Seems interesting will definitely give it a try.
Few observations/ questions from reading the documentation-
> Continue will only be as helpful as the LLM you are using to power the edits and explanations
Are there any others apart from gpt4 suitable for programming copilot tasks ?
> If files get too large, it can be difficult for Continue to fit them into the limited LLM context windows. Try to highlight the section of code that include the relevant context. It's rare that you need the entire file.
Most of the value and real world use case benefits come from usage in a brownfield development where a legacy code isn’t well understood and is large (exceed current LLM context ?)
> telemetry through posthog
Can organisations setup their own telemetry and development data collection to further analyse how and where the Copilot is being used ?
> Finops
How does one get visibility of token / api usage and track api spends ?
> We've found claude-2 very capable, especially for chat functionality, and especially in situations where you're looking for the equivalent of a faster Google search, even smaller models will do. For inline edits, gpt4 well outperforms others, but we've only optimized the prompt for gpt4. There's a LOT of tinkering to be done here, and it seems clear that OSS models will be capable soon.
> Definitely value there. We have an embeddings search plugin heading out the door soon, but we very consciously avoided this for a while - it obstructs understanding of what code enters the context window, and we think transparency is underrated.
> Yes! You could have your own PostHog telemetry by simply switching out the key, but we also deposit higher quality development data on your machine (we never see it). Benefits being both 1) understanding ROI of the tool, and 2) being able to train custom models.
> This is a reasonable request! We'll add a feature for this. Right now, you can use the usage dashboard of whichever provider's key you use.
Are there any others apart from gpt4 suitable for programming copilot tasks ?
> If files get too large, it can be difficult for Continue to fit them into the limited LLM context windows. Try to highlight the section of code that include the relevant context. It's rare that you need the entire file.
Most of the value and real world use case benefits come from usage in a brownfield development where a legacy code isn’t well understood and is large (exceed current LLM context ?)
> telemetry through posthog Can organisations setup their own telemetry and development data collection to further analyse how and where the Copilot is being used ?
> Finops How does one get visibility of token / api usage and track api spends ?