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Update SDK to version v1.81.2
- Generated from OpenAPI spec version v1.81.2 - Auto-generated by GitHub Actions
1 parent 7924682 commit da3993f

10 files changed

Lines changed: 28 additions & 11 deletions

.sdk-version

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v1.81.0
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v1.81.2

docs/AutoUnstripRequest.md

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@@ -7,6 +7,8 @@ Name | Type | Description | Notes
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------------ | ------------- | ------------- | -------------
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**min_similarity** | **float** | Minimum similarity expected for a match, default is 0.9 | [optional] [default to 0.9]
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**apply** | **bool** | Whether to apply the matched function names to the target binary, default is False | [optional] [default to False]
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**confidence_threshold** | **float** | Confidence threshold for applying function names, default is 0.9 | [optional] [default to 0.9]
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**min_group_size** | **int** | Minimum number of matching functions required to consider for a match, default is 10 | [optional] [default to 10]
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## Example
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docs/AutoUnstripResponse.md

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**total_time** | **int** | | [optional]
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**matches** | [**List[MatchedFunctionSuggestion]**](MatchedFunctionSuggestion.md) | | [optional]
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**applied** | **bool** | | [optional]
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**error_message** | **str** | | [optional]
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## Example
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revengai/__init__.py

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""" # noqa: E501
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__version__ = "v1.81.0"
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__version__ = "v1.81.2"
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# Define package exports
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__all__ = [

revengai/api_client.py

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@@ -90,7 +90,7 @@ def __init__(
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self.default_headers[header_name] = header_value
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self.cookie = cookie
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# Set default User-Agent.
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self.user_agent = 'OpenAPI-Generator/v1.81.0/python'
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self.user_agent = 'OpenAPI-Generator/v1.81.2/python'
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self.client_side_validation = configuration.client_side_validation
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def __enter__(self):

revengai/configuration.py

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@@ -529,8 +529,8 @@ def to_debug_report(self) -> str:
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return "Python SDK Debug Report:\n"\
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"OS: {env}\n"\
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"Python Version: {pyversion}\n"\
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"Version of the API: v1.81.0\n"\
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"SDK Package Version: v1.81.0".\
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"Version of the API: v1.81.2\n"\
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"SDK Package Version: v1.81.2".\
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format(env=sys.platform, pyversion=sys.version)
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def get_host_settings(self) -> List[HostSetting]:

revengai/models/auto_unstrip_request.py

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@@ -28,7 +28,9 @@ class AutoUnstripRequest(BaseModel):
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""" # noqa: E501
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min_similarity: Optional[Union[Annotated[float, Field(le=1.0, strict=True, ge=0.0)], Annotated[int, Field(le=1, strict=True, ge=0)]]] = Field(default=0.9, description="Minimum similarity expected for a match, default is 0.9")
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apply: Optional[StrictBool] = Field(default=False, description="Whether to apply the matched function names to the target binary, default is False")
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__properties: ClassVar[List[str]] = ["min_similarity", "apply"]
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confidence_threshold: Optional[Union[Annotated[float, Field(le=1.0, strict=True, ge=0.0)], Annotated[int, Field(le=1, strict=True, ge=0)]]] = Field(default=0.9, description="Confidence threshold for applying function names, default is 0.9")
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min_group_size: Optional[Annotated[int, Field(le=20, strict=True, ge=1)]] = Field(default=10, description="Minimum number of matching functions required to consider for a match, default is 10")
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__properties: ClassVar[List[str]] = ["min_similarity", "apply", "confidence_threshold", "min_group_size"]
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model_config = ConfigDict(
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populate_by_name=True,
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_obj = cls.model_validate({
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"min_similarity": obj.get("min_similarity") if obj.get("min_similarity") is not None else 0.9,
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"apply": obj.get("apply") if obj.get("apply") is not None else False
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"apply": obj.get("apply") if obj.get("apply") is not None else False,
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"confidence_threshold": obj.get("confidence_threshold") if obj.get("confidence_threshold") is not None else 0.9,
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"min_group_size": obj.get("min_group_size") if obj.get("min_group_size") is not None else 10
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})
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return _obj
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revengai/models/auto_unstrip_response.py

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total_time: Optional[StrictInt] = None
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matches: Optional[List[MatchedFunctionSuggestion]] = None
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applied: Optional[StrictBool] = None
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__properties: ClassVar[List[str]] = ["progress", "status", "total_time", "matches", "applied"]
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error_message: Optional[StrictStr] = None
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__properties: ClassVar[List[str]] = ["progress", "status", "total_time", "matches", "applied", "error_message"]
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model_config = ConfigDict(
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populate_by_name=True,
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if self.applied is None and "applied" in self.model_fields_set:
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_dict['applied'] = None
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# set to None if error_message (nullable) is None
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# and model_fields_set contains the field
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if self.error_message is None and "error_message" in self.model_fields_set:
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_dict['error_message'] = None
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return _dict
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@classmethod
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"status": obj.get("status"),
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"total_time": obj.get("total_time"),
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"matches": [MatchedFunctionSuggestion.from_dict(_item) for _item in obj["matches"]] if obj.get("matches") is not None else None,
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"applied": obj.get("applied")
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"applied": obj.get("applied"),
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"error_message": obj.get("error_message")
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})
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return _obj
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test/test_auto_unstrip_request.py

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if include_optional:
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return AutoUnstripRequest(
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min_similarity = 0.0,
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apply = True
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apply = True,
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confidence_threshold = 0.0,
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min_group_size = 1.0
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)
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else:
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return AutoUnstripRequest(

test/test_auto_unstrip_response.py

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function_vaddr = 56,
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suggested_name = '', )
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],
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applied = True
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applied = True,
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error_message = ''
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)
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else:
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return AutoUnstripResponse(

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