Introduced beartype (#3460)

### What problem does this PR solve?

Introduced [beartype](https://github.com/beartype/beartype) for runtime
type-checking.

### Type of change

- [x] New Feature (non-breaking change which adds functionality)

agent/component/base.py

@@ -19,7 +19,6 @@ import builtins
 import json
 import os
 from functools import partial
-from typing import Tuple, Union
 
 import pandas as pd
 
@@ -417,7 +416,7 @@ class ComponentBase(ABC):
     def _run(self, history, **kwargs):
         raise NotImplementedError()
 
-    def output(self, allow_partial=True) -> Tuple[str, Union[pd.DataFrame, partial]]:
+    def output(self, allow_partial=True) -> tuple[str, pd.DataFrame | partial]:
         o = getattr(self._param, self._param.output_var_name)
         if not isinstance(o, partial) and not isinstance(o, pd.DataFrame):
             if not isinstance(o, list): o = [o]

api/db/db_models.py

@@ -17,7 +17,6 @@ import logging
 import inspect
 import os
 import sys
-import typing
 import operator
 from enum import Enum
 from functools import wraps
@@ -121,13 +120,13 @@ class SerializedField(LongTextField):
                 f"the serialized type {self._serialized_type} is not supported")
 
 
-def is_continuous_field(cls: typing.Type) -> bool:
+def is_continuous_field(cls: type) -> bool:
     if cls in CONTINUOUS_FIELD_TYPE:
         return True
     for p in cls.__bases__:
         if p in CONTINUOUS_FIELD_TYPE:
             return True
-        elif p != Field and p != object:
+        elif p is not Field and p is not object:
             if is_continuous_field(p):
                 return True
     else:
@@ -159,7 +158,7 @@ class BaseModel(Model):
     def to_dict(self):
         return self.__dict__['__data__']
 
-    def to_human_model_dict(self, only_primary_with: list = None):
+    def to_human_model_dict(self, only_primary_with: list | None = None):
         model_dict = self.__dict__['__data__']
 
         if not only_primary_with:

api/db/db_utils.py

@@ -15,7 +15,6 @@
 #
 import operator
 from functools import reduce
-from typing import Dict, Type, Union
 
 from playhouse.pool import PooledMySQLDatabase
 
@@ -87,7 +86,7 @@ supported_operators = {
 
 
 def query_dict2expression(
-        model: Type[DataBaseModel], query: Dict[str, Union[bool, int, str, list, tuple]]):
+        model: type[DataBaseModel], query: dict[str, bool | int | str | list | tuple]):
     expression = []
 
     for field, value in query.items():
@@ -105,8 +104,8 @@ def query_dict2expression(
     return reduce(operator.iand, expression)
 
 
-def query_db(model: Type[DataBaseModel], limit: int = 0, offset: int = 0,
-             query: dict = None, order_by: Union[str, list, tuple] = None):
+def query_db(model: type[DataBaseModel], limit: int = 0, offset: int = 0,
+             query: dict = None, order_by: str | list | tuple | None = None):
     data = model.select()
     if query:
         data = data.where(query_dict2expression(model, query))

api/ragflow_server.py

@@ -14,6 +14,9 @@
 #  limitations under the License.
 #
 
+from beartype.claw import beartype_packages
+beartype_packages(["agent", "api", "deepdoc", "plugins", "rag", "ragflow_sdk"])  # <-- raise exceptions in your code
+
 import logging
 from api.utils.log_utils import initRootLogger
 initRootLogger("ragflow_server")

api/utils/log_utils.py

@@ -28,13 +28,12 @@ def get_project_base_directory():
     )
     return PROJECT_BASE
 
-def initRootLogger(script_path: str, log_level: int = logging.INFO, log_format: str = "%(asctime)-15s %(levelname)-8s %(process)d %(message)s"):
+def initRootLogger(logfile_basename: str, log_level: int = logging.INFO, log_format: str = "%(asctime)-15s %(levelname)-8s %(process)d %(message)s"):
     logger = logging.getLogger()
     if logger.hasHandlers():
         return
 
-    script_name = os.path.basename(script_path)
-    log_path = os.path.abspath(os.path.join(get_project_base_directory(), "logs", f"{os.path.splitext(script_name)[0]}.log"))
+    log_path = os.path.abspath(os.path.join(get_project_base_directory(), "logs", f"{logfile_basename}.log"))
 
     os.makedirs(os.path.dirname(log_path), exist_ok=True)
     logger.setLevel(log_level)
@@ -50,5 +49,5 @@ def initRootLogger(script_path: str, log_level: int = logging.INFO, log_format:
     handler2.setFormatter(formatter)
     logger.addHandler(handler2)
 
-    msg = f"{script_name} log path: {log_path}"
+    msg = f"{logfile_basename} log path: {log_path}"
     logger.info(msg)

api/versions.py

@@ -13,11 +13,9 @@
 #  See the License for the specific language governing permissions and
 #  limitations under the License.
 #
-import dotenv
-import typing
 import subprocess
 
-def get_ragflow_version() -> typing.Optional[str]:
+def get_ragflow_version() -> str:
     return RAGFLOW_VERSION_INFO
 
 
@@ -42,7 +40,7 @@ def get_closest_tag_and_count():
             return closest_tag
         else:
             return f"{commit_id}({closest_tag}~{commits_count})"
-    except Exception as e:
+    except Exception:
         return 'unknown'
 
 

deepdoc/parser/json_parser.py

@@ -3,12 +3,11 @@
 # from https://github.com/langchain-ai/langchain/blob/master/libs/text-splitters/langchain_text_splitters/json.py
 
 import json
-from typing import Any, Dict, List, Optional
+from typing import Any
 from rag.nlp import find_codec
-
 class RAGFlowJsonParser:
     def __init__(
-        self, max_chunk_size: int = 2000, min_chunk_size: Optional[int] = None
+        self, max_chunk_size: int = 2000, min_chunk_size: int | None = None
     ):
         super().__init__()
         self.max_chunk_size = max_chunk_size * 2
@@ -27,12 +26,12 @@ class RAGFlowJsonParser:
         return sections
 
