From the uDemy course on LLM engineering.
https://www.udemy.com/course/llm-engineering-master-ai-and-large-language-models
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167 lines
5.0 KiB
167 lines
5.0 KiB
{ |
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"metadata": { |
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"colab": { |
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"provenance": [] |
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}, |
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"kernelspec": { |
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"name": "python3", |
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"display_name": "Python 3" |
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"language_info": { |
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"name": "python" |
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} |
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}, |
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"cells": [ |
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{ |
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"cell_type": "markdown", |
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"source": [ |
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"Import libraries as needed & keep your gemini api key ready" |
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], |
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"metadata": { |
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"id": "2UAcHYzT6ikw" |
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} |
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}, |
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{ |
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"cell_type": "code", |
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"source": [ |
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"#!pip install gradio" |
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], |
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"metadata": { |
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"id": "XW0IY4xK6JZ1" |
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}, |
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"execution_count": 14, |
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"outputs": [] |
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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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"metadata": { |
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"id": "dwoPNMMP4ZSh" |
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}, |
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"outputs": [], |
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"source": [ |
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"from google import genai\n", |
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"from google.genai import types\n", |
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"from google.colab import userdata\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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"source": [ |
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"def get_trip_itinerary(budget: int) -> str:\n", |
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" \"\"\"\n", |
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" Returns a trip itinerary based on the given budget.\n", |
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" \"\"\"\n", |
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" itinerary_dict: Dict[int, str] = {\n", |
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" 500: \"Paris: 3-day budget trip covering Eiffel Tower, Louvre, and Seine River Cruise.\",\n", |
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" 1000: \"Tokyo: 5-day adventure covering Shibuya, Akihabara, Mount Fuji day trip.\",\n", |
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" 2000: \"New York: 7-day luxury stay covering Times Square, Broadway show, and helicopter tour.\",\n", |
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" 3000: \"Dubai: 7-day ultra-luxury trip with Burj Khalifa VIP tour, desert safari, and yacht cruise.\",\n", |
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" }\n", |
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"\n", |
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" return itinerary_dict.get(budget, \"No itinerary found for this budget. Try another amount!\")\n" |
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], |
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"metadata": { |
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"id": "cnYD07T24ueV" |
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}, |
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"execution_count": 3, |
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"outputs": [] |
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}, |
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{ |
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"cell_type": "code", |
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"source": [ |
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"from google.genai import types\n", |
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"\n", |
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"config = types.GenerateContentConfig(tools=[get_trip_itinerary])\n", |
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"\n", |
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"from google import genai\n", |
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"\n", |
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"client = genai.Client(api_key=userdata.get('gemini_api'))\n", |
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"\n", |
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"response = client.models.generate_content(\n", |
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" model='gemini-2.0-flash',\n", |
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" config=config,\n", |
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" contents='Based on the user budget suggest trip itinerary'\n", |
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")\n" |
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], |
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"metadata": { |
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"id": "3WRUXvD45VFC" |
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}, |
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"execution_count": 7, |
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"outputs": [] |
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}, |
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{ |
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"cell_type": "code", |
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"source": [ |
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"import gradio as gr\n", |
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"\n", |
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"# Chat function using Gemini\n", |
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"chat = client.chats.create(model='gemini-2.0-flash', config=config)\n", |
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"\n", |
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"def chat_with_ai(user_input: str):\n", |
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" response = chat.send_message(user_input)\n", |
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" return response.text\n", |
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"\n", |
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"# Gradio Chat Interface\n", |
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"demo = gr.Interface(fn=chat_with_ai, inputs=\"text\", outputs=\"text\", title=\"AI Trip Planner\")\n", |
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"\n", |
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"demo.launch()\n" |
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], |
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"metadata": { |
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"colab": { |
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"base_uri": "https://localhost:8080/", |
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"height": 645 |
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}, |
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"id": "5fE700z96DHs", |
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"outputId": "3e35423c-8b2b-4868-8113-00d9d3a7a2ba" |
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}, |
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"execution_count": 13, |
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"outputs": [ |
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{ |
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"output_type": "stream", |
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"name": "stdout", |
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"text": [ |
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"Running Gradio in a Colab notebook requires sharing enabled. Automatically setting `share=True` (you can turn this off by setting `share=False` in `launch()` explicitly).\n", |
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"\n", |
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"Colab notebook detected. To show errors in colab notebook, set debug=True in launch()\n", |
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"* Running on public URL: https://079a23f363400da700.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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"output_type": "display_data", |
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"data": { |
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"text/plain": [ |
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"<IPython.core.display.HTML object>" |
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], |
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"text/html": [ |
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"<div><iframe src=\"https://079a23f363400da700.gradio.live\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>" |
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"metadata": {} |
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}, |
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{ |
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"output_type": "execute_result", |
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"data": { |
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"text/plain": [] |
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"execution_count": 13 |
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}, |
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{ |
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"cell_type": "code", |
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"source": [], |
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"metadata": { |
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"id": "XC9zzq8X5u8m" |
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}, |
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"execution_count": null, |
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"outputs": [] |
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} |
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