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#1128 | Remove deprecated type hints from typing module (#1131)

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This commit is contained in:
Sandra Serrano
2024-01-09 18:35:24 +01:00
committed by GitHub
parent c9df7a2020
commit 0de9491c61
41 changed files with 272 additions and 267 deletions
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3
embedchain/config/add_config.py
View File

@@ -1,7 +1,8 @@
import builtins
import logging
from collections.abc import Callable
from importlib import import_module
from typing import Callable, Optional
from typing import Optional
from embedchain.config.base_config import BaseConfig
from embedchain.helpers.json_serializable import register_deserializable

6
embedchain/config/base_config.py
View File

@@ -1,4 +1,4 @@
from typing import Any, Dict
from typing import Any
from embedchain.helpers.json_serializable import JSONSerializable
@@ -12,10 +12,10 @@ class BaseConfig(JSONSerializable):
"""Initializes a configuration class for a class."""
pass
def as_dict(self) -> Dict[str, Any]:
def as_dict(self) -> dict[str, Any]:
"""Return config object as a dict
:return: config object as dict
:rtype: Dict[str, Any]
:rtype: dict[str, Any]
"""
return vars(self)

8
embedchain/config/cache_config.py
View File

@@ -1,4 +1,4 @@
from typing import Any, Dict, Optional
from typing import Any, Optional
from embedchain.config.base_config import BaseConfig
from embedchain.helpers.json_serializable import register_deserializable
@@ -30,7 +30,7 @@ class CacheSimilarityEvalConfig(BaseConfig):
self.positive = positive
@staticmethod
def from_config(config: Optional[Dict[str, Any]]):
def from_config(config: Optional[dict[str, Any]]):
if config is None:
return CacheSimilarityEvalConfig()
else:
@@ -65,7 +65,7 @@ class CacheInitConfig(BaseConfig):
self.auto_flush = auto_flush
@staticmethod
def from_config(config: Optional[Dict[str, Any]]):
def from_config(config: Optional[dict[str, Any]]):
if config is None:
return CacheInitConfig()
else:
@@ -86,7 +86,7 @@ class CacheConfig(BaseConfig):
self.init_config = init_config
@staticmethod
def from_config(config: Optional[Dict[str, Any]]):
def from_config(config: Optional[dict[str, Any]]):
if config is None:
return CacheConfig()
else:

12
embedchain/config/llm/base.py
View File

@@ -1,7 +1,7 @@
import logging
import re
from string import Template
from typing import Any, Dict, List, Optional
from typing import Any, Optional
from embedchain.config.base_config import BaseConfig
from embedchain.helpers.json_serializable import register_deserializable
@@ -68,12 +68,12 @@ class BaseLlmConfig(BaseConfig):
stream: bool = False,
deployment_name: Optional[str] = None,
system_prompt: Optional[str] = None,
where: Dict[str, Any] = None,
where: dict[str, Any] = None,
query_type: Optional[str] = None,
callbacks: Optional[List] = None,
callbacks: Optional[list] = None,
api_key: Optional[str] = None,
endpoint: Optional[str] = None,
model_kwargs: Optional[Dict[str, Any]] = None,
model_kwargs: Optional[dict[str, Any]] = None,
):
"""
Initializes a configuration class instance for the LLM.
@@ -106,7 +106,7 @@ class BaseLlmConfig(BaseConfig):
:param system_prompt: System prompt string, defaults to None
:type system_prompt: Optional[str], optional
:param where: A dictionary of key-value pairs to filter the database results., defaults to None
:type where: Dict[str, Any], optional
:type where: dict[str, Any], optional
:param api_key: The api key of the custom endpoint, defaults to None
:type api_key: Optional[str], optional
:param endpoint: The api url of the custom endpoint, defaults to None
@@ -114,7 +114,7 @@ class BaseLlmConfig(BaseConfig):
:param model_kwargs: A dictionary of key-value pairs to pass to the model, defaults to None
:type model_kwargs: Optional[Dict[str, Any]], optional
:param callbacks: Langchain callback functions to use, defaults to None
:type callbacks: Optional[List], optional
:type callbacks: Optional[list], optional
:param query_type: The type of query to use, defaults to None
:type query_type: Optional[str], optional
:raises ValueError: If the template is not valid as template should