     @staticmethod
-    def _json_size(data: Dict) -> int:
+    def _json_size(data: dict) -> int:
         """Calculate the size of the serialized JSON object."""
         return len(json.dumps(data, ensure_ascii=False))
 
     @staticmethod
-    def _set_nested_dict(d: Dict, path: List[str], value: Any) -> None:
+    def _set_nested_dict(d: dict, path: list[str], value: Any) -> None:
         """Set a value in a nested dictionary based on the given path."""
         for key in path[:-1]:
             d = d.setdefault(key, {})
@@ -54,10 +53,10 @@ class RAGFlowJsonParser:
         
     def _json_split(
         self,
-        data: Dict[str, Any],
-        current_path: Optional[List[str]] = None,
-        chunks: Optional[List[Dict]] = None,
-    ) -> List[Dict]:
+        data: dict[str, Any],
+        current_path: list[str] | None,
+        chunks: list[dict] | None,
+    ) -> list[dict]:
         """
         Split json into maximum size dictionaries while preserving structure.
         """
@@ -87,9 +86,9 @@ class RAGFlowJsonParser:
 
     def split_json(
         self,
-        json_data: Dict[str, Any],
+        json_data: dict[str, Any],
         convert_lists: bool = False,
-    ) -> List[Dict]:
+    ) -> list[dict]:
         """Splits JSON into a list of JSON chunks"""
 
         if convert_lists:
@@ -104,10 +103,10 @@ class RAGFlowJsonParser:
 
     def split_text(
         self,
-        json_data: Dict[str, Any],
+        json_data: dict[str, Any],
         convert_lists: bool = False,
         ensure_ascii: bool = True,
-    ) -> List[str]:
+    ) -> list[str]:
         """Splits JSON into a list of JSON formatted strings"""
 
         chunks = self.split_json(json_data=json_data, convert_lists=convert_lists)

docs/references/python_api_reference.md

@@ -1059,7 +1059,7 @@ Deletes chat assistants by ID.
 
 #### ids: `list[str]`
 
-The IDs of the chat assistants to delete. Defaults to `None`. If it is ot specified, all chat assistants in the system will be deleted.
+The IDs of the chat assistants to delete. Defaults to `None`. If it is empty or not specified, all chat assistants in the system will be deleted.
 
 ### Returns
 

graphrag/community_reports_extractor.py

@@ -9,8 +9,8 @@ import logging
 import json
 import re
 import traceback
+from typing import Callable
 from dataclasses import dataclass
-from typing import List, Callable
 import networkx as nx
 import pandas as pd
 from graphrag import leiden
@@ -26,8 +26,8 @@ from timeit import default_timer as timer
 class CommunityReportsResult:
     """Community reports result class definition."""
 
-    output: List[str]
-    structured_output: List[dict]
+    output: list[str]
+    structured_output: list[dict]
 
 
 class CommunityReportsExtractor:
@@ -53,7 +53,7 @@ class CommunityReportsExtractor:
         self._max_report_length = max_report_length or 1500
 
     def __call__(self, graph: nx.Graph, callback: Callable | None = None):
-        communities: dict[str, dict[str, List]] = leiden.run(graph, {})
+        communities: dict[str, dict[str, list]] = leiden.run(graph, {})
         total = sum([len(comm.items()) for _, comm in communities.items()])
         relations_df = pd.DataFrame([{"source":s, "target": t, **attr} for s, t, attr in graph.edges(data=True)])
         res_str = []

graphrag/entity_embedding.py

@@ -6,7 +6,6 @@ Reference:
 """
 
 from typing import Any
-
 import numpy as np
 import networkx as nx
 from graphrag.leiden import stable_largest_connected_component

graphrag/graph_extractor.py

@@ -9,8 +9,8 @@ import logging
 import numbers
 import re
 import traceback
+from typing import Any, Callable
 from dataclasses import dataclass
-from typing import Any, Mapping, Callable
 import tiktoken
 from graphrag.graph_prompt import GRAPH_EXTRACTION_PROMPT, CONTINUE_PROMPT, LOOP_PROMPT
 from graphrag.utils import ErrorHandlerFn, perform_variable_replacements, clean_str

graphrag/index.py

@@ -18,7 +18,6 @@ import os
 from concurrent.futures import ThreadPoolExecutor
 import json
 from functools import reduce
-from typing import List
 import networkx as nx
 from api.db import LLMType
 from api.db.services.llm_service import LLMBundle
@@ -53,7 +52,7 @@ def graph_merge(g1, g2):
     return g
 
 
-def build_knowledge_graph_chunks(tenant_id: str, chunks: List[str], callback, entity_types=DEFAULT_ENTITY_TYPES):
+def build_knowledge_graph_chunks(tenant_id: str, chunks: list[str], callback, entity_types=DEFAULT_ENTITY_TYPES):
     _, tenant = TenantService.get_by_id(tenant_id)
     llm_bdl = LLMBundle(tenant_id, LLMType.CHAT, tenant.llm_id)
     ext = GraphExtractor(llm_bdl)

graphrag/leiden.py

@@ -6,8 +6,8 @@ Reference:
 """
 
 import logging
-from typing import Any, cast, List
 import html
+from typing import Any
 from graspologic.partition import hierarchical_leiden
 from graspologic.utils import largest_connected_component
 
@@ -132,7 +132,7 @@ def run(graph: nx.Graph, args: dict[str, Any]) -> dict[int, dict[str, dict]]:
     return results_by_level
 
