week1: add Fernando notebooks (day2 + exercise), outputs cleared
This commit is contained in:
nandoclal
494
week1/community-contributions/fernando/day2.ipynb
Normal file
494
week1/community-contributions/fernando/day2.ipynb
Normal file
@@ -0,0 +1,494 @@
|
|||||||
|
{
|
||||||
|
"cells": [
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"id": "d15d8294-3328-4e07-ad16-8a03e9bbfdb9",
|
||||||
|
"metadata": {},
|
||||||
|
"source": [
|
||||||
|
"# Welcome to the Day 2 Lab!\n"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"id": "ada885d9-4d42-4d9b-97f0-74fbbbfe93a9",
|
||||||
|
"metadata": {},
|
||||||
|
"source": [
|
||||||
|
"<table style=\"margin: 0; text-align: left;\">\n",
|
||||||
|
" <tr>\n",
|
||||||
|
" <td style=\"width: 150px; height: 150px; vertical-align: middle;\">\n",
|
||||||
|
" <img src=\"../assets/resources.jpg\" width=\"150\" height=\"150\" style=\"display: block;\" />\n",
|
||||||
|
" </td>\n",
|
||||||
|
" <td>\n",
|
||||||
|
" <h2 style=\"color:#f71;\">Just before we get started --</h2>\n",
|
||||||
|
" <span style=\"color:#f71;\">I thought I'd take a second to point you at this page of useful resources for the course. This includes links to all the slides.<br/>\n",
|
||||||
|
" <a href=\"https://edwarddonner.com/2024/11/13/llm-engineering-resources/\">https://edwarddonner.com/2024/11/13/llm-engineering-resources/</a><br/>\n",
|
||||||
|
" Please keep this bookmarked, and I'll continue to add more useful links there over time.\n",
|
||||||
|
" </span>\n",
|
||||||
|
" </td>\n",
|
||||||
|
" </tr>\n",
|
||||||
|
"</table>"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"id": "79ffe36f",
|
||||||
|
"metadata": {},
|
||||||
|
"source": [
|
||||||
|
"## First - let's talk about the Chat Completions API\n",
|
||||||
|
"\n",
|
||||||
|
"1. The simplest way to call an LLM\n",
|
||||||
|
"2. It's called Chat Completions because it's saying: \"here is a conversation, please predict what should come next\"\n",
|
||||||
|
"3. The Chat Completions API was invented by OpenAI, but it's so popular that everybody uses it!\n",
|
||||||
|
"\n",
|
||||||
|
"### We will start by calling OpenAI again - but don't worry non-OpenAI people, your time is coming!\n"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"id": "e38f17a0",
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"import os\n",
|
||||||
|
"from dotenv import load_dotenv\n",
|
||||||
|
"\n",
|
||||||
|
"load_dotenv(override=True)\n",
|
||||||
|
"api_key = os.getenv('OPENAI_API_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",
|
||||||
|
"else:\n",
|
||||||
|
" print(\"API key found and looks good so far!\")\n"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"id": "97846274",
|
||||||
|
"metadata": {},
|
||||||
|
"source": [
|
||||||
|
"## Do you know what an Endpoint is?\n",
|
||||||
|
"\n",
|
||||||
|
"If not, please review the Technical Foundations guide in the guides folder\n",
|
||||||
|
"\n",
|
||||||
|
"And, here is an endpoint that might interest you..."
