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🤖 I have created a release *beep* *boop* --- ## [0.26.0](https://github.com/googleapis/genai-toolbox/compare/v0.25.0...v0.26.0) (2026-01-22) ### ⚠ BREAKING CHANGES * Validate tool naming ([#2305](https://github.com/googleapis/genai-toolbox/issues/2305)) ([5054212](5054212fa4)) * **tools/cloudgda:** Update description and parameter name for cloudgda tool ([#2288](https://github.com/googleapis/genai-toolbox/issues/2288)) ([6b02591](6b02591703)) ### Features * Add new `user-agent-metadata` flag ([#2302](https://github.com/googleapis/genai-toolbox/issues/2302)) ([adc9589](adc9589766)) * Add remaining flag to Toolbox server in MCP registry ([#2272](https://github.com/googleapis/genai-toolbox/issues/2272)) ([5e0999e](5e0999ebf5)) * **embeddingModel:** Add embedding model to MCP handler ([#2310](https://github.com/googleapis/genai-toolbox/issues/2310)) ([e4f60e5](e4f60e5633)) * **sources/bigquery:** Make maximum rows returned from queries configurable ([#2262](https://github.com/googleapis/genai-toolbox/issues/2262)) ([4abf0c3](4abf0c39e7)) * **prebuilt/cloud-sql:** Add create backup tool for Cloud SQL ([#2141](https://github.com/googleapis/genai-toolbox/issues/2141)) ([8e0fb03](8e0fb03483)) * **prebuilt/cloud-sql:** Add restore backup tool for Cloud SQL ([#2171](https://github.com/googleapis/genai-toolbox/issues/2171)) ([00c3e6d](00c3e6d8cb)) * Support combining multiple prebuilt configurations ([#2295](https://github.com/googleapis/genai-toolbox/issues/2295)) ([e535b37](e535b372ea)) * Support MCP specs version 2025-11-25 ([#2303](https://github.com/googleapis/genai-toolbox/issues/2303)) ([4d23a3b](4d23a3bbf2)) * **tools:** Add `valueFromParam` support to Tool config ([#2333](https://github.com/googleapis/genai-toolbox/issues/2333)) ([15101b1](15101b1edb)) ### Bug Fixes * **tools/cloudhealthcare:** Add check for client authorization before retrieving token string ([#2327](https://github.com/googleapis/genai-toolbox/issues/2327)) ([c25a233](c25a2330fe)) --- This PR was generated with [Release Please](https://github.com/googleapis/release-please). See [documentation](https://github.com/googleapis/release-please#release-please). --------- Co-authored-by: release-please[bot] <55107282+release-please[bot]@users.noreply.github.com> Co-authored-by: Yuan Teoh <45984206+Yuan325@users.noreply.github.com>
1038 lines
36 KiB
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1038 lines
36 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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||
"metadata": {
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||
"id": "KWS7OXcEJptT"
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||
},
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||
"outputs": [],
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"source": [
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||
"# Copyright 2025 Google LLC\n",
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"#\n",
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||
"# Licensed under the Apache License, Version 2.0 (the \"License\");\n",
|
||
"# you may not use this file except in compliance with the License.\n",
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"# You may obtain a copy of the License at\n",
|
||
"#\n",
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||
"# https://www.apache.org/licenses/LICENSE-2.0\n",
|
||
"#\n",
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||
"# Unless required by applicable law or agreed to in writing, software\n",
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||
"# distributed under the License is distributed on an \"AS IS\" BASIS,\n",
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||
"# 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."
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]
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},
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{
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||
"cell_type": "markdown",
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"metadata": {
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"id": "5sZ7_HCYJm4y"
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},
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"source": [
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"[](https://colab.research.google.com/github/googleapis/genai-toolbox/blob/main/docs/en/getting-started/colab_quickstart.ipynb)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "DMLivT-MIcmV"
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},
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"source": [
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"# Getting Started With MCP Toolbox\n",
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"\n",
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"This guide demonstrates how to quickly run\n",
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"[Toolbox](https://github.com/googleapis/genai-toolbox) end-to-end in Google\n",
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"Colab using Python, PostgreSQL, and either [Google\n",
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"GenAI](https://pypi.org/project/google-genai/), [ADK](https://google.github.io/adk-docs/),\n",
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"[Langgraph](https://www.langchain.com/langgraph)\n",
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"or [LlamaIndex](https://www.llamaindex.ai/).\n",
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"\n",
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"Within this Colab environment, you'll\n",
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"- Set up a `PostgreSQL database`.\n",
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"- Launch a Toolbox server.\n",
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"- Connect to Toolbox and develop a sample `Hotel Booking` application.\n",
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"\n",
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"Here is the simplified flow of a Toolbox Application:\n",
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"\n",
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"<img src=\"https://services.google.com/fh/files/misc/toolbox_flow.png\" alt=\"Toolbox Flow\"/>\n",
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"\n"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "nBWNgqEWIoSG"
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},
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"source": [
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"## Step 1: Set up your database\n",
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"\n",
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"In this section, we will\n",
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"1. Create a database.\n",
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"1. Create a user to access the database.\n",
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"1. Insert example data into the database."
