{ "cells": [ { "cell_type": "markdown", "id": "603cd418-504a-4b4d-b1c3-be04febf3e79", "metadata": {}, "source": [ "# Article Title Generator\n", "\n", "Summarization use-case in which the user provides an article, which the LLM will analyze to suggest an SEO-optimized title.\n", "\n", "**NOTES**:\n", "\n", "1. This version does NOT support website scrapping. You must copy and paste the required article.\n", "2. The following models were configured:\n", " a. OpenAI gpt-4o-mini\n", " b. Llama llama3.2\n", " c. Deepseek deepseek-r1:1.5b\n", " It is possible to configure additional models by adding the new model to the MODELS dictionary and its\n", " initialization to the CLIENTS dictionary. Then, call the model with --> ***answer =\n", " get_answer('NEW_MODEL')***.\n", "3. Users are encouraged to assess and rank the suggested titles using any headline analyzer tool online.\n", " Example: https://www.isitwp.com/headline-analyzer/. " ] }, { "cell_type": "code", "execution_count": null, "id": "e773daa6-d05e-49bf-ad8e-a8ed4882b77e", "metadata": {}, "outputs": [], "source": [ "# Confirming Llama is loaded\n", "!ollama pull llama3.2" ] }, { "cell_type": "code", "execution_count": null, "id": "279b0c00-9bb0-4c7f-9c6d-aa0b108274b9", "metadata": {}, "outputs": [], "source": [ "# imports\n", "import os\n", "from dotenv import load_dotenv\n", "from IPython.display import Markdown, display\n", "from openai import OpenAI" ] }, { "cell_type": "code", "execution_count": null, "id": "d4730d8d-3e20-4f3c-a4ff-ed2ac0a8aa27", "metadata": {}, "outputs": [], "source": [ "# set environment variables for OpenAi\n", "load_dotenv(override=True)\n", "api_key = os.getenv('OPENAI_API_KEY')\n", "\n", "# validate API Key\n", "if not api_key:\n", " raise ValueError(\"No API key was found! Please check the .env file.\")" ] }, { "cell_type": "code", "execution_count": null, "id": "1abbb826-de66-498c-94d8-33369ad01885", "metadata": {}, "outputs": [], "source": [ "# constants\n", "MODELS = { 'GPT': 'gpt-4o-mini', \n", " 'LLAMA': 'llama3.2', \n", " 'DEEPSEEK': 'deepseek-r1:1.5b'\n", " }\n", "\n", "CLIENTS = { 'GPT': OpenAI(), \n", " 'LLAMA': OpenAI(base_url='http://localhost:11434/v1', api_key='ollama'),\n", " 'DEEPSEEK': OpenAI(base_url='http://localhost:11434/v1', api_key='ollama') \n", " }" ] }, { "cell_type": "markdown", "id": "6f490fe4-32d5-41f3-890d-ecf4e5e01dd4", "metadata": {}, "source": [ "### Copy & paste your article (without a title)" ] }, { "cell_type": "code", "execution_count": null, "id": "ddd76319-13ce-480b-baa7-cab6a5c88168", "metadata": {}, "outputs": [], "source": [ "# article - copy & paste your article\n", "article = \"\"\"\n", " REPLACE WITH YOUR ARTICLE CONTENT\n", " \"\"\"" ] }, { "cell_type": "code", "execution_count": null, "id": "1914afad-dbd8-4c1f-8e68-80b0e5d743a9", "metadata": {}, "outputs": [], "source": [ "# system prompt\n", "system_prompt = \"\"\"\n", " You are an experienced SEO-focused copywriter. The user will provide an article, and your task is to analyze its content and generate the most effective, keyword-optimized title to maximize SEO performance.Respond in Markdown format.\n", " \"\"\"" ] }, { "cell_type": "code", "execution_count": null, "id": "176cfac7-5e6d-4d4a-a1c4-1b63b60de1f7", "metadata": {}, "outputs": [], "source": [ "# user prompt\n", "user_prompt = f\"Following the article to be analyzed. Respond in Markdown format./n/n{article}\"\n", " " ] }, { "cell_type": "code", "execution_count": null, "id": "c45fc7d7-08c9-4e34-b427-b928a219bb94", "metadata": {}, "outputs": [], "source": [ "# message list\n", "messages = [\n", " {\"role\": \"system\", \"content\": system_prompt},\n", " {\"role\": \"user\", \"content\": user_prompt}\n", " ]" ] }, { "cell_type": "code", "execution_count": null, "id": "f67b881f-1040-4cf7-82c5-e85f4c0bd252", "metadata": {}, "outputs": [], "source": [ "# call model and get answer\n", "def get_answer(model):\n", " # set required client\n", " client = CLIENTS[model]\n", "\n", " # call model\n", " response = client.chat.completions.create(\n", " model=MODELS[model],\n", " messages=messages\n", " )\n", " \n", " # return answer\n", " return response.choices[0].message.content\n", " " ] }, { "cell_type": "markdown", "id": "947b42ed-5b43-486d-8af3-e5b671c1fd0e", "metadata": {}, "source": [ "### Get OpenAI Suggested Title" ] }, { "cell_type": "code", "execution_count": null, "id": "eb6f66e3-ab99-4f76-9358-896cb43c1fa1", "metadata": {}, "outputs": [], "source": [ "# get openAi answer\n", "answer = get_answer('GPT')\n", "\n", "# display openAi answer\n", "display(Markdown(f\"### {MODELS['GPT']} Answer\\n\\n{answer}\" ))" ] }, { "cell_type": "markdown", "id": "70073ebf-a00a-416b-854d-642d450cd99b", "metadata": {}, "source": [ "### Get Llama Suggested Title" ] }, { "cell_type": "code", "execution_count": null, "id": "caa190bb-de5f-45cc-b671-5d62688f7b25", "metadata": {}, "outputs": [], "source": [ "# get Llama answer\n", "answer = get_answer('LLAMA')\n", "\n", "# display Llama answer\n", "display(Markdown(f\"### {MODELS['LLAMA']} Answer\\n\\n{answer}\" ))" ] }, { "cell_type": "markdown", "id": "811edc4f-20e2-482d-ac89-fae9d1b70bed", "metadata": {}, "source": [ "### Get Deepseek Suggested Title" ] }, { "cell_type": "code", "execution_count": null, "id": "082628e4-ff4c-46dd-ae5f-76578eb017ad", "metadata": {}, "outputs": [], "source": [ "# get Deepseek answer\n", "answer = get_answer('DEEPSEEK')\n", "\n", "# display Deepseek answer\n", "display(Markdown(f\"### {MODELS['DEEPSEEK']} Answer\\n\\n{answer}\" ))" ] }, { "cell_type": "markdown", "id": "7fc404a6-3a91-4c09-89de-867d3d69b4b2", "metadata": {}, "source": [ "### Suggested future improvements\n", "\n", "1. Add website scrapping support to replace copy/pasting of articles.\n", "2. Improve the system_prompt to provide specific SEO best practices to adopt during the title generation.\n", "3. Rephrase the system_prompt to ensure the model provides a single Title (not a list of suggestions). \n", "4. Add the logic that would allow each model to assess the recommendations from the different models and \n", " select the best among these. " ] }, { "cell_type": "code", "execution_count": null, "id": "cf7403ac-d43b-4493-98bb-6fee94950cb0", "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.11.11" } }, "nbformat": 4, "nbformat_minor": 5 }