Homogenize Generator meta output

[nachollorca]

Is your feature request related to a problem? Please describe.
The dictionaries returned by generators have matching keys to an extent, but some are using different notations for the same concept, mainly within the metadata / usage keys. For example:

• OpenAI generators use prompt_tokens/completion tokens, while Cohere/Anthropic/AmazonBedrock use input_tokens/output_tokens.
• Some generators use finish_reason, while others use stop_reason

Describe the solution you'd like
I would like generators to output the same scheme and keys to the extent that it is possible, i.e. for matching concepts. In particular, I would prefer to use input_tokens/output_tokens and stop_reason.

Describe alternatives you've considered
So far, in apps where we swap generators depending on the use case, the alternative is:

meta = pipe_result["answer_generator"]["replies"][0].meta
usage = meta["usage"]

output.input_tokens = usage["prompt_tokens"] if "prompt_tokens" in usage else usage["input_tokens"]
output.output_tokens = usage["completion_tokens"] if "completion_tokens" in usage else usage["output_tokens"]
output.finish_reason = meta["finish_reason"] if "finish_reason" in meta else meta["stop_reason"]`

[vblagoje]

Taking into account tendency for other LLM providers/libraries to converge on OpenAI API - let's got with OpenAI naming scheme.

[nachollorca]

Alright, I'll go for OpenAI's convention :)

[CarlosFerLo]

Been having a look at all generators and all the keywords seem to keep the OpenAI standard.