] = os.getenv('OPENAI_API_KEY', 'your-key-if-not-using-env')\n", |
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"os.environ['ANTHROPIC_API_KEY'] = os.getenv('ANTHROPIC_API_KEY', 'your-key-if-not-using-env')\n", |
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"os.environ['GOOGLE_API_KEY'] = os.getenv('GOOGLE_API_KEY', 'your-key-if-not-using-env')" |
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] |
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}, |
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{ |
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"cell_type": "code", |
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"execution_count": null, |
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"id": "22586021-1795-4929-8079-63f5bb4edd4c", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"# Connect to OpenAI, Anthropic and Google\n", |
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"\n", |
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"openai = OpenAI()\n", |
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"\n", |
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"claude = anthropic.Anthropic()\n", |
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"\n", |
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"google.generativeai.configure()" |
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] |
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}, |
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{ |
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"cell_type": "code", |
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"execution_count": null, |
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"id": "b16e6021-6dc4-4397-985a-6679d6c8ffd5", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"# A generic system message - no more snarky adversarial AIs!\n", |
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"\n", |
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"system_message = \"You are a helpful assistant\"" |
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] |
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}, |
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{ |
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"cell_type": "code", |
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"execution_count": null, |
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"id": "02ef9b69-ef31-427d-86d0-b8c799e1c1b1", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"# Let's wrap a call to GPT-4o-mini in a simple function\n", |
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"\n", |
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"def message_gpt(prompt):\n", |
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" messages = [\n", |
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" {\"role\": \"system\", \"content\": system_message},\n", |
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" {\"role\": \"user\", \"content\": prompt}\n", |
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" ]\n", |
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" completion = openai.chat.completions.create(\n", |
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" model='gpt-4o-mini',\n", |
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" messages=messages,\n", |
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" )\n", |
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" return completion.choices[0].message.content" |
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] |
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}, |
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{ |
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"cell_type": "code", |
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"execution_count": null, |
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"id": "aef7d314-2b13-436b-b02d-8de3b72b193f", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"message_gpt(\"What is today's date?\")" |
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] |
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}, |
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{ |
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"cell_type": "markdown", |
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"id": "f94013d1-4f27-4329-97e8-8c58db93636a", |
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"metadata": {}, |
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"source": [ |
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"## User Interface time!" |
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] |
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}, |
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{ |
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"cell_type": "code", |
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"execution_count": null, |
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"id": "bc664b7a-c01d-4fea-a1de-ae22cdd5141a", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"# here's a simple function\n", |
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"\n", |
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"def shout(text):\n", |
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" print(f\"Shout has been called with input {text}\")\n", |
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" return text.upper()" |
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] |
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}, |
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{ |
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"cell_type": "code", |
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"execution_count": null, |
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"id": "083ea451-d3a0-4d13-b599-93ed49b975e4", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"shout(\"hello\")" |
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] |
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}, |
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{ |
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"cell_type": "code", |
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"execution_count": null, |
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"id": "08f1f15a-122e-4502-b112-6ee2817dda32", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"gr.Interface(fn=shout, inputs=\"textbox\", outputs=\"textbox\").launch()" |
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] |
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}, |
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{ |
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"cell_type": "code", |
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"execution_count": null, |
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"id": "c9a359a4-685c-4c99-891c-bb4d1cb7f426", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"gr.Interface(fn=shout, inputs=\"textbox\", outputs=\"textbox\", flagging_mode=\"never\").launch(share=True)" |
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] |
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}, |
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{ |
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"cell_type": "code", |
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"execution_count": null, |
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"id": "3cc67b26-dd5f-406d-88f6-2306ee2950c0", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"view = gr.Interface(\n", |
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" fn=shout,\n", |
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" inputs=[gr.Textbox(label=\"Your message:\", lines=6)],\n", |
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" outputs=[gr.Textbox(label=\"Response:\", lines=8)],\n", |
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" flagging_mode=\"never\"\n", |
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")\n", |
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"view.launch()" |
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] |
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}, |
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{ |
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"cell_type": "code", |
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"execution_count": null, |
