This project performs vector search using Python and Google Cloud services like BigQuery. Follow the steps below to set up the environment, install dependencies, and authenticate with Google Cloud.
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gcloud auth login
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## Create Table in BigQuery
This document provides the steps to create a table in Google BigQuery with the following specifications:
-**Table Name**: `your_table_name`
-**Columns**:
-`bpnId`: STRING (TEXT)
-`embeddings`: FLOAT64 (REPEATED)
-`text`: STRING (NOT NULL)
## Prerequisites
- Google Cloud account
- Access to BigQuery
-`gcloud` command-line tool installed and configured (optional)
## Steps to Create the Table
1.**Open BigQuery**:
- Go to the [Google Cloud Console](https://console.cloud.google.com/).
- Navigate to the BigQuery section.
2.**Select Dataset**:
- In the left panel, select your project.
- Click on the dataset where you want to create the table. If you don't have a dataset, create one by clicking on the project name and then "Create Dataset."
3.**Create Table**:
- Click on the dataset name.
- Click on "Create Table."
4.**Configure Table Settings**:
-**Source**: Select "Empty table."
-**Table Name**: Enter your desired table name (e.g., `your_table_name`).
-**Schema**: Define the schema as follows:
- Click on "Add field" to add the first column:
-**Field name**: `bpnId`
-**Type**: STRING
-**Mode**: REQUIRED
- Click on "Add field" to add the second column:
-**Field name**: `embeddings`
-**Type**: FLOAT
-**Mode**: REPEATED
- Click on "Add field" to add the third column:
-**Field name**: `text`
-**Type**: STRING
-**Mode**: REQUIRED
5.**Create the Table**:
- After filling in the details, click on the "Create table" button at the bottom of the page.
## Example SQL Command
You can also create the table using a SQL command in the BigQuery console or through the `bq` command-line tool. Here’s an example:
