Merge pull request #93 from mfahlandt/vertexai-docs

feat: add documentation for google vertex ai backend

docs/reference/providers/backend.md

@@ -2,14 +2,15 @@
 
 A Backend (also called Provider) is a service that provides access to the AI language model. There are many different backends available for K8sGPT. Each backend has its own strengths and weaknesses, so it is important to choose the one that is right for your needs.
 
-Currently, we have a total of 8 backends available:
+Currently, we have a total of 10 backends available:
 
 - [OpenAI](https://openai.com/)
 - [Cohere](https://cohere.com/)
 - [Amazon Bedrock](https://aws.amazon.com/bedrock/)
 - [Amazon SageMaker](https://aws.amazon.com/sagemaker/)
 - [Azure OpenAI](https://azure.microsoft.com/en-us/products/cognitive-services/openai-service)
 - [Google Gemini](https://ai.google.dev/docs/gemini_api_overview)
+- [Google Vertex AI](https://cloud.google.com/vertex-ai)
 - [Hugging Face](https://huggingface.co)
 - [LocalAI](https://github.com/go-skynet/LocalAI)
 - FakeAI
@@ -111,13 +112,36 @@ Google [Gemini](https://blog.google/technology/ai/google-gemini-ai/#performance)
 - To use Google Gemini API in K8sGPT, obtain [the API key](https://ai.google.dev/tutorials/setup).
 - To configure Google backend in K8sGPT with `gemini-pro` model (see all [models](https://ai.google.dev/models) here) use auth command:
     ```bash
-    k8sgpt auth add --backend google --model gemini-pro --password "<Your API KEY>"
+    k8sgpt auth add --backend googlevertexai --model gemini-pro --password "<Your API KEY>"
     ```
 - Run the following command to analyze issues within your cluster with the Google provider:
     ```bash
     k8sgpt analyze --explain --backend google
     ```
 
+## Google Gemini via Vertex AI
+
+Google [Gemini](https://blog.google/technology/ai/google-gemini-ai/#performance) allows generative AI capabilities with multimodal approach (it is capable to understand not only text, but also code, audio, image and video). 
+
+- To use [Google Vertex AI](https://cloud.google.com/vertex-ai?#build-with-gemini) you need to be authorized via [Google Cloud SDK](https://cloud.google.com/sdk/install). 
+    The [Vertex AI API](https://console.cloud.google.com/apis/library/vertex-ai.googleapis.com) needs to be enabled.
+
+> Note: Vertex AI Gemini API is currently available in these [regions](https://cloud.google.com/vertex-ai/docs/generative-ai/model-reference/gemini?hl=de#http_request), verify if those are working for your environment
+
+- Open a terminal or command prompt and run the following command to authenticate using your Google Cloud credentials:
+    ```bash
+    gcloud auth application-default login
+    ```
+
+- To configure Google backend in K8sGPT with `gemini-pro` model (see all [models](https://ai.google.dev/models) here) use auth command:
+    ```bash
+    k8sgpt auth add --backend googlevertexai --model "gemini-pro" --providerRegion "us-central1" --providerId "<your project id>"
+    ```
+- Run the following command to analyze issues within your cluster with the Google provider:
+    ```bash
+    k8sgpt analyze --explain --backend googlevertexai
+    ``` 
+
 ## HuggingFace
 
 Hugging Face is a versatile backend for K8sGPT, offering access to a wide range of pre-trained language models. It provides easy-to-use interfaces for both training and inference tasks. Refer to the Hugging Face [documentation](https://huggingface.co/docs) for further insights into model usage and capabilities.