vectorize_client.models.start_extraction_request

Vectorize API (Beta)

API for Vectorize services

The version of the OpenAPI document: 0.0.1 Generated by OpenAPI Generator (https://openapi-generator.tech)

Do not edit the class manually.

View Source

 1# coding: utf-8
 2
 3"""
 4    Vectorize API (Beta)
 5
 6    API for Vectorize services
 7
 8    The version of the OpenAPI document: 0.0.1
 9    Generated by OpenAPI Generator (https://openapi-generator.tech)
10
11    Do not edit the class manually.
12"""  # noqa: E501
13
14
15from __future__ import annotations
16import pprint
17import re  # noqa: F401
18import json
19
20from pydantic import BaseModel, ConfigDict, Field, StrictFloat, StrictInt, StrictStr
21from typing import Any, ClassVar, Dict, List, Optional, Union
22from vectorize_client.models.extraction_chunking_strategy import ExtractionChunkingStrategy
23from vectorize_client.models.extraction_type import ExtractionType
24from vectorize_client.models.metadata_extraction_strategy import MetadataExtractionStrategy
25from typing import Optional, Set
26from typing_extensions import Self
27
28class StartExtractionRequest(BaseModel):
29    """
30    StartExtractionRequest
31    """ # noqa: E501
32    file_id: StrictStr = Field(alias="fileId")
33    type: Optional[ExtractionType] = ExtractionType.IRIS
34    chunking_strategy: Optional[ExtractionChunkingStrategy] = Field(default=ExtractionChunkingStrategy.MARKDOWN, alias="chunkingStrategy")
35    chunk_size: Optional[Union[StrictFloat, StrictInt]] = Field(default=256, alias="chunkSize")
36    metadata: Optional[MetadataExtractionStrategy] = None
37    __properties: ClassVar[List[str]] = ["fileId", "type", "chunkingStrategy", "chunkSize", "metadata"]
38
39    model_config = ConfigDict(
40        populate_by_name=True,
41        validate_assignment=True,
42        protected_namespaces=(),
43    )
44
45
46    def to_str(self) -> str:
47        """Returns the string representation of the model using alias"""
48        return pprint.pformat(self.model_dump(by_alias=True))
49
50    def to_json(self) -> str:
51        """Returns the JSON representation of the model using alias"""
52        # TODO: pydantic v2: use .model_dump_json(by_alias=True, exclude_unset=True) instead
53        return json.dumps(self.to_dict())
54
55    @classmethod
56    def from_json(cls, json_str: str) -> Optional[Self]:
57        """Create an instance of StartExtractionRequest from a JSON string"""
58        return cls.from_dict(json.loads(json_str))
59
60    def to_dict(self) -> Dict[str, Any]:
61        """Return the dictionary representation of the model using alias.
62
63        This has the following differences from calling pydantic's
64        `self.model_dump(by_alias=True)`:
65
66        * `None` is only added to the output dict for nullable fields that
67          were set at model initialization. Other fields with value `None`
68          are ignored.
69        """
70        excluded_fields: Set[str] = set([
71        ])
72
73        _dict = self.model_dump(
74            by_alias=True,
75            exclude=excluded_fields,
76            exclude_none=True,
77        )
78        # override the default output from pydantic by calling `to_dict()` of metadata
79        if self.metadata:
80            _dict['metadata'] = self.metadata.to_dict()
81        return _dict
82
83    @classmethod
84    def from_dict(cls, obj: Optional[Dict[str, Any]]) -> Optional[Self]:
85        """Create an instance of StartExtractionRequest from a dict"""
86        if obj is None:
87            return None
88
89        if not isinstance(obj, dict):
90            return cls.model_validate(obj)
91
92        _obj = cls.model_validate({
93            "fileId": obj.get("fileId"),
94            "type": obj.get("type") if obj.get("type") is not None else ExtractionType.IRIS,
95            "chunkingStrategy": obj.get("chunkingStrategy") if obj.get("chunkingStrategy") is not None else ExtractionChunkingStrategy.MARKDOWN,
96            "chunkSize": obj.get("chunkSize") if obj.get("chunkSize") is not None else 256,
97            "metadata": MetadataExtractionStrategy.from_dict(obj["metadata"]) if obj.get("metadata") is not None else None
98        })
99        return _obj

