From the uDemy course on LLM engineering.
https://www.udemy.com/course/llm-engineering-master-ai-and-large-language-models
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125 lines
3.0 KiB
125 lines
3.0 KiB
{ |
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"cells": [ |
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{ |
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"cell_type": "markdown", |
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"id": "135ee16c-2741-4ebf-aca9-1d263083b3ce", |
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"metadata": {}, |
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"source": [ |
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"# End of week 1 exercise\n", |
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"\n", |
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"Build a tutor tool by using Ollama." |
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] |
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}, |
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{ |
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"cell_type": "code", |
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"execution_count": null, |
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"id": "c1070317-3ed9-4659-abe3-828943230e03", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"# imports\n", |
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"import ollama\n", |
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"from IPython.display import Markdown, display, clear_output" |
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] |
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}, |
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{ |
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"cell_type": "code", |
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"execution_count": null, |
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"id": "4a456906-915a-4bfd-bb9d-57e505c5093f", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"# constants\n", |
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"MODEL_LLAMA = 'llama3.2'" |
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] |
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}, |
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{ |
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"cell_type": "code", |
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"execution_count": null, |
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"id": "3f0d0137-52b0-47a8-81a8-11a90a010798", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"# here is the question; type over this to ask something new\n", |
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"\n", |
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"question = \"\"\"\n", |
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"Please explain what this code does and why:\n", |
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"yield from {book.get(\"author\") for book in books if book.get(\"author\")}\n", |
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"\"\"\"\n", |
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"\n" |
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] |
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}, |
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{ |
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"cell_type": "code", |
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"execution_count": null, |
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"id": "8f7c8ea8-4082-4ad0-8751-3301adcf6538", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"# Get Llama 3.2 to answer, with streaming\n", |
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"\n", |
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"\n", |
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"messages=[{\"role\":\"user\",\"content\":question}]\n", |
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"\n", |
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"for chunk in ollama.chat(model=MODEL_LLAMA, messages=messages, stream=True):\n", |
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" print(chunk['message']['content'], end='', flush=True)\n", |
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"\n", |
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"\n" |
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] |
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}, |
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{ |
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"cell_type": "code", |
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"execution_count": null, |
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"id": "d1f71014-e780-4d3f-a227-1a7c18158a4c", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"#Alternative answer with streaming in Markdown!\n", |
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"\n", |
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"def stream_response():\n", |
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" messages = [{\"role\": \"user\", \"content\": question}]\n", |
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" \n", |
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" display_markdown = display(Markdown(\"\"), display_id=True)\n", |
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"\n", |
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" response_text = \"\"\n", |
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" for chunk in ollama.chat(model=MODEL_LLAMA, messages=messages, stream=True):\n", |
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" \n", |
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" response_text += chunk['message']['content']\n", |
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" clear_output(wait=True) # Clears previous output\n", |
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" display_markdown.update(Markdown(response_text)) # Updates Markdown dynamically\n", |
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"\n", |
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"# Run the function\n", |
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"stream_response()" |
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] |
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}, |
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{ |
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"cell_type": "code", |
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"execution_count": null, |
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"id": "c38fdd2a-4b09-402c-ba46-999b22b0cb15", |
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"metadata": {}, |
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"outputs": [], |
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"source": [] |
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} |
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], |
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"metadata": { |
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"kernelspec": { |
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"display_name": "Python 3 (ipykernel)", |
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"language": "python", |
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"name": "python3" |
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}, |
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"language_info": { |
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"codemirror_mode": { |
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"name": "ipython", |
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"version": 3 |
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}, |
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"file_extension": ".py", |
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"mimetype": "text/x-python", |
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"name": "python", |
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"nbconvert_exporter": "python", |
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"pygments_lexer": "ipython3", |
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"version": "3.13.2" |
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} |
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}, |
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"nbformat": 4, |
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"nbformat_minor": 5 |
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}
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