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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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"metadata": {
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"id": "EeFDe-j4HUmn"
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},
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"outputs": [],
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"source": [
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"# Install postgresql to run a DB server on colab\n",
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"%%shell\n",
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"\n",
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"sudo apt-get -y -qq update > /dev/null 2>&1\n",
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"sudo apt-get -y -qq install postgresql > /dev/null 2>&1"
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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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"metadata": {
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"id": "5D9t-ZB1Dre-"
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},
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"outputs": [],
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"source": [
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"# Start the postgresql server.\n",
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"!sudo service postgresql start"
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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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"metadata": {
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"id": "qJJbo5T7sjyd"
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},
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"outputs": [],
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"source": [
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"# Check that postgres is running\n",
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"!sudo lsof -i :5432"
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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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"metadata": {
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"id": "zTtKdvbwAag3"
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},
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"outputs": [],
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"source": [
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"# Create a dedicated database and a user to access our DB securely\n",
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"%%shell\n",
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"\n",
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"sudo -u postgres psql << EOF\n",
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"CREATE USER toolbox_user WITH PASSWORD 'my-password';\n",
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"CREATE DATABASE toolbox_db;\n",
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"GRANT ALL PRIVILEGES ON DATABASE toolbox_db TO toolbox_user;\n",
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"ALTER DATABASE toolbox_db OWNER TO toolbox_user;\n",
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"EOF"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "zVx18ijjrWSO"
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},
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"source": [
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"> **Tip:** For a real application, it’s best to follow the principle of least permission and only grant the privileges your application needs.\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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"execution_count": null,
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"metadata": {
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"id": "6t_nLJIHCRgy"
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},
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"outputs": [],
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"source": [
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"# Connect to the database with the new user and create a hotels table.\n",
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"%%shell\n",
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"\n",
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"export PGPASSWORD=my-password\n",
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"psql -h 127.0.0.1 -U toolbox_user -d toolbox_db --no-password << EOF\n",
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"CREATE TABLE hotels(\n",
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" id INTEGER NOT NULL PRIMARY KEY,\n",
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" name VARCHAR NOT NULL,\n",
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" location VARCHAR NOT NULL,\n",
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" price_tier VARCHAR NOT NULL,\n",
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" checkin_date DATE NOT NULL,\n",
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" checkout_date DATE NOT NULL,\n",
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" booked BIT NOT NULL\n",
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");\n",
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"INSERT INTO hotels(id, name, location, price_tier, checkin_date, checkout_date, booked)\n",
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"VALUES\n",
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" (1, 'Hilton Basel', 'Basel', 'Luxury', '2024-04-22', '2024-04-20', B'0'),\n",
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" (2, 'Marriott Zurich', 'Zurich', 'Upscale', '2024-04-14', '2024-04-21', B'0'),\n",
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" (3, 'Hyatt Regency Basel', 'Basel', 'Upper Upscale', '2024-04-02', '2024-04-20', B'0'),\n",
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" (4, 'Radisson Blu Lucerne', 'Lucerne', 'Midscale', '2024-04-24', '2024-04-05', B'0'),\n",
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" (5, 'Best Western Bern', 'Bern', 'Upper Midscale', '2024-04-23', '2024-04-01', B'0'),\n",
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" (6, 'InterContinental Geneva', 'Geneva', 'Luxury', '2024-04-23', '2024-04-28', B'0'),\n",
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" (7, 'Sheraton Zurich', 'Zurich', 'Upper Upscale', '2024-04-27', '2024-04-02', B'0'),\n",
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" (8, 'Holiday Inn Basel', 'Basel', 'Upper Midscale', '2024-04-24', '2024-04-09', B'0'),\n",
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" (9, 'Courtyard Zurich', 'Zurich', 'Upscale', '2024-04-03', '2024-04-13', B'0'),\n",
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" (10, 'Comfort Inn Bern', 'Bern', 'Midscale', '2024-04-04', '2024-04-16', B'0');\n",
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"SELECT * from hotels;\n",
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"EOF"
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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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"metadata": {
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"id": "rw5fBXxpJ3-Q"
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},
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"outputs": [],
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"source": [
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"# Check that database is running\n",
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"!sudo lsof -i :5432"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Optional: Enable Vertex AI API for Google Cloud\n",
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"\n",
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"If you're using a model hosted on **Vertex AI**, run the following command to enable the API:\n",
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"\n",
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"```bash\n",
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"!gcloud services enable aiplatform.googleapis.com\n"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "EPuheP8DIt3p"
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},
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"source": [
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"## Step 2: Install and configure Toolbox\n",
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"\n",
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"In this section, we will\n",
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"1. Download the latest version of the toolbox binary.\n",
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"2. Create a toolbox config file.\n",
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"3. Start a toolbox server using the config file.\n",
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"\n"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "Bl1IeaqZbMYh"
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},
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"source": [
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"Download the [latest](https://github.com/googleapis/genai-toolbox/releases) version of Toolbox as a binary."
