378 lines
11 KiB
Plaintext
378 lines
11 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "75e2ef28-594f-4c18-9d22-c6b8cd40ead2",
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"metadata": {},
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"source": [
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"# Day 3 - Conversational AI - aka Chatbot!"
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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": 1,
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"id": "70e39cd8-ec79-4e3e-9c26-5659d42d0861",
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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 os\n",
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"import ollama\n",
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"import gradio as gr"
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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": 2,
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"id": "6541d58e-2297-4de1-b1f7-77da1b98b8bb",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Initialize\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": 3,
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"id": "e16839b5-c03b-4d9d-add6-87a0f6f37575",
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"metadata": {},
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"outputs": [],
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"source": [
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"system_message = \"You are a helpful assistant\""
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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": 5,
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"id": "1eacc8a4-4b48-4358-9e06-ce0020041bc1",
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"metadata": {},
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"outputs": [],
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"source": [
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"\n",
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"\n",
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"def chat(message, history):\n",
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" messages = [{\"role\": \"system\", \"content\": system_message}] + history + [{\"role\": \"user\", \"content\": message}]\n",
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"\n",
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" print(\"History is:\")\n",
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" print(history)\n",
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" print(\"And messages is:\")\n",
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" print(messages)\n",
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"\n",
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" stream = ollama.chat(model=MODEL_LLAMA, messages=messages, stream=True)\n",
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"\n",
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" response_text = \"\"\n",
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" for chunk in stream:\n",
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" response_text += chunk['message']['content']\n",
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" yield response_text"
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]
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},
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{
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"cell_type": "markdown",
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"id": "1334422a-808f-4147-9c4c-57d63d9780d0",
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"metadata": {},
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"source": [
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"## And then enter Gradio's magic!"
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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": 7,
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"id": "0866ca56-100a-44ab-8bd0-1568feaf6bf2",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"* Running on local URL: http://127.0.0.1:7861\n",
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"* Running on public URL: https://6539f61952f430fa2d.gradio.live\n",
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"\n",
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"This share link expires in 72 hours. For free permanent hosting and GPU upgrades, run `gradio deploy` from the terminal in the working directory to deploy to Hugging Face Spaces (https://huggingface.co/spaces)\n"
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]
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},
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{
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"data": {
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"text/html": [
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"<div><iframe src=\"https://6539f61952f430fa2d.gradio.live\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
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],
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"text/plain": [
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"<IPython.core.display.HTML object>"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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},
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{
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"data": {
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"text/plain": []
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},
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"execution_count": 7,
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"metadata": {},
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"output_type": "execute_result"
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},
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"History is:\n",
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"[]\n",
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"And messages is:\n",
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"[{'role': 'system', 'content': 'You are a helpful assistant'}, {'role': 'user', 'content': 'hello'}]\n"
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]
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}
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],
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"source": [
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"gr.ChatInterface(fn=chat, type=\"messages\").launch(share=True)"
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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": 8,
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"id": "1f91b414-8bab-472d-b9c9-3fa51259bdfe",
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"metadata": {
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"editable": true,
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"slideshow": {
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"slide_type": ""
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},
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"tags": []
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},
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"outputs": [],
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"source": [
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"system_message = \"You are a helpful assistant in a clothes store. You should try to gently encourage \\\n",
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"the customer to try items that are on sale. Hats are 60% off, and most other items are 50% off. \\\n",
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"For example, if the customer says 'I'm looking to buy a hat', \\\n",
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"you could reply something like, 'Wonderful - we have lots of hats - including several that are part of our sales event.'\\\n",
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"Encourage the customer to buy hats if they are unsure what to get.\""
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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": 9,
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"id": "4e5be3ec-c26c-42bc-ac16-c39d369883f6",
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"metadata": {},
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"outputs": [],
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"source": [
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"def chat(message, history):\n",
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" messages = [{\"role\": \"system\", \"content\": system_message}] + history + [{\"role\": \"user\", \"content\": message}]\n",
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"\n",
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"\n",
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" stream = ollama.chat(model=MODEL_LLAMA, messages=messages, stream=True)\n",
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"\n",
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" response_text = \"\"\n",
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" for chunk in stream:\n",
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" response_text += chunk['message']['content']\n",
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" yield response_text"
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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": 10,
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"id": "413e9e4e-7836-43ac-a0c3-e1ab5ed6b136",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"* Running on local URL: http://127.0.0.1:7862\n",
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"* Running on public URL: https://79f09af36adcf63688.gradio.live\n",
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"\n",
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"This share link expires in 72 hours. For free permanent hosting and GPU upgrades, run `gradio deploy` from the terminal in the working directory to deploy to Hugging Face Spaces (https://huggingface.co/spaces)\n"
