wehub-resource-sync
656 lines
22 KiB
Plaintext
656 lines
22 KiB
Plaintext
{
|
|
"cells": [
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"id": "ijGzTHJJUCPY"
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"# Copyright 2024 Google LLC\n",
|
|
"#\n",
|
|
"# Licensed under the Apache License, Version 2.0 (the \"License\");\n",
|
|
"# you may not use this file except in compliance with the License.\n",
|
|
"# You may obtain a copy of the License at\n",
|
|
"#\n",
|
|
"# https://www.apache.org/licenses/LICENSE-2.0\n",
|
|
"#\n",
|
|
"# Unless required by applicable law or agreed to in writing, software\n",
|
|
"# distributed under the License is distributed on an \"AS IS\" BASIS,\n",
|
|
"# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
|
|
"# See the License for the specific language governing permissions and\n",
|
|
"# limitations under the License."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"id": "VEqbX8OhE8y9"
|
|
},
|
|
"source": [
|
|
"# Getting Started with Chat with Gemini\n",
|
|
"\n",
|
|
"<table align=\"left\">\n",
|
|
" <td style=\"text-align: center\">\n",
|
|
" <a href=\"https://colab.research.google.com/github/GoogleCloudPlatform/generative-ai/blob/main/gemini/getting-started/intro_gemini_chat.ipynb\">\n",
|
|
" <img width=\"32px\" src=\"https://www.gstatic.com/pantheon/images/bigquery/welcome_page/colab-logo.svg\" alt=\"Google Colaboratory logo\"><br> Open in Colab\n",
|
|
" </a>\n",
|
|
" </td>\n",
|
|
" <td style=\"text-align: center\">\n",
|
|
" <a href=\"https://console.cloud.google.com/agent-platform/colab/import/https:%2F%2Fraw.githubusercontent.com%2FGoogleCloudPlatform%2Fgenerative-ai%2Fmain%2Fgemini%2Fgetting-started%2Fintro_gemini_chat.ipynb\">\n",
|
|
" <img width=\"32px\" src=\"https://lh3.googleusercontent.com/JmcxdQi-qOpctIvWKgPtrzZdJJK-J3sWE1RsfjZNwshCFgE_9fULcNpuXYTilIR2hjwN\" alt=\"Google Cloud Colab Enterprise logo\"><br> Open in Colab Enterprise\n",
|
|
" </a>\n",
|
|
" </td>\n",
|
|
" <td style=\"text-align: center\">\n",
|
|
" <a href=\"https://console.cloud.google.com/agent-platform/workbench/instances?download_url=https://raw.githubusercontent.com/GoogleCloudPlatform/generative-ai/main/gemini/getting-started/intro_gemini_chat.ipynb\">\n",
|
|
" <img width=\"32px\" src=\"https://storage.googleapis.com/github-repo/workbench-icon.svg\" alt=\"Workbench logo\"><br> Open in Workbench\n",
|
|
" </a>\n",
|
|
" </td>\n",
|
|
" <td style=\"text-align: center\">\n",
|
|
" <a href=\"https://github.com/GoogleCloudPlatform/generative-ai/blob/main/gemini/getting-started/intro_gemini_chat.ipynb\">\n",
|
|
" <img width=\"32px\" src=\"https://raw.githubusercontent.com/primer/octicons/refs/heads/main/icons/mark-github-24.svg\" alt=\"GitHub logo\"><br> View on GitHub\n",
|
|
" </a>\n",
|
|
" </td>\n",
|
|
"</table>\n",
|
|
"\n",
|
|
"<div style=\"clear: both;\"></div>\n",
|
|
"\n",
|
|
"<p>\n",
|
|
"<b>Share to:</b>\n",
|
|
"\n",
|
|
"<a href=\"https://www.linkedin.com/sharing/share-offsite/?url=https%3A//github.com/GoogleCloudPlatform/generative-ai/blob/main/gemini/getting-started/intro_gemini_chat.ipynb\" target=\"_blank\">\n",
|
|
" <img width=\"20px\" src=\"https://upload.wikimedia.org/wikipedia/commons/8/81/LinkedIn_icon.svg\" alt=\"LinkedIn logo\">\n",
|
|
"</a>\n",
|
|
"\n",
|
|
"<a href=\"https://bsky.app/intent/compose?text=https%3A//github.com/GoogleCloudPlatform/generative-ai/blob/main/gemini/getting-started/intro_gemini_chat.ipynb\" target=\"_blank\">\n",
|
|
" <img width=\"20px\" src=\"https://upload.wikimedia.org/wikipedia/commons/7/7a/Bluesky_Logo.svg\" alt=\"Bluesky logo\">\n",
|
|
"</a>\n",
|
|
"\n",
|
|
"<a href=\"https://twitter.com/intent/tweet?url=https%3A//github.com/GoogleCloudPlatform/generative-ai/blob/main/gemini/getting-started/intro_gemini_chat.ipynb\" target=\"_blank\">\n",