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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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"metadata": {
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"id": "lbsQ1Aa-IszB"
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},
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"outputs": [],
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"source": [
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"version = \"0.26.0\" # x-release-please-version\n",
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"! curl -O https://storage.googleapis.com/genai-toolbox/v{version}/linux/amd64/toolbox\n",
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"\n",
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"# Make the binary executable\n",
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"! chmod +x toolbox"
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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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"metadata": {
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"id": "Ovlzi2RVJGM5"
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},
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"outputs": [],
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"source": [
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"TOOLBOX_BINARY_PATH = \"/content/toolbox\"\n",
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"SERVER_PORT = 5000"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "4HQwVY5Pu1Xi"
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},
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"source": [
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"> Note: To include a literal dollar sign (e.g., $1) as part of your SQL statement within the Python string for tools.yml, you must escape both the backslash and the dollar sign. Use \\\\\\$1 in Python to output \\$1 in the tools.yml file.\n",
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"\n",
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"> Note: You can also set up Colab secrets to store any sensitive information like passwords. You can easily add secrets through the left panel:\n",
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"\n",
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"<img src=\"https://services.google.com/fh/files/misc/colab_secret.png\" alt=\"Colab Secrets\" width=\"400\"/>\n"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "KNg7v_FeTYJu"
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},
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"source": [
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"Create a tools file with the following functions:\n",
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"\n",
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"- `Database Connection (sources)`: `Includes details for connecting to our hotels database.`\n",
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"- `Tool Definitions (tools)`: `Defines five tools for database interaction:`\n",
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" - `search-hotels-by-name`\n",
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" - `search-hotels-by-location`\n",
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" - `book-hotel`\n",
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" - `update-hotel`\n",
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" - `cancel-hotel`\n",
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"\n",
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"Our application will leverage these tools to interact with the hotels database.\n",
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"\n",
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"For detailed configuration options, please refer to the [Toolbox documentation](https://googleapis.github.io/genai-toolbox/getting-started/configure/).\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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"execution_count": null,
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"metadata": {
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"id": "Jje8N5fScchw"
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},
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"outputs": [],
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"source": [
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"# Create a tools file at runtime.\n",
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"# You can also upload a tools file and use that to run toolbox.\n",
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"tools_file_name = \"tools.yml\"\n",
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"file_content = f\"\"\"\n",
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"sources:\n",
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" my-pg-source:\n",
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" kind: postgres\n",
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" host: 127.0.0.1\n",
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" port: 5432\n",
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" database: toolbox_db\n",
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" user: toolbox_user\n",
