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Module 9 - GenAI (LLMs and Prompt Engineering)/4. Google Gemini Walkthrough/Untitled.ipynb

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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 2,
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"id": "d51ed763-72b9-4f29-b10e-b75c537597c9",
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"metadata": {},
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"outputs": [],
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"source": [
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"# ! pip install google-generativeai"
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]
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},
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{
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"cell_type": "markdown",
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"id": "9d1d7b5d-b943-4bab-bbbe-8a176fd5130e",
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"metadata": {},
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"source": [
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"## **Importing Google Gemini AI**"
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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": "dfb7d1b8-f430-4f9b-b2a4-417a8db6313c",
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"metadata": {},
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"outputs": [],
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"source": [
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"import google.generativeai as genai"
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]
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},
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{
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"cell_type": "markdown",
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"id": "b3e0b31b-e2db-43e7-9999-347e3c441724",
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"metadata": {},
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"source": [
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"## **Setting the API Key**"
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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": 4,
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"id": "0ad6eea9-585d-427f-aa76-da4d26111804",
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"metadata": {},
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"outputs": [],
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"source": [
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"f = open(\"keys/.gemini.txt\")\n",
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"key = f.read()\n",
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"\n",
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"genai.configure(api_key=key)"
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]
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},
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{
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"cell_type": "markdown",
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"id": "991360dd-a618-479a-904d-5e07661e2697",
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"metadata": {},
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"source": [
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"## **Available Models**"
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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": 6,
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"id": "672b0037-b730-4955-9402-bbecf0f27fe1",
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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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"models/gemini-1.0-pro\n",
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"models/gemini-1.0-pro-001\n",
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"models/gemini-1.0-pro-latest\n",
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"models/gemini-1.0-pro-vision-latest\n",
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"models/gemini-1.5-pro-latest\n",
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"models/gemini-pro\n",
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"models/gemini-pro-vision\n"
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]
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}
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],
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"source": [
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"for m in genai.list_models():\n",
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" if 'generateContent' in m.supported_generation_methods:\n",
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" print(m.name)"
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]
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},
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{
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"cell_type": "markdown",
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"id": "7ef743af-5075-469a-9126-200e13439f7c",
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"metadata": {},
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"source": [
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"## **Prompting the Gemini Model**"
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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": "74ced0d0-98ef-48a5-bb03-8372a4576604",
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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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"planet.\n"
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]
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}
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],
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"source": [
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"model = genai.GenerativeModel(model_name=\"gemini-pro\")\n",
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"\n",
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"user_prompt = \"\"\"Complete the following:\n",
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" In our solar system, Earth is a \"\"\"\n",
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"\n",
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"response = model.generate_content(user_prompt)\n",
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"\n",
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"print(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": 8,
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"id": "ab0e6f5b-63c6-4d7d-a488-ed22c6344a77",
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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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"In our solar system, Earth is a terrestrial or rocky planet, composed primarily of metals and minerals. It is the third planet from the Sun, residing in the inner solar system.\n"
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]
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}
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],
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"source": [
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"model = genai.GenerativeModel(model_name=\"gemini-pro\")\n",
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"\n",
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"user_prompt = \"\"\"Generate some factual information to complete the following in 2-3 lines:\n",
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" In our solar system, Earth is a \"\"\"\n",
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"\n",
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"response = model.generate_content(user_prompt)\n",
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"\n",
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"print(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": "27c53a90-0a98-4404-87b2-1d17e5bca01f",
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"metadata": {},
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"source": [
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"## **Converstation AI using Gemini AI**"
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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": "513a14c4-0211-473c-80d8-90a918376cac",
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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": "3.9.13"
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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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