From b93474b586cdafe4e65676e9ec355f24236466f6 Mon Sep 17 00:00:00 2001 From: lmmelo <40006175+lmmelo@users.noreply.github.com> Date: Thu, 6 Feb 2025 19:00:13 +0000 Subject: [PATCH] Added my contributions to community-contributions --- .../0225_day2_exercise_by_LM.ipynb | 185 ++++++++++++++++++ 1 file changed, 185 insertions(+) create mode 100644 week1/community-contributions/0225_day2_exercise_by_LM.ipynb diff --git a/week1/community-contributions/0225_day2_exercise_by_LM.ipynb b/week1/community-contributions/0225_day2_exercise_by_LM.ipynb new file mode 100644 index 0000000..a6ec6f1 --- /dev/null +++ b/week1/community-contributions/0225_day2_exercise_by_LM.ipynb @@ -0,0 +1,185 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "fef36918-109d-41e3-8603-75ff81b42379", + "metadata": {}, + "source": [ + "# Solution for exercise day 2 - slight modification: model is a parameter also - display_summary(\"deepseek-r1:1.5b\",\"https://yoururl\")\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b50349ac-93ea-496b-ae20-bd72a93bb138", + "metadata": {}, + "outputs": [], + "source": [ + "# imports\n", + "\n", + "import requests\n", + "from bs4 import BeautifulSoup\n", + "from IPython.display import Markdown, display" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "edd073c7-8444-4a0d-b84e-4b2ed0ee7f35", + "metadata": {}, + "outputs": [], + "source": [ + "# Constants\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": "2e3a6e1a-e4c7-4448-9852-1b6ba2bd8d66", + "metadata": {}, + "outputs": [], + "source": [ + "# A class to represent a Webpage\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": "ae3752ca-3a97-4d6a-ac84-5b75ebfb50ed", + "metadata": {}, + "outputs": [], + "source": [ + "# Define the system prompt \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": "48b5240f-7617-4e51-a320-cba9650bec84", + "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": "6f7d84f0-60f2-4cbf-b4d1-173a79fe3380", + "metadata": {}, + "outputs": [], + "source": [ + "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": "25520a31-c857-4ed5-86da-50dfe5fab7bb", + "metadata": {}, + "outputs": [], + "source": [ + "def summarize(model,url):\n", + " website = Website(url)\n", + " payload = {\n", + " \"model\": model,\n", + " \"messages\": messages_for(website),\n", + " \"stream\": False\n", + " }\n", + " response = requests.post(OLLAMA_API, json=payload, headers=HEADERS)\n", + " return response.json()['message']['content']" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "430776ed-8516-43a9-8a22-618d9080f2e1", + "metadata": {}, + "outputs": [], + "source": [ + "# A function to display this nicely in the Jupyter output, using markdown\n", + "def display_summary(model,url):\n", + " summary = summarize(model,url)\n", + " display(Markdown(summary))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b2b05c1f-e4a2-4f65-bd6d-634d72e38b6e", + "metadata": {}, + "outputs": [], + "source": [ + "#!ollama pull deepseek-r1:1.5b" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "01513f8a-15b7-4053-bfe4-44b36e5494d1", + "metadata": {}, + "outputs": [], + "source": [ + "display_summary(\"deepseek-r1:1.5b\",\"https://www.ipma.pt\")" + ] + } + ], + "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": "3.12.9" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +}