# Connect to a database

{% hint style="info" %}
There is a slightly difference between Docker and Epsilla Cloud when connecting to a database.
{% endhint %}

## Connect to a database using Epsilla Docker

### Step 0. Download docker image and start

Epsilla vector database docker images can be found at [docker hub](https://hub.docker.com/r/epsilla/vectordb).

Use the command below to pull the latest version of Epsilla vector DB:

```sh
docker pull epsilla/vectordb
```

You can also specify the version to pull:

```bash
docker pull epsilla/vectordb:0.3.1
```

Start the docker as the backend service

```sh
docker run --pull=always -d -p 8888:8888 epsilla/vectordb
```

Use the EMBEDDING\_MODELS environment variable to enable more built-in embedding models (learn more about [embeddings](/epsilladb/epsilla-vector-database/advanced-topics/embeddings.md)):

```bash
docker run --pull=always -d -p 8888:8888 -e EMBEDDING_MODELS="BAAI/bge-small-zh-v1.5,BAAI/bge-base-en" epsilla/vectordb
```

### Step 1. Initialize Client

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

```python
### client connect to localhost
from pyepsilla import vectordb
db = vectordb.Client()


### client connect to remote server
from pyepsilla import vectordb
db = vectordb.Client(
    protocol='http',      # http or https. Default is http
    host='3.100.100.100', # The host machine for the vector db. Default localhost
    port='8888'           # The port for the vector db, default 8888
)
```

{% endtab %}

{% tab title="JavaScript" %}

```javascript
// client connect to localhost
const epsillajs = require('epsillajs');
const db = new epsillajs.EpsillaDB();

// client connect to remote server
const epsillajs = require('epsillajs');
const db = new epsillajs.EpsillaDB({
    protocol: 'http',      // http or https. Default is http
    host: '3.100.100.100', // The host machine for the vector db. Default localhost
    port: '8888'           // The port for the vector db, default 8888
});
```

{% endtab %}
{% endtabs %}

In order to use OpenAI for embedding, pass in X-OpenAI-API-Key header:

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

```python
db = vectordb.Client(
    ...
    headers={
        "X-OpenAI-API-Key": <Your OpenAI API key here>
    }
)
```

{% endtab %}

{% tab title="JavaScript" %}

```javascript
const db = new epsillajs.EpsillaDB({
    ...
    headers: {
        "X-OpenAI-API-Key": <Your OpenAI API key here>
    }
});
```

{% endtab %}
{% endtabs %}

### Step 2. Load database

Use the command to load a database into memory. Epsilla can hold multiple databases in memory at the same time.

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

```python
status_code, response = db.load_db(
    db_name="myDB",         # The name of the DB. Can give any valid
                            # name when loading a DB from disk.
    db_path="/tmp/epsilla", # The path on the disk where the DB is persisted. 
                            # If the path doesn't exist, will create
                            # a new DB at this path.
    vector_scale=1000000,   # (Optional) the limit of the number of records in
                            # the table. Can provide any positive number at
                            # load_db time. If not specified, the default value
                            # is 150000.
    wal_enabled=True        # (Optional) Enable write ahead log or not. Default 
                            # is True. For high throughput low consistency case,
                            # can disable it to save disk IO.
)
```

{% endtab %}

{% tab title="JavaScript" %}

```javascript
const load = await db.loadDB(
    "/tmp/epsilla", // The path on the disk where the DB is persisted. 
                    // If the path doesn't exist, will create
                    // a new DB at this path.
    "MyDB",         // The name of the DB. Can give any valid
                    // name when loading a DB from disk.
    1000000,        // (Optional) the limit of the number of records in
                    // the table. Can provide any positive number at
                    // loadDB time. If not specified, the default value
                    // is 150000.
    true            // (Optional) Enable write ahead log or not. Default 
                    // is True. For high throughput low consistency case,
                    // can disable it to save disk IO.
);
```

{% endtab %}
{% endtabs %}

### Step 3. Use database

You can use the command to switch between multiple databases that are already loaded in memory. Then the following interactions will be towards this database.

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

```python
db.use_db(db_name="myDB")
```

{% endtab %}

{% tab title="JavaScript" %}

```javascript
db.useDB("MyDB");
```

{% endtab %}
{% endtabs %}

## Connect to a vector database on Epsilla Cloud

First, create a vector database on Cloud GUI.

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

{% hint style="info" %}
We will support creating vector databases via Python/JavaScript client in the near future.
{% endhint %}

Then connect to the created database. Replace the Project ID, Database ID and API Key.

{% 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 %}

The Project ID and Database ID can be copied from the database card under project resources:

<figure><img src="/files/Q2WzOOqmrSfc7ITGu1Xv" alt=""><figcaption></figcaption></figure>

The API Key can be created under project configurations:

<figure><img src="/files/W3sXbt3PdRKa5Y0Ud9ao" alt=""><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/user-manual/connect-to-a-database.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.