 
-def add_community_info2graph(graph: nx.Graph, nodes: List[str], community_title):
+def add_community_info2graph(graph: nx.Graph, nodes: list[str], community_title):
     for n in nodes:
         if "communities" not in graph.nodes[n]:
             graph.nodes[n]["communities"] = []

graphrag/mind_map_extractor.py

@@ -19,9 +19,9 @@ import collections
 import os
 import re
 import traceback
+from typing import Any
 from concurrent.futures import ThreadPoolExecutor
 from dataclasses import dataclass
-from typing import Any
 
 from graphrag.mind_map_prompt import MIND_MAP_EXTRACTION_PROMPT
 from graphrag.utils import ErrorHandlerFn, perform_variable_replacements

graphrag/search.py

@@ -15,7 +15,6 @@
 #
 import json
 from copy import deepcopy
-from typing import Dict
 
 import pandas as pd
 from rag.utils.doc_store_conn import OrderByExpr, FusionExpr
@@ -25,7 +24,7 @@ from rag.nlp.search import Dealer
 
 class KGSearch(Dealer):
     def search(self, req, idxnm, kb_ids, emb_mdl, highlight=False):
-        def merge_into_first(sres, title="") -> Dict[str, str]:
+        def merge_into_first(sres, title="") -> dict[str, str]:
             if not sres:
                 return {}
             content_with_weight = ""

graphrag/utils.py

@@ -7,8 +7,7 @@ Reference:
 
 import html
 import re
-from collections.abc import Callable
-from typing import Any
+from typing import Any, Callable
 
 ErrorHandlerFn = Callable[[BaseException | None, str | None, dict | None], None]
 

poetry.lock

@@ -1,4 +1,4 @@
-# This file is automatically @generated by Poetry 1.8.2 and should not be changed by hand.
+# This file is automatically @generated by Poetry 1.8.4 and should not be changed by hand.
 
 [[package]]
 name = "accelerate"
@@ -413,7 +413,7 @@ name = "aspose-slides"
 version = "24.11.0"
 description = "Aspose.Slides for Python via .NET is a presentation file formats processing library for working with Microsoft PowerPoint files without using Microsoft PowerPoint."
 optional = false
-python-versions = "<3.14,>=3.5"
+python-versions = ">=3.5,<3.14"
 files = [
     {file = "Aspose.Slides-24.11.0-py3-none-macosx_10_14_x86_64.whl", hash = "sha256:b4819364497f9e075e00e63ee8fba8745dda4c910e199d5201e4abeebdcdec89"},
     {file = "Aspose.Slides-24.11.0-py3-none-macosx_11_0_arm64.whl", hash = "sha256:bbeb5f0b14901f29f209beeac694a183f8d36c9475556ddeed3b2edb8107536a"},
@@ -565,7 +565,7 @@ name = "bce-python-sdk"
 version = "0.9.23"
 description = "BCE SDK for python"
 optional = false
-python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,<4,>=2.7"
+python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, <4"
 files = [
     {file = "bce_python_sdk-0.9.23-py3-none-any.whl", hash = "sha256:8debe21a040e00060f6044877d594765ed7b18bc765c6bf16b878bca864140a3"},
     {file = "bce_python_sdk-0.9.23.tar.gz", hash = "sha256:19739fed5cd0725356fc5ffa2acbdd8fb23f2a81edb91db21a03174551d0cf41"},
@@ -1706,7 +1706,7 @@ name = "deprecated"
 version = "1.2.15"
 description = "Python @deprecated decorator to deprecate old python classes, functions or methods."
 optional = false
-python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,>=2.7"
+python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
 files = [
     {file = "Deprecated-1.2.15-py2.py3-none-any.whl", hash = "sha256:353bc4a8ac4bfc96800ddab349d89c25dec1079f65fd53acdcc1e0b975b21320"},
     {file = "deprecated-1.2.15.tar.gz", hash = "sha256:683e561a90de76239796e6b6feac66b99030d2dd3fcf61ef996330f14bbb9b0d"},
@@ -2023,7 +2023,7 @@ name = "fastembed"
 version = "0.3.6"
 description = "Fast, light, accurate library built for retrieval embedding generation"
 optional = false
-python-versions = "<3.13,>=3.8.0"
+python-versions = ">=3.8.0,<3.13"
 files = [
     {file = "fastembed-0.3.6-py3-none-any.whl", hash = "sha256:2bf70edae28bb4ccd9e01617098c2075b0ba35b88025a3d22b0e1e85b2c488ce"},
     {file = "fastembed-0.3.6.tar.gz", hash = "sha256:c93c8ec99b8c008c2d192d6297866b8d70ec7ac8f5696b34eb5ea91f85efd15f"},
@@ -2940,7 +2940,7 @@ name = "graspologic"
 version = "3.4.1"
 description = "A set of Python modules for graph statistics"
 optional = false
-python-versions = "<3.13,>=3.9"
+python-versions = ">=3.9,<3.13"
 files = [
     {file = "graspologic-3.4.1-py3-none-any.whl", hash = "sha256:c6563e087eda599bad1de831d4b7321c0daa7a82f4e85a7d7737ff67e07cdda2"},
     {file = "graspologic-3.4.1.tar.gz", hash = "sha256:7561f0b852a2bccd351bff77e8db07d9892f9dfa35a420fdec01690e4fdc8075"},
@@ -3625,7 +3625,7 @@ name = "infinity-emb"
 version = "0.0.66"
 description = "Infinity is a high-throughput, low-latency REST API for serving text-embeddings, reranking models and clip."
 optional = false
-python-versions = "<4,>=3.9"
+python-versions = ">=3.9,<4"
 files = [
     {file = "infinity_emb-0.0.66-py3-none-any.whl", hash = "sha256:1dc6ed9fa48e6cbe83650a7583dbbb4bc393900c39c326bb0aff2ddc090ac018"},
     {file = "infinity_emb-0.0.66.tar.gz", hash = "sha256:9c9a361ccebf8e8f626c1f685286518d03d0c35e7d14179ae7c2500b4fc68b98"},
@@ -4070,7 +4070,7 @@ name = "litellm"
 version = "1.48.0"
 description = "Library to easily interface with LLM API providers"
 optional = false
-python-versions = "!=2.7.*,!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,!=3.6.*,!=3.7.*,>=3.8"
+python-versions = ">=3.8, !=2.7.*, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*, !=3.6.*, !=3.7.*"
 files = [
     {file = "litellm-1.48.0-py3-none-any.whl", hash = "sha256:7765e8a92069778f5fc66aacfabd0e2f8ec8d74fb117f5e475567d89b0d376b9"},
     {file = "litellm-1.48.0.tar.gz", hash = "sha256:31a9b8a25a9daf44c24ddc08bf74298da920f2c5cea44135e5061278d0aa6fc9"},
@@ -6197,7 +6197,7 @@ name = "psutil"
 version = "6.1.0"
 description = "Cross-platform lib for process and system monitoring in Python."
 optional = false
-python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,>=2.7"
+python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*"
 files = [
     {file = "psutil-6.1.0-cp27-cp27m-macosx_10_9_x86_64.whl", hash = "sha256:ff34df86226c0227c52f38b919213157588a678d049688eded74c76c8ba4a5d0"},
     {file = "psutil-6.1.0-cp27-cp27m-manylinux2010_i686.whl", hash = "sha256:c0e0c00aa18ca2d3b2b991643b799a15fc8f0563d2ebb6040f64ce8dc027b942"},
@@ -6219,8 +6219,8 @@ files = [
 ]
 