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" password: my-password\n",
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"tools:\n",
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" search-hotels-by-name:\n",
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" kind: postgres-sql\n",
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" source: my-pg-source\n",
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" description: Search for hotels based on name.\n",
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" parameters:\n",
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" - name: name\n",
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" type: string\n",
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" description: The name of the hotel.\n",
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" statement: SELECT * FROM hotels WHERE name ILIKE '%' || \\$1 || '%';\n",
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" search-hotels-by-location:\n",
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" kind: postgres-sql\n",
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" source: my-pg-source\n",
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" description: Search for hotels based on location.\n",
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" parameters:\n",
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" - name: location\n",
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" type: string\n",
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" description: The location of the hotel.\n",
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" statement: SELECT * FROM hotels WHERE location ILIKE '%' || \\$1 || '%';\n",
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" book-hotel:\n",
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" kind: postgres-sql\n",
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" source: my-pg-source\n",
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" description: >-\n",
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" Book a hotel by its ID. If the hotel is successfully booked, returns a NULL, raises an error if not.\n",
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" parameters:\n",
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" - name: hotel_id\n",
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" type: string\n",
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" description: The ID of the hotel to book.\n",
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" statement: UPDATE hotels SET booked = B'1' WHERE id = \\$1;\n",
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" update-hotel:\n",
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" kind: postgres-sql\n",
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" source: my-pg-source\n",
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" description: >-\n",
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" Update a hotel's check-in and check-out dates by its ID. Returns a message\n",
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" indicating whether the hotel was successfully updated or not.\n",
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" parameters:\n",
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" - name: hotel_id\n",
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" type: string\n",
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" description: The ID of the hotel to update.\n",
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" - name: checkin_date\n",
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" type: string\n",
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" description: The new check-in date of the hotel.\n",
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" - name: checkout_date\n",
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" type: string\n",
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" description: The new check-out date of the hotel.\n",
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" statement: >-\n",
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" UPDATE hotels SET checkin_date = CAST(\\$2 as date), checkout_date = CAST(\\$3\n",
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" as date) WHERE id = \\$1;\n",
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" cancel-hotel:\n",
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" kind: postgres-sql\n",
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" source: my-pg-source\n",
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" description: Cancel a hotel by its ID.\n",
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" parameters:\n",
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" - name: hotel_id\n",
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" type: string\n",
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" description: The ID of the hotel to cancel.\n",
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" statement: UPDATE hotels SET booked = B'0' WHERE id = \\$1;\n",
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"toolsets:\n",
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" my-toolset:\n",
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" - search-hotels-by-name\n",
