Comments (3)
Hey Xiaowei, let me try to answer your question as much as possible:
-
At
berkeley-function-leaderboard/data/function/gorilla_openfunctions_v1_test_function.py
, we have had all the executable functions ready. When we are evaluating the results, we import all the functions andexec()
the function calls. We will have two types of results : (1) definitive result: meaning that those result will not change subject to time. Then we do a exact match (2) real-time result: for those result that will be changing subjected to time, we will perform a type match. -
For the leaderboard ranking on the blog post, we compute the result as
(num_of_entries_per_category * accuracy_per_category)/total_entries
All categories are included except for "SQL" and "Chatable" which we generate to experiment. -
Sorry for the confusion. The
no_function_call
is renamed torelevance
as of now since we believe it's better representative of what we are testing. Those two should have same content but you should use the "relevance" one. -
Thank you for pointing this out. I will perform a manual check on the indices you are mentioning. I will get back to you in this PR.
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Fanjia, thanks for the response! Add some comments inline.
Hey Xiaowei, let me try to answer your question as much as possible:
- At
berkeley-function-leaderboard/data/function/gorilla_openfunctions_v1_test_function.py
, we have had all the executable functions ready. When we are evaluating the results, we import all the functions andexec()
the function calls. We will have two types of results : (1) definitive result: meaning that those result will not change subject to time. Then we do a exact match (2) real-time result: for those result that will be changing subjected to time, we will perform a type match.
Is this execution script also in the repo?
- For the leaderboard ranking on the blog post, we compute the result as
(num_of_entries_per_category * accuracy_per_category)/total_entries
All categories are included except for "SQL" and "Chatable" which we generate to experiment.
Do we also include REST, Java, JavaScript tests? I don't see those numbers in the table.
- Sorry for the confusion. The
no_function_call
is renamed torelevance
as of now since we believe it's better representative of what we are testing. Those two should have same content but you should use the "relevance" one.- Thank you for pointing this out. I will perform a manual check on the indices you are mentioning. I will get back to you in this PR.
Two more questions:
- I see Gemini pro results have been put to the leaderboard. But I haven't seen the code checked in yet.
- For each test example, there is a "human_eval_answer" field. Are they the same as the ones the possible_answer folder?
Thanks!
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Some additional minor data issues:
In the single_function (generic) test cases,
index 337, the cards parameter in poker_game_winner function definition is not complete.
"cards": {"type": "object", "description": "An object containing the player name as key and the cards as values in a list."}
index 297, the question is same as the target
"question": "music.theory.chordProgression(progression=['I', 'V', 'vi', 'IV'])",
In the possible_answers files, some function names have the "_1" suffix. Is this expected?
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Related Issues (20)
- Mistral HOT 2
- [feature] Guidance on Self-Hosting API Endpoints HOT 7
- [OpenFunctions] Unnecessarily and incorrectly invoking functions HOT 1
- Location of gorilla-cli HOT 1
- [bug] Hosted Gorilla: MULTIPLE FUNCTIONS calls HOT 6
- How to get started with OpenFunctions? HOT 4
- [bug] Hosted Gorilla: Running the notebook gives an error as its communicating with OpenAI. Throttling? HOT 1
- when is the training code available? HOT 2
- [RFC] Rearchitect the APIZoo data management
- Kubernetes Pod API json filename
- Berkeley Function Leaderboard for OpenFunctionsv2 Error Handling Error
- [feature] use OpenCodeInterpreter-DS (based on Deepseek Coder) as base for improved coding scores HOT 1
- Berkeley Function Calling Leaderboard Ground Truth Errors HOT 1
- Scene Understading and general response without function calling HOT 2
- Simple OpenAI Function Calling sample does not return correct answer HOT 2
- Running OpenFunctions-v2 locally with llama.cpp HOT 3
- OpenFunctions-v2: How to get prompt for multiturn conversation in inference_local.py?
- [API Zoo] Error Updating API Zoo Index HOT 1
- [Leaderboard] the model is not redirected to its provenance webpage...
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