|
|
" <img width=\"20px\" src=\"https://upload.wikimedia.org/wikipedia/commons/5/5a/X_icon_2.svg\" alt=\"X logo\">\n",
|
|
"</a>\n",
|
|
"\n",
|
|
"<a href=\"https://reddit.com/submit?url=https%3A//github.com/GoogleCloudPlatform/generative-ai/blob/main/gemini/getting-started/intro_gemini_chat.ipynb\" target=\"_blank\">\n",
|
|
" <img width=\"20px\" src=\"https://redditinc.com/hubfs/Reddit%20Inc/Brand/Reddit_Logo.png\" alt=\"Reddit logo\">\n",
|
|
"</a>\n",
|
|
"\n",
|
|
"<a href=\"https://www.facebook.com/sharer/sharer.php?u=https%3A//github.com/GoogleCloudPlatform/generative-ai/blob/main/gemini/getting-started/intro_gemini_chat.ipynb\" target=\"_blank\">\n",
|
|
" <img width=\"20px\" src=\"https://upload.wikimedia.org/wikipedia/commons/5/51/Facebook_f_logo_%282019%29.svg\" alt=\"Facebook logo\">\n",
|
|
"</a>\n",
|
|
"</p>"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"id": "f95c904716cd"
|
|
},
|
|
"source": [
|
|
"| Authors |\n",
|
|
"| --- |\n",
|
|
"| [Eric Dong](https://github.com/gericdong), [Holt Skinner](https://github.com/holtskinner) |"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"id": "CkHPv2myT2cx"
|
|
},
|
|
"source": [
|
|
"## Overview\n",
|
|
"\n",
|
|
"**YouTube Video: Introduction to Gemini on Vertex AI**\n",
|
|
"\n",
|
|
"<a href=\"https://www.youtube.com/watch?v=YfiLUpNejpE&list=PLIivdWyY5sqJio2yeg1dlfILOUO2FoFRx\" target=\"_blank\">\n",
|
|
" <img src=\"https://img.youtube.com/vi/YfiLUpNejpE/maxresdefault.jpg\" alt=\"Introduction to Gemini on Vertex AI\" width=\"500\">\n",
|
|
"</a>\n",
|
|
"\n",
|
|
"This notebook demonstrates how to send chat prompts to the Gemini model. Gemini supports prompts with multimodal input, including natural language tasks, multi-turn text, images, video, audio, and code generation. It can output text and code.\n",
|
|
"\n",
|
|
"Learn more about [Sending chat prompt requests (Gemini)](https://cloud.google.com/vertex-ai/docs/generative-ai/multimodal/send-chat-prompts-gemini)."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"id": "DrkcqHrrwMAo"
|
|
},
|
|
"source": [
|
|
"### Objectives\n",
|
|
"\n",
|
|
"In this tutorial, you learn how to send chat prompts to the Gemini model.\n",
|
|
"\n",
|
|
"You will complete the following tasks:\n",
|
|
"\n",
|
|
"- Sending chat prompts using Google Gen AI SDK for Python\n",
|
|
"- Sending chat prompts using LangChain"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"id": "C9nEPojogw-g"
|
|
},
|
|
"source": [
|
|
"### Costs\n",
|
|
"This tutorial uses billable components of Google Cloud:\n",
|
|
"\n",
|
|
"- Vertex AI\n",
|
|
"\n",
|
|
"Learn about [Vertex AI pricing](https://cloud.google.com/vertex-ai/pricing) and use the [Pricing Calculator](https://cloud.google.com/products/calculator/) to generate a cost estimate based on your projected usage."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"id": "r11Gu7qNgx1p"
|
|
},
|
|
"source": [
|
|
"## Getting Started"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"id": "No17Cw5hgx12"
|
|
},
|
|
"source": [
|
|
"### Install libraries\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"id": "tFy3H3aPgx12"
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"%pip install --upgrade --quiet google-genai langchain-google-vertexai langchain"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"id": "dmWOrTJ3gx13"
|
|
},
|
|
"source": [
|
|
"### Authenticate your notebook environment (Colab only)\n",
|
|
"\n",
|
|
"If you are running this notebook on Google Colab, run the cell below to authenticate your environment.\n",
|
|
"\n",
|
|
"This step is not required if you are using [Vertex AI Workbench](https://cloud.google.com/vertex-ai-workbench)."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"id": "NyKGtVQjgx13"
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"import sys\n",
