Utilizing Gemini: Through Vertex AI or through Google/generative-ai?

I'm in the process of developing a chatbot application and I'm exploring options for integrating Gemini, a large language model (LLM).

I'm considering whether to utilize Vertex AI (@google-cloud/vertexai) for integration or to directly incorporate Gemini (@google/generative-ai)

google-cloud/vertexai:

https://cloud.google.com/vertex-ai/docs/generative-ai/start/quickstarts/quickstart-multimodal

google/generative-ai:

https://ai.google.dev/tutorials/node_quickstart.

Given that Gemini is an LLM and Vertex AI is a platform, I'm seeking insights on which approach might be more suitable for my project. Any recommendations or considerations would be greatly appreciated .

Gemini is a large language model as you specified. You can use it (via API calls) by calling either Google AI APIs or Vertex AI APIs.

If you are relatively new to Gemini and wants to explore the feature and build some prototype for your chatbot app, Google AI APIs (with Google AI Studio) is a fast way to get started. While your app and idea matures and you'd like to leverage more MLOps tools that streamline the usage, deployment, and monitoring of models, you can move to Google Cloud Vertex AI which provides Gemini APIs along with many other features. Basically, to help you productionize your app.

Depending on your app requirement and stages of your development, you can choose the path:

• Start with Google AI Studio and migrate Gemini app to Vertex AI
• Prototype and build with Vertex AI if you already have GCP established.

Pay attention to the Google AI vs. Vertex AI differences when making decision.

It's worth noting that Google reserves the right to use your input and output to the API to improve the product when using the unpaid version of the Gemini API