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{ |
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"cells": [ |
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{ |
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"cell_type": "markdown", |
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"id": "fe12c203-e6a6-452c-a655-afb8a03a4ff5", |
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"metadata": {}, |
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"source": [ |
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"# End of week 1 exercise Solution Ollama with streaming\n", |
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"\n", |
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"A tool that takes a technical question, and responds with an explanation." |
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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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"\n", |
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"import ollama\n", |
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"import requests\n", |
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"from IPython.display import Markdown, display" |
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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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"\n", |
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"MODEL_LLAMA = 'llama3.2'\n", |
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"MODEL_LLAMA1b = \"llama3.2:1b\"" |
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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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"# Environment\n", |
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"\n", |
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"system_prompt = \"\"\"\n", |
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"You are an assistant that takes a technical question and respond with an explanation.\n", |
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"\"\"\"\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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"question2 = \"\"\"\n", |
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"What is the purpose of using yield from in the following code, and how does it differ from a standard for loop with yield?\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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"user_prompt = \"Answer these two questions in detail please, Question1:\" + question + \"Question2:\" + question2\n", |
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"\n", |
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"def message():\n", |
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" return [\n", |
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" {\"role\": \"system\", \"content\": system_prompt},\n", |
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" {\"role\": \"user\", \"content\": user_prompt}\n", |
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" ]" |
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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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"# Llama 3.2 answer, with streaming\n", |
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"\n", |
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"def llama():\n", |
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" response = ollama.chat(\n", |
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" model = MODEL_LLAMA,\n", |
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" messages = message(),\n", |
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" stream =True\n", |
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" )\n", |
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" full_response = \"\"\n", |
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" display_handle = display(Markdown(\"\"), display_id=True)\n", |
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" for chunk in response:\n", |
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" content = chunk.get(\"message\", {}).get(\"content\", \"\")\n", |
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" if content:\n", |
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" full_response += content\n", |
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" display_handle.update(Markdown(full_response))\n", |
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"llama()" |
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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": "342a470c-9aab-4051-ad21-514dceec76eb", |
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"metadata": {}, |
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"outputs": [], |
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"source": [ |
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"# Llama 3.2:1b answer\n", |
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"\n", |
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"def llama():\n", |
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" response = ollama.chat(\n", |
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" model = MODEL_LLAMA1b,\n", |
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" messages = message()\n", |
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" )\n", |
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" return display(Markdown(response['message']['content']))\n", |
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"\n", |
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"llama()" |
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] |
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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": "3.10.7" |
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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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