|
|
"\n",
|
|
"# Additional authentication is required for Google Colab\n",
|
|
"if \"google.colab\" in sys.modules:\n",
|
|
" # Authenticate user to Google Cloud\n",
|
|
" from google.colab import auth\n",
|
|
"\n",
|
|
" auth.authenticate_user()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"id": "DF4l8DTdWgPY"
|
|
},
|
|
"source": [
|
|
"### Define Google Cloud project information and initialize Vertex AI\n",
|
|
"\n",
|
|
"To get started using Vertex AI, you must have an existing Google Cloud project and [enable the Vertex AI API](https://console.cloud.google.com/flows/enableapi?apiid=aiplatform.googleapis.com).\n",
|
|
"\n",
|
|
"Learn more about [setting up a project and a development environment](https://cloud.google.com/vertex-ai/docs/start/cloud-environment)."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"id": "Nqwi-5ufWp_B"
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"# Use the environment variable if the user doesn't provide Project ID.\n",
|
|
"import os\n",
|
|
"\n",
|
|
"from google import genai\n",
|
|
"\n",
|
|
"# fmt: off\n",
|
|
"PROJECT_ID = \"[your-project-id]\" # @param {type: \"string\", placeholder: \"[your-project-id]\", isTemplate: true}\n",
|
|
"# fmt: on\n",
|
|
"if not PROJECT_ID or PROJECT_ID == \"[your-project-id]\":\n",
|
|
" PROJECT_ID = str(os.environ.get(\"GOOGLE_CLOUD_PROJECT\"))\n",
|
|
"\n",
|
|
"LOCATION = os.environ.get(\"GOOGLE_CLOUD_REGION\", \"global\")\n",
|
|
"\n",
|
|
"client = genai.Client(enterprise=True, project=PROJECT_ID, location=LOCATION)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"id": "jXHfaVS66_01"
|
|
},
|
|
"source": [
|
|
"### Import libraries"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"id": "lslYAvw37JGQ"
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"from IPython.display import Markdown, display\n",
|
|
"from google.genai.types import GenerateContentConfig, ModelContent, UserContent\n",
|
|
"from langchain.chains import ConversationChain\n",
|
|
"from langchain.memory import ConversationBufferMemory\n",
|
|
"from langchain.prompts import (\n",
|
|
" ChatPromptTemplate,\n",
|
|
" HumanMessagePromptTemplate,\n",
|
|
" MessagesPlaceholder,\n",
|
|
" SystemMessagePromptTemplate,\n",
|
|
")\n",
|
|
"from langchain_core.messages import HumanMessage, SystemMessage\n",
|
|
"from langchain_google_vertexai import ChatVertexAI, HarmBlockThreshold, HarmCategory"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"id": "4437b7608c8e"
|
|
},
|
|
"source": [
|
|
"## Sending chat prompts using Gen AI SDK for Python\n",
|
|
"\n",
|
|
"### Load the Gemini model"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"id": "2998506fe6d1"
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"MODEL_ID = \"gemini-3.5-flash\""
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"id": "wl2AZceWjXoy"
|
|
},
|
|
"source": [
|
|
"### Start a chat session\n",
|
|
"\n",
|
|
"You start a stateful chat session and then send chat prompts with configuration parameters including generation configurations and safety settings."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"id": "_vLprtHAjNOO"
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"chat = client.chats.create(\n",
|
|
" model=MODEL_ID,\n",
|
|
" config=GenerateContentConfig(\n",
|
|
" system_instruction=\"You are an astronomer, knowledgeable about the solar system..\"\n",
|
|
" ),\n",
|
|
")\n",
|
|
"\n",
|
|
"response = chat.send_message(\n",
|
|
" \"\"\"How many moons does Mars have? Tell me some fun facts about them.\"\"\"\n",
|
|
")\n",
|
|
"\n",
|
|
"display(Markdown(response.text))"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"id": "V2axT2nKuVzP"
|
|
},
|
|
"source": [
|
|
"You can check out the metadata of the response including the `safety_ratings` and `usage_metadata`."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"id": "ih0v9B1vspiF"