 [package.extras]
-dev = ["black", "check-manifest", "coverage", "packaging", "pylint", "pyperf", "pypinfo", "pytest-cov", "requests", "rstcheck", "ruff", "sphinx", "sphinx_rtd_theme", "toml-sort", "twine", "virtualenv", "wheel"]
-test = ["pytest", "pytest-xdist", "setuptools"]
+dev = ["black", "check-manifest", "coverage", "packaging", "pylint", "pyperf", "pypinfo", "pytest-cov", "requests", "rstcheck", "ruff", "sphinx", "sphinx-rtd-theme", "toml-sort", "twine", "virtualenv", "wheel"]
+test = ["enum34", "futures", "ipaddress", "mock (==1.0.1)", "pytest (==4.6.11)", "pytest-xdist", "setuptools", "unittest2"]
 
 [[package]]
 name = "psycopg2-binary"
@@ -7690,40 +7690,30 @@ files = [
     {file = "ruamel.yaml.clib-0.2.12-cp310-cp310-manylinux2014_aarch64.whl", hash = "sha256:a606ef75a60ecf3d924613892cc603b154178ee25abb3055db5062da811fd969"},
     {file = "ruamel.yaml.clib-0.2.12-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:fd5415dded15c3822597455bc02bcd66e81ef8b7a48cb71a33628fc9fdde39df"},
     {file = "ruamel.yaml.clib-0.2.12-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:f66efbc1caa63c088dead1c4170d148eabc9b80d95fb75b6c92ac0aad2437d76"},
-    {file = "ruamel.yaml.clib-0.2.12-cp310-cp310-musllinux_1_1_i686.whl", hash = "sha256:22353049ba4181685023b25b5b51a574bce33e7f51c759371a7422dcae5402a6"},
-    {file = "ruamel.yaml.clib-0.2.12-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:932205970b9f9991b34f55136be327501903f7c66830e9760a8ffb15b07f05cd"},
     {file = "ruamel.yaml.clib-0.2.12-cp310-cp310-win32.whl", hash = "sha256:3eac5a91891ceb88138c113f9db04f3cebdae277f5d44eaa3651a4f573e6a5da"},
     {file = "ruamel.yaml.clib-0.2.12-cp310-cp310-win_amd64.whl", hash = "sha256:ab007f2f5a87bd08ab1499bdf96f3d5c6ad4dcfa364884cb4549aa0154b13a28"},
     {file = "ruamel.yaml.clib-0.2.12-cp311-cp311-macosx_13_0_arm64.whl", hash = "sha256:4a6679521a58256a90b0d89e03992c15144c5f3858f40d7c18886023d7943db6"},
     {file = "ruamel.yaml.clib-0.2.12-cp311-cp311-manylinux2014_aarch64.whl", hash = "sha256:d84318609196d6bd6da0edfa25cedfbabd8dbde5140a0a23af29ad4b8f91fb1e"},
     {file = "ruamel.yaml.clib-0.2.12-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:bb43a269eb827806502c7c8efb7ae7e9e9d0573257a46e8e952f4d4caba4f31e"},
     {file = "ruamel.yaml.clib-0.2.12-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:811ea1594b8a0fb466172c384267a4e5e367298af6b228931f273b111f17ef52"},
-    {file = "ruamel.yaml.clib-0.2.12-cp311-cp311-musllinux_1_1_i686.whl", hash = "sha256:cf12567a7b565cbf65d438dec6cfbe2917d3c1bdddfce84a9930b7d35ea59642"},
-    {file = "ruamel.yaml.clib-0.2.12-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:7dd5adc8b930b12c8fc5b99e2d535a09889941aa0d0bd06f4749e9a9397c71d2"},
     {file = "ruamel.yaml.clib-0.2.12-cp311-cp311-win32.whl", hash = "sha256:bd0a08f0bab19093c54e18a14a10b4322e1eacc5217056f3c063bd2f59853ce4"},
     {file = "ruamel.yaml.clib-0.2.12-cp311-cp311-win_amd64.whl", hash = "sha256:a274fb2cb086c7a3dea4322ec27f4cb5cc4b6298adb583ab0e211a4682f241eb"},
     {file = "ruamel.yaml.clib-0.2.12-cp312-cp312-macosx_14_0_arm64.whl", hash = "sha256:20b0f8dc160ba83b6dcc0e256846e1a02d044e13f7ea74a3d1d56ede4e48c632"},
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-    {file = "ruamel.yaml.clib-0.2.12-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:e143ada795c341b56de9418c58d028989093ee611aa27ffb9b7f609c00d813ed"},
     {file = "ruamel.yaml.clib-0.2.12-cp39-cp39-win32.whl", hash = "sha256:beffaed67936fbbeffd10966a4eb53c402fafd3d6833770516bf7314bc6ffa12"},
     {file = "ruamel.yaml.clib-0.2.12-cp39-cp39-win_amd64.whl", hash = "sha256:040ae85536960525ea62868b642bdb0c2cc6021c9f9d507810c0c604e66f5a7b"},
     {file = "ruamel.yaml.clib-0.2.12.tar.gz", hash = "sha256:6c8fbb13ec503f99a91901ab46e0b07ae7941cd527393187039aec586fdfd36f"},
@@ -7734,7 +7724,7 @@ name = "s3transfer"
 version = "0.10.3"
 description = "An Amazon S3 Transfer Manager"
 optional = false
-python-versions = ">=3.8"
+python-versions = ">= 3.8"
 files = [
     {file = "s3transfer-0.10.3-py3-none-any.whl", hash = "sha256:263ed587a5803c6c708d3ce44dc4dfedaab4c1a32e8329bab818933d79ddcf5d"},
     {file = "s3transfer-0.10.3.tar.gz", hash = "sha256:4f50ed74ab84d474ce614475e0b8d5047ff080810aac5d01ea25231cfc944b0c"},
@@ -8196,7 +8186,7 @@ name = "smart-open"
 version = "7.0.5"
 description = "Utils for streaming large files (S3, HDFS, GCS, Azure Blob Storage, gzip, bz2...)"
 optional = false
-python-versions = "<4.0,>=3.7"
+python-versions = ">=3.7,<4.0"
 files = [
     {file = "smart_open-7.0.5-py3-none-any.whl", hash = "sha256:8523ed805c12dff3eaa50e9c903a6cb0ae78800626631c5fe7ea073439847b89"},
     {file = "smart_open-7.0.5.tar.gz", hash = "sha256:d3672003b1dbc85e2013e4983b88eb9a5ccfd389b0d4e5015f39a9ee5620ec18"},
@@ -9967,4 +9957,4 @@ cffi = ["cffi (>=1.11)"]
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.11,<3.13"
-content-hash = "045015d496b77682204fcdb5b2576ebf8f7efcf8340e1e9839de246d9d39c08a"
+content-hash = "dcf6c6a1d7fc52f982ef717bc48b13837e693b53a4fc5d9c06cefd253227259f"