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"id": "5af5c188",
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"import requests\n",
|
||||||
|
"\n",
|
||||||
|
"headers = {\"Authorization\": f\"Bearer {api_key}\", \"Content-Type\": \"application/json\"}\n",
|
||||||
|
"\n",
|
||||||
|
"payload = {\n",
|
||||||
|
" \"model\": \"gpt-5-nano\",\n",
|
||||||
|
" \"messages\": [\n",
|
||||||
|
" {\"role\": \"user\", \"content\": \"Tell me a fun fact\"}]\n",
|
||||||
|
"}\n",
|
||||||
|
"\n",
|
||||||
|
"payload"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"id": "2d0ab242",
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"response = requests.post(\n",
|
||||||
|
" \"https://api.openai.com/v1/chat/completions\",\n",
|
||||||
|
" headers=headers,\n",
|
||||||
|
" json=payload\n",
|
||||||
|
")\n",
|
||||||
|
"\n",
|
||||||
|
"response.json()"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"id": "cb11a9f6",
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"response.json()[\"choices\"][0][\"message\"][\"content\"]"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"id": "cea3026a",
|
||||||
|
"metadata": {},
|
||||||
|
"source": [
|
||||||
|
"# What is the openai package?\n",
|
||||||
|
"\n",
|
||||||
|
"It's known as a Python Client Library.\n",
|
||||||
|
"\n",
|
||||||
|
"It's nothing more than a wrapper around making this exact call to the http endpoint.\n",
|
||||||
|
"\n",
|
||||||
|
"It just allows you to work with nice Python code instead of messing around with janky json objects.\n",
|
||||||
|
"\n",
|
||||||
|
"But that's it. It's open-source and lightweight. Some people think it contains OpenAI model code - it doesn't!\n"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"id": "490fdf09",
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"# Create OpenAI client\n",
|
||||||
|
"\n",
|
||||||
|
"from openai import OpenAI\n",
|
||||||
|
"openai = OpenAI()\n",
|
||||||
|
"\n",
|
||||||
|
"response = openai.chat.completions.create(model=\"gpt-5-nano\", messages=[{\"role\": \"user\", \"content\": \"Tell me a fun fact\"}])\n",
|
||||||
|
"\n",
|
||||||
|
"response.choices[0].message.content\n",
|
||||||
|
"\n"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"id": "c7739cda",
|
||||||
|
"metadata": {},
|
||||||
|
"source": [
|
||||||
|
"## And then this great thing happened:\n",
|
||||||
|
"\n",
|
||||||
|
"OpenAI's Chat Completions API was so popular, that the other model providers created endpoints that are identical.\n",
|
||||||
|
"\n",
|
||||||
|
"They are known as the \"OpenAI Compatible Endpoints\".\n",
|
||||||
|
"\n",
|
||||||
|
"For example, google made one here: https://generativelanguage.googleapis.com/v1beta/openai/\n",
|
||||||
|
"\n",
|
||||||
|
"And OpenAI decided to be kind: they said, hey, you can just use the same client library that we made for GPT. We'll allow you to specify a different endpoint URL and a different key, to use another provider.\n",
|
||||||
|
"\n",
|
||||||
|
"So you can use:\n",
|
||||||
|
"\n",
|
||||||
|
"```python\n",
|
||||||
|
"gemini = OpenAI(base_url=\"https://generativelanguage.googleapis.com/v1beta/openai/\", api_key=\"AIz....\")\n",
|
||||||
|
"gemini.chat.completions.create(...)\n",
|
||||||
|
"```\n",
|
||||||
|
"\n",
|
||||||
|
"And to be clear - even though OpenAI is in the code, we're only using this lightweight python client library to call the endpoint - there's no OpenAI model involved here.\n",
|
||||||
|
"\n",
|
||||||
|
"If you're confused, please review Guide 9 in the Guides folder!\n",
|
||||||
|
"\n",
|
||||||
|
"And now let's try it!"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"id": "f74293bc",