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" - search-hotels-by-location\n",
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" - book-hotel\n",
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" - update-hotel\n",
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" - cancel-hotel\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,
|
||
"metadata": {
|
||
"id": "JPNXr4y58tMH"
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"# Write the file content into the tools file.\n",
|
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"! echo \"{file_content}\" > \"{tools_file_name}\""
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]
|
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},
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{
|
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"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {
|
||
"id": "5ZH5VuYzdP_W"
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"TOOLS_FILE_PATH = f\"/content/{tools_file_name}\""
|
||
]
|
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},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {
|
||
"id": "iZGQzYUF-pho"
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
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"# Start a toolbox server\n",
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"! nohup {TOOLBOX_BINARY_PATH} --tools-file {TOOLS_FILE_PATH} -p {SERVER_PORT} > toolbox.log 2>&1 &"
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]
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},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {
|
||
"id": "1PJpKOBieKOV"
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
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"# Check if toolbox is running\n",
|
||
"!sudo lsof -i :{SERVER_PORT}"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {
|
||
"id": "4yFH4JK7JEAv"
|
||
},
|
||
"source": [
|
||
"## Step 3: Connect your agent to Toolbox\n",
|
||
"\n",
|
||
"In this section, you will\n",
|
||
"1. Establish a connection to the tools by creating a Toolbox client.\n",
|
||
"2. Build an agent that leverages the tools and an LLM for Hotel Booking functionality.\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {
|
||
"id": "yfg-u9Y4Mu_a"
|
||
},
|
||
"source": [
|
||
"> You need to authenticate as an IAM user so this notebook can access your Google Cloud Project. This access is necessary to use Google's LLM models."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {
|
||
"id": "ky64V76MMttC"
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"# Run this and allow access through the pop-up\n",
|
||
"from google.colab import auth\n",
|
||
"\n",
|
||
"auth.authenticate_user()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {
|
||
"id": "u0Jc-0YNdhQd"
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"# @markdown Please fill in the value below with your GCP project ID and then run the cell.\n",
|
||
"\n",
|
||
"# Please fill in these values.\n",
|
||
"project_id = \"\" # @param {type:\"string\"}\n",
|
||
"\n",
|
||
"# Quick input validations.\n",
|
||
"assert project_id, \"⚠️ Please provide a Google Cloud project ID\"\n",
|
||
"\n",
|
||
"# Configure gcloud.\n",
|
||
"!gcloud config set project {project_id}"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {
|
||
"id": "J46eLkFbNhWq"
|
||
},
|
||
"source": [
|
||
"> You can either use LangGraph or LlamaIndex to develop a Toolbox based\n",
|
||
"> application. Run one of the sections below\n",
|
||
"> - [Connect using Google GenAI](#scrollTo=Fv2-uT4mvYtp)\n",
|
||
"> - [Connect using ADK](#scrollTo=QqRlWqvYNKSo)\n",
|
||
"> - [Connect Using LangGraph](#scrollTo=pbapNMhhL33S)\n",
|
||
"> - [Connect using LlamaIndex](#scrollTo=04iysrm_L_7v)\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {
|
||
"id": "QqRlWqvYNKSo"
|
||
},
|
||
"source": [
|
||
"### Connect Using ADK"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {
|
||
"id": "dhQTKlpVNKSo"
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"! pip install toolbox-core --quiet\n",
|
||
"! pip install google-adk --quiet"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {
|
||
"id": "tSLO_0vKNKSo"
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"from google.adk.agents import Agent\n",
|
||
"from google.adk.runners import Runner\n",
|
||
"from google.adk.sessions import InMemorySessionService\n",
|
||
"from google.adk.artifacts.in_memory_artifact_service import InMemoryArtifactService\n",
|
||
"from google.genai import types\n",
|
||
"from toolbox_core import ToolboxSyncClient\n",
|
||
"\n",
|
||
"import os\n",
|
||
"# TODO(developer): replace this with your Google API key\n",
|
||
"os.environ['GOOGLE_API_KEY'] = \"<GOOGLE_API_KEY>\"\n",
|
||
"\n",
|
||
"toolbox_client = ToolboxSyncClient(\"http://127.0.0.1:5000\")\n",
|
||
"\n",
|
||
"prompt = \"\"\"\n",
|
||
" You're a helpful hotel assistant. You handle hotel searching, booking and\n",
|
||
" cancellations. When the user searches for a hotel, mention it's name, id,\n",
|
||
" location and price tier. Always mention hotel ids while performing any\n",
|
||
" searches. This is very important for any operations. For any bookings or\n",
|
||
" cancellations, please provide the appropriate confirmation. Be sure to\n",
|
||
