diff --git a/api/controllers/console/datasets/error.py b/api/controllers/console/datasets/error.py index 2f00a84de..cb68bb5e8 100644 --- a/api/controllers/console/datasets/error.py +++ b/api/controllers/console/datasets/error.py @@ -25,12 +25,6 @@ class UnsupportedFileTypeError(BaseHTTPException): code = 415 -class HighQualityDatasetOnlyError(BaseHTTPException): - error_code = "high_quality_dataset_only" - description = "Current operation only supports 'high-quality' datasets." - code = 400 - - class DatasetNotInitializedError(BaseHTTPException): error_code = "dataset_not_initialized" description = "The dataset is still being initialized or indexing. Please wait a moment." diff --git a/api/controllers/console/workspace/error.py b/api/controllers/console/workspace/error.py index 8b70ca62b..4427d1ff7 100644 --- a/api/controllers/console/workspace/error.py +++ b/api/controllers/console/workspace/error.py @@ -13,12 +13,6 @@ class CurrentPasswordIncorrectError(BaseHTTPException): code = 400 -class ProviderRequestFailedError(BaseHTTPException): - error_code = "provider_request_failed" - description = None - code = 400 - - class InvalidInvitationCodeError(BaseHTTPException): error_code = "invalid_invitation_code" description = "Invalid invitation code." diff --git a/api/controllers/service_api/dataset/error.py b/api/controllers/service_api/dataset/error.py index 5ff5e08c7..ecc47b40a 100644 --- a/api/controllers/service_api/dataset/error.py +++ b/api/controllers/service_api/dataset/error.py @@ -25,12 +25,6 @@ class UnsupportedFileTypeError(BaseHTTPException): code = 415 -class HighQualityDatasetOnlyError(BaseHTTPException): - error_code = "high_quality_dataset_only" - description = "Current operation only supports 'high-quality' datasets." - code = 400 - - class DatasetNotInitializedError(BaseHTTPException): error_code = "dataset_not_initialized" description = "The dataset is still being initialized or indexing. Please wait a moment." diff --git a/api/core/app/task_pipeline/exc.py b/api/core/app/task_pipeline/exc.py index e4b4168d0..df6277697 100644 --- a/api/core/app/task_pipeline/exc.py +++ b/api/core/app/task_pipeline/exc.py @@ -10,8 +10,3 @@ class RecordNotFoundError(TaskPipilineError): class WorkflowRunNotFoundError(RecordNotFoundError): def __init__(self, workflow_run_id: str): super().__init__("WorkflowRun", workflow_run_id) - - -class WorkflowNodeExecutionNotFoundError(RecordNotFoundError): - def __init__(self, workflow_node_execution_id: str): - super().__init__("WorkflowNodeExecution", workflow_node_execution_id) diff --git a/api/core/file/tool_file_parser.py b/api/core/file/tool_file_parser.py index 656c9d48e..fac68beb0 100644 --- a/api/core/file/tool_file_parser.py +++ b/api/core/file/tool_file_parser.py @@ -7,13 +7,6 @@ if TYPE_CHECKING: _tool_file_manager_factory: Callable[[], "ToolFileManager"] | None = None -class ToolFileParser: - @staticmethod - def get_tool_file_manager() -> "ToolFileManager": - assert _tool_file_manager_factory is not None - return _tool_file_manager_factory() - - def set_tool_file_manager_factory(factory: Callable[[], "ToolFileManager"]) -> None: global _tool_file_manager_factory _tool_file_manager_factory = factory diff --git a/api/core/helper/url_signer.py b/api/core/helper/url_signer.py deleted file mode 100644 index dfb143f4c..000000000 --- a/api/core/helper/url_signer.py +++ /dev/null @@ -1,52 +0,0 @@ -import base64 -import hashlib -import hmac -import os -import time - -from pydantic import BaseModel, Field - -from configs import dify_config - - -class SignedUrlParams(BaseModel): - sign_key: str = Field(..., description="The sign key") - timestamp: str = Field(..., description="Timestamp") - nonce: str = Field(..., description="Nonce") - sign: str = Field(..., description="Signature") - - -class UrlSigner: - @classmethod - def get_signed_url(cls, url: str, sign_key: str, prefix: str) -> str: - signed_url_params = cls.get_signed_url_params(sign_key, prefix) - return ( - f"{url}?timestamp={signed_url_params.timestamp}" - f"&nonce={signed_url_params.nonce}&sign={signed_url_params.sign}" - ) - - @classmethod - def get_signed_url_params(cls, sign_key: str, prefix: str) -> SignedUrlParams: - timestamp = str(int(time.time())) - nonce = os.urandom(16).hex() - sign = cls._sign(sign_key, timestamp, nonce, prefix) - - return SignedUrlParams(sign_key=sign_key, timestamp=timestamp, nonce=nonce, sign=sign) - - @classmethod - def verify(cls, sign_key: str, timestamp: str, nonce: str, sign: str, prefix: str) -> bool: - recalculated_sign = cls._sign(sign_key, timestamp, nonce, prefix) - - return sign == recalculated_sign - - @classmethod - def _sign(cls, sign_key: str, timestamp: str, nonce: str, prefix: str) -> str: - if not dify_config.SECRET_KEY: - raise Exception("SECRET_KEY is not set") - - data_to_sign = f"{prefix}|{sign_key}|{timestamp}|{nonce}" - secret_key = dify_config.SECRET_KEY.encode() - sign = hmac.new(secret_key, data_to_sign.encode(), hashlib.sha256).digest() - encoded_sign = base64.urlsafe_b64encode(sign).decode() - - return encoded_sign diff --git a/api/core/plugin/entities/plugin.py b/api/core/plugin/entities/plugin.py index e5cf7ee03..a07b58d9e 100644 --- a/api/core/plugin/entities/plugin.py +++ b/api/core/plugin/entities/plugin.py @@ -135,17 +135,6 @@ class PluginEntity(PluginInstallation): return self -class GithubPackage(BaseModel): - repo: str - version: str - package: str - - -class GithubVersion(BaseModel): - repo: str - version: str - - class GenericProviderID: organization: str plugin_name: str diff --git a/api/core/rag/cleaner/unstructured/unstructured_extra_whitespace_cleaner.py b/api/core/rag/cleaner/unstructured/unstructured_extra_whitespace_cleaner.py deleted file mode 100644 index 167a919e6..000000000 --- a/api/core/rag/cleaner/unstructured/unstructured_extra_whitespace_cleaner.py +++ /dev/null @@ -1,12 +0,0 @@ -"""Abstract interface for document clean implementations.""" - -from core.rag.cleaner.cleaner_base import BaseCleaner - - -class UnstructuredNonAsciiCharsCleaner(BaseCleaner): - def clean(self, content) -> str: - """clean document content.""" - from unstructured.cleaners.core import clean_extra_whitespace - - # Returns "ITEM 1A: RISK FACTORS" - return clean_extra_whitespace(content) diff --git a/api/core/rag/cleaner/unstructured/unstructured_group_broken_paragraphs_cleaner.py b/api/core/rag/cleaner/unstructured/unstructured_group_broken_paragraphs_cleaner.py deleted file mode 100644 index 9c682d29d..000000000 --- a/api/core/rag/cleaner/unstructured/unstructured_group_broken_paragraphs_cleaner.py +++ /dev/null @@ -1,15 +0,0 @@ -"""Abstract interface for document clean implementations.""" - -from core.rag.cleaner.cleaner_base import BaseCleaner - - -class UnstructuredGroupBrokenParagraphsCleaner(BaseCleaner): - def clean(self, content) -> str: - """clean document content.""" - import re - - from unstructured.cleaners.core import group_broken_paragraphs - - para_split_re = re.compile(r"(\s*\n\s*){3}") - - return group_broken_paragraphs(content, paragraph_split=para_split_re) diff --git a/api/core/rag/cleaner/unstructured/unstructured_non_ascii_chars_cleaner.py b/api/core/rag/cleaner/unstructured/unstructured_non_ascii_chars_cleaner.py deleted file mode 100644 index 0cdbb171e..000000000 --- a/api/core/rag/cleaner/unstructured/unstructured_non_ascii_chars_cleaner.py +++ /dev/null @@ -1,12 +0,0 @@ -"""Abstract interface for document clean implementations.""" - -from core.rag.cleaner.cleaner_base import BaseCleaner - - -class UnstructuredNonAsciiCharsCleaner(BaseCleaner): - def clean(self, content) -> str: - """clean document content.""" - from unstructured.cleaners.core import clean_non_ascii_chars - - # Returns "This text contains non-ascii characters!" - return clean_non_ascii_chars(content) diff --git a/api/core/rag/cleaner/unstructured/unstructured_replace_unicode_quotes_cleaner.py b/api/core/rag/cleaner/unstructured/unstructured_replace_unicode_quotes_cleaner.py deleted file mode 100644 index 9f42044a2..000000000 --- a/api/core/rag/cleaner/unstructured/unstructured_replace_unicode_quotes_cleaner.py +++ /dev/null @@ -1,12 +0,0 @@ -"""Abstract interface for document clean implementations.""" - -from core.rag.cleaner.cleaner_base import BaseCleaner - - -class UnstructuredNonAsciiCharsCleaner(BaseCleaner): - def