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Gemini CLI

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1339 points sync | 8 comments | 25 Jun 25 13:10 UTC | HN request time: 3.832s | source | bottom
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iandanforth ◴[25 Jun 25 13:37 UTC] No.44377207[source]▶
I love how fragmented Google's Gemini offerings are. I'm a Pro subscriber, but I now learn I should be a "Gemini Code Assist Standard or Enterprise" user to get additional usage. I didn't even know that existed! As a run of the mill Google user I get a generous usage tier but paying them specifically for "Gemini" doesn't get me anything when it comes to "Gemini CLI". Delightful!
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behnamoh ◴[25 Jun 25 14:07 UTC] No.44377524[source]▶
Actually, that's the reason a lot of startups and solo developers prefer non-Google solutions, even though the quality of Gemini 2.5 Pro is insanely high. The Google Cloud Dashboard is a mess, and they haven't fixed it in years. They have Vertex that is supposed to host some of their models, but I don't understand what's the difference between that and their own cloud. And then you have two different APIs depending on the level of your project: This is literally the opposite of what we would expect from an AI provider where you start small and regardless of the scale of your project, you do not face obstacles. So essentially, Google has built an API solution that does not scale because as soon as your project gets bigger, you have to switch from the Google AI Studio API to the Vertex API. And I find it ridiculous because their OpenAI compatible API does not work all the time. And a lot of tools that rely on that actually don't work.

Google's AI offerings that should be simplified/consolidated:

- Jules vs Gemini CLI?

- Vertex API (requires a Google Cloud Account) vs Google AI Studio API

Also, since Vertex depends on Google Cloud, projects get more complicated because you have to modify these in your app [1]:

``` # Replace the `GOOGLE_CLOUD_PROJECT` and `GOOGLE_CLOUD_LOCATION` values # with appropriate values for your project. export GOOGLE_CLOUD_PROJECT=GOOGLE_CLOUD_PROJECT export GOOGLE_CLOUD_LOCATION=global export GOOGLE_GENAI_USE_VERTEXAI=True ```

[1]: https://cloud.google.com/vertex-ai/generative-ai/docs/start/...

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cperry ◴[25 Jun 25 15:34 UTC] No.44378498[source]▶
@sachinag is afk but wanted me to flag that he's on point for fixing the Cloud Dashboard - it's WIP!
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sachinag ◴[25 Jun 25 15:52 UTC] No.44378681[source]▶
Thanks Chris!

"The Google Cloud Dashboard is a mess, and they haven't fixed it in years." Tell me what you want, and I'll do my best to make it happen.

In the interim, I would also suggest checking out Cloud Hub - https://console.cloud.google.com/cloud-hub/ - this is us really rethinking the level of abstraction to be higher than the base infrastructure. You can read more about the philosophy and approach here: https://cloud.google.com/blog/products/application-developme...

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1. behnamoh ◴[25 Jun 25 16:17 UTC] No.44378993[source]▶
One more suggestion: Please remove the need to make a project before we can use Gemini API. That seriously impedes our motivation in using Gemini for one-off scripts and proof-of-concept products where creating a project is overkill.

Ideally what I want is this: I google "gemini api" and that leads me to a page where I can login using my Google account and see the API settings. I create one and start using it right away. No extra wizardry, no multiple packages that must be installed, just the gemini package (no gauth!) and I should be good to go.

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2. sitkack ◴[25 Jun 25 16:24 UTC] No.44379074[source]▶
That will never happen. Just make a scrub project that is your misc-dev-drawer.
3. sachinag ◴[25 Jun 25 17:13 UTC] No.44379659[source]▶
Totally fair. Yes, Google AI Studio [ https://aistudio.google.com ] lets you do this but Google Cloud doesn't at this time. That's super duper irritating, I know.
4. dieortin ◴[25 Jun 25 20:08 UTC] No.44381360[source]▶
AFAIK you can very easily get an API key from AI studio without creating any cloud project
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5. behnamoh ◴[25 Jun 25 20:19 UTC] No.44381452[source]▶
read my comment above. G Studio API is limited.
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6. sachinag ◴[26 Jun 25 00:22 UTC] No.44383078{3}[source]▶
Ah I think I see based on the other comment but just to confirm - you want to use Vertex provided Gemini API endpoints without having to create a Google Cloud project. Is that correct? (I’m just trying to get as precise about the problem statement and what success looks like - that helps me figure out a path to the best solution.)

Appreciate the feedback!

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7. behnamoh ◴[26 Jun 25 03:00 UTC] No.44383845{4}[source]▶
Yes! The main pain points I've faced are:

1. There should be no need to create a project to use the Vertex Gemini API. I know Google AI Studio doesn't need a project, but that API is limited compared to Vertex API, which brings me to the next point.

2. There should be one unified API, not two! That'll help scale products with ease. Currently Google recommends using Google AI Studio API for simple projects and one-off scripts, and Vertex for "real" projects. No other competitor does this (look at OpenAI for instance).

3. The OpenAI compatibility layer isn't complete and doesn't support other Gemini features that only the Gemini API supports (e.g,. setting safety level).

4. Devs should need to install only one package to use Google Gemini. Please get rid of gauth.

5. The documentation on Gemini API is fragmented. Ironically, Googling "gemini api doc" doesn't lead to the page that discusses how to get started easily and quickly.

8. ctippett ◴[26 Jun 25 07:52 UTC] No.44385174[source]▶
Creating an API key from AI Studio automatically creates a Google Cloud project in the background for you. You can see it when you're logged into the console or via `gcloud projects list`

It's similar to how a bunch of projects get created whenever you use Apps Scripts.