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"\n",
|
||||||
|
"GEMINI_BASE_URL = \"https://generativelanguage.googleapis.com/v1beta/openai/\"\n",
|
||||||
|
"\n",
|
||||||
|
"google_api_key = os.getenv(\"GOOGLE_API_KEY\")\n",
|
||||||
|
"\n",
|
||||||
|
"if not google_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 google_api_key.startswith(\"AIz\"):\n",
|
||||||
|
" print(\"An API key was found, but it doesn't start AIz\")\n",
|
||||||
|
"else:\n",
|
||||||
|
" print(\"API key found and looks good so far!\")\n"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"id": "8fc5520d",
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"import google.generativeai as genai\n",
|
||||||
|
"from dotenv import load_dotenv\n",
|
||||||
|
"import os\n",
|
||||||
|
"\n",
|
||||||
|
"load_dotenv()\n",
|
||||||
|
"genai.configure(api_key=os.getenv(\"GOOGLE_API_KEY\"))\n",
|
||||||
|
"\n",
|
||||||
|
"# Lista de modelos disponibles\n",
|
||||||
|
"for model in genai.list_models():\n",
|
||||||
|
" print(model.name, \"-\", model.supported_generation_methods)\n"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"id": "d060f484",
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"import google.generativeai as genai\n",
|
||||||
|
"from dotenv import load_dotenv\n",
|
||||||
|
"import os\n",
|
||||||
|
"\n",
|
||||||
|
"load_dotenv()\n",
|
||||||
|
"genai.configure(api_key=os.getenv(\"GOOGLE_API_KEY\"))\n",
|
||||||
|
"\n",
|
||||||
|
"model = genai.GenerativeModel(\"models/gemini-2.5-pro\") # Usa el modelo que viste en la lista, ejemplo \"gemini-1.5-pro\" o \"gemini-1.5-flash\"\n",
|
||||||
|
"response = model.generate_content(\"Tell me a fun fact\")\n",
|
||||||
|
"\n",
|
||||||
|
"print(response.text)"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"gemini = OpenAI(base_url=GEMINI_BASE_URL, api_key=google_api_key)\n",
|
||||||
|
"\n",
|
||||||
|
"response = gemini.chat.completions.create(model=\"models/gemini-2.5-pro\", messages=[{\"role\": \"user\", \"content\": \"Tell me a fun fact\"}])\n",
|
||||||
|
"\n",
|
||||||
|
"response.choices[0].message.content"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"id": "a5b069be",
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": []
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"id": "65272432",
|
||||||
|
"metadata": {},
|
||||||
|
"source": [
|
||||||
|
"## And Ollama also gives an OpenAI compatible endpoint\n",
|
||||||
|
"\n",
|
||||||
|
"...and it's on your local machine!\n",
|
||||||
|
"\n",
|
||||||
|
"If the next cell doesn't print \"Ollama is running\" then please open a terminal and run `ollama serve`"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"id": "f06280ad",
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"requests.get(\"http://localhost:11434\").content"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"id": "c6ef3807",
|
||||||
|
"metadata": {},
|
||||||
|
"source": [
|
||||||
|
"### Download llama3.2 from meta\n",
|
||||||
|
"\n",
|
||||||
|
"Change this to llama3.2:1b if your computer is smaller.\n",
|
||||||
|
"\n",
|
||||||
|
"Don't use llama3.3 or llama4! They are too big for your computer.."
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"id": "e633481d",
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"!ollama pull llama3.2"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"id": "ce240975",
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"import requests\n",
|
||||||
|
"response = requests.get(\"http://localhost:11434/v1/models\")\n",
|
||||||
|
"print(response.json())\n"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"id": "d9419762",