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]
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},
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{
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"data": {
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"text/html": [
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"<div><iframe src=\"https://79f09af36adcf63688.gradio.live\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
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],
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"text/plain": [
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"<IPython.core.display.HTML object>"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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},
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{
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"data": {
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"text/plain": []
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},
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"execution_count": 10,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"gr.ChatInterface(fn=chat, type=\"messages\").launch(share=True)"
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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": 11,
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"id": "d75f0ffa-55c8-4152-b451-945021676837",
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"metadata": {},
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"outputs": [],
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"source": [
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"system_message += \"\\nIf the customer asks for shoes, you should respond that shoes are not on sale today, \\\n",
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"but remind the customer to look at hats!\""
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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": 12,
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"id": "c602a8dd-2df7-4eb7-b539-4e01865a6351",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"* Running on local URL: http://127.0.0.1:7863\n",
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"* Running on public URL: https://30446ba4b8f125e235.gradio.live\n",
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"\n",
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"This share link expires in 72 hours. For free permanent hosting and GPU upgrades, run `gradio deploy` from the terminal in the working directory to deploy to Hugging Face Spaces (https://huggingface.co/spaces)\n"
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]
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},
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{
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"data": {
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"text/html": [
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"<div><iframe src=\"https://30446ba4b8f125e235.gradio.live\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
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],
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"text/plain": [
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"<IPython.core.display.HTML object>"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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},
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{
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"data": {
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"text/plain": []
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},
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"execution_count": 12,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"gr.ChatInterface(fn=chat, type=\"messages\").launch(share=True)"
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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": 13,
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"id": "5b128796-1bea-445d-9e3b-8321ca822257",
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"metadata": {},
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"outputs": [],
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"source": [
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"def chat(message, history):\n",
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"\n",
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" relevant_system_message = system_message\n",
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" if 'belt' in message:\n",
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" relevant_system_message += \" The store does not sell belts; if you are asked for belts, be sure to point out other items on sale.\"\n",
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" \n",
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" messages = [{\"role\": \"system\", \"content\": relevant_system_message}] + history + [{\"role\": \"user\", \"content\": message}]\n",
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"\n",
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"\n",
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" stream = ollama.chat(model=MODEL_LLAMA, messages=messages, stream=True)\n",
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"\n",
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" response_text = \"\"\n",
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" for chunk in stream:\n",
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" response_text += chunk['message']['content']\n",
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" yield response_text"
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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": 15,
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"id": "20570de2-eaad-42cc-a92c-c779d71b48b6",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"* Running on local URL: http://127.0.0.1:7865\n",
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"* Running on public URL: https://3933c80bf256709cf9.gradio.live\n",
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"\n",
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"This share link expires in 72 hours. For free permanent hosting and GPU upgrades, run `gradio deploy` from the terminal in the working directory to deploy to Hugging Face Spaces (https://huggingface.co/spaces)\n"
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]
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},
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{
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"data": {
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"text/html": [
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"<div><iframe src=\"https://3933c80bf256709cf9.gradio.live\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
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],
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"text/plain": [
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"<IPython.core.display.HTML object>"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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},
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{
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"data": {
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"text/plain": []
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},
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"execution_count": 15,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"gr.ChatInterface(fn=chat, type=\"messages\").launch(share=True)"
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]
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},
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{
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"cell_type": "markdown",
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"id": "82a57ee0-b945-48a7-a024-01b56a5d4b3e",
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"metadata": {},
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"source": [
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"<table style=\"margin: 0; text-align: left;\">\n",
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" <tr>\n",
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" <td style=\"width: 150px; height: 150px; vertical-align: middle;\">\n",
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" <img src=\"../business.jpg\" width=\"150\" height=\"150\" style=\"display: block;\" />\n",
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" </td>\n",
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" <td>\n",
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" <h2 style=\"color:#181;\">Business Applications</h2>\n",
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" <span style=\"color:#181;\">Conversational Assistants are of course a hugely common use case for Gen AI, and the latest frontier models are remarkably good at nuanced conversation. And Gradio makes it easy to have a user interface. Another crucial skill we covered is how to use prompting to provide context, information and examples.\n",
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"<br/><br/>\n",
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"Consider how you could apply an AI Assistant to your business, and make yourself a prototype. Use the system prompt to give context on your business, and set the tone for the LLM.</span>\n",
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" </td>\n",
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" </tr>\n",
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"</table>"
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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": "6dfb9e21-df67-4c2b-b952-5e7e7961b03d",
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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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