pyproject.toml

@@ -17,6 +17,7 @@ azure-storage-file-datalake = "12.16.0"
 anthropic = "=0.34.1"
 arxiv = "2.1.3"
 aspose-slides = { version = "^24.9.0", markers = "platform_machine == 'x86_64'" }
+beartype = "^0.18.5"
 bio = "1.7.1"
 boto3 = "1.34.140"
 botocore = "1.34.140"

rag/llm/embedding_model.py

@@ -15,7 +15,6 @@
 #
 import logging
 import re
-from typing import Optional
 import threading
 import requests
 from huggingface_hub import snapshot_download
@@ -242,10 +241,10 @@ class FastEmbed(Base):
 
     def __init__(
             self,
-            key: Optional[str] = None,
+            key: str | None = None,
             model_name: str = "BAAI/bge-small-en-v1.5",
-            cache_dir: Optional[str] = None,
-            threads: Optional[int] = None,
+            cache_dir: str | None = None,
+            threads: int | None = None,
             **kwargs,
     ):
         if not settings.LIGHTEN and not FastEmbed._model:

rag/nlp/search.py

@@ -17,7 +17,6 @@
 import logging
 import re
 import json
-from typing import List, Optional, Dict, Union
 from dataclasses import dataclass
 
 from rag.utils import rmSpace
@@ -37,13 +36,13 @@ class Dealer:
     @dataclass
     class SearchResult:
         total: int
-        ids: List[str]
-        query_vector: List[float] = None
-        field: Optional[Dict] = None
-        highlight: Optional[Dict] = None
-        aggregation: Union[List, Dict, None] = None
-        keywords: Optional[List[str]] = None
-        group_docs: List[List] = None
+        ids: list[str]
+        query_vector: list[float] | None = None
+        field: dict | None = None
+        highlight: dict | None = None
+        aggregation: list | dict | None = None
+        keywords: list[str] | None = None
+        group_docs: list[list] | None = None
 
     def get_vector(self, txt, emb_mdl, topk=10, similarity=0.1):
         qv, _ = emb_mdl.encode_queries(txt)

rag/raptor.py

@@ -17,7 +17,6 @@ import logging
 import re
 from concurrent.futures import ThreadPoolExecutor, ALL_COMPLETED, wait
 from threading import Lock
-from typing import Tuple
 import umap
 import numpy as np
 from sklearn.mixture import GaussianMixture
@@ -45,7 +44,7 @@ class RecursiveAbstractiveProcessing4TreeOrganizedRetrieval:
         optimal_clusters = n_clusters[np.argmin(bics)]
         return optimal_clusters
 
