# Enabling the Textual Agent

To enable the Textual Agent on a self-hosted instance of Tonic Textual, you must configure the connection to the AI model that you want to use.

Textual supports:

* Any OpenAI-compatible endpoint
* Gemini
* Amazon Bedrock

## Selecting the model provider

To identify the provider, set the [environment variable ](/textual/textual-install-administer/configuring-textual/textual-env-var-configure.md)`CHAT_LLM_PROVIDER`.

The available values are:

* `openai` - Indicates to use an OpenAI-compatible model.
* `gemini` - Indicates to use a Gemini model.
* `bedrock` - Indicates to use a model on Amazon Bedrock.

## Connecting to an OpenAI-compatible model

If you set `CHAT_LLM_PROVIDER` to `openai`, then to configure the connection to an OpenAI-compatible model, set the following environment variables:

* `CHAT_MODEL_ENDPOINT` - The endpoint URL for the OpenAI service.
* `CHAT_MODEL_NAME` - The name of the OpenAI-compatible model to use.
* `CHAT_API_KEY` - The API key to use for authentication.

## Connecting to a Gemini model

If you set `CHAT_LLM_PROVIDER` to `gemini`, then to configure the connection to a Gemini model, set the following environment variables:

* `CHAT_MODEL_ENDPOINT` - The endpoint URL for the Gemini service.
* `CHAT_MODEL_NAME` - The name of the Gemini model to use.
* `CHAT_API_KEY` - The Gemini API key to use for authentication.

## Connecting to a model on Amazon Bedrock

If you set `CHAT_LLM_PROVIDER` to `bedrock`, then to configure the connection to a model on Amazon Bedrock, set the following environment variables:

* `CHAT_MODEL_NAME` - The name of the model to use.

Optionally, also set:

* `CHAT_AMAZON_BEDROCK_REGION` - The AWS Region where Amazon Bedrock is located. If you do not provide this, then Textual uses the AWS Region that is set as the value of `AWS_DEFAULT_REGION`.
* `CHAT_AMAZON_BEDROCK_MAX_TOKENS` - The maximum number of output tokens for Amazon Bedrock responses. The default value is 64000.


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