clean(self, content) -> str: - """Replaces unicode quote characters, such as the \x91 character in a string.""" - - from unstructured.cleaners.core import replace_unicode_quotes - - return replace_unicode_quotes(content) diff --git a/api/core/rag/cleaner/unstructured/unstructured_translate_text_cleaner.py b/api/core/rag/cleaner/unstructured/unstructured_translate_text_cleaner.py deleted file mode 100644 index 32ae7217e..000000000 --- a/api/core/rag/cleaner/unstructured/unstructured_translate_text_cleaner.py +++ /dev/null @@ -1,11 +0,0 @@ -"""Abstract interface for document clean implementations.""" - -from core.rag.cleaner.cleaner_base import BaseCleaner - - -class UnstructuredTranslateTextCleaner(BaseCleaner): - def clean(self, content) -> str: - """clean document content.""" - from unstructured.cleaners.translate import translate_text - - return translate_text(content) diff --git a/api/core/rag/datasource/vdb/tidb_on_qdrant/tidb_entities.py b/api/core/rag/datasource/vdb/tidb_on_qdrant/tidb_entities.py deleted file mode 100644 index 1e62b3c58..000000000 --- a/api/core/rag/datasource/vdb/tidb_on_qdrant/tidb_entities.py +++ /dev/null @@ -1,17 +0,0 @@ -from typing import Optional - -from pydantic import BaseModel - - -class ClusterEntity(BaseModel): - """ - Model Config Entity. - """ - - name: str - cluster_id: str - displayName: str - region: str - spendingLimit: Optional[int] = 1000 - version: str - createdBy: str diff --git a/api/core/rag/extractor/blob/blob.py b/api/core/rag/extractor/blob/blob.py index e46ab8b7f..01003a13b 100644 --- a/api/core/rag/extractor/blob/blob.py +++ b/api/core/rag/extractor/blob/blob.py @@ -9,8 +9,7 @@ from __future__ import annotations import contextlib import mimetypes -from abc import ABC, abstractmethod -from collections.abc import Generator, Iterable, Mapping +from collections.abc import Generator, Mapping from io import BufferedReader, BytesIO from pathlib import Path, PurePath from typing import Any, Optional, Union @@ -143,21 +142,3 @@ class Blob(BaseModel): if self.source: str_repr += f" {self.source}" return str_repr - - -class BlobLoader(ABC): - """Abstract interface for blob loaders implementation. - - Implementer should be able to load raw content from a datasource system according - to some criteria and return the raw content lazily as a stream of blobs. - """ - - @abstractmethod - def yield_blobs( - self, - ) -> Iterable[Blob]: - """A lazy loader for raw data represented by Blob object. - - Returns: - A generator over blobs - """ diff --git a/api/core/rag/extractor/unstructured/unstructured_pdf_extractor.py b/api/core/rag/extractor/unstructured/unstructured_pdf_extractor.py deleted file mode 100644 index dd8a979e7..000000000 --- a/api/core/rag/extractor/unstructured/unstructured_pdf_extractor.py +++ /dev/null @@ -1,47 +0,0 @@ -import logging - -from core.rag.extractor.extractor_base import BaseExtractor -from core.rag.models.document import Document - -logger = logging.getLogger(__name__) - - -class UnstructuredPDFExtractor(BaseExtractor): - """Load pdf files. - - - Args: - file_path: Path to the file to load. - - api_url: Unstructured API URL - - api_key: Unstructured API Key - """ - - def __init__(self, file_path: str, api_url: str, api_key: str): - """Initialize with file path.""" - self._file_path = file_path - self._api_url = api_url - self._api_key = api_key - - def extract(self) -> list[Document]: - if self._api_url: - from unstructured.partition.api import partition_via_api - - elements = partition_via_api( - filename=self._file_path, api_url=self._api_url, api_key=self._api_key, strategy="auto" - ) - else: - from unstructured.partition.pdf import partition_pdf - - elements = partition_pdf(filename=self._file_path, strategy="auto") - - from unstructured.chunking.title import chunk_by_title - - chunks = chunk_by_title(elements, max_characters=2000, combine_text_under_n_chars=2000) - documents = [] - for chunk in chunks: - text = chunk.text.strip() - documents.append(Document(page_content=text)) - - return documents diff --git a/api/core/rag/extractor/unstructured/unstructured_text_extractor.py b/api/core/rag/extractor/unstructured/unstructured_text_extractor.py