-    def __call__(self, chunks: Tuple[str, np.ndarray], random_state, callback=None):
+    def __call__(self, chunks: tuple[str, np.ndarray], random_state, callback=None):
         layers = [(0, len(chunks))]
         start, end = 0, len(chunks)
         if len(chunks) <= 1: return

rag/svr/task_executor.py

@@ -13,6 +13,9 @@
 #  See the License for the specific language governing permissions and
 #  limitations under the License.
 #
+from beartype.claw import beartype_packages
+beartype_packages(["agent", "api", "deepdoc", "plugins", "rag", "ragflow_sdk"])  # <-- raise exceptions in your code
+
 import logging
 import sys
 from api.utils.log_utils import initRootLogger

rag/utils/doc_store_conn.py

@@ -1,19 +1,17 @@
 from abc import ABC, abstractmethod
-from typing import Optional, Union
 from dataclasses import dataclass
 import numpy as np
 import polars as pl
-from typing import List, Dict
 
 DEFAULT_MATCH_VECTOR_TOPN = 10
 DEFAULT_MATCH_SPARSE_TOPN = 10
-VEC = Union[list, np.ndarray]
+VEC = list | np.ndarray
 
 
 @dataclass
 class SparseVector:
     indices: list[int]
-    values: Union[list[float], list[int], None] = None
+    values: list[float] | list[int] | None = None
 
     def __post_init__(self):
         assert (self.values is None) or (len(self.indices) == len(self.values))
@@ -82,7 +80,7 @@ class MatchSparseExpr(ABC):
         sparse_data: SparseVector | dict,
         distance_type: str,
         topn: int,
-        opt_params: Optional[dict] = None,
+        opt_params: dict | None = None,
     ):
         self.vector_column_name = vector_column_name
         self.sparse_data = sparse_data
@@ -98,7 +96,7 @@ class MatchTensorExpr(ABC):
         query_data: VEC,
         query_data_type: str,
         topn: int,
-        extra_option: Optional[dict] = None,
+        extra_option: dict | None = None,
     ):
         self.column_name = column_name
         self.query_data = query_data
@@ -108,16 +106,13 @@ class MatchTensorExpr(ABC):
 
 
 class FusionExpr(ABC):
-    def __init__(self, method: str, topn: int, fusion_params: Optional[dict] = None):
+    def __init__(self, method: str, topn: int, fusion_params: dict | None = None):
         self.method = method
         self.topn = topn
         self.fusion_params = fusion_params
 
 
-MatchExpr = Union[
-    MatchTextExpr, MatchDenseExpr, MatchSparseExpr, MatchTensorExpr, FusionExpr
-]
-
+MatchExpr = MatchTextExpr | MatchDenseExpr | MatchSparseExpr | MatchTensorExpr | FusionExpr
 
 class OrderByExpr(ABC):
     def __init__(self):
@@ -229,11 +224,11 @@ class DocStoreConnection(ABC):
         raise NotImplementedError("Not implemented")
 
     @abstractmethod
-    def getFields(self, res, fields: List[str]) -> Dict[str, dict]:
+    def getFields(self, res, fields: list[str]) -> dict[str, dict]:
         raise NotImplementedError("Not implemented")
 
     @abstractmethod
-    def getHighlight(self, res, keywords: List[str], fieldnm: str):
+    def getHighlight(self, res, keywords: list[str], fieldnm: str):
         raise NotImplementedError("Not implemented")
 
     @abstractmethod

rag/utils/es_conn.py

@@ -3,7 +3,6 @@ import re
 import json
 import time
 import os
-from typing import List, Dict
 
 import copy
 from elasticsearch import Elasticsearch
@@ -363,7 +362,7 @@ class ESConnection(DocStoreConnection):
             rr.append(d["_source"])
         return rr
 
-    def getFields(self, res, fields: List[str]) -> Dict[str, dict]:
+    def getFields(self, res, fields: list[str]) -> dict[str, dict]:
         res_fields = {}
         if not fields:
             return {}
@@ -382,7 +381,7 @@ class ESConnection(DocStoreConnection):
                 res_fields[d["id"]] = m
         return res_fields
 
-    def getHighlight(self, res, keywords: List[str], fieldnm: str):
+    def getHighlight(self, res, keywords: list[str], fieldnm: str):
         ans = {}
         for d in res["hits"]["hits"]:
             hlts = d.get("highlight")

rag/utils/infinity_conn.py

@@ -3,7 +3,6 @@ import os
 import re
 import json
 import time
-from typing import List, Dict
 import infinity
 from infinity.common import ConflictType, InfinityException
 from infinity.index import IndexInfo, IndexType
@@ -384,7 +383,7 @@ class InfinityConnection(DocStoreConnection):
     def getChunkIds(self, res):
         return list(res["id"])
 
-    def getFields(self, res, fields: List[str]) -> Dict[str, dict]:
+    def getFields(self, res, fields: list[str]) -> list[str, dict]:
         res_fields = {}
         if not fields:
             return {}
@@ -412,7 +411,7 @@ class InfinityConnection(DocStoreConnection):
             res_fields[id] = m
         return res_fields
 
-    def getHighlight(self, res, keywords: List[str], fieldnm: str):
+    def getHighlight(self, res, keywords: list[str], fieldnm: str):
         ans = {}
         num_rows = len(res)
         column_id = res["id"]

sdk/python/poetry.lock

@@ -1,5 +1,23 @@
 # This file is automatically @generated by Poetry 1.8.4 and should not be changed by hand.
 