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"id": "f235288e-63a2-4341-935b-1441f9be969b", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"view = gr.Interface(\n", |
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" fn=message_gpt,\n", |
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" inputs=[gr.Textbox(label=\"Your message:\", lines=6)],\n", |
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" outputs=[gr.Textbox(label=\"Response:\", lines=8)],\n", |
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" flagging_mode=\"never\"\n", |
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")\n", |
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"view.launch()" |
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] |
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}, |
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{ |
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"cell_type": "code", |
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"execution_count": null, |
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"id": "af9a3262-e626-4e4b-80b0-aca152405e63", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"system_message = \"You are a helpful assistant that responds in markdown\"\n", |
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"\n", |
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"view = gr.Interface(\n", |
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" fn=message_gpt,\n", |
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" inputs=[gr.Textbox(label=\"Your message:\")],\n", |
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" outputs=[gr.Markdown(label=\"Response:\")],\n", |
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" flagging_mode=\"never\"\n", |
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")\n", |
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"view.launch()" |
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] |
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}, |
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{ |
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"cell_type": "code", |
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"execution_count": null, |
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"id": "88c04ebf-0671-4fea-95c9-bc1565d4bb4f", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"# Let's create a call that streams back results\n", |
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"\n", |
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"def stream_gpt(prompt):\n", |
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" messages = [\n", |
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" {\"role\": \"system\", \"content\": system_message},\n", |
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" {\"role\": \"user\", \"content\": prompt}\n", |
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" ]\n", |
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" stream = openai.chat.completions.create(\n", |
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" model='gpt-4o-mini',\n", |
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" messages=messages,\n", |
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" stream=True\n", |
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" )\n", |
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" result = \"\"\n", |
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" for chunk in stream:\n", |
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" result += chunk.choices[0].delta.content or \"\"\n", |
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" yield result" |
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] |
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}, |
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{ |
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"cell_type": "code", |
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"execution_count": null, |
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"id": "0bb1f789-ff11-4cba-ac67-11b815e29d09", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"view = gr.Interface(\n", |
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" fn=stream_gpt,\n", |
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" inputs=[gr.Textbox(label=\"Your message:\")],\n", |
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" outputs=[gr.Markdown(label=\"Response:\")],\n", |
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" flagging_mode=\"never\"\n", |
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")\n", |
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"view.launch()" |
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] |
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}, |
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{ |
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"cell_type": "code", |
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"execution_count": null, |
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"id": "bbc8e930-ba2a-4194-8f7c-044659150626", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"def stream_claude(prompt):\n", |
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" result = claude.messages.stream(\n", |
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" model=\"claude-3-haiku-20240307\",\n", |
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" max_tokens=1000,\n", |
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" temperature=0.7,\n", |
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" system=system_message,\n", |
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" messages=[\n", |
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" {\"role\": \"user\", \"content\": prompt},\n", |
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" ],\n", |
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" )\n", |
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" response = \"\"\n", |
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" with result as stream:\n", |
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" for text in stream.text_stream:\n", |
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" response += text or \"\"\n", |
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" yield response" |
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] |
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}, |
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{ |
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"cell_type": "code", |
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"execution_count": null, |
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"id": "a0066ffd-196e-4eaf-ad1e-d492958b62af", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"view = gr.Interface(\n", |
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" fn=stream_claude,\n", |
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" inputs=[gr.Textbox(label=\"Your message:\")],\n", |
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" outputs=[gr.Markdown(label=\"Response:\")],\n", |
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" flagging_mode=\"never\"\n", |
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")\n", |
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"view.launch()" |
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] |
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}, |
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{ |
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"cell_type": "markdown", |
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"id": "72d7de50-22ba-4758-92ea-9a4820947488", |
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"metadata": {}, |
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"source": [ |
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"# Add Gemini Model" |
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] |
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}, |
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{ |
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"cell_type": "code", |
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"execution_count": null, |
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"id": "026abd83-fb9a-4c8f-9f4d-cc73f9d20779", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"import google.generativeai as genai\n", |