" update checkin or checkout dates if mentioned by the user.\n",
|
||
" Don't ask for confirmations from the user.\n",
|
||
"\"\"\"\n",
|
||
"\n",
|
||
"root_agent = Agent(\n",
|
||
" model='gemini-2.0-flash-001',\n",
|
||
" name='hotel_agent',\n",
|
||
" description='A helpful AI assistant.',\n",
|
||
" instruction=prompt,\n",
|
||
" tools=toolbox_client.load_toolset(\"my-toolset\"),\n",
|
||
")\n",
|
||
"\n",
|
||
"session_service = InMemorySessionService()\n",
|
||
"artifacts_service = InMemoryArtifactService()\n",
|
||
"session = await session_service.create_session(\n",
|
||
" state={}, app_name='hotel_agent', user_id='123'\n",
|
||
")\n",
|
||
"runner = Runner(\n",
|
||
" app_name='hotel_agent',\n",
|
||
" agent=root_agent,\n",
|
||
" artifact_service=artifacts_service,\n",
|
||
" session_service=session_service,\n",
|
||
")\n",
|
||
"\n",
|
||
"queries = [\n",
|
||
" \"Find hotels in Basel with Basel in it's name.\",\n",
|
||
" \"Can you book the Hilton Basel for me?\",\n",
|
||
" \"Oh wait, this is too expensive. Please cancel it and book the Hyatt Regency instead.\",\n",
|
||
" \"My check in dates would be from April 10, 2024 to April 19, 2024.\",\n",
|
||
"]\n",
|
||
"\n",
|
||
"for query in queries:\n",
|
||
" content = types.Content(role='user', parts=[types.Part(text=query)])\n",
|
||
" events = runner.run(session_id=session.id,\n",
|
||
" user_id='123', new_message=content)\n",
|
||
"\n",
|
||
" responses = (\n",
|
||
" part.text\n",
|
||
" for event in events\n",
|
||
" for part in event.content.parts\n",
|
||
" if part.text is not None\n",
|
||
" )\n",
|
||
"\n",
|
||
" for text in responses:\n",
|
||
" print(text)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {
|
||
"id": "pbapNMhhL33S"
|
||
},
|
||
"source": [
|
||
"### Connect Using LangGraph"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {
|
||
"id": "uraBx8mbMXnV"
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"# Install the Toolbox Langchain package\n",
|
||
"!pip install toolbox-langchain --quiet\n",
|
||
"!pip install langgraph --quiet\n",
|
||
"\n",
|
||
"# Install the Langchain llm package\n",
|
||
"# TODO(developer): replace this with another model if needed\n",
|
||
"! pip install langchain-google-vertexai --quiet\n",
|
||
"# ! pip install langchain-google-genai\n",
|
||
"# ! pip install langchain-anthropic"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {
|
||
"id": "0oHNnZnBM8FU"
|
||
},
|
||
"source": [
|
||
"Create a LangGraph Hotel Agent which can Search, Book and Cancel hotels."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {
|
||
"id": "Br3ucM46M9uc"
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"from langgraph.prebuilt import create_react_agent\n",
|
||
"# TODO(developer): replace this with another import if needed\n",
|
||
"from langchain_google_vertexai import ChatVertexAI\n",
|
||
"# from langchain_google_genai import ChatGoogleGenerativeAI\n",
|
||
"# from langchain_anthropic import ChatAnthropic\n",
|
||
"from langgraph.checkpoint.memory import MemorySaver\n",
|
||
"\n",
|
||
"from toolbox_langchain import ToolboxClient\n",
|
||
"\n",
|
||
"prompt = \"\"\"\n",
|
||
" You're a helpful hotel assistant. You handle hotel searching, booking and\n",
|
||
" cancellations. When the user searches for a hotel, mention it's name, id,\n",
|
||
" location and price tier. Always mention hotel id while performing any\n",
|
||
" searches. This is very important for any operations. For any bookings or\n",
|
||
" cancellations, please provide the appropriate confirmation. Be sure to\n",
|
||
" update checkin or checkout dates if mentioned by the user.\n",
|
||
" Don't ask for confirmations from the user.\n",
|
||
"\"\"\"\n",
|
||
"\n",
|
||
"queries = [\n",
|
||
" \"Find hotels in Basel with Basel in it's name.\",\n",
|
||
" \"Can you book the Hilton Basel for me?\",\n",
|
||
" \"Oh wait, this is too expensive. Please cancel it and book the Hyatt Regency instead.\",\n",
|
||
" \"My check in dates would be from April 10, 2024 to April 19, 2024.\",\n",
|
||
"]\n",
|
||
"\n",
|
||
"async def run_application():\n",
|
||
" # Create an LLM to bind with the agent.\n",
|
||
" # TODO(developer): replace this with another model if needed\n",
|
||
" model = ChatVertexAI(model_name=\"gemini-2.0-flash-001\", project=project_id)\n",
|
||
" # model = ChatGoogleGenerativeAI(model=\"gemini-2.0-flash-001\")\n",
|
||
" # model = ChatAnthropic(model=\"claude-3-5-sonnet-20240620\")\n",
|
||
"\n",
|
||
" # Load the tools from the Toolbox server\n",
|
||
" client = ToolboxClient(\"http://127.0.0.1:5000\")\n",
|
||
" tools = await client.aload_toolset()\n",
|
||
"\n",
|
||
" # Create a Langraph agent\n",
|
||
" agent = create_react_agent(model, tools, checkpointer=MemorySaver())\n",
|
||
" config = {\"configurable\": {\"thread_id\": \"thread-1\"}}\n",
|
||
" for query in queries:\n",
|
||
" inputs = {\"messages\": [(\"user\", prompt + query)]}\n",
|
||
" response = agent.invoke(inputs, stream_mode=\"values\", config=config)\n",
|
||
" print(response[\"messages\"][-1].content)\n",
|
||
"\n",
|
||
"await run_application()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {
|
||
"id": "04iysrm_L_7v"
|
||
},
|
||
"source": [
|
||
"### Connect using LlamaIndex"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {
|
||
"id": "6b6Loh8SJ_iA"