class StartExtractionRequest(pydantic.main.BaseModel): View Source

 29class StartExtractionRequest(BaseModel):
 30    """
 31    StartExtractionRequest
 32    """ # noqa: E501
 33    file_id: StrictStr = Field(alias="fileId")
 34    type: Optional[ExtractionType] = ExtractionType.IRIS
 35    chunking_strategy: Optional[ExtractionChunkingStrategy] = Field(default=ExtractionChunkingStrategy.MARKDOWN, alias="chunkingStrategy")
 36    chunk_size: Optional[Union[StrictFloat, StrictInt]] = Field(default=256, alias="chunkSize")
 37    metadata: Optional[MetadataExtractionStrategy] = None
 38    __properties: ClassVar[List[str]] = ["fileId", "type", "chunkingStrategy", "chunkSize", "metadata"]
 39
 40    model_config = ConfigDict(
 41        populate_by_name=True,
 42        validate_assignment=True,
 43        protected_namespaces=(),
 44    )
 45
 46
 47    def to_str(self) -> str:
 48        """Returns the string representation of the model using alias"""
 49        return pprint.pformat(self.model_dump(by_alias=True))
 50
 51    def to_json(self) -> str:
 52        """Returns the JSON representation of the model using alias"""
 53        # TODO: pydantic v2: use .model_dump_json(by_alias=True, exclude_unset=True) instead
 54        return json.dumps(self.to_dict())
 55
 56    @classmethod
 57    def from_json(cls, json_str: str) -> Optional[Self]:
 58        """Create an instance of StartExtractionRequest from a JSON string"""
 59        return cls.from_dict(json.loads(json_str))
 60
 61    def to_dict(self) -> Dict[str, Any]:
 62        """Return the dictionary representation of the model using alias.
 63
 64        This has the following differences from calling pydantic's
 65        `self.model_dump(by_alias=True)`:
 66
 67        * `None` is only added to the output dict for nullable fields that
 68          were set at model initialization. Other fields with value `None`
 69          are ignored.
 70        """
 71        excluded_fields: Set[str] = set([
 72        ])
 73
 74        _dict = self.model_dump(
 75            by_alias=True,
 76            exclude=excluded_fields,
 77            exclude_none=True,
 78        )
 79        # override the default output from pydantic by calling `to_dict()` of metadata
 80        if self.metadata:
 81            _dict['metadata'] = self.metadata.to_dict()
 82        return _dict
 83
 84    @classmethod
 85    def from_dict(cls, obj: Optional[Dict[str, Any]]) -> Optional[Self]:
 86        """Create an instance of StartExtractionRequest from a dict"""
 87        if obj is None:
 88            return None
 89
 90        if not isinstance(obj, dict):
 91            return cls.model_validate(obj)
 92
 93        _obj = cls.model_validate({
 94            "fileId": obj.get("fileId"),
 95            "type": obj.get("type") if obj.get("type") is not None else ExtractionType.IRIS,
 96            "chunkingStrategy": obj.get("chunkingStrategy") if obj.get("chunkingStrategy") is not None else ExtractionChunkingStrategy.MARKDOWN,
 97            "chunkSize": obj.get("chunkSize") if obj.get("chunkSize") is not None else 256,
 98            "metadata": MetadataExtractionStrategy.from_dict(obj["metadata"]) if obj.get("metadata") is not None else None
 99        })
100        return _obj

StartExtractionRequest

file_id: typing.Annotated[str, Strict(strict=True)]

type: Optional[vectorize_client.models.extraction_type.ExtractionType]

chunking_strategy: Optional[vectorize_client.models.extraction_chunking_strategy.ExtractionChunkingStrategy]

chunk_size: Union[Annotated[float, Strict(strict=True)], Annotated[int, Strict(strict=True)], NoneType]

metadata: Optional[vectorize_client.models.metadata_extraction_strategy.MetadataExtractionStrategy]

model_config = {'populate_by_name': True, 'validate_assignment': True, 'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

def to_str(self) -> str: View Source

47    def to_str(self) -> str:
48        """Returns the string representation of the model using alias"""
49        return pprint.pformat(self.model_dump(by_alias=True))

Returns the string representation of the model using alias

def to_json(self) -> str: View Source

51    def to_json(self) -> str:
52        """Returns the JSON representation of the model using alias"""
53        # TODO: pydantic v2: use .model_dump_json(by_alias=True, exclude_unset=True) instead
54        return json.dumps(self.to_dict())

Returns the JSON representation of the model using alias

@classmethod

def from_json(cls, json_str: str) -> Optional[Self]: View Source

56    @classmethod
57    def from_json(cls, json_str: str) -> Optional[Self]:
58        """Create an instance of StartExtractionRequest from a JSON string"""
59        return cls.from_dict(json.loads(json_str))

Create an instance of StartExtractionRequest from a JSON string

def to_dict(self) -> Dict[str, Any]: View Source

61    def to_dict(self) -> Dict[str, Any]:
62        """Return the dictionary representation of the model using alias.
63
64        This has the following differences from calling pydantic's
65        `self.model_dump(by_alias=True)`:
66
67        * `None` is only added to the output dict for nullable fields that
68          were set at model initialization. Other fields with value `None`
69          are ignored.
70        """
71        excluded_fields: Set[str] = set([
72        ])
73
74        _dict = self.model_dump(
75            by_alias=True,
76            exclude=excluded_fields,
77            exclude_none=True,
78        )
79        # override the default output from pydantic by calling `to_dict()` of metadata
80        if self.metadata:
81            _dict['metadata'] = self.metadata.to_dict()
82        return _dict

Return the dictionary representation of the model using alias.

This has the following differences from calling pydantic's self.model_dump(by_alias=True):

None is only added to the output dict for nullable fields that were set at model initialization. Other fields with value None are ignored.

@classmethod

def from_dict(cls, obj: Optional[Dict[str, Any]]) -> Optional[Self]: View Source

 84    @classmethod
 85    def from_dict(cls, obj: Optional[Dict[str, Any]]) -> Optional[Self]:
 86        """Create an instance of StartExtractionRequest from a dict"""
 87        if obj is None:
 88            return None
 89
 90        if not isinstance(obj, dict):
 91            return cls.model_validate(obj)
 92
 93        _obj = cls.model_validate({
 94            "fileId": obj.get("fileId"),
 95            "type": obj.get("type") if obj.get("type") is not None else ExtractionType.IRIS,
 96            "chunkingStrategy": obj.get("chunkingStrategy") if obj.get("chunkingStrategy") is not None else ExtractionChunkingStrategy.MARKDOWN,
 97            "chunkSize": obj.get("chunkSize") if obj.get("chunkSize") is not None else 256,
 98            "metadata": MetadataExtractionStrategy.from_dict(obj["metadata"]) if obj.get("metadata") is not None else None
 99        })
100        return _obj

Create an instance of StartExtractionRequest from a dict