From 604aca783c6b2a748365d53676606867e23b72b4 Mon Sep 17 00:00:00 2001 From: Rohit Nain Date: Sun, 24 Aug 2025 17:57:52 +0530 Subject: [PATCH] Revert "day-2 exercise with ollama" This reverts commit 17463e83ffc9b119065f97fc8f80fe4e5adad89d. --- .../Day-2_exercise_with_ollama3.ipynb | 290 ------------------ 1 file changed, 290 deletions(-) delete mode 100644 week1/community-contributions/Day-2_exercise_with_ollama3.ipynb diff --git a/week1/community-contributions/Day-2_exercise_with_ollama3.ipynb b/week1/community-contributions/Day-2_exercise_with_ollama3.ipynb deleted file mode 100644 index 1168770..0000000 --- a/week1/community-contributions/Day-2_exercise_with_ollama3.ipynb +++ /dev/null @@ -1,290 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "id": "135717e7", - "metadata": { - "vscode": { - "languageId": "plaintext" - } - }, - "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", - "import ollama" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "29a9e634", - "metadata": { - "vscode": { - "languageId": "plaintext" - } - }, - "outputs": [], - "source": [ - "# OPTION 1\n", - "# using openai\n", - "\n", - "# message = \"Hello, GPT! This is my first ever message to you! Hi!\"\n", - "# client = OpenAI(base_url=\"http://localhost:11434/v1\", api_key=\"not-needed\")\n", - "# response = openai.chat.completions.create(model=``, messages=[{\"role\":\"user\", \"content\":message}])\n", - "# print(response.choices[0].message.content)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "306993ed", - "metadata": { - "vscode": { - "languageId": "plaintext" - } - }, - "outputs": [], - "source": [ - "# OPTION 2\n", - "# using Ollama\n", - "\n", - "message = \"Hello, GPT! This is my first ever message to you! Hi!\"\n", - "model=\"llama3\"\n", - "response=ollama.chat(model=model,messages=[{\"role\":\"user\",\"content\":message}])\n", - "print(response[\"message\"][\"content\"])\n" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "856f767b", - "metadata": { - "vscode": { - "languageId": "plaintext" - } - }, - "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": 5, - "id": "4ce558dc", - "metadata": { - "vscode": { - "languageId": "plaintext" - } - }, - "outputs": [], - "source": [ - "# Let's try one out. Change the website and add print statements to follow along.\n", - "\n", - "ed = Website(\"https://edwarddonner.com\")" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "5e3956f8", - "metadata": { - "vscode": { - "languageId": "plaintext" - } - }, - "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": 7, - "id": "99d791b4", - "metadata": { - "vscode": { - "languageId": "plaintext" - } - }, - "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": 8, - "id": "5d89b748", - "metadata": { - "vscode": { - "languageId": "plaintext" - } - }, - "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": 9, - "id": "9a97d3e2", - "metadata": { - "vscode": { - "languageId": "plaintext" - } - }, - "outputs": [], - "source": [ - "# And now: call the OpenAI API. You will get very familiar with this!\n", - "\n", - "def summarize(url):\n", - " website = Website(url)\n", - " response=ollama.chat(model=model,messages=messages_for(website))\n", - " return(response[\"message\"][\"content\"])" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "ec13fe0a", - "metadata": { - "vscode": { - "languageId": "plaintext" - } - }, - "outputs": [], - "source": [ - "summarize(\"https://edwarddonner.com\")" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "id": "e3ade092", - "metadata": { - "vscode": { - "languageId": "plaintext" - } - }, - "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": "be2d49e6", - "metadata": { - "vscode": { - "languageId": "plaintext" - } - }, - "outputs": [], - "source": [ - "display_summary(\"https://edwarddonner.com\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "1ccbf33b", - "metadata": { - "vscode": { - "languageId": "plaintext" - } - }, - "outputs": [], - "source": [ - "display_summary(\"https://cnn.com\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "ae3d0eae", - "metadata": { - "vscode": { - "languageId": "plaintext" - } - }, - "outputs": [], - "source": [ - "display_summary(\"https://anthropic.com\")" - ] - } - ], - "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": "3.11.13" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -}