From the uDemy course on LLM engineering.
https://www.udemy.com/course/llm-engineering-master-ai-and-large-language-models
You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
156 lines
5.1 KiB
156 lines
5.1 KiB
{ |
|
"cells": [ |
|
{ |
|
"cell_type": "code", |
|
"execution_count": null, |
|
"id": "1a69176d-95f0-4d9d-b3d2-98e8c46efe29", |
|
"metadata": {}, |
|
"outputs": [], |
|
"source": [ |
|
"import os\n", |
|
"import time\n", |
|
"import ollama\n", |
|
"from dotenv import load_dotenv\n", |
|
"import requests\n", |
|
"from bs4 import BeautifulSoup\n", |
|
"from IPython.display import Markdown, display, update_display\n", |
|
"from openai import OpenAI\n", |
|
"\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", |
|
"MODEL_GPT = 'gpt-4o-mini'\n", |
|
"MODEL_LLAMA = 'llama3.2'\n", |
|
"\n", |
|
"load_dotenv(override=True)\n", |
|
"api_key = os.getenv('OPENAI_API_KEY')\n", |
|
"\n", |
|
"openai = OpenAI()" |
|
] |
|
}, |
|
{ |
|
"cell_type": "code", |
|
"execution_count": null, |
|
"id": "7287074c-d2d6-4dee-9e54-b94c2a182fb2", |
|
"metadata": {}, |
|
"outputs": [], |
|
"source": [ |
|
"#First, choose your poison.\n", |
|
"print(\"Hi, I'm your code assistant.\\n\")\n", |
|
"\n", |
|
"chosen_model = input(\"Would you like Chat GPT or Ollama to answer your question? (c) / (o):\\n\").strip()\n", |
|
"\n", |
|
"chosen_model = \"o\"\n", |
|
"\n", |
|
"if(chosen_model.strip() in [\"c\", \"C\"]):\n", |
|
" print(\"You chose Chat GPT.\")\n", |
|
" chosen_model = \"c\"\n", |
|
"elif(chosen_model.strip() in [\"o\", \"O\", \"0\"]):\n", |
|
" print(\"You chose Ollama.\")\n", |
|
"else:\n", |
|
" print(\"I didn't understand your input. We'll go on with Ollama.\\n\")\n", |
|
"\n", |
|
"question = input(\"What is your question regarding coding or LLMs?\\n\").strip()\n" |
|
] |
|
}, |
|
{ |
|
"cell_type": "code", |
|
"execution_count": null, |
|
"id": "fea154e9-b07e-42fa-b3fb-4085b11a82df", |
|
"metadata": {}, |
|
"outputs": [], |
|
"source": [ |
|
"#Alternative without i/o\n", |
|
"chosen_model = \"o\"\n", |
|
"question = \"Is Python indentation-sensitive?\"" |
|
] |
|
}, |
|
{ |
|
"cell_type": "code", |
|
"execution_count": null, |
|
"id": "1fb48035-2e4a-4271-adb2-43bfb4a04081", |
|
"metadata": {}, |
|
"outputs": [], |
|
"source": [ |
|
"assistant_system_prompt = \"You are the worlds most powerful coding co-pilot and advisor. You will be asked questions about coding, LLMs, and \\\n", |
|
"similar topics. You answer the questions in a friendly, helpful, and succinct way. In the unlikely event that you're asked a question that has \\\n", |
|
"no discernible bearing on coding or LLMs, ask the user for clarification and point out that you're programmed to answer questions concerning \\\n", |
|
"AI, large language models, and coding in general.\\nFormat your answer in Markdown.\"" |
|
] |
|
}, |
|
{ |
|
"cell_type": "code", |
|
"execution_count": null, |
|
"id": "eadbbef9-9bae-447b-9c8b-102cbb4b5345", |
|
"metadata": {}, |
|
"outputs": [], |
|
"source": [ |
|
"def get_assistant_advice(chosen_model, question):\n", |
|
" if chosen_model == \"o\":\n", |
|
" stream = ollama.chat(\n", |
|
" model=MODEL_LLAMA,\n", |
|
" messages=[\n", |
|
" {\"role\": \"system\", \"content\": assistant_system_prompt},\n", |
|
" {\"role\": \"user\", \"content\": question}\n", |
|
" ],\n", |
|
" stream=True\n", |
|
" )\n", |
|
" \n", |
|
" response = \"\"\n", |
|
" display_handle = display(Markdown(\"\"), display_id=True)\n", |
|
" for chunk in stream:\n", |
|
" response += chunk.message.content or ''\n", |
|
" response = response.replace(\"```\",\"\").replace(\"markdown\", \"\")\n", |
|
" update_display(Markdown(response), display_id=display_handle.display_id)\n", |
|
" else:\n", |
|
" stream = openai.chat.completions.create(\n", |
|
" model=MODEL_GPT,\n", |
|
" messages=[\n", |
|
" {\"role\": \"system\", \"content\": assistant_system_prompt},\n", |
|
" {\"role\": \"user\", \"content\": question}\n", |
|
" ],\n", |
|
" stream=True\n", |
|
" )\n", |
|
" \n", |
|
" response = \"\"\n", |
|
" display_handle = display(Markdown(\"\"), display_id=True)\n", |
|
" for chunk in stream:\n", |
|
" response += chunk.choices[0].delta.content or ''\n", |
|
" response = response.replace(\"```\",\"\").replace(\"markdown\", \"\")\n", |
|
" update_display(Markdown(response), display_id=display_handle.display_id)" |
|
] |
|
}, |
|
{ |
|
"cell_type": "code", |
|
"execution_count": null, |
|
"id": "c1bb5437-55f5-47d5-b9f8-3d90c183180e", |
|
"metadata": {}, |
|
"outputs": [], |
|
"source": [ |
|
"get_assistant_advice(chosen_model, question)" |
|
] |
|
} |
|
], |
|
"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 |
|
}
|
|
|