+[[package]]
+name = "beartype"
+version = "0.18.5"
+description = "Unbearably fast runtime type checking in pure Python."
+optional = false
+python-versions = ">=3.8.0"
+files = [
+    {file = "beartype-0.18.5-py3-none-any.whl", hash = "sha256:5301a14f2a9a5540fe47ec6d34d758e9cd8331d36c4760fc7a5499ab86310089"},
+    {file = "beartype-0.18.5.tar.gz", hash = "sha256:264ddc2f1da9ec94ff639141fbe33d22e12a9f75aa863b83b7046ffff1381927"},
+]
+
+[package.extras]
+all = ["typing-extensions (>=3.10.0.0)"]
+dev = ["autoapi (>=0.9.0)", "coverage (>=5.5)", "equinox", "mypy (>=0.800)", "numpy", "pandera", "pydata-sphinx-theme (<=0.7.2)", "pytest (>=4.0.0)", "sphinx", "sphinx (>=4.2.0,<6.0.0)", "sphinxext-opengraph (>=0.7.5)", "tox (>=3.20.1)", "typing-extensions (>=3.10.0.0)"]
+doc-rtd = ["autoapi (>=0.9.0)", "pydata-sphinx-theme (<=0.7.2)", "sphinx (>=4.2.0,<6.0.0)", "sphinxext-opengraph (>=0.7.5)"]
+test-tox = ["equinox", "mypy (>=0.800)", "numpy", "pandera", "pytest (>=4.0.0)", "sphinx", "typing-extensions (>=3.10.0.0)"]
+test-tox-coverage = ["coverage (>=5.5)"]
+
 [[package]]
 name = "certifi"
 version = "2024.8.30"
@@ -177,13 +195,13 @@ files = [
 
 [[package]]
 name = "packaging"
-version = "24.1"
+version = "24.2"
 description = "Core utilities for Python packages"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "packaging-24.1-py3-none-any.whl", hash = "sha256:5b8f2217dbdbd2f7f384c41c628544e6d52f2d0f53c6d0c3ea61aa5d1d7ff124"},
-    {file = "packaging-24.1.tar.gz", hash = "sha256:026ed72c8ed3fcce5bf8950572258698927fd1dbda10a5e981cdf0ac37f4f002"},
+    {file = "packaging-24.2-py3-none-any.whl", hash = "sha256:09abb1bccd265c01f4a3aa3f7a7db064b36514d2cba19a2f694fe6150451a759"},
+    {file = "packaging-24.2.tar.gz", hash = "sha256:c228a6dc5e932d346bc5739379109d49e8853dd8223571c7c5b55260edc0b97f"},
 ]
 
 [[package]]
@@ -246,13 +264,13 @@ use-chardet-on-py3 = ["chardet (>=3.0.2,<6)"]
 
 [[package]]
 name = "tomli"
-version = "2.0.2"
+version = "2.1.0"
 description = "A lil' TOML parser"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "tomli-2.0.2-py3-none-any.whl", hash = "sha256:2ebe24485c53d303f690b0ec092806a085f07af5a5aa1464f3931eec36caaa38"},
-    {file = "tomli-2.0.2.tar.gz", hash = "sha256:d46d457a85337051c36524bc5349dd91b1877838e2979ac5ced3e710ed8a60ed"},
+    {file = "tomli-2.1.0-py3-none-any.whl", hash = "sha256:a5c57c3d1c56f5ccdf89f6523458f60ef716e210fc47c4cfb188c5ba473e0391"},
+    {file = "tomli-2.1.0.tar.gz", hash = "sha256:3f646cae2aec94e17d04973e4249548320197cfabdf130015d023de4b74d8ab8"},
 ]
 
 [[package]]
@@ -275,4 +293,4 @@ zstd = ["zstandard (>=0.18.0)"]
 [metadata]
 lock-version = "2.0"
 python-versions = "^3.10"
-content-hash = "202bfd3e121f1d57a2f9c9d91cd7a50eacf2362cd1995c9f6347bcb100cf9336"
+content-hash = "19565d31d822b0573f505662c664d735194134a505f43bbd1657c033f87bb82d"

sdk/python/pyproject.toml

@@ -10,6 +10,7 @@ package-mode = true
 [tool.poetry.dependencies]
 python = "^3.10"
 requests = "^2.30.0"
+beartype = "^0.18.5"
 pytest = "^8.0.0"
 
 

sdk/python/ragflow_sdk/__init__.py

@@ -1,3 +1,6 @@
+from beartype.claw import beartype_this_package
+beartype_this_package()  # <-- raise exceptions in your code
+
 import importlib.metadata
 
 __version__ = importlib.metadata.version("ragflow_sdk")

sdk/python/ragflow_sdk/modules/chat.py

@@ -1,4 +1,3 @@
-from typing import List
 
 from .base import Base
 from .session import Session
@@ -58,7 +57,7 @@ class Chat(Base):
         raise Exception(res["message"])
 
     def list_sessions(self,page: int = 1, page_size: int = 30, orderby: str = "create_time", desc: bool = True,
-                      id: str = None, name: str = None) -> List[Session]:
+                      id: str = None, name: str = None) -> list[Session]:
         res = self.get(f'/chats/{self.id}/sessions',{"page": page, "page_size": page_size, "orderby": orderby, "desc": desc, "id": id, "name": name} )
         res = res.json()
         if res.get("code") == 0:
@@ -68,7 +67,7 @@ class Chat(Base):
             return result_list
         raise Exception(res["message"])
 
-    def delete_sessions(self,ids:List[str]=None):
+    def delete_sessions(self,ids: list[str] | None = None):
         res = self.rm(f"/chats/{self.id}/sessions", {"ids": ids})
         res = res.json()
         if res.get("code") != 0:

sdk/python/ragflow_sdk/modules/dataset.py

@@ -1,5 +1,3 @@
-from typing import List
-
 from .document import Document
 
 from .base import Base
@@ -35,7 +33,7 @@ class DataSet(Base):
         if res.get("code") != 0:
             raise Exception(res["message"])
 
-    def upload_documents(self,document_list: List[dict]):
+    def upload_documents(self,document_list: list[dict]):
         url = f"/datasets/{self.id}/documents"
         files = [("file",(ele["displayed_name"],ele["blob"])) for ele in document_list]
         res = self.post(path=url,json=None,files=files)
@@ -48,7 +46,7 @@ class DataSet(Base):
             return doc_list
         raise Exception(res.get("message"))
 