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"\n", |
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"def stream_gemini(prompt):\n", |
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" gemini = genai.GenerativeModel(\n", |
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" model_name='gemini-1.5-flash',\n", |
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" safety_settings=None,\n", |
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" system_instruction=system_message\n", |
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" )\n", |
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"\n", |
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" response = gemini.generate_content(prompt, safety_settings=[\n", |
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" {\"category\": \"HARM_CATEGORY_DANGEROUS_CONTENT\", \"threshold\": \"BLOCK_NONE\"},\n", |
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" {\"category\": \"HARM_CATEGORY_SEXUALLY_EXPLICIT\", \"threshold\": \"BLOCK_NONE\"},\n", |
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" {\"category\": \"HARM_CATEGORY_HATE_SPEECH\", \"threshold\": \"BLOCK_NONE\"},\n", |
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" {\"category\": \"HARM_CATEGORY_HARASSMENT\", \"threshold\": \"BLOCK_NONE\"}], stream=True)\n", |
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" \n", |
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" result = \"\"\n", |
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" for chunk in response:\n", |
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" result += chunk.text\n", |
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" yield result\n" |
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] |
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}, |
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{ |
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"cell_type": "code", |
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"execution_count": null, |
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"id": "cf6fc87f-dd11-4668-9faa-19cb4f4865f1", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"view = gr.Interface(\n", |
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" fn=stream_gemini,\n", |
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" inputs=[gr.Textbox(label=\"Your message:\")],\n", |
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" outputs=[gr.Markdown(label=\"Response:\")],\n", |
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" flagging_mode=\"never\"\n", |
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")\n", |
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"view.launch()" |
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] |
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}, |
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{ |
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"cell_type": "markdown", |
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"id": "bc5a70b9-2afe-4a7c-9bed-2429229e021b", |
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"metadata": {}, |
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"source": [ |
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"## Minor improvement\n", |
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"\n", |
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"I've made a small improvement to this code.\n", |
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"\n", |
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"Previously, it had these lines:\n", |
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"\n", |
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"```\n", |
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"for chunk in result:\n", |
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" yield chunk\n", |
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"```\n", |
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"\n", |
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"There's actually a more elegant way to achieve this (which Python people might call more 'Pythonic'):\n", |
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"\n", |
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"`yield from result`" |
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] |
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}, |
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{ |
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"cell_type": "code", |
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"execution_count": null, |
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"id": "0087623a-4e31-470b-b2e6-d8d16fc7bcf5", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"def stream_model(prompt, model):\n", |
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" print(model) #Shows what model is being used\n", |
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" if model==\"GPT\":\n", |
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" result = stream_gpt(prompt)\n", |
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" elif model==\"Claude\":\n", |
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" result = stream_claude(prompt)\n", |
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" else:\n", |
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" raise ValueError(\"Unknown model\")\n", |
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" yield from result" |
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] |
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}, |
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{ |
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"cell_type": "code", |
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"execution_count": null, |
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"id": "8d8ce810-997c-4b6a-bc4f-1fc847ac8855", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"view = gr.Interface(\n", |
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" fn=stream_model,\n", |
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" inputs=[gr.Textbox(label=\"Your message:\"), gr.Dropdown([\"GPT\", \"Claude\", \"Gemini\"], label=\"Select model\")],\n", |
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" outputs=[gr.Markdown(label=\"Response:\")],\n", |
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" flagging_mode=\"never\"\n", |
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")\n", |
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"view.launch()" |
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] |
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}, |
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{ |
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"cell_type": "markdown", |
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"id": "76211a29-e1d5-49a9-b176-bb2d50e85155", |
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"metadata": {}, |
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"source": [ |
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"# Added Gemini Model to the Model Selection" |
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] |
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}, |
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{ |
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"cell_type": "code", |
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"execution_count": null, |
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"id": "4b1eb9ab-927b-44a7-9565-180bde4453b7", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"def stream_model(prompt, model):\n", |
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" print(model) #Shows what model is being used\n", |
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" if model==\"GPT\":\n", |
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" result = stream_gpt(prompt)\n", |
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" elif model==\"Claude\":\n", |
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" result = stream_claude(prompt)\n", |
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" elif model==\"Gemini\":\n", |
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" result = stream_gemini(prompt)\n", |