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"from openai import OpenAI\n",
|
||||||
|
"\n",
|
||||||
|
"OLLAMA_BASE_URL = \"http://localhost:11434/v1\"\n",
|
||||||
|
"\n",
|
||||||
|
"ollama = OpenAI(base_url=OLLAMA_BASE_URL, api_key='ollama')\n"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"id": "e2456cdf",
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"# Get a fun fact\n",
|
||||||
|
"\n",
|
||||||
|
"response = ollama.chat.completions.create(model=\"llama3.2\", messages=[{\"role\": \"user\", \"content\": \"Tell me a fun fact\"}])\n",
|
||||||
|
"\n",
|
||||||
|
"response.choices[0].message.content"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"id": "3d7cebd7",
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"# Now let's try deepseek-r1:1.5b - this is DeepSeek \"distilled\" into Qwen from Alibaba Cloud\n",
|
||||||
|
"\n",
|
||||||
|
"!ollama pull deepseek-r1:1.5b"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"id": "25002f25",
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"#response = ollama.chat.completions.create(model=\"deepseek-r1:1.5b\", messages=[{\"role\": \"user\", \"content\": \"Tell me a fun fact\"}])\n",
|
||||||
|
"#response.choices[0].message.content\n",
|
||||||
|
"\n",
|
||||||
|
"from ollama import chat # pip install ollama\n",
|
||||||
|
"\n",
|
||||||
|
"resp = chat(\n",
|
||||||
|
" model='deepseek-r1:1.5b',\n",
|
||||||
|
" messages=[{'role': 'user', 'content': 'Tell me a fun fact'}],\n",
|
||||||
|
")\n",
|
||||||
|
"\n",
|
||||||
|
"print(resp['message']['content'])\n",
|
||||||
|
"# o\n",
|
||||||
|
"print(resp.message.content)\n"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"id": "6e9fa1fc-eac5-4d1d-9be4-541b3f2b3458",
|
||||||
|
"metadata": {},
|
||||||
|
"source": [
|
||||||
|
"# HOMEWORK EXERCISE ASSIGNMENT\n",
|
||||||
|
"\n",
|
||||||
|
"Upgrade the day 1 project to summarize a webpage to use an Open Source model running locally via Ollama rather than OpenAI\n",
|
||||||
|
"\n",
|
||||||
|
"You'll be able to use this technique for all subsequent projects if you'd prefer not to use paid APIs.\n",
|
||||||
|
"\n",
|
||||||
|
"**Benefits:**\n",
|
||||||
|
"1. No API charges - open-source\n",
|
||||||
|
"2. Data doesn't leave your box\n",
|
||||||
|
"\n",
|
||||||
|
"**Disadvantages:**\n",
|
||||||
|
"1. Significantly less power than Frontier Model\n",
|
||||||
|
"\n",
|
||||||
|
"## Recap on installation of Ollama\n",
|
||||||
|
"\n",
|
||||||
|
"Simply visit [ollama.com](https://ollama.com) and install!\n",
|
||||||
|
"\n",
|
||||||
|
"Once complete, the ollama server should already be running locally. \n",
|
||||||
|
"If you visit: \n",
|
||||||
|
"[http://localhost:11434/](http://localhost:11434/)\n",
|
||||||
|
"\n",
|
||||||
|
"You should see the message `Ollama is running`. \n",
|
||||||
|
"\n",
|
||||||
|
"If not, bring up a new Terminal (Mac) or Powershell (Windows) and enter `ollama serve` \n",
|
||||||
|
"And in another Terminal (Mac) or Powershell (Windows), enter `ollama pull llama3.2` \n",
|
||||||
|
"Then try [http://localhost:11434/](http://localhost:11434/) again.\n",
|
||||||
|
"\n",
|
||||||
|
"If Ollama is slow on your machine, try using `llama3.2:1b` as an alternative. Run `ollama pull llama3.2:1b` from a Terminal or Powershell, and change the code from `MODEL = \"llama3.2\"` to `MODEL = \"llama3.2:1b\"`"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"id": "6de38216-6d1c-48c4-877b-86d403f4e0f8",
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"# imports\n",
|
||||||
|
"import os\n",
|
||||||
|
