I spent only two minutes reading their documentation and it’s clear no one did any proofreading and it’s full of mistakes made by non-native speakers.
Example: the second sentence on the first page says “softwares” but “software” is a mass noun that cannot be pluralized.
Example: the third page about tokens has some zipped code to “calculate the token usage for your intput/output” and obviously “intput” should be “input” but misspelled.
As a company that produces LLMs, they could have even used their own LLM to edit their documentation to fix grammar issues, and yet they did not.
Maybe I’m just extra sensitive to grammar and spelling issues but this kind of lack of attention to detail is a huge subconscious turnoff. I had to fight my urge to close the tab.
The tool calling Python example would have benefitted from actually parsing the tool call. As is, it explains almost nothing.
> Example: the second sentence on the first page says “softwares” but “software” is a mass noun that cannot be pluralized.
I constantly see and hear this mistake from actual humans too.
It's fairly ironic that your own comment contains run-on sentences, speculative claims and phrasing peculiarities like "could have even" instead of "could even have". Perhaps you are less sensitive to this than you think!
There is a difference between conversational speech and formal speech like documentation. It isn't rational to criticise use of the first when such speech is complaining about errors in the latter.
It's strange that you criticise "could have even" when it is a phrasing clearly being used for emphasis. "Could even have" makes no clearer sense in context.
No irony detected.