| Name |
Type |
Description |
Notes |
| model_id |
int |
ID of the model used for function matching, used to determine the embedding model |
|
| function_ids |
List[int] |
ID's of functions to find matches for, must be at least one function ID |
|
| min_similarity |
float |
Minimum similarity expected for a match as a percentage, default is 90 |
[optional] [default to 90] |
| filters |
FunctionMatchingFilters |
|
[optional] |
| results_per_function |
int |
Maximum number of matches to return per function, default is 1, max is 50 |
[optional] [default to 1] |
| page |
int |
Page number for paginated results, default is 1 (first page) |
[optional] [default to 1] |
| page_size |
int |
Number of functions to return per page, default is 0 (all functions), max is 1000 |
[optional] [default to 0] |
| status_only |
bool |
If set to true, only returns the status of the matching operation without the actual results |
[optional] [default to False] |
| no_cache |
bool |
If set to true, forces the system to bypass any cached results and perform a fresh computation |
[optional] [default to False] |
| use_canonical_names |
bool |
Whether to use canonical function names during function matching for confidence results, default is False |
[optional] [default to False] |
from revengai.models.function_matching_request import FunctionMatchingRequest
# TODO update the JSON string below
json = "{}"
# create an instance of FunctionMatchingRequest from a JSON string
function_matching_request_instance = FunctionMatchingRequest.from_json(json)
# print the JSON string representation of the object
print(FunctionMatchingRequest.to_json())
# convert the object into a dict
function_matching_request_dict = function_matching_request_instance.to_dict()
# create an instance of FunctionMatchingRequest from a dict
function_matching_request_from_dict = FunctionMatchingRequest.from_dict(function_matching_request_dict)[Back to Model list] [Back to API list] [Back to README]