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"print(response)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"id": "ZuHvZevgwdj5"
|
|
},
|
|
"source": [
|
|
"You can retrieve the history of the chat session."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"id": "FYuqKyyktFq7"
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"print(chat.get_history())"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"id": "kiS2CywXxU2y"
|
|
},
|
|
"source": [
|
|
"### Code chat\n",
|
|
"\n",
|
|
"Gemini also supports code generation from a text prompt."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"id": "1lWiPGQ-cDqC"
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"code_chat = client.chats.create(\n",
|
|
" model=MODEL_ID,\n",
|
|
" config=GenerateContentConfig(\n",
|
|
" system_instruction=\"You are an expert software engineer, proficient in Python.\"\n",
|
|
" ),\n",
|
|
")\n",
|
|
"\n",
|
|
"\n",
|
|
"response = code_chat.send_message(\n",
|
|
" \"Write a function that checks if a year is a leap year\"\n",
|
|
")\n",
|
|
"\n",
|
|
"display(Markdown(response.text))"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"id": "kI781aqpy-lH"
|
|
},
|
|
"source": [
|
|
"You can generate unit tests to test the function in this multi-turn chat."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"id": "TGHToON4xyOV"
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"response = code_chat.send_message(\"Write a unit test of the generated function\")\n",
|
|
"\n",
|
|
"display(Markdown(response.text))"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"id": "jeZNScL7Ci2A"
|
|
},
|
|
"source": [
|
|
"### Add chat history\n",
|
|
"\n",
|
|
"You can add chat history to a chat by adding messages from role `user` and `model` alternately. System messages can be set in the first part for the first message."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"id": "JzqUThJv77G9"
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"chat2 = client.chats.create(\n",
|
|
" model=MODEL_ID,\n",
|
|
" history=[\n",
|
|
" UserContent(\n",
|
|
" \"\"\"My name is Ned. You are my personal assistant. My favorite movies are Lord of the Rings and Hobbit.\n",
|
|
" Who do you work for?\n",
|
|
" \"\"\"\n",
|
|
" ),\n",
|
|
" ModelContent(\"I work for Ned.\"),\n",
|
|
" UserContent(\"What do I like?\"),\n",
|
|
" ModelContent(\"Ned likes watching movies.\"),\n",
|
|
" ],\n",
|
|
")\n",
|
|
"\n",
|
|
"response = chat2.send_message(\"Are my favorite movies based on a book series?\")\n",
|
|
"display(Markdown(response.text))"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"id": "G64BrDoxC-K3"
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"response = chat2.send_message(\"When were these books published?\")\n",
|
|
"display(Markdown(response.text))"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"id": "c4e8deb52116"
|
|
},
|
|
"source": [
|
|
"### Multimodal "
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"id": "WFlnwb0u54iN"
|
|
},
|
|
"source": [
|
|
"## Sending chat prompts using LangChain\n",
|
|
"\n",
|
|
"The Gemini API in Vertex AI is integrated with the LangChain Python SDK, making it convenient to build applications on top of Gemini models."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"id": "ga2YnFYPXZgh"
|
|
},
|
|
"source": [
|
|
"### Start a chat session\n",
|
|
"\n",
|
|
"You can start a chat by sending chat prompts to the Gemini 3 model directly. Gemini 3 doesn't support `SystemMessage` at the moment, but `SystemMessage` can be added to the first human message by setting the `convert_system_message_to_human` to `True`."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"id": "s41n0UEwGVZV"