-    def list_documents(self, id: str = None, keywords: str = None, page: int =1, page_size: int = 30, orderby: str = "create_time", desc: bool = True):
+    def list_documents(self, id: str | None = None, keywords: str | None = None, page: int = 1, page_size: int = 30, orderby: str = "create_time", desc: bool = True):
         res = self.get(f"/datasets/{self.id}/documents",params={"id": id,"keywords": keywords,"page": page,"page_size": page_size,"orderby": orderby,"desc": desc})
         res = res.json()
         documents = []
@@ -58,7 +56,7 @@ class DataSet(Base):
             return documents
         raise Exception(res["message"])
 
-    def delete_documents(self,ids: List[str] = None):
+    def delete_documents(self,ids: list[str] | None = None):
         res = self.rm(f"/datasets/{self.id}/documents",{"ids":ids})
         res = res.json()
         if res.get("code") != 0:

sdk/python/ragflow_sdk/modules/document.py

@@ -1,7 +1,6 @@
 import json
 from .base import Base
 from .chunk import Chunk
-from typing import List
 
 
 class Document(Base):
@@ -63,14 +62,14 @@ class Document(Base):
         raise Exception(res.get("message"))
 
 
-    def add_chunk(self, content: str,important_keywords:List[str]=[]):
+    def add_chunk(self, content: str,important_keywords: list[str] = []):
         res = self.post(f'/datasets/{self.dataset_id}/documents/{self.id}/chunks', {"content":content,"important_keywords":important_keywords})
         res = res.json()
         if res.get("code") == 0:
             return Chunk(self.rag,res["data"].get("chunk"))
         raise Exception(res.get("message"))
 
-    def delete_chunks(self,ids:List[str] = None):
+    def delete_chunks(self,ids:list[str] | None = None):
         res = self.rm(f"/datasets/{self.dataset_id}/documents/{self.id}/chunks",{"chunk_ids":ids})
         res = res.json()
         if res.get("code")!=0:

sdk/python/ragflow_sdk/ragflow.py

@@ -13,14 +13,11 @@
 #  See the License for the specific language governing permissions and
 #  limitations under the License.
 
-from typing import List
-
 import requests
 
 from .modules.chat import Chat
 from .modules.chunk import Chunk
 from .modules.dataset import DataSet
-from .modules.document import Document
 
 
 class RAGFlow:
@@ -64,7 +61,7 @@ class RAGFlow:
             return DataSet(self, res["data"])
         raise Exception(res["message"])
 
-    def delete_datasets(self, ids: List[str] = None):
+    def delete_datasets(self, ids: list[str] | None = None):
         res = self.delete("/datasets",{"ids": ids})
         res=res.json()
         if res.get("code") != 0:
@@ -77,8 +74,8 @@ class RAGFlow:
         raise Exception("Dataset %s not found" % name)
 
     def list_datasets(self, page: int = 1, page_size: int = 30, orderby: str = "create_time", desc: bool = True,
-                      id: str = None, name: str = None) -> \
-            List[DataSet]:
+                      id: str | None = None, name: str | None = None) -> \
+            list[DataSet]:
         res = self.get("/datasets",
                        {"page": page, "page_size": page_size, "orderby": orderby, "desc": desc, "id": id, "name": name})
         res = res.json()
@@ -89,8 +86,8 @@ class RAGFlow:
             return result_list
         raise Exception(res["message"])
 
-    def create_chat(self, name: str, avatar: str = "", dataset_ids: List[str] = [],
-                         llm: Chat.LLM = None, prompt: Chat.Prompt = None) -> Chat:
+    def create_chat(self, name: str, avatar: str = "", dataset_ids: list[str] = [],
+                         llm: Chat.LLM | None = None, prompt: Chat.Prompt | None = None) -> Chat:
         dataset_list = []
         for id in dataset_ids:
             dataset_list.append(id)
@@ -135,7 +132,7 @@ class RAGFlow:
             return Chat(self, res["data"])
         raise Exception(res["message"])
 
-    def delete_chats(self,ids: List[str] = None) -> bool:
+    def delete_chats(self,ids: list[str] | None = None):
         res = self.delete('/chats',
                       {"ids":ids})
         res = res.json()
@@ -143,7 +140,7 @@ class RAGFlow:
             raise Exception(res["message"])
 
     def list_chats(self, page: int = 1, page_size: int = 30, orderby: str = "create_time", desc: bool = True,
-                      id: str = None, name: str = None) -> List[Chat]:
+                      id: str | None = None, name: str | None = None) -> list[Chat]:
         res = self.get("/chats",{"page": page, "page_size": page_size, "orderby": orderby, "desc": desc, "id": id, "name": name})
         res = res.json()
         result_list = []
@@ -154,7 +151,7 @@ class RAGFlow:
         raise Exception(res["message"])
 
 
-    def retrieve(self, dataset_ids, document_ids=None, question="", page=1, page_size=30, similarity_threshold=0.2, vector_similarity_weight=0.3, top_k=1024, rerank_id:str=None, keyword:bool=False, ):
+    def retrieve(self, dataset_ids, document_ids=None, question="", page=1, page_size=30, similarity_threshold=0.2, vector_similarity_weight=0.3, top_k=1024, rerank_id: str | None = None, keyword:bool=False, ):
             if document_ids is None:
                 document_ids = []
             data_json ={
@@ -170,7 +167,7 @@ class RAGFlow:
                 "documents": document_ids
             }
             # Send a POST request to the backend service (using requests library as an example, actual implementation may vary)
-            res = self.post(f'/retrieval',json=data_json)
+            res = self.post('/retrieval',json=data_json)
             res = res.json()
             if res.get("code") ==0:
                 chunks=[]