"from dotenv import load_dotenv\n",
|
||||||
|
"from scraper import fetch_website_contents\n",
|
||||||
|
"from IPython.display import Markdown, display\n",
|
||||||
|
"from ollama import Client \n",
|
||||||
|
"\n",
|
||||||
|
"# Cliente Ollama local\n",
|
||||||
|
"ollama = Client()\n",
|
||||||
|
"\n",
|
||||||
|
"system_prompt = \"\"\"\n",
|
||||||
|
"You are a helpful assistant that analyzes the contents of a website,\n",
|
||||||
|
"and provides a short, snarky, humorous summary, ignoring text that might be navigation related.\n",
|
||||||
|
"Respond in markdown. Do not wrap the markdown in a code block - respond just with the markdown.\n",
|
||||||
|
"\"\"\"\n",
|
||||||
|
"\n",
|
||||||
|
"user_prompt_prefix = \"\"\"\n",
|
||||||
|
"Here are the contents of a website.\n",
|
||||||
|
"Provide a short summary of this website.\n",
|
||||||
|
"If it includes news or announcements, then summarize these too.\n",
|
||||||
|
"\"\"\"\n",
|
||||||
|
"\n",
|
||||||
|
"def messages_for(website):\n",
|
||||||
|
" return [\n",
|
||||||
|
" {\"role\": \"system\", \"content\": system_prompt},\n",
|
||||||
|
" {\"role\": \"user\", \"content\": user_prompt_prefix + website}\n",
|
||||||
|
" ]\n",
|
||||||
|
"\n",
|
||||||
|
"def summarize(url):\n",
|
||||||
|
" website = fetch_website_contents(url)\n",
|
||||||
|
" response = ollama.chat(\n",
|
||||||
|
" model='llama3.2',\n",
|
||||||
|
" messages=messages_for(website)\n",
|
||||||
|
" )\n",
|
||||||
|
" return response['message']['content']\n",
|
||||||
|
"\n",
|
||||||
|
"def display_summary(url):\n",
|
||||||
|
" summary = summarize(url)\n",
|
||||||
|
" display(Markdown(summary))\n",
|
||||||
|
"\n",
|
||||||
|
"# Ejecuta el resumen\n",
|
||||||
|
"display_summary(\"https://www.reforma.com\")\n"
|
||||||
|
]
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"metadata": {
|
||||||
|
"kernelspec": {
|
||||||
|
"display_name": ".venv",
|
||||||
|
"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": "3.12.12"
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"nbformat": 4,
|
||||||
|
"nbformat_minor": 5
|
||||||
|
}
|
||||||
175
week1/community-contributions/fernando/week1 EXERCISE.ipynb
Normal file
175
week1/community-contributions/fernando/week1 EXERCISE.ipynb
Normal file
@@ -0,0 +1,175 @@
|
|||||||
|
{
|
||||||
|
"cells": [
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"id": "fe12c203-e6a6-452c-a655-afb8a03a4ff5",
|
||||||
|
"metadata": {},
|
||||||
|
"source": [
|
||||||
|
"# End of week 1 exercise\n",
|
||||||
|
"\n",
|
||||||
|
"To demonstrate your familiarity with OpenAI API, and also Ollama, build a tool that takes a technical question, \n",
|
||||||
|
"and responds with an explanation. This is a tool that you will be able to use yourself during the course!"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"id": "c1070317-3ed9-4659-abe3-828943230e03",
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"# imports\n",
|
||||||
|
"import os\n",
|
||||||
|
"from openai import OpenAI\n",
|
||||||
|
"from dotenv import load_dotenv"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"id": "4a456906-915a-4bfd-bb9d-57e505c5093f",
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"# constants\n",
|
||||||
|
"MODEL_GPT = 'gpt-4o-mini'\n",
|
||||||
|
"MODEL_LLAMA = 'llama3.2'"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"id": "a8d7923c-5f28-4c30-8556-342d7c8497c1",
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"# set up environment\n",
|
||||||
|
"system_prompt = \"\"\"\n",
|
||||||
|
"You are a technical expert of AI and LLMs.\n",
|
||||||
|
"\"\"\"\n",
|
||||||
|
"\n",
|
||||||
|
"user_prompt_prefix = \"\"\"\n",