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"system_message = \"You are a helpful assistant who translates English to French.\"\n",
|
|
"human_message = \"Translate this sentence from English to French. I love programming.\"\n",
|
|
"\n",
|
|
"messages = [SystemMessage(content=system_message), HumanMessage(content=human_message)]\n",
|
|
"\n",
|
|
"chat = ChatVertexAI(\n",
|
|
" project=PROJECT_ID,\n",
|
|
" model_name=MODEL_ID,\n",
|
|
" convert_system_message_to_human=True,\n",
|
|
" safety_settings={\n",
|
|
" HarmCategory.HARM_CATEGORY_HATE_SPEECH: HarmBlockThreshold.BLOCK_LOW_AND_ABOVE\n",
|
|
" },\n",
|
|
")\n",
|
|
"\n",
|
|
"result = chat.generate([messages])\n",
|
|
"print(result.generations[0][0].text)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"id": "4VprmGzu4FPO"
|
|
},
|
|
"source": [
|
|
"You can check out the metadata of the generated content."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"id": "hBLFXgzsIJhw"
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"print(result.generations[0][0].generation_info)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"id": "RgYHzIUP4PMo"
|
|
},
|
|
"source": [
|
|
"### Use a chat chain with chat prompt template"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"id": "9vZr5vyrV-eI"
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"system_message = \"You are a helpful assistant who translates English to French.\"\n",
|
|
"human_message = \"Translate this sentence from English to French. I love programming.\"\n",
|
|
"\n",
|
|
"messages = [SystemMessage(content=system_message), HumanMessage(content=human_message)]\n",
|
|
"prompt = ChatPromptTemplate.from_messages(messages)\n",
|
|
"\n",
|
|
"chat = ChatVertexAI(\n",
|
|
" project=PROJECT_ID,\n",
|
|
" model_name=MODEL_ID,\n",
|
|
" convert_system_message_to_human=True,\n",
|
|
" safety_settings={\n",
|
|
" HarmCategory.HARM_CATEGORY_HATE_SPEECH: HarmBlockThreshold.BLOCK_LOW_AND_ABOVE\n",
|
|
" },\n",
|
|
")\n",
|
|
"\n",
|
|
"chain = prompt | chat\n",
|
|
"chain.invoke({})"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"id": "lB50i-JG9RQp"
|
|
},
|
|
"source": [
|
|
"### Use a conversation chain\n",
|
|
"\n",
|
|
"You also can wrap up a chat in `ConversationChain`, which has built-in memory for remembering past user inputs and model outputs."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"id": "UFxQ6AN_5vDQ"
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"model = ChatVertexAI(\n",
|
|
" project=PROJECT_ID,\n",
|
|
" model_name=MODEL_ID,\n",
|
|
" convert_system_message_to_human=True,\n",
|
|
" safety_settings={\n",
|
|
" HarmCategory.HARM_CATEGORY_HATE_SPEECH: HarmBlockThreshold.BLOCK_LOW_AND_ABOVE\n",
|
|
" },\n",
|
|
")\n",
|
|
"\n",
|
|
"prompt = ChatPromptTemplate(\n",
|
|
" messages=[\n",
|
|
" SystemMessagePromptTemplate.from_template(\n",
|
|
" \"You are a helpful assistant who is good at language translation.\"\n",
|
|
" ),\n",
|
|
" MessagesPlaceholder(variable_name=\"history\"),\n",
|
|
" HumanMessagePromptTemplate.from_template(\"{input}\"),\n",
|
|
" ]\n",
|
|
")\n",
|
|
"\n",
|
|
"memory = ConversationBufferMemory(memory_key=\"history\", return_messages=True)\n",
|
|
"conversation = ConversationChain(llm=model, prompt=prompt, verbose=True, memory=memory)\n",
|
|
"\n",
|
|
"conversation.invoke(\n",
|
|
" input=\"Translate this sentence from English to French. I love programming.\"\n",
|
|
")"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"id": "AJMP2JrMDmS-"
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"conversation.invoke(\"Translate it to Spanish\")"
|
|
]
|
|
}
|
|
],
|
|
"metadata": {
|
|
"colab": {
|
|
"name": "intro_gemini_chat.ipynb",
|
|
"toc_visible": true
|
|
},
|
|
"kernelspec": {
|
|
"display_name": "Python 3",
|
|
"name": "python3"
|
|
}
|
|
},
|
|
"nbformat": 4,
|
|
"nbformat_minor": 0
|
|
}
|