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"# Install the Toolbox LlamaIndex package\n",
|
||
"!pip install toolbox-llamaindex --quiet\n",
|
||
"\n",
|
||
"# Install the llamaindex llm package\n",
|
||
"# TODO(developer): replace this with another model if needed\n",
|
||
"! pip install llama-index-llms-google-genai --quiet\n",
|
||
"# ! pip install llama-index-llms-anthropic"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {
|
||
"id": "zjsq_xXice11"
|
||
},
|
||
"source": [
|
||
"Create a LlamaIndex Hotel Agent which can Search, Book and Cancel hotels."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {
|
||
"id": "EaBX4Dh6cU31"
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"import asyncio\n",
|
||
"import os\n",
|
||
"\n",
|
||
"from llama_index.core.agent.workflow import AgentWorkflow\n",
|
||
"\n",
|
||
"from llama_index.core.workflow import Context\n",
|
||
"\n",
|
||
"# TODO(developer): replace this with another import if needed\n",
|
||
"from llama_index.llms.google_genai import GoogleGenAI\n",
|
||
"# from llama_index.llms.anthropic import Anthropic\n",
|
||
"\n",
|
||
"from toolbox_llamaindex import ToolboxClient\n",
|
||
"\n",
|
||
"prompt = \"\"\"\n",
|
||
" You're a helpful hotel assistant. You handle hotel searching, booking and\n",
|
||
" cancellations. When the user searches for a hotel, mention it's name, id,\n",
|
||
" location and price tier. Always mention hotel ids while performing any\n",
|
||
" searches. This is very important for any operations. For any bookings or\n",
|
||
" cancellations, please provide the appropriate confirmation. Be sure to\n",
|
||
" update checkin or checkout dates if mentioned by the user.\n",
|
||
" Don't ask for confirmations from the user.\n",
|
||
"\"\"\"\n",
|
||
"\n",
|
||
"queries = [\n",
|
||
" \"Find hotels in Basel with Basel in it's name.\",\n",
|
||
" \"Can you book the Hilton Basel for me?\",\n",
|
||
" \"Oh wait, this is too expensive. Please cancel it and book the Hyatt Regency instead.\",\n",
|
||
" \"My check in dates would be from April 10, 2024 to April 19, 2024.\",\n",
|
||
"]\n",
|
||
"\n",
|
||
"async def run_application():\n",
|
||
" # Create an LLM to bind with the agent.\n",
|
||
" # TODO(developer): replace this with another model if needed\n",
|
||
" llm = GoogleGenAI(\n",
|
||
" model=\"gemini-2.0-flash-001\",\n",
|
||
" vertexai_config={\"project\": project_id, \"location\": \"us-central1\"},\n",
|
||
" )\n",
|
||
" # llm = GoogleGenAI(\n",
|
||
" # api_key=os.getenv(\"GOOGLE_API_KEY\"),\n",
|
||
" # model=\"gemini-2.0-flash-001\",\n",
|
||
" # )\n",
|
||
" # llm = Anthropic(\n",
|
||
" # model=\"claude-3-7-sonnet-latest\",\n",
|
||
" # api_key=os.getenv(\"ANTHROPIC_API_KEY\")\n",
|
||
" # )\n",
|
||
"\n",
|
||
" # Load the tools from the Toolbox server\n",
|
||
" client = ToolboxClient(\"http://127.0.0.1:5000\")\n",
|
||
" tools = await client.aload_toolset()\n",
|
||
"\n",
|
||
" # Create a LlamaIndex agent\n",
|
||
" agent = AgentWorkflow.from_tools_or_functions(\n",
|
||
" tools,\n",
|
||
" llm=llm,\n",
|
||
" system_prompt=prompt,\n",
|
||
" )\n",
|
||
"\n",
|
||
" # Run the agent\n",
|
||
" ctx = Context(agent)\n",
|
||
" for query in queries:\n",
|
||
" response = await agent.run(user_msg=query, ctx=ctx)\n",
|
||
" print(f\"---- {query} ----\")\n",
|
||
" print(str(response))\n",
|
||
"\n",
|
||
"await run_application()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {
|
||
"id": "Fv2-uT4mvYtp"
|
||
},
|
||
"source": [
|
||
"### Connect Using Google GenAI"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {
|
||
"id": "mHSvk5_AvYtu"
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"# Install the Toolbox Core package\n",
|
||
"!pip install toolbox-core --quiet\n",
|
||
"\n",
|
||
"# Install the Google GenAI package\n",
|
||
"!pip install google-genai --quiet"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {
|
||
"id": "sO_7FGSYvYtu"
|
||
},
|
||
"source": [
|
||
"Create a Google GenAI Application which can Search, Book and Cancel hotels."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {
|
||
"id": "-NVVBiLnvYtu"
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"import asyncio\n",
|
||
"\n",
|
||
"from google import genai\n",
|
||
"from google.genai.types import (\n",
|
||
" Content,\n",
|
||
" FunctionDeclaration,\n",
|
||
" GenerateContentConfig,\n",
|
||
" Part,\n",
|
||
" Tool,\n",
|
||
")\n",
|
||
"\n",
|
||
"from toolbox_core import ToolboxClient\n",
|
||
"\n",
|
||
"prompt = \"\"\"\n",
|
||
" You're a helpful hotel assistant. You handle hotel searching, booking and\n",
|
||
" cancellations. When the user searches for a hotel, mention it's name, id,\n",
|
||
" location and price tier. Always mention hotel id while performing any\n",
|
||
" searches. This is very important for any operations. For any bookings or\n",
|
||
" cancellations, please provide the appropriate confirmation. Be sure to\n",
|
||
" update checkin or checkout dates if mentioned by the user.\n",
|
||
" Don't ask for confirmations from the user.\n",
|
||
"\"\"\"\n",
|
||
"\n",
|
||
"queries = [\n",
|
||
" \"Find hotels in Basel with Basel in it's name.\",\n",
|
||
" \"Please book the hotel Hilton Basel for me.\",\n",
|
||
" \"This is too expensive. Please cancel it.\",\n",
|
||
" \"Please book Hyatt Regency for me\",\n",
|
||
" \"My check in dates for my booking would be from April 10, 2024 to April 19, 2024.\",\n",
