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Allow costs and window size limits to be specified in the config_list #1682
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Codecov ReportAttention:
Additional details and impacted files@@ Coverage Diff @@
## main #1682 +/- ##
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+ Coverage 37.85% 49.60% +11.75%
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Files 50 50
Lines 5733 5737 +4
Branches 1297 1408 +111
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+ Hits 2170 2846 +676
+ Misses 3391 2662 -729
- Partials 172 229 +57
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@@ -314,6 +327,8 @@ class OpenAIWrapper: | |||
"api_version", | |||
"api_type", | |||
"tags", | |||
"window_size", |
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are we doing anything with window size? or planning to do anything with it?
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Yes. Both :)
I have yet to modify WebSurfer (this is still a raft PR), but it will use WindowSize to understand how to break up pages.
I also use it in the complex_tasks branch with SocietyOfMind and will port those changes to main once this is ready and merged.
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wondering if this needs to be passed into cost
or if we can just pass all the args into the client constructor (as I believe is already done?) and re-use in different methods, that way we don't have to change the API every time we want to use a new config value
I'd love to figure this out. I think the issue I was working around is that the main wrapper client takes the config list, which may create many OAI or Azure clients, and we don't know which is used until we make the call. The cost method I had initially targeted for modification is a member of the wrapper client class. I'm not sure I fully understand the solution to this you are proposing, but I would be happy to get rid of the new parameter if possible. |
If we pass any extra kwargs that we need to the client constructors so for example |
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Looks good. Though I think docs is an important piece that is missing from this PR:
- https://microsoft.github.io/autogen/docs/llm_configuration
- Docstrings at
openai_utils.py
self, | ||
response: Union[ChatCompletion, Completion], | ||
token_cost_1k: Optional[Union[float, Dict[str, float]]] = None, | ||
) -> float: |
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Not critical, yet it might be reasonable to switch to Decimal type (float
smells in currency/money values :) - openai_utils.py included
Should we force or at least warn user to pass in token_cost if they are using azure? From my previous experience azure always return 'gpt-4' in response['model'], this will very likely cause a wrong calculation of cost. |
That is a good idea. This has been my experience too. Perhaps it should warn or force for any model that isn't OpenAI. |
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Closing this PR, since it is quite dated. Will open a new issue. |
Why are these changes needed?
See issue #1680.
TL;DR:
Token limits and costs are hardcoded in various files. Adding new models requires editing numerous files. Costs are keyed off model names, but those name may not be reliable. For example, "gpt-4" on Azure might point to an 8k, 32k, or 128k model. There is no requirement that these match with OpenAI names. Likewise, model names may not match at all (e.g., "my-gpt-4")
Adding new models or providers requires hand-editing core library files.
This PR allows costs and limits to be specified in the config. E.g.,
Limitations: Vision models are not fully-supported. We can compute the cost only after we get the tokens counts back after making the call.
Related issue number
Closes #1680, #1270
Checks