> ## Documentation Index > Fetch the complete documentation index at: https://docs-classic.cognigy.com/llms.txt > Use this file to discover all available pages before exploring further. # Google Vertex AI [Updated in 2026.11](https://docs-classic.cognigy.com/release-notes/2026.11.md) > [!WARNING] > > As of Cognigy 2026.6.0, the support for the Completions API for custom LLMs is deprecated. The full removal is planned for Cognigy 2026.24.0. To start using a Google Vertex AI or Gemini model with Cognigy features, follow these steps: 1. [Add a Model](#add-models) 2. [Apply the Model](#apply-the-model) ## Restriction * Only users with the [admin role](https://docs-classic.cognigy.com/ai/administer/access/members.md) in Cognigy can upload JSON service account files to configure Google models. ## Add Models You can add a model using one of the following interfaces: * [GUI](#add-models-via-gui) * [API](#add-models-via-the-api) ### Add Models via GUI To add a model provided by Google Vertex AI to Cognigy, follow these steps: > [tab] Standard Model (Cognigy 2025.15 and earlier versions) > > | Parameter | Description | > | - | - | > | JSON | To upload the JSON file with a key for your model, you need to obtain this key. Go to the Google Cloud console and find Vertex AI via the search bar. On the **Vertex AI** page, click the **Enable All Recommended APIs** button to activate an API connection, if it is not activated. Ensure that the Vertex AI API is enabled. In the left-side menu, go to the **IAM & Admin > Service Accounts**. Select **Actions** and click **Manage Keys**. On the **Keys** page, select **Add Key** and click **Create new Key**. In the appeared window, select the **JSON** key type and click **Create**. The file will be downloaded. You can also use this key for [Google Gemini](https://docs-classic.cognigy.com/ai/agents/develop/gen-ai-and-llms/providers/google-gemini.md). | > | Location | Add a [region](https://cloud.google.com/vertex-ai/docs/general/locations) for the model. For example, `us-central1`. | > | API Endpoint | Add a [service endpoint](https://cloud.google.com/vertex-ai/docs/reference/rest#service-endpoint) for the model. For example, `us-central1-aiplatform.googleapis.com`. Note that the endpoint should be specified without `https://` or `http://`. | > | Publisher | Add an owner's name of the model. If not specified, `Google` will be used by default. | > [tab] Custom Model > > | Parameter | Description | > | - | - | > | Model Type | Select the **Completion** type. | > | Model Name | Enter the name of the model that you want to use as a custom model. To find model names, refer to the [Google Vertex AI](https://cloud.google.com/vertex-ai/generative-ai/docs/learn/model-versioning) documentation. Note that, within this connection, Cognigy supports only the `text-bison` models. | > | JSON | To upload the JSON file with a key for your model, you need to obtain this key. Go to the Google Cloud console and find Vertex AI via the search bar. On the **Vertex AI** page, click the **Enable All Recommended APIs** button to activate an API connection, if it is not activated. Ensure that the Vertex AI API is enabled. In the left-side menu, go to the **IAM & Admin > Service Accounts**. Select **Actions** and click **Manage Keys**. On the **Keys** page, select **Add Key** and click **Create new Key**. In the appeared window, select the **JSON** key type and click **Create**. The file will be downloaded. You can also use this key for [Google Gemini](https://docs-classic.cognigy.com/ai/agents/develop/gen-ai-and-llms/providers/google-gemini.md). | > | Location | Add a [region](https://cloud.google.com/vertex-ai/docs/general/locations) for the model. For example, `us-central1`. | > | API Endpoint | Add a [service endpoint](https://cloud.google.com/vertex-ai/docs/reference/rest#service-endpoint) for the model. For example, `us-central1-aiplatform.googleapis.com`. Note that the endpoint should be specified without `https://` or `http://`. | > | Publisher | Add an owner's name of the model. If not specified, `Google` will be used by default. | Apply changes. Check if the connection was set up by clicking **Test**. You can switch generative models at any time using the **Model** list without setting up a new connection. For embedding models, the selection is locked because different embedding models can generate incompatible embeddings for [Knowledge AI](https://docs-classic.cognigy.com/ai/agents/develop/knowledge-ai/overview#embedding-model). To switch an embedding, delete the connection and create a new one. ### Add Models via the API You can add either a standard or custom model using the [Cognigy API POST /v2.0/largelanguagemodels](https://api-trial.cognigy.ai/openapi#post-/v2.0/largelanguagemodels) request. Then, test your connection for the created model via the [Cognigy API POST /v2.0/largelanguagemodels//test](https://api-trial.cognigy.ai/openapi#post-/v2.0/largelanguagemodels/-largeLanguageModelId-/test). ## Apply the Model To apply a model, follow these steps: 1. In the left-side menu of the Project, go to **Manage > Settings**. 2. Go to the section based on your use case for using a model: * **Generative AI Settings**. In the **Generative AI Settings** section, activate **Enable Generative AI Features**. This setting is toggled on by default if you have previously set up the Generative AI credentials. * **Knowledge AI Settings**. Use this section if you need to add a model for Knowledge AI. Select a model for the **Knowledge Search** and **Answer Extraction** features. Refer to the [list of standard models](https://docs-classic.cognigy.com/ai/agents/develop/gen-ai-and-llms/model-support-by-feature.md) and find the models that support these features. 3. Navigate to the desired feature and select a model from the list. If there are no models available for the selected feature, the system will automatically select **None**. Save changes. ## More Information * [Other LLM Operations](https://docs-classic.cognigy.com/ai/agents/develop/gen-ai-and-llms/other-operations.md) * [Overview](https://docs-classic.cognigy.com/ai/agents/develop/gen-ai-and-llms/llms.md) * [All LLM Providers](https://docs-classic.cognigy.com/ai/agents/develop/gen-ai-and-llms/providers/all-providers.md) * [Model support by feature](https://docs-classic.cognigy.com/ai/agents/develop/gen-ai-and-llms/model-support-by-feature.md) This documentation is built and hosted on [Mintlify](https://mintlify.com), a developer documentation platform.