|
||
"]\n",
|
||
"\n",
|
||
"\n",
|
||
"async def run_application():\n",
|
||
" toolbox_client = ToolboxClient(\"http://127.0.0.1:5000\")\n",
|
||
"\n",
|
||
" # The toolbox_tools list contains Python callables (functions/methods) designed for LLM tool-use\n",
|
||
" # integration. While this example uses Google's genai client, these callables can be adapted for\n",
|
||
" # various function-calling or agent frameworks. For easier integration with supported frameworks\n",
|
||
" # (https://github.com/googleapis/mcp-toolbox-python-sdk/tree/main/packages), use the\n",
|
||
" # provided wrapper packages, which handle framework-specific boilerplate.\n",
|
||
" toolbox_tools = await toolbox_client.load_toolset(\"my-toolset\")\n",
|
||
" genai_client = genai.Client(\n",
|
||
" vertexai=True, project=project_id, location=\"us-central1\"\n",
|
||
" )\n",
|
||
"\n",
|
||
" genai_tools = [\n",
|
||
" Tool(\n",
|
||
" function_declarations=[\n",
|
||
" FunctionDeclaration.from_callable_with_api_option(callable=tool)\n",
|
||
" ]\n",
|
||
" )\n",
|
||
" for tool in toolbox_tools\n",
|
||
" ]\n",
|
||
" history = []\n",
|
||
" for query in queries:\n",
|
||
" user_prompt_content = Content(\n",
|
||
" role=\"user\",\n",
|
||
" parts=[Part.from_text(text=query)],\n",
|
||
" )\n",
|
||
" history.append(user_prompt_content)\n",
|
||
"\n",
|
||
" response = genai_client.models.generate_content(\n",
|
||
" model=\"gemini-2.0-flash-001\",\n",
|
||
" contents=history,\n",
|
||
" config=GenerateContentConfig(\n",
|
||
" system_instruction=prompt,\n",
|
||
" tools=genai_tools,\n",
|
||
" ),\n",
|
||
" )\n",
|
||
" history.append(response.candidates[0].content)\n",
|
||
" function_response_parts = []\n",
|
||
" for function_call in response.function_calls:\n",
|
||
" fn_name = function_call.name\n",
|
||
" # The tools are sorted alphabetically\n",
|
||
" if fn_name == \"search-hotels-by-name\":\n",
|
||
" function_result = await toolbox_tools[3](**function_call.args)\n",
|
||
" elif fn_name == \"search-hotels-by-location\":\n",
|
||
" function_result = await toolbox_tools[2](**function_call.args)\n",
|
||
" elif fn_name == \"book-hotel\":\n",
|
||
" function_result = await toolbox_tools[0](**function_call.args)\n",
|
||
" elif fn_name == \"update-hotel\":\n",
|
||
" function_result = await toolbox_tools[4](**function_call.args)\n",
|
||
" elif fn_name == \"cancel-hotel\":\n",
|
||
" function_result = await toolbox_tools[1](**function_call.args)\n",
|
||
" else:\n",
|
||
" raise ValueError(\"Function name not present.\")\n",
|
||
" function_response = {\"result\": function_result}\n",
|
||
" function_response_part = Part.from_function_response(\n",
|
||
" name=function_call.name,\n",
|
||
" response=function_response,\n",
|
||
" )\n",
|
||
" function_response_parts.append(function_response_part)\n",
|
||
"\n",
|
||
" if function_response_parts:\n",
|
||
" tool_response_content = Content(role=\"tool\", parts=function_response_parts)\n",
|
||
" history.append(tool_response_content)\n",
|
||
"\n",
|
||
" response2 = genai_client.models.generate_content(\n",
|
||
" model=\"gemini-2.0-flash-001\",\n",
|
||
" contents=history,\n",
|
||
" config=GenerateContentConfig(\n",
|
||
" tools=genai_tools,\n",
|
||
" ),\n",
|
||
" )\n",
|
||
" final_model_response_content = response2.candidates[0].content\n",
|
||
" history.append(final_model_response_content)\n",
|
||
" print(response2.text)\n",
|
||
"\n",
|
||
"\n",
|
||
"asyncio.run(run_application())"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {
|
||
"id": "Kd-wF_Z9vVe3"
|
||
},
|
||
"source": [
|
||
"### Observe the output\n",
|
||
"\n",
|
||
"You can see that the `Hyatt Regency Basel` has been booked for the correct dates."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {
|
||
"id": "ZTW9bTUoqHis"
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"%%shell\n",
|
||
"\n",
|
||
"export PGPASSWORD=my-password\n",
|
||
"psql -h 127.0.0.1 -U toolbox_user -d toolbox_db --no-password << EOF\n",
|
||
"SELECT * from hotels;\n",
|
||
"EOF"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {
|
||
"id": "qV36Do-Bub12"
|
||
},
|
||
"source": [
|
||
"## Optional: Cleanup"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {
|
||
"id": "yatf9YoGclV9"
|
||
},
|
||
"source": [
|
||
"Executing this will terminate the processes running on the database and Toolbox ports.\n",
|
||
"\n",
|
||
"This is necessary before re-running the startup cells for these services to prevent `port already in use` errors."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {
|
||
"id": "WC8doSdzJkDE"
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"!lsof -t -i :5432 | xargs kill -9"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {
|
||
"id": "D09SAmLzufwO"
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"# Verify that the database process is killed\n",
|
||
"!sudo lsof -i :5432"
|
||
]
|
||
}
|
||
],
|
||
"metadata": {
|
||
"colab": {
|
||
"collapsed_sections": [
|
||
"Rwgv1LDdNKSn",
|
||
"pbapNMhhL33S",
|
||
"04iysrm_L_7v"
|
||
],
|
||
"provenance": [],
|
||
"toc_visible": true
|
||
},
|
||
"kernelspec": {
|
||
"display_name": "Python 3",
|
||
"name": "python3"
|
||
},
|
||
"language_info": {
|
||
"name": "python"
|
||
}
|
||
},
|
||
"nbformat": 4,
|
||
"nbformat_minor": 0
|
||
}
|