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" else:\n", |
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" raise ValueError(\"Unknown model\")\n", |
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" yield from result" |
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] |
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}, |
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{ |
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"cell_type": "code", |
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"execution_count": null, |
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"id": "89adb706-8f6d-43c2-b99c-e4786278e7b0", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"view = gr.Interface(\n", |
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" fn=stream_model,\n", |
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" inputs=[gr.Textbox(label=\"Your message:\"), gr.Dropdown([\"GPT\", \"Claude\", \"Gemini\"], label=\"Select model\")],\n", |
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" outputs=[gr.Markdown(label=\"Response:\")],\n", |
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" flagging_mode=\"never\"\n", |
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")\n", |
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"view.launch()" |
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] |
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}, |
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{ |
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"cell_type": "markdown", |
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"id": "d933865b-654c-4b92-aa45-cf389f1eda3d", |
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"metadata": {}, |
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"source": [ |
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"# Building a company brochure generator\n", |
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"\n", |
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"Now you know how - it's simple!" |
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] |
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}, |
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{ |
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"cell_type": "code", |
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"execution_count": null, |
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"id": "1626eb2e-eee8-4183-bda5-1591b58ae3cf", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"# A class to represent a Webpage\n", |
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"\n", |
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"class Website:\n", |
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" url: str\n", |
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" title: str\n", |
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" text: str\n", |
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"\n", |
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" def __init__(self, url):\n", |
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" self.url = url\n", |
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" response = requests.get(url)\n", |
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" self.body = response.content\n", |
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" soup = BeautifulSoup(self.body, 'html.parser')\n", |
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" self.title = soup.title.string if soup.title else \"No title found\"\n", |
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" for irrelevant in soup.body([\"script\", \"style\", \"img\", \"input\"]):\n", |
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" irrelevant.decompose()\n", |
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" self.text = soup.body.get_text(separator=\"\\n\", strip=True)\n", |
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"\n", |
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" def get_contents(self):\n", |
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" return f\"Webpage Title:\\n{self.title}\\nWebpage Contents:\\n{self.text}\\n\\n\"" |
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] |
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}, |
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{ |
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"cell_type": "code", |
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"execution_count": null, |
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"id": "c701ec17-ecd5-4000-9f68-34634c8ed49d", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"system_message = \"You are an assistant that analyzes the contents of a company website landing page \\\n", |
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"and creates a short brochure about the company for prospective customers, investors and recruits. Do not use any logos. Respond in markdown.\"" |
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] |
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}, |
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{ |
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"cell_type": "code", |
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"execution_count": null, |
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"id": "5def90e0-4343-4f58-9d4a-0e36e445efa4", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"def stream_brochure(company_name, url, model, response_tone):\n", |
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" prompt = f\"Please generate a {response_tone} company brochure for {company_name}. Here is their landing page:\\n\"\n", |
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" prompt += Website(url).get_contents()\n", |
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" if model==\"GPT\":\n", |
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" result = stream_gpt(prompt)\n", |
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" elif model==\"Claude\":\n", |
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" result = stream_claude(prompt)\n", |
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" elif model==\"Gemini\":\n", |
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" result = stream_gemini(prompt)\n", |
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" else:\n", |
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" raise ValueError(\"Unknown model\")\n", |
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" yield from result" |
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] |
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}, |
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{ |
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"cell_type": "code", |
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"execution_count": null, |
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"id": "66399365-5d67-4984-9d47-93ed26c0bd3d", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"view = gr.Interface(\n", |
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" fn=stream_brochure,\n", |
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" inputs=[\n", |
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" gr.Textbox(label=\"Company name:\"),\n", |
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" gr.Textbox(label=\"Landing page URL including http:// or https://\"),\n", |
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" gr.Dropdown([\"GPT\", \"Claude\", \"Gemini\"], label=\"Select model\"),\n", |
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" gr.Dropdown([\"Informational\", \"Promotional\", \"Humorous\"], label=\"Select tone\")],\n", |
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" outputs=[gr.Markdown(label=\"Brochure:\")],\n", |
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" flagging_mode=\"never\"\n", |
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")\n", |
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"view.launch()" |
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] |
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}, |
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{ |
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"cell_type": "code", |
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{ |
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