deleted file mode 100644 index 22dfdd207..000000000 --- a/api/core/rag/extractor/unstructured/unstructured_text_extractor.py +++ /dev/null @@ -1,34 +0,0 @@ -import logging - -from core.rag.extractor.extractor_base import BaseExtractor -from core.rag.models.document import Document - -logger = logging.getLogger(__name__) - - -class UnstructuredTextExtractor(BaseExtractor): - """Load msg files. - - - Args: - file_path: Path to the file to load. - """ - - def __init__(self, file_path: str, api_url: str): - """Initialize with file path.""" - self._file_path = file_path - self._api_url = api_url - - def extract(self) -> list[Document]: - from unstructured.partition.text import partition_text - - elements = partition_text(filename=self._file_path) - from unstructured.chunking.title import chunk_by_title - - chunks = chunk_by_title(elements, max_characters=2000, combine_text_under_n_chars=2000) - documents = [] - for chunk in chunks: - text = chunk.text.strip() - documents.append(Document(page_content=text)) - - return documents diff --git a/api/core/rag/splitter/text_splitter.py b/api/core/rag/splitter/text_splitter.py index b711e8434..529d8ccd2 100644 --- a/api/core/rag/splitter/text_splitter.py +++ b/api/core/rag/splitter/text_splitter.py @@ -10,7 +10,6 @@ from typing import ( Any, Literal, Optional, - TypedDict, TypeVar, Union, ) @@ -168,167 +167,6 @@ class TextSplitter(BaseDocumentTransformer, ABC): raise NotImplementedError -class CharacterTextSplitter(TextSplitter): - """Splitting text that looks at characters.""" - - def __init__(self, separator: str = "\n\n", **kwargs: Any) -> None: - """Create a new TextSplitter.""" - super().__init__(**kwargs) - self._separator = separator - - def split_text(self, text: str) -> list[str]: - """Split incoming text and return chunks.""" - # First we naively split the large input into a bunch of smaller ones. - splits = _split_text_with_regex(text, self._separator, self._keep_separator) - _separator = "" if self._keep_separator else self._separator - _good_splits_lengths = [] # cache the lengths of the splits - if splits: - _good_splits_lengths.extend(self._length_function(splits)) - return self._merge_splits(splits, _separator, _good_splits_lengths) - - -class LineType(TypedDict): - """Line type as typed dict.""" - - metadata: dict[str, str] - content: str - - -class HeaderType(TypedDict): - """Header type as typed dict.""" - - level: int - name: str - data: str - - -class MarkdownHeaderTextSplitter: - """Splitting markdown files based on specified headers.""" - - def __init__(self, headers_to_split_on: list[tuple[str, str]], return_each_line: bool = False): - """Create a new MarkdownHeaderTextSplitter. - - Args: - headers_to_split_on: Headers we want to track - return_each_line: Return each line w/ associated headers - """ - # Output line-by-line or aggregated into chunks w/ common headers - self.return_each_line = return_each_line - # Given the headers we want to split on, - # (e.g., "#, ##, etc") order by length - self.headers_to_split_on = sorted(headers_to_split_on, key=lambda split: len(split[0]), reverse=True) - - def aggregate_lines_to_chunks(self, lines: list[LineType]) -> list[Document]: - """Combine lines with common metadata into chunks - Args: - lines: Line of text / associated header metadata - """ - aggregated_chunks: list[LineType] = [] - - for line in lines: - if aggregated_chunks and aggregated_chunks[-1]["metadata"] == line["metadata"]: - # If the last line in the aggregated list - # has the same metadata as the current line, - # append the current content to the last lines's content - aggregated_chunks[-1]["content"] += " \n" + line["content"] - else: - # Otherwise, append the current line to the aggregated list - aggregated_chunks.append(line) - - return [Document(page_content=chunk["content"], metadata=chunk["metadata"]) for chunk in aggregated_chunks] - - def split_text(self, text: str) -> list[Document]: - """Split markdown file - Args: - text: Markdown file""" - - # Split the input text by newline character ("\n"). - lines = text.split("\n") - # Final output - lines_with_metadata: list[LineType] = [] - # Content and