diff --git a/week1/community-contributions/day1-research-paper-summarization.ipynb b/week1/community-contributions/day1-research-paper-summarization.ipynb new file mode 100644 index 0000000..9de589b --- /dev/null +++ b/week1/community-contributions/day1-research-paper-summarization.ipynb @@ -0,0 +1,233 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "1b8f7ac7-7089-427a-8f63-57211da7e691", + "metadata": {}, + "source": [ + "## Summarizing Research Papers" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "641d5c00-ff09-4697-9c87-5de5df1469f8", + "metadata": {}, + "outputs": [], + "source": [ + "# imports\n", + "\n", + "import os\n", + "import requests\n", + "from dotenv import load_dotenv\n", + "from bs4 import BeautifulSoup\n", + "from IPython.display import Markdown, display\n", + "from openai import OpenAI\n", + "\n", + "# If you get an error running this cell, then please head over to the troubleshooting notebook!" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "1a6a2864-fd9d-43e2-b0ca-1476c0153077", + "metadata": {}, + "outputs": [], + "source": [ + "# Load environment variables in a file called .env\n", + "\n", + "load_dotenv(override=True)\n", + "api_key = os.getenv('OPENAI_API_KEY')\n", + "\n", + "# Check the key\n", + "\n", + "if not api_key:\n", + " print(\"No API key was found - please head over to the troubleshooting notebook in this folder to identify & fix!\")\n", + "elif not api_key.startswith(\"sk-proj-\"):\n", + " print(\"An API key was found, but it doesn't start sk-proj-; please check you're using the right key - see troubleshooting notebook\")\n", + "elif api_key.strip() != api_key:\n", + " print(\"An API key was found, but it looks like it might have space or tab characters at the start or end - please remove them - see troubleshooting notebook\")\n", + "else:\n", + " print(\"API key found and looks good so far!\")\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "340e3166-5aa7-4bcf-9cf0-e2fc776dc322", + "metadata": {}, + "outputs": [], + "source": [ + "openai = OpenAI()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "73198fb7-581f-42ac-99a6-76c56c86248d", + "metadata": {}, + "outputs": [], + "source": [ + "# A class to represent a Webpage\n", + "# If you're not familiar with Classes, check out the \"Intermediate Python\" notebook\n", + "\n", + "# Some websites need you to use proper headers when fetching them:\n", + "headers = {\n", + " \"User-Agent\": \"Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/117.0.0.0 Safari/537.36\"\n", + "}\n", + "\n", + "class Paper:\n", + "\n", + " def __init__(self, url):\n", + " \"\"\"\n", + " Create this Website object from the given url using the BeautifulSoup library\n", + " \"\"\"\n", + " self.url = url\n", + " response = requests.get(url, headers=headers)\n", + " soup = BeautifulSoup(response.content, 'html.parser')\n", + " self.title = soup.title.string if soup.title else \"No title found\"\n", + " for irrelevant in soup.body([\"script\", \"style\", \"img\", \"input\"]):\n", + " irrelevant.decompose()\n", + " self.text = soup.body.get_text(separator=\"\\n\", strip=True)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "3b39c3ad-d238-418e-9e6a-55a4fd717ebc", + "metadata": {}, + "outputs": [], + "source": [ + "#Insert Paper URL\n", + "res = Paper(\" \")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "83bc1eec-4187-4c6c-b188-3f72564351f1", + "metadata": {}, + "outputs": [], + "source": [ + "system_prompt = \"\"\"You are a research paper summarizer. You take the url of the research paper and extract the following:\n", + "1) Title and Author of the research paper.\n", + "2) Year it was published it\n", + "3) Objective or aim of the research to specify why the research was conducted\n", + "4) Background or Introduction to explain the need to conduct this research or any topics the readers must have knowledge about\n", + "5) Type of research/study/experiment to explain what kind of research it is.\n", + "6) Methods or methodology to explain what the researchers did to conduct the research\n", + "7) Results and key findings to explain what the researchers found\n", + "8) Conclusion tells about the conclusions that can be drawn from this research including limitations and future direction\"\"\"" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "4aba1b51-9a72-4325-8c86-3968b9d3172e", + "metadata": {}, + "outputs": [], + "source": [ + "# A function that writes a User Prompt that asks for summaries of websites:\n", + "\n", + "def user_prompt_for(paper):\n", + " user_prompt = f\"You are looking at a website titled {paper.title}\"\n", + " user_prompt += \"\\nThe contents of this paper is as follows; \\\n", + "please provide a short summary of this paper in markdown. \\\n", + "If it includes additional headings, then summarize these too.\\n\\n\"\n", + " user_prompt += paper.text\n", + " return user_prompt" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "659cb3c4-8a02-493d-abe7-20da9219e358", + "metadata": {}, + "outputs": [], + "source": [ + "# See how this function creates exactly the format above\n", + "def messages_for(paper):\n", + " return [\n", + " {\"role\": \"system\", \"content\": system_prompt},\n", + " {\"role\": \"user\", \"content\": user_prompt_for(paper)}\n", + " ]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "08ea1193-1bbb-40de-ba64-d02ffe109372", + "metadata": {}, + "outputs": [], + "source": [ + "messages_for(res)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "e07d00e7-1b87-4ca8-a69d-4a206e34a2b2", + "metadata": {}, + "outputs": [], + "source": [ + "# And now: call the OpenAI API. You will get very familiar with this!