Recent submissions

Comment · 1 year ago
Thanks! - I like it too :)
Comment · 1 year ago
This sounds accurate. I see myself as a Pain Manager more than a Product manager. Product just solves the pain that users have ;)

Sometimes we get it right the first time we launch it, I think most of the time we get it right over a period of time.

Trying to do a little bit better everyday and ship as fast as possible!

Comment · 1 year ago
You don't have to specify role when you call through Python (https://cloud.google.com/vertex-ai/generative-ai/docs/start/...)

(which I think is what you are using but maybe i'm wrong).

Feel free to DM me on @chrischo_pm on X. Stuff that you are describing shouldn't happen

Comment · 1 year ago
Can you tell me the exact instance when this happened please? I will take this feedback back to my colleagues. But in order to change how we behave I need a baseline and data
Comment · 1 year ago
ooh i like!
Comment · 1 year ago
I think you are talking about generativeai vs. vertexai vs. genai sdk.

And you are watching us evolve overtime to do better.

Couple clarifications 1. Going forward we only recommend using genai SDK 2. Subtle API differences - this is a bit harder to articulate but we are working to improve this. Please dm at @chrischo_pm if you would like to discuss further :)

Comment · 1 year ago
We have Python/Go in GA.

Java/JS is in preview (not ready for production) and will be GA soon!

Comment · 1 year ago
one step ahead of you ;)
Comment · 1 year ago
We have moved our quota system to Dynamic Shared Quota (https://cloud.google.com/vertex-ai/generative-ai/docs/quotas) for 2.0+ models. There are no quotas in DSQ. If you need a guaranteed throughput there is an option to purchase Provisioned Throughput (https://cloud.google.com/vertex-ai/generative-ai/docs/provis...).
Comment · 1 year ago
lemming, this is super helpful, thank you. We provide the genai SDK (https://github.com/googleapis/python-genai) to reduce the learning curve in 4 languages (GA: Python, Go Preview: Node.JS, Java). The SDK works for all Gemini APIs provided by Google AI Studio (https://ai.google.dev/) and Vertex AI.
Comment · 1 year ago
Ramoz, good to hear that native Structured Outputs are working! But if the docs are 'confusing and partially incomplete,' that’s not a good DevEx. Good docs are non-negotiable. We are in the process of revamping the whole documentation site. Stay tuned, you will see something better than what we have today.
Comment · 1 year ago
Comment · 1 year ago
simonw, 'Google's service auth SO hard to figure out' – absolutely hear you. We're taking this feedback on auth complexity seriously. We have a new Vertex express mode in Preview (https://cloud.google.com/vertex-ai/generative-ai/docs/start/... , not ready for primetime yet!) that you can sign up for a free tier and get API Key right away. We are improving the experience, again if you would like to give feedback, please DM me on @chrischo_pm on X.
Comment · 1 year ago
We built the OpenAI Compatible API (https://cloud.google.com/vertex-ai/generative-ai/docs/multim...) layer to help customers that are already using OAI library to test out Gemini easily with basic inference but not as a replacement library for the genai sdk (https://github.com/googleapis/python-genai). We recommend using th genai SDK for working with Gemini.
Comment · 1 year ago
I couldn’t have said it better. My billing friends are working to address some of these concerns along with the Vertex team. We are planning to address this issue. Please stay tuned, we will come back to this thread to announce when we can In fact, if you can DM me (@chrischo_pm on X) with, I would love to learn more if you are interested.

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