# Epsilla Cloud

## 1. Sign up Epsilla Cloud

Create an Epsilla Cloud account at <https://cloud.epsilla.com/>, then sign in.

<figure><img src="/files/CumdyHglOp73VS1lTuEP" alt="" width="292"><figcaption></figcaption></figure>

## 2. Get your project API Key

Navigate to the 'Configurations' tab within the project, create a new API Key, and keep it at a secure place.

<figure><img src="/files/W3sXbt3PdRKa5Y0Ud9ao" alt=""><figcaption></figcaption></figure>

## 3. Create a vector database, then create a table

Navigate to the 'Resource' tab, and click 'Create Vector Database'.

<figure><img src="/files/3jCF32AuX9e7kP2kUFXO" alt=""><figcaption></figcaption></figure>

Give the database a name, and click 'Create'. It takes a few seconds to spin up a vector database.

<figure><img src="/files/i96vXXAyiWvWsqoEEPbg" alt=""><figcaption></figcaption></figure>

Within the newly created database, create a new table. Give the table a name. Adjust the table schema according to your business logic, then click 'Create'.

<figure><img src="/files/RZDDzp6kY3k5INc1P8e2" alt=""><figcaption></figcaption></figure>

## 4. Use GUI to CRUD data to the table.

Epsilla automatically generates sample queries for the table. Start with inserting some sample data:

<figure><img src="/files/V1kXrk3szHK9mPQNNAXn" alt=""><figcaption></figcaption></figure>

Then query the table with top K semantic similarity search.

<figure><img src="/files/ilIKW4qNiQeeq5Al5yNY" alt=""><figcaption></figcaption></figure>

Switch between Shell, Python, and JavaScript tags, and click the 'Copy' button to copy the curl command, Python code snippet, and JavaScript code snippet of the query.

<figure><img src="/files/NQcgYIx14CiYDrls4Sls" alt=""><figcaption></figcaption></figure>

{% hint style="info" %}
Copying the code snippet is the easiest way to integrate with your application as it already has the **project\_id** and **db\_id** prefilled.

Remember to replace **"YOUR-API-KEY"** part with the API Key you get earlier.
{% endhint %}

## 5. Connect to Epsilla

First, install Epsilla Python/JavaScript client.

{% tabs %}
{% tab title="Python" %}

```bash
pip3 install --upgrade pyepsilla
```

{% endtab %}

{% tab title="JavaScript" %}

```sh
npm install epsillajs
```

{% endtab %}
{% endtabs %}

Then connect to the created database.

{% tabs %}
{% tab title="Python" %}

```python
from pyepsilla import cloud
client = cloud.Client(
  project_id="PROJECT-ID",     # Copied from the GUI code snippet
  api_key="YOUR-API-KEY"       # Replace with your API Key
)
db = client.vectordb(db_id="DB-ID") # Copied from the GUI code snippet
```

{% endtab %}

{% tab title="JavaScript" %}

```javascript
const epsillajs = require('epsillajs');
const client = new epsillajs.EpsillaCloud({
  projectID: 'PROJECT-ID',  // Copied from the GUI code snippet
  apiKey: 'YOUR-API-KEY'    // Replace with your API Key
});
const db = new epsillajs.VectorDB(
  'DB-ID',                  // Copied from the GUI code snippet
   client
 ); 
await db.connect();
```

{% endtab %}
{% endtabs %}

## 6. Insert new records

You can insert multiple records in a batch.

{% tabs %}
{% tab title="Python" %}

```python
status_code, response = db.insert(table_name="MyTable", 
  records=[
    {"ID": 1, "Doc": "Berlin", "Embedding": [0.05, 0.61, 0.76, 0.74]},
    {"ID": 2, "Doc": "London", "Embedding": [0.19, 0.81, 0.75, 0.11]},
    {"ID": 3, "Doc": "Moscow", "Embedding": [0.36, 0.55, 0.47, 0.94]},
    {"ID": 4, "Doc": "San Francisco", "Embedding": [0.18, 0.01, 0.85, 0.80]},
    {"ID": 5, "Doc": "Shanghai", "Embedding": [0.24, 0.18, 0.22, 0.44]}
  ]
)
```

{% endtab %}

{% tab title="JavaScript" %}

```javascript
await db.insert('MyTable',
  [
    {"ID": 1, "Doc": "Berlin", "Embedding": [0.05, 0.61, 0.76, 0.74]},
    {"ID": 2, "Doc": "London", "Embedding": [0.19, 0.81, 0.75, 0.11]},
    {"ID": 3, "Doc": "Moscow", "Embedding": [0.36, 0.55, 0.47, 0.94]},
    {"ID": 4, "Doc": "San Francisco", "Embedding": [0.18, 0.01, 0.85, 0.80]},
    {"ID": 5, "Doc": "Shanghai", "Embedding": [0.24, 0.18, 0.22, 0.44]}
  ]
);
```

{% endtab %}

{% tab title="cURL" %}

```sh
curl -X POST 'https://api-us-east-1-1-aws.epsilla.com/api/v2/project/<PROJECT-ID>/vectordb/<DB-ID>/data/insert' \
    -H "X-API-Key: Your-API-Key-Here" \
    -H "Content-Type: application/json" \
    -d '{
        "table": "MyTable",
        "data": [
            {
              "ID": 1,
              "Doc": "Berlin",
              "Embedding": [0.05, 0.61, 0.76, 0.74]
            },
            {
              "ID": 2,
              "Doc": "London",
              "Embedding": [0.19, 0.81, 0.75, 0.11]
            },
            {
              "ID": 3,
              "Doc": "Moscow",
              "Embedding": [0.36, 0.55, 0.47, 0.94]
            },
            {
              "ID": 4,
              "Doc": "San Francisco",
              "Embedding": [0.18, 0.01, 0.85, 0.80]
            },
            {
              "ID": 5,
              "Doc": "Shanghai",
              "Embedding": [0.24, 0.18, 0.22, 0.44]
            }
         ]
     }'
```

{% endtab %}
{% endtabs %}

## 6. Search

{% tabs %}
{% tab title="Python" %}

```python
status_code, response = db.query(
  table_name="MyTable",
  query_field="Embedding",
  query_vector=[0.35, 0.55, 0.47, 0.94],
  limit=2
)
```

{% endtab %}

{% tab title="JavaScript" %}

```javascript
// search
const query = await db.query(
  'MyTable',
  {
    queryField: "Embedding",                 // query field
    queryVector: [0.35, 0.55, 0.47, 0.94],   // query vector
    limit: 2                                 // top K
  }
);
```

{% endtab %}

{% tab title="cURL" %}

```sh
curl -X POST 'https://api-us-east-1-1-aws.epsilla.com/api/v2/project/<PROJECT-ID>/vectordb/<DB-ID>/data/query' \
    -H "X-API-Key: Your-API-Key-Here" \
    -H "Content-Type: application/json" \
    -d '{
        "table": "MyTable",
        "queryField": "Embedding",
        "queryVector": [0.35, 0.55, 0.47, 0.94],
        "limit": 2
     }'        
```

{% endtab %}
{% endtabs %}

## 7. Delete a table and delete a database

Use the GUI to delete a table and delete a database.

<figure><img src="/files/joj7nFV9pZ2xPVwJT6pG" alt="" width="381"><figcaption></figcaption></figure>


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://epsilla-inc.gitbook.io/epsilladb/epsilla-vector-database/quick-start/epsilla-cloud.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.