metadata of the chunk currently being processed - current_content: list[str] = [] - current_metadata: dict[str, str] = {} - # Keep track of the nested header structure - # header_stack: List[Dict[str, Union[int, str]]] = [] - header_stack: list[HeaderType] = [] - initial_metadata: dict[str, str] = {} - - for line in lines: - stripped_line = line.strip() - # Check each line against each of the header types (e.g., #, ##) - for sep, name in self.headers_to_split_on: - # Check if line starts with a header that we intend to split on - if stripped_line.startswith(sep) and ( - # Header with no text OR header is followed by space - # Both are valid conditions that sep is being used a header - len(stripped_line) == len(sep) or stripped_line[len(sep)] == " " - ): - # Ensure we are tracking the header as metadata - if name is not None: - # Get the current header level - current_header_level = sep.count("#") - - # Pop out headers of lower or same level from the stack - while header_stack and header_stack[-1]["level"] >= current_header_level: - # We have encountered a new header - # at the same or higher level - popped_header = header_stack.pop() - # Clear the metadata for the - # popped header in initial_metadata - if popped_header["name"] in initial_metadata: - initial_metadata.pop(popped_header["name"]) - - # Push the current header to the stack - header: HeaderType = { - "level": current_header_level, - "name": name, - "data": stripped_line[len(sep) :].strip(), - } - header_stack.append(header) - # Update initial_metadata with the current header - initial_metadata[name] = header["data"] - - # Add the previous line to the lines_with_metadata - # only if current_content is not empty - if current_content: - lines_with_metadata.append( - { - "content": "\n".join(current_content), - "metadata": current_metadata.copy(), - } - ) - current_content.clear() - - break - else: - if stripped_line: - current_content.append(stripped_line) - elif current_content: - lines_with_metadata.append( - { - "content": "\n".join(current_content), - "metadata": current_metadata.copy(), - } - ) - current_content.clear() - - current_metadata = initial_metadata.copy() - - if current_content: - lines_with_metadata.append({"content": "\n".join(current_content), "metadata": current_metadata}) - - # lines_with_metadata has each line with associated header metadata - # aggregate these into chunks based on common metadata - if not self.return_each_line: - return self.aggregate_lines_to_chunks(lines_with_metadata) - else: - return [ - Document(page_content=chunk["content"], metadata=chunk["metadata"]) for chunk in lines_with_metadata - ] - - -# should be in newer Python versions (3.10+) # @dataclass(frozen=True, kw_only=True, slots=True) @dataclass(frozen=True) class Tokenizer: diff --git a/api/core/workflow/entities/workflow_entities.py b/api/core/workflow/entities/workflow_entities.py deleted file mode 100644 index 8896416f1..000000000 --- a/api/core/workflow/entities/workflow_entities.py +++ /dev/null @@ -1,79 +0,0 @@ -from typing import Optional - -from pydantic import BaseModel - -from core.app.entities.app_invoke_entities import InvokeFrom -from core.workflow.nodes.base import BaseIterationState, BaseLoopState, BaseNode -from models.enums import UserFrom -from models.workflow import Workflow, WorkflowType - -from .node_entities import NodeRunResult -from .variable_pool import VariablePool - - -class WorkflowNodeAndResult: - node: BaseNode - result: Optional[NodeRunResult] = None - - def __init__(self, node: BaseNode, result: Optional[NodeRunResult] = None): - self.node = node - self.result = result - - -class WorkflowRunState: - tenant_id: str - app_id: str - workflow_id: str - workflow_type: WorkflowType - user_id: str - user_from: UserFrom - invoke_from: InvokeFrom - - workflow_call_depth: int - - start_at: float - variable_pool: VariablePool - - total_tokens: int = 0 - - workflow_nodes_and_results: list[WorkflowNodeAndResult] - - class NodeRun(BaseModel): - node_id: str - iteration_node_id: str - loop_node_id: str - - workflow_node_runs: list[NodeRun] - workflow_node_steps: int - - current_iteration_state: Optional[BaseIterationState] - current_loop_state: Optional[BaseLoopState] - - def __init__( - self, - workflow: Workflow, - start_at: float, - variable_pool: VariablePool, - user_id: str, - user_from: UserFrom, - invoke_from: InvokeFrom, - workflow_call_depth: int, - ): - self.workflow_id = workflow.id - self.tenant_id = workflow.tenant_id - self.app_id = workflow.app_id - self.workflow_type = WorkflowType.value_of(workflow.type) - self.user_id = user_id - self.user_from = user_from - self.invoke_from = invoke_from - self.workflow_call_depth = workflow_call_depth - - self.start_at = start_at - self.variable_pool = variable_pool - - self.total_tokens = 0 - - self.workflow_node_steps = 1 - self.workflow_node_runs = [] - self.current_iteration_state = None - self.current_loop_state = None diff --git a/api/core/workflow/workflow_type_encoder.py b/api/core/workflow/workflow_type_encoder.py index 0123fdac1..2c634d25e 100644 --- a/api/core/workflow/workflow_type_encoder.py +++ b/api/core/workflow/workflow_type_encoder.py @@ -1,4 +1,3 @@ -import json from collections.abc import Mapping from typing import Any @@ -8,18 +7,6 @@ from core.file.models import File from core.variables import Segment -class WorkflowRuntimeTypeEncoder(json.JSONEncoder): - def default(self, o: Any): - if isinstance(o, Segment): - return o.value - elif isinstance(o, File): - return o.to_dict() - elif isinstance(o, BaseModel): - return o.model_dump(mode="json") - else: - return super().default(o) - - class WorkflowRuntimeTypeConverter: def to_json_encodable(self, value: Mapping[str, Any] | None) -> Mapping[str, Any] | None: result = self._to_json_encodable_recursive(value) diff --git a/api/libs/helper.py b/api/libs/helper.py index 48126461a..00772d530 100644 --- a/api/libs/helper.py +++ b/api/libs/helper.py @@ -148,25 +148,6 @@ class StrLen: return value -class FloatRange: - """Restrict input to an float in a range (inclusive)""" - - def __init__(self, low, high, argument="argument"): - self.low = low - self.high = high - self.argument = argument - - def __call__(self, value): - value = _get_float(value) - if value < self.low or value > self.high: - error = "Invalid {arg}: {val}. {arg} must be within the range {lo} - {hi}".format( - arg=self.argument, val=value, lo=self.low, hi=self.high - ) - raise ValueError(error) - - return value - - class DatetimeString: def __init__(self, format, argument="argument"): self.format = format diff --git a/api/libs/jsonutil.py b/api/libs/jsonutil.py deleted file mode 100644 index fa2967103..000000000 --- a/api/libs/jsonutil.py +++ /dev/null @@ -1,11 +0,0 @@ -import json - -from pydantic import BaseModel - - -class PydanticModelEncoder(json.JSONEncoder): - def default(self, o): - if isinstance(o, BaseModel): - return o.model_dump() - else: - super().default(o) diff --git a/api/models/model.py b/api/models/model.py index 7e9e91727..2377aeed8 100644 --- a/api/models/model.py +++ b/api/models/model.py @@ -610,14 +610,6 @@ class InstalledApp(Base): return tenant -class ConversationSource(StrEnum): - """This enumeration is designed for use with `Conversation.from_source`.""" - - # NOTE(QuantumGhost): The enumeration members may not cover all possible cases. - API = "api" - CONSOLE = "console" - - class Conversation(Base): __tablename__ = "conversations" __table_args__ = ( diff --git a/api/services/entities/knowledge_entities/knowledge_entities.py b/api/services/entities/knowledge_entities/knowledge_entities.py index 88d4224e9..344c67885 100644 --- a/api/services/entities/knowledge_entities/knowledge_entities.py +++ b/api/services/entities/knowledge_entities/knowledge_entities.py @@ -4,13 +4,6 @@ from typing import Literal, Optional from pydantic import BaseModel -class SegmentUpdateEntity(BaseModel): - content: str - answer: Optional[str] = None - keywords: Optional[list[str]] = None - enabled: Optional[bool] = None - - class ParentMode(StrEnum): FULL_DOC = "full-doc" PARAGRAPH = "paragraph" @@ -153,10 +146,6 @@ class MetadataUpdateArgs(BaseModel): value: Optional[str | int | float] = None -class MetadataValueUpdateArgs(BaseModel): - fields: list[MetadataUpdateArgs] - - class MetadataDetail(BaseModel): id: str name: str