|
||||||
|
"Provide deep explanations of the provided text.\n",
|
||||||
|
"\"\"\"\n",
|
||||||
|
"\n",
|
||||||
|
"user_prompt = \"\"\"\n",
|
||||||
|
"Explain the provided text.\n",
|
||||||
|
"\"\"\"\n",
|
||||||
|
"client = OpenAI()\n"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"id": "3f0d0137-52b0-47a8-81a8-11a90a010798",
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"# here is the question; type over this to ask something new\n",
|
||||||
|
"\n",
|
||||||
|
"question = \"\"\"\n",
|
||||||
|
"Ollama does have an OpenAI compatible endpoint, but Gemini doesn't?\n",
|
||||||
|
"\"\"\""
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"# Get gpt-4o-mini to answer, with streaming\n",
|
||||||
|
"def messages_for(question):\n",
|
||||||
|
" return [\n",
|
||||||
|
" {\"role\": \"system\", \"content\": system_prompt},\n",
|
||||||
|
" {\"role\": \"user\", \"content\": user_prompt_prefix + question}\n",
|
||||||
|
" ]\n",
|
||||||
|
"\n",
|
||||||
|
"def run_model_streaming(model_name, question):\n",
|
||||||
|
" stream = client.chat.completions.create(\n",
|
||||||
|
" model=model_name,\n",
|
||||||
|
" messages=messages_for(question),\n",
|
||||||
|
" stream=True\n",
|
||||||
|
" )\n",
|
||||||
|
" for chunk in stream:\n",
|
||||||
|
" content = chunk.choices[0].delta.content\n",
|
||||||
|
" if content:\n",
|
||||||
|
" print(content, end=\"\", flush=True)\n",
|
||||||
|
"\n",
|
||||||
|
"run_model_streaming(MODEL_GPT, question)"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"id": "8f7c8ea8-4082-4ad0-8751-3301adcf6538",
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"# Get Llama 3.2 to answer\n",
|
||||||
|
"# imports\n",
|
||||||
|
"import os\n",
|
||||||
|
"from openai import OpenAI\n",
|
||||||
|
"from dotenv import load_dotenv\n",
|
||||||
|
"\n",
|
||||||
|
"# set up environment\n",
|
||||||
|
"client = OpenAI(\n",
|
||||||
|
" base_url=os.getenv(\"OPENAI_BASE_URL\", \"http://localhost:11434/v1\"),\n",
|
||||||
|
" api_key=os.getenv(\"OPENAI_API_KEY\", \"ollama\")\n",
|
||||||
|
")\n",
|
||||||
|
"\n",
|
||||||
|
"system_prompt = \"\"\"\n",
|
||||||
|
"You are a technical expert of AI and LLMs.\n",
|
||||||
|
"\"\"\"\n",
|
||||||
|
"\n",
|
||||||
|
"user_prompt_prefix = \"\"\"\n",
|
||||||
|
"Provide deep explanations of the provided text.\n",
|
||||||
|
"\"\"\"\n",
|
||||||
|
"\n",
|
||||||
|
"# question\n",
|
||||||
|
"question = \"\"\"\n",
|
||||||
|
"Ollama does have an OpenAI compatible endpoint, but Gemini doesn't?\n",
|
||||||
|
"\"\"\"\n",
|
||||||
|
"\n",
|
||||||
|
"# message\n",
|
||||||
|
"def messages_for(question):\n",
|
||||||
|
" return [\n",
|
||||||
|
" {\"role\": \"system\", \"content\": system_prompt},\n",
|
||||||
|
" {\"role\": \"user\", \"content\": user_prompt_prefix + question}\n",
|
||||||
|
" ]\n",
|
||||||
|
"\n",
|
||||||
|
"# response\n",
|
||||||
|
"def run_model(model_name, question):\n",
|
||||||
|
" response = client.chat.completions.create(\n",
|
||||||
|
" model=model_name,\n",
|
||||||
|
" messages=messages_for(question)\n",
|
||||||
|
" )\n",
|
||||||
|
" return response.choices[0].message.content\n",
|
||||||
|
"\n",
|
||||||
|
"# run and print result\n",
|
||||||
|
"print(run_model(MODEL_LLAMA, question))\n"
|
||||||
|
]
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"metadata": {
|
||||||
|
"kernelspec": {
|
||||||
|
"display_name": ".venv",
|
||||||
|
"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": "3.12.12"
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"nbformat": 4,
|
||||||
|
"nbformat_minor": 5
|
||||||
|
}
|
||||||
Reference in New Issue
Block a user