219 lines
6.8 KiB
Plaintext
219 lines
6.8 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "31d3c4a4-5442-4074-b812-42d60e0a0c04",
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"metadata": {
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"ExecuteTime": {
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"end_time": "2025-04-26T11:54:29.195103Z",
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"start_time": "2025-04-26T11:54:29.192394Z"
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}
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},
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"outputs": [],
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"source": [
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"# In this example we read a footbal (soccer) game stat and we create a narration about the game as we are running a podcast\n",
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"# use this website as an example: https://understat.com/match/27683"
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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": "cf45e9d5-4913-416c-9880-5be60a96c0e6",
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"metadata": {
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"ExecuteTime": {
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"end_time": "2025-04-26T11:54:30.218768Z",
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"start_time": "2025-04-26T11:54:30.215752Z"
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}
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},
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"outputs": [],
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"source": [
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"import os\n",
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"import requests\n",
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"from dotenv import load_dotenv\n",
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"from IPython.display import Markdown, display\n",
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"from bs4 import BeautifulSoup\n",
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"import 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": "af8fea69-60aa-430c-a16c-8757b487e07a",
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"metadata": {
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"ExecuteTime": {
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"end_time": "2025-04-26T11:54:31.218616Z",
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"start_time": "2025-04-26T11:54:31.214154Z"
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}
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},
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"outputs": [],
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"source": [
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"load_dotenv(override=True)\n",
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"api_key = os.getenv('OPENAI_API_KEY')\n",
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"\n",
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"# Check the key\n",
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"\n",
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"if not api_key:\n",
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" print(\"No API key was found - please head over to the troubleshooting notebook in this folder to identify & fix!\")\n",
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"elif not api_key.startswith(\"sk-proj-\"):\n",
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" print(\n",
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" \"An API key was found, but it doesn't start sk-proj-; please check you're using the right key - see troubleshooting notebook\")\n",
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"elif api_key.strip() != api_key:\n",
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" print(\n",
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" \"An API key was found, but it looks like it might have space or tab characters at the start or end - please remove them - see troubleshooting notebook\")\n",
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"else:\n",
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" print(\"API key found and looks good so far!\")"
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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": "daee94d2-f82b-43f0-95d1-15370eda1bc7",
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"metadata": {
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"ExecuteTime": {
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"end_time": "2025-04-26T11:54:32.216785Z",
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"start_time": "2025-04-26T11:54:32.183600Z"
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}
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},
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"outputs": [],
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"source": [
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"url = \"https://understat.com/match/27683\""
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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": "0712dd1d-b6bc-41c6-84ec-d965f696f7aa",
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"metadata": {
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"ExecuteTime": {
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"end_time": "2025-04-26T11:54:33.025841Z",
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"start_time": "2025-04-26T11:54:33.023289Z"
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}
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},
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"outputs": [],
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"source": [
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"system_prompt = (\"You are a football (soccer) analyst. Yuo are used to read stats of football \\\n",
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" games and extract relevant information. You are asked to be a podcast host and \\\n",
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" you need to create a narration of the game based on the stats you read and based \\\n",
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" on the play by play moves (the one with minutes upfront). You're talking to the \\\n",
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" general audience so try to use a easy language and do not be too much telegraphic\")"
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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": "70c972a6-8af6-4ff2-a338-6d7ba90e2045",
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"metadata": {
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"ExecuteTime": {
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"end_time": "2025-04-26T11:54:33.730097Z",
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"start_time": "2025-04-26T11:54:33.725360Z"
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}
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},
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"outputs": [],
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"source": [
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"# Some websites need you to use proper headers when fetching them:\n",
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"headers = {\n",
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" \"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",
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"}\n",
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"\n",
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"class Website:\n",
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" def __init__(self, url):\n",
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" \"\"\"\n",
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" Create this Website object from the given url using the BeautifulSoup library\n",
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" \"\"\"\n",
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" self.url = url\n",
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" response = requests.get(url, headers=headers)\n",
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" soup = BeautifulSoup(response.content, 'html.parser')\n",
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" self.title = soup.title.string if soup.title else \"No title found\"\n",
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" for irrelevant in soup.body([\"script\", \"style\", \"img\", \"input\"]):\n",
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" irrelevant.decompose()\n",
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" self.text = soup.body.get_text(separator=\"\\n\", strip=True)\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": "4ccc1ba81c76ffb9",
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"metadata": {
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"ExecuteTime": {
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"end_time": "2025-04-26T11:54:40.042357Z",
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"start_time": "2025-04-26T11:54:40.040384Z"
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}
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},
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"outputs": [],
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"source": [
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"def create_user_prompt(game):\n",
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" user_prompt = f\"You are looking at {game.title} football game\"\n",
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" user_prompt += \"\\nThis is the entire webpage of the game \\\n",
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" Please provide a narration of the game in markdown. \\\n",
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" Focus only on what happened on the game and the stats and ignore all the standings and anything else.\\n\\n\"\n",
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" user_prompt += game.text\n",
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" return user_prompt\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": "82b71c1a-895a-48e7-a945-13e615bb0096",
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"metadata": {
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"ExecuteTime": {
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"end_time": "2025-04-26T11:54:41.316244Z",
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"start_time": "2025-04-26T11:54:41.314110Z"
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}
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},
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"outputs": [],
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"source": [
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"# Define messages with system_prompt and user_prompt\n",
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"def messages_for(system_prompt_input, user_prompt_input):\n",
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" return [\n",
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" {\"role\": \"system\", \"content\": system_prompt_input},\n",
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" {\"role\": \"user\", \"content\": user_prompt_input}\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": "854dc42e-2bbd-493b-958f-c20484908300",
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"metadata": {
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"ExecuteTime": {
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"end_time": "2025-04-26T11:54:55.239164Z",
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"start_time": "2025-04-26T11:54:41.987168Z"
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}
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},
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"outputs": [],
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"source": [
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"# And now: call the OpenAI API.\n",
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"game = Website(url)\n",
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"\n",
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"response = ollama.chat(model=\"llama3.2\", messages=messages_for(system_prompt, create_user_prompt(game)))\n",
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"\n",
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"\n",
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"# Response is provided in Markdown and displayed accordingly\n",
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"display(Markdown(response['message']['content']))"
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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": "3.11.12"
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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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