\n", + "\n", + "def summarize(url):\n", + " paper = Paper(url)\n", + " response = openai.chat.completions.create(\n", + " model = \"gpt-4o-mini\",\n", + " messages = messages_for(paper)\n", + " )\n", + " return response.choices[0].message.content" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "5c12df95-1700-47ee-891b-96b0a7227bdd", + "metadata": {}, + "outputs": [], + "source": [ + "# A function to display this nicely in the Jupyter output, using markdown\n", + "\n", + "def display_summary(url):\n", + " summary = summarize(url)\n", + " display(Markdown(summary))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "05cff05f-2b74-44a4-9dbd-57c08f8f56cb", + "metadata": { + "scrolled": true + }, + "outputs": [], + "source": [ + "# Insert Paper URL in the quotes below\n", + "display_summary(\" \")" + ] + } + ], + "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 +} diff --git a/week1/community-contributions/day2 EXERCISE-Summarization-Ollama.ipynb b/week1/community-contributions/day2 EXERCISE-Summarization-Ollama.ipynb new file mode 100644 index 0000000..4d1abc6 --- /dev/null +++ b/week1/community-contributions/day2 EXERCISE-Summarization-Ollama.ipynb @@ -0,0 +1,192 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "e3ce0a59-fbfb-4377-85db-f62f95039200", + "metadata": {}, + "source": [ + "# Day2 EXERCISE - Summarization using Ollama" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "4e2a9393-7767-488e-a8bf-27c12dca35bd", + "metadata": {}, + "outputs": [], + "source": [ + "# imports\n", + "\n", + "import os\n", + "from dotenv import load_dotenv\n", + "import requests\n", + "from bs4 import BeautifulSoup\n", + "from IPython.display import Markdown, display" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "29ddd15d-a3c5-4f4e-a678-873f56162724", + "metadata": {}, + "outputs": [], + "source": [ + "# Constants\n", + "\n", + "OLLAMA_API = \"http://localhost:11434/api/chat\"\n", + "HEADERS = {\"Content-Type\": \"application/json\"}\n", + "MODEL = \"llama3.2\"" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "cb5c0f84-4e4d-4f87-b492-e09d0333a638", + "metadata": {}, + "outputs": [], + "source": [ + "# A class to represent a Webpage\n", + "# If you're not familiar with Classes, check out the \"Intermediate Python\" notebook\n", + "\n", + "# Some websites need you to use proper headers when fetching them:\n", + "headers = {\n", + " \"User-Agent\": \"Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/117.0.0.0 Safari/537.36\"\n", + "}\n", + "\n", + "class Website:\n", + "\n", + " def __init__(self, url):\n", + " \"\"\"\n", + " Create this Website object from the given url using the BeautifulSoup library\n", + " \"\"\"\n", + " self.url = url\n", + " response = requests.get(url, headers=headers)\n", + " soup = BeautifulSoup(response.content, 'html.parser')\n", + " self.title = soup.title.string if soup.title else \"No title found\"\n", + " for irrelevant in soup.body([\"script\", \"style\", \"img\", \"input\"]):\n", + " irrelevant.decompose()\n", + " self.text = soup.body.get_text(separator=\"\\n\", strip=True)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "23457b52-c85b-4dc1-b946-6f1461dc0675", + "metadata": {}, + "outputs": [], + "source": [ + "\n", + "ed = Website(\"https://edwarddonner.com\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "bed206ed-43c1-4f68-ad01-a738b3b4648d", + "metadata": {}, + "outputs": [], + "source": [ + "# Define our system prompt - you can experiment with this later, changing the last sentence to 'Respond in markdown in Spanish.\"\n", + "\n", + "system_prompt = \"You are an assistant that analyzes the contents of a website \\\n", + "and provides a short summary, ignoring text that might be navigation related. \\\n", + "Respond in markdown.\"" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "e558f381-614a-461f-83bc-e5bdc99460df", + "metadata": {}, + "outputs": [], + "source": [ + "# A function that writes a User Prompt that asks for summaries of websites:\n", + "\n", + "def user_prompt_for(website):\n", + " user_prompt = f\"You are looking at a website titled {website.title}\"\n", + " user_prompt += \"\\nThe contents of this website is as follows; \\\n", + "please provide a short summary of this website in markdown. \\\n", + "If it includes news or announcements, then summarize these too.\\n\\n\"\n", + " user_prompt += website.text\n", + " return user_prompt" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "e5ba638d-aeb9-441e-a62a-8e8027ad8439", + "metadata": {}, + "outputs": [], + "source": [ + "# See how this function creates exactly the format above\n", + "\n", + "def messages_for(website):\n", + " return [\n", + " {\"role\": \"system\", \"content\": system_prompt},\n", + " {\"role\": \"user\", \"content\": user_prompt_for(website)}\n", + " ]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "e85ca2ec-3e46-4b8f-9c2f-66e7d20138fa", + "metadata": {}, + "outputs": [], + "source": [ + "#website search\n", + "\n", + "ed = Website(\"https://edwarddonner.com\")\n", + "messages=messages_for(ed)\n", + "\n", + "payload = {\n", + " \"model\": MODEL,\n", + " \"messages\": messages,\n", + " \"stream\": False\n", + " }" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "7745b9c4-57dc-4867-9180-61fa5db55eb8", + "metadata": {}, + "outputs": [], + "source": [ + "import ollama\n", + "\n", + "response = ollama.chat(model=MODEL, messages=messages)\n", + "print(response['message']['content'])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "402d5686-4e76-4110-b65a-b3906c35c0a4", + "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 +}