vectorize_client.models.extraction_result

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, StrictBool, StrictStr
21from typing import Any, ClassVar, Dict, List, Optional
22from typing import Optional, Set
23from typing_extensions import Self
24
25class ExtractionResult(BaseModel):
26    """
27    ExtractionResult
28    """ # noqa: E501
29    success: StrictBool
30    chunks: Optional[List[StrictStr]] = None
31    text: Optional[StrictStr] = None
32    metadata: Optional[StrictStr] = None
33    metadata_schema: Optional[StrictStr] = Field(default=None, alias="metadataSchema")
34    chunks_metadata: Optional[List[StrictStr]] = Field(default=None, alias="chunksMetadata")
35    chunks_schema: Optional[List[StrictStr]] = Field(default=None, alias="chunksSchema")
36    error: Optional[StrictStr] = None
37    __properties: ClassVar[List[str]] = ["success", "chunks", "text", "metadata", "metadataSchema", "chunksMetadata", "chunksSchema", "error"]
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 ExtractionResult 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        return _dict
79
80    @classmethod
81    def from_dict(cls, obj: Optional[Dict[str, Any]]) -> Optional[Self]:
82        """Create an instance of ExtractionResult from a dict"""
83        if obj is None:
84            return None
85
86        if not isinstance(obj, dict):
87            return cls.model_validate(obj)
88
89        _obj = cls.model_validate({
90            "success": obj.get("success"),
91            "chunks": obj.get("chunks"),
92            "text": obj.get("text"),
93            "metadata": obj.get("metadata"),
94            "metadataSchema": obj.get("metadataSchema"),
95            "chunksMetadata": obj.get("chunksMetadata"),
96            "chunksSchema": obj.get("chunksSchema"),
97            "error": obj.get("error")
98        })
99        return _obj

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

 26class ExtractionResult(BaseModel):
 27    """
 28    ExtractionResult
 29    """ # noqa: E501
 30    success: StrictBool
 31    chunks: Optional[List[StrictStr]] = None
 32    text: Optional[StrictStr] = None
 33    metadata: Optional[StrictStr] = None
 34    metadata_schema: Optional[StrictStr] = Field(default=None, alias="metadataSchema")
 35    chunks_metadata: Optional[List[StrictStr]] = Field(default=None, alias="chunksMetadata")
 36    chunks_schema: Optional[List[StrictStr]] = Field(default=None, alias="chunksSchema")
 37    error: Optional[StrictStr] = None
 38    __properties: ClassVar[List[str]] = ["success", "chunks", "text", "metadata", "metadataSchema", "chunksMetadata", "chunksSchema", "error"]
 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 ExtractionResult 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        return _dict
 80
 81    @classmethod
 82    def from_dict(cls, obj: Optional[Dict[str, Any]]) -> Optional[Self]:
 83        """Create an instance of ExtractionResult from a dict"""
 84        if obj is None:
 85            return None
 86
 87        if not isinstance(obj, dict):
 88            return cls.model_validate(obj)
 89
 90        _obj = cls.model_validate({
 91            "success": obj.get("success"),
 92            "chunks": obj.get("chunks"),
 93            "text": obj.get("text"),
 94            "metadata": obj.get("metadata"),
 95            "metadataSchema": obj.get("metadataSchema"),
 96            "chunksMetadata": obj.get("chunksMetadata"),
 97            "chunksSchema": obj.get("chunksSchema"),
 98            "error": obj.get("error")
 99        })
100        return _obj

ExtractionResult

success: typing.Annotated[bool, Strict(strict=True)]

chunks: Optional[List[Annotated[str, Strict(strict=True)]]]

text: Optional[Annotated[str, Strict(strict=True)]]

metadata: Optional[Annotated[str, Strict(strict=True)]]

metadata_schema: Optional[Annotated[str, Strict(strict=True)]]

chunks_metadata: Optional[List[Annotated[str, Strict(strict=True)]]]

chunks_schema: Optional[List[Annotated[str, Strict(strict=True)]]]

error: Optional[Annotated[str, Strict(strict=True)]]

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 ExtractionResult from a JSON string"""
59        return cls.from_dict(json.loads(json_str))

Create an instance of ExtractionResult 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        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

 81    @classmethod
 82    def from_dict(cls, obj: Optional[Dict[str, Any]]) -> Optional[Self]:
 83        """Create an instance of ExtractionResult from a dict"""
 84        if obj is None:
 85            return None
 86
 87        if not isinstance(obj, dict):
 88            return cls.model_validate(obj)
 89
 90        _obj = cls.model_validate({
 91            "success": obj.get("success"),
 92            "chunks": obj.get("chunks"),
 93            "text": obj.get("text"),
 94            "metadata": obj.get("metadata"),
 95            "metadataSchema": obj.get("metadataSchema"),
 96            "chunksMetadata": obj.get("chunksMetadata"),
 97            "chunksSchema": obj.get("chunksSchema"),
 98            "error": obj.get("error")
 99        })
100        return _obj

Create an instance of ExtractionResult from a dict