12
embedchain/config/vectordb/elasticsearch.py
View File

@@ -1,5 +1,5 @@
import os
from typing import Dict, List, Optional, Union
from typing import Optional, Union
from embedchain.config.vectordb.base import BaseVectorDbConfig
from embedchain.helpers.json_serializable import register_deserializable
@@ -11,9 +11,9 @@ class ElasticsearchDBConfig(BaseVectorDbConfig):
self,
collection_name: Optional[str] = None,
dir: Optional[str] = None,
es_url: Union[str, List[str]] = None,
es_url: Union[str, list[str]] = None,
cloud_id: Optional[str] = None,
**ES_EXTRA_PARAMS: Dict[str, any],
**ES_EXTRA_PARAMS: dict[str, any],
):
"""
Initializes a configuration class instance for an Elasticsearch client.
@@ -23,13 +23,13 @@ class ElasticsearchDBConfig(BaseVectorDbConfig):
:param dir: Path to the database directory, where the database is stored, defaults to None
:type dir: Optional[str], optional
:param es_url: elasticsearch url or list of nodes url to be used for connection, defaults to None
:type es_url: Union[str, List[str]], optional
:type es_url: Union[str, list[str]], optional
:param ES_EXTRA_PARAMS: extra params dict that can be passed to elasticsearch.
:type ES_EXTRA_PARAMS: Dict[str, Any], optional
:type ES_EXTRA_PARAMS: dict[str, Any], optional
"""
if es_url and cloud_id:
raise ValueError("Only one of `es_url` and `cloud_id` can be set.")
# self, es_url: Union[str, List[str]] = None, **ES_EXTRA_PARAMS: Dict[str, any]):
# self, es_url: Union[str, list[str]] = None, **ES_EXTRA_PARAMS: dict[str, any]):
self.ES_URL = es_url or os.environ.get("ELASTICSEARCH_URL")
self.CLOUD_ID = cloud_id or os.environ.get("ELASTICSEARCH_CLOUD_ID")
if not self.ES_URL and not self.CLOUD_ID:

8
embedchain/config/vectordb/opensearch.py
View File

@@ -1,4 +1,4 @@
from typing import Dict, Optional, Tuple
from typing import Optional
from embedchain.config.vectordb.base import BaseVectorDbConfig
from embedchain.helpers.json_serializable import register_deserializable
@@ -9,11 +9,11 @@ class OpenSearchDBConfig(BaseVectorDbConfig):
def __init__(
self,
opensearch_url: str,
http_auth: Tuple[str, str],
http_auth: tuple[str, str],
vector_dimension: int = 1536,
collection_name: Optional[str] = None,
dir: Optional[str] = None,
**extra_params: Dict[str, any],
**extra_params: dict[str, any],
):
"""
Initializes a configuration class instance for an OpenSearch client.
@@ -23,7 +23,7 @@ class OpenSearchDBConfig(BaseVectorDbConfig):
:param opensearch_url: URL of the OpenSearch domain
:type opensearch_url: str, Eg, "http://localhost:9200"
:param http_auth: Tuple of username and password
:type http_auth: Tuple[str, str], Eg, ("username", "password")
:type http_auth: tuple[str, str], Eg, ("username", "password")
:param vector_dimension: Dimension of the vector, defaults to 1536 (openai embedding model)
:type vector_dimension: int, optional
:param dir: Path to the database directory, where the database is stored, defaults to None

4
embedchain/config/vectordb/pinecone.py
View File

@@ -1,4 +1,4 @@
from typing import Dict, Optional
from typing import Optional
from embedchain.config.vectordb.base import BaseVectorDbConfig
from embedchain.helpers.json_serializable import register_deserializable
@@ -12,7 +12,7 @@ class PineconeDBConfig(BaseVectorDbConfig):
dir: Optional[str] = None,
vector_dimension: int = 1536,
metric: Optional[str] = "cosine",
**extra_params: Dict[str, any],
**extra_params: dict[str, any],
):
self.metric = metric
self.vector_dimension = vector_dimension

12
embedchain/config/vectordb/qdrant.py
View File

@@ -1,4 +1,4 @@
from typing import Dict, Optional
from typing import Optional
from embedchain.config.vectordb.base import BaseVectorDbConfig
from embedchain.helpers.json_serializable import register_deserializable
@@ -15,10 +15,10 @@ class QdrantDBConfig(BaseVectorDbConfig):
self,
collection_name: Optional[str] = None,
dir: Optional[str] = None,
hnsw_config: Optional[Dict[str, any]] = None,
quantization_config: Optional[Dict[str, any]] = None,
hnsw_config: Optional[dict[str, any]] = None,
quantization_config: Optional[dict[str, any]] = None,
on_disk: Optional[bool] = None,
**extra_params: Dict[str, any],
**extra_params: dict[str, any],
):
"""
Initializes a configuration class instance for a qdrant client.
@@ -28,9 +28,9 @@ class QdrantDBConfig(BaseVectorDbConfig):
:param dir: Path to the database directory, where the database is stored, defaults to None
:type dir: Optional[str], optional
:param hnsw_config: Params for HNSW index
:type hnsw_config: Optional[Dict[str, any]], defaults to None
:type hnsw_config: Optional[dict[str, any]], defaults to None
:param quantization_config: Params for quantization, if None - quantization will be disabled
:type quantization_config: Optional[Dict[str, any]], defaults to None
:type quantization_config: Optional[dict[str, any]], defaults to None
:param on_disk: If true - point`s payload will not be stored in memory.
It will be read from the disk every time it is requested.
This setting saves RAM by (slightly) increasing the response time.

4
embedchain/config/vectordb/weaviate.py
View File

@@ -1,4 +1,4 @@
from typing import Dict, Optional
from typing import Optional
from embedchain.config.vectordb.base import BaseVectorDbConfig
from embedchain.helpers.json_serializable import register_deserializable
@@ -10,7 +10,7 @@ class WeaviateDBConfig(BaseVectorDbConfig):
self,
collection_name: Optional[str] = None,
dir: Optional[str] = None,
**extra_params: Dict[str, any],
**extra_params: dict[str, any],
):
self.extra_params = extra_params
super().__init__(collection_name=collection_name, dir=dir)