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.
127 lines
4.2 KiB
127 lines
4.2 KiB
{ |
|
"cells": [ |
|
{ |
|
"cell_type": "code", |
|
"execution_count": null, |
|
"id": "0ee39d65-f27d-416d-8b46-43d15aebe752", |
|
"metadata": {}, |
|
"outputs": [], |
|
"source": [ |
|
"# Below is a sample for email reviewer using Bahasa Indonesia. " |
|
] |
|
}, |
|
{ |
|
"cell_type": "code", |
|
"execution_count": null, |
|
"id": "f9fd62af-9b14-490b-8d0b-990da96101bf", |
|
"metadata": {}, |
|
"outputs": [], |
|
"source": [ |
|
"# Step 1: Create your prompts\n", |
|
"\n", |
|
"system_prompt = \"Anda adalah seorang Asisten untuk menganalisa email berdasarkan user prompt yang nanti akan diberikan. Summarize the email and give me a tone about that email\"\n", |
|
"user_prompt = \"\"\"\n", |
|
" Subject: Permintaan Pertemuan\n", |
|
"\n", |
|
"Yang terhormat Bapak Rijal,\n", |
|
"\n", |
|
"Saya ingin meminta waktu Anda untuk membahas Generative AI untuk bisnis. Apakah Anda tersedia pada besok pukul 19:00? \n", |
|
"Jika tidak, mohon beri tahu waktu yang lebih sesuai bagi Anda.\n", |
|
"\n", |
|
"Terima kasih atas perhatian Anda.\n", |
|
"\n", |
|
"Salam,\n", |
|
"\n", |
|
"Mentari\n", |
|
"\"\"\"\n", |
|
"\n", |
|
"# Step 2: Make the messages list\n", |
|
"\n", |
|
"messages = [\n", |
|
" {\"role\": \"system\", \"content\": system_prompt},\n", |
|
" {\"role\": \"user\", \"content\": user_prompt}\n", |
|
" ] # fill this in\n", |
|
"\n", |
|
"# Step 3: Call OpenAI\n", |
|
"\n", |
|
"response = openai.chat.completions.create(\n", |
|
" model = \"gpt-4o-mini\",\n", |
|
" messages = messages\n", |
|
" )\n", |
|
"\n", |
|
"# Step 4: print the result\n", |
|
"\n", |
|
"print(response.choices[0].message.content)" |
|
] |
|
}, |
|
{ |
|
"cell_type": "code", |
|
"execution_count": null, |
|
"id": "d10208fa-02d8-41a0-b9bb-0bf30f237f25", |
|
"metadata": {}, |
|
"outputs": [], |
|
"source": [ |
|
"# Step 1: Create your prompts\n", |
|
"\n", |
|
"system_prompt = \"Anda adalah seorang Asisten untuk menganalisa email berdasarkan user prompt yang nanti akan diberikan. Summarize the email and give me a tone about that email\"\n", |
|
"user_prompt = \"\"\"\n", |
|
" Subject: Feedback terkait Bapak\n", |
|
"\n", |
|
"Yang terhormat Bapak Rijal,\n", |
|
"\n", |
|
"Saya ingin memberikan sedikit feedback untuk BBapak.\n", |
|
"\n", |
|
"Kemampuan Anda dalam memimpin tim ini mampu membawa saya dan rekan lainnya untuk mengerahkan semua kemampuan saya agar jadi lebih baik.\n", |
|
"Selama ini saya cukup senang bekerja dengan Anda karena memberikan saya peluang untuk mencoba banyak hal baru. Tapi ada beberapa kekhawatiran yang mau saya sampaikan, terutama terkait target yang perlu dicapai oleh tim. Saya pikir melihat performa ke belakang, target yang ditentukan harus lebih realistis lagi.\n", |
|
"Saya beruntung bisa berkesempatan bekerja dengan Anda sehingga banyak ilmu yang saya dapat. Kira-kira untuk ke depannya, hal apa lagi yang bisa tim ini tingkatkan agar kita bisa mencapai target yang lebih baik?\n", |
|
"Selama ini, banyak terjadi miskomunikasi dalam pekerjaan. Dan menurut saya salah satunya karena arahan yang Anda berikan kurang jelas dan kurang ditangkap sepenuhnya oleh anggota yang lain. Saya dan tim berharap ke depan bisa mendapatkan arahan yang lebih jelas dan satu arah.\n", |
|
"\n", |
|
"Terima kasih atas perhatian Anda.\n", |
|
"\n", |
|
"Salam,\n", |
|
"\n", |
|
"Mentari\n", |
|
"\"\"\"\n", |
|
"\n", |
|
"# Step 2: Make the messages list\n", |
|
"\n", |
|
"messages = [\n", |
|
" {\"role\": \"system\", \"content\": system_prompt},\n", |
|
" {\"role\": \"user\", \"content\": user_prompt}\n", |
|
" ] # fill this in\n", |
|
"\n", |
|
"# Step 3: Call OpenAI\n", |
|
"\n", |
|
"response = openai.chat.completions.create(\n", |
|
" model = \"gpt-4o-mini\",\n", |
|
" messages = messages\n", |
|
" )\n", |
|
"\n", |
|
"# Step 4: print the result\n", |
|
"\n", |
|
"print(response.choices[0].message.content)" |
|
] |
|
} |
|
], |
|
"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 |
|
}
|
|
|