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

embedchain/llm/base.py

@@ -1,5 +1,6 @@
 import logging
-from typing import Any, Dict, Generator, List, Optional
+from collections.abc import Generator
+from typing import Any, Optional
 
 from langchain.schema import BaseMessage as LCBaseMessage
 
@@ -55,7 +56,7 @@ class BaseLlm(JSONSerializable):
         app_id: str,
         question: str,
         answer: str,
-        metadata: Optional[Dict[str, Any]] = None,
+        metadata: Optional[dict[str, Any]] = None,
         session_id: str = "default",
     ):
         chat_message = ChatMessage()
@@ -64,7 +65,7 @@ class BaseLlm(JSONSerializable):
         self.memory.add(app_id=app_id, chat_message=chat_message, session_id=session_id)
         self.update_history(app_id=app_id, session_id=session_id)
 
-    def generate_prompt(self, input_query: str, contexts: List[str], **kwargs: Dict[str, Any]) -> str:
+    def generate_prompt(self, input_query: str, contexts: list[str], **kwargs: dict[str, Any]) -> str:
         """
         Generates a prompt based on the given query and context, ready to be
         passed to an LLM
@@ -72,7 +73,7 @@ class BaseLlm(JSONSerializable):
         :param input_query: The query to use.
         :type input_query: str
         :param contexts: List of similar documents to the query used as context.
-        :type contexts: List[str]
+        :type contexts: list[str]
         :return: The prompt
         :rtype: str
         """
@@ -170,7 +171,7 @@ class BaseLlm(JSONSerializable):
             yield chunk
         logging.info(f"Answer: {streamed_answer}")
 
-    def query(self, input_query: str, contexts: List[str], config: BaseLlmConfig = None, dry_run=False):
+    def query(self, input_query: str, contexts: list[str], config: BaseLlmConfig = None, dry_run=False):
         """
         Queries the vector database based on the given input query.
         Gets relevant doc based on the query and then passes it to an
@@ -179,7 +180,7 @@ class BaseLlm(JSONSerializable):
         :param input_query: The query to use.
         :type input_query: str
         :param contexts: Embeddings retrieved from the database to be used as context.
-        :type contexts: List[str]
+        :type contexts: list[str]
         :param config: The `BaseLlmConfig` instance to use as configuration options. This is used for one method call.
         To persistently use a config, declare it during app init., defaults to None
         :type config: Optional[BaseLlmConfig], optional
@@ -223,7 +224,7 @@ class BaseLlm(JSONSerializable):
                 self.config: BaseLlmConfig = BaseLlmConfig.deserialize(prev_config)
 
     def chat(
-        self, input_query: str, contexts: List[str], config: BaseLlmConfig = None, dry_run=False, session_id: str = None
+        self, input_query: str, contexts: list[str], config: BaseLlmConfig = None, dry_run=False, session_id: str = None
     ):
         """
         Queries the vector database on the given input query.
@@ -235,7 +236,7 @@ class BaseLlm(JSONSerializable):
         :param input_query: The query to use.
         :type input_query: str
         :param contexts: Embeddings retrieved from the database to be used as context.
-        :type contexts: List[str]
+        :type contexts: list[str]
         :param config: The `BaseLlmConfig` instance to use as configuration options. This is used for one method call.
         To persistently use a config, declare it during app init., defaults to None
         :type config: Optional[BaseLlmConfig], optional
@@ -281,7 +282,7 @@ class BaseLlm(JSONSerializable):
                 self.config: BaseLlmConfig = BaseLlmConfig.deserialize(prev_config)
 
     @staticmethod
-    def _get_messages(prompt: str, system_prompt: Optional[str] = None) -> List[LCBaseMessage]:
+    def _get_messages(prompt: str, system_prompt: Optional[str] = None) -> list[LCBaseMessage]:
         """
         Construct a list of langchain messages
 
@@ -290,7 +291,7 @@ class BaseLlm(JSONSerializable):
         :param system_prompt: System prompt, defaults to None
         :type system_prompt: Optional[str], optional
         :return: List of messages
-        :rtype: List[BaseMessage]
+        :rtype: list[BaseMessage]
         """
         from langchain.schema import HumanMessage, SystemMessage
 

embedchain/llm/google.py

@@ -1,7 +1,8 @@
 import importlib
 import logging
 import os
-from typing import Any, Generator, Optional, Union
+from collections.abc import Generator
+from typing import Any, Optional, Union
 
 import google.generativeai as genai
 

embedchain/llm/gpt4all.py

@@ -1,6 +1,7 @@
 import os
+from collections.abc import Iterable
 from pathlib import Path
-from typing import Iterable, Optional, Union
+from typing import Optional, Union
 
 from langchain.callbacks.stdout import StdOutCallbackHandler
 from langchain.callbacks.streaming_stdout import StreamingStdOutCallbackHandler

embedchain/llm/ollama.py

@@ -1,4 +1,5 @@
-from typing import Iterable, Optional, Union
+from collections.abc import Iterable
+from typing import Optional, Union
 
 from langchain.callbacks.manager import CallbackManager
 from langchain.callbacks.stdout import StdOutCallbackHandler

embedchain/llm/openai.py

@@ -1,6 +1,6 @@
 import json
 import os
-from typing import Any, Dict, Optional
+from typing import Any, Optional
 
 from langchain.chat_models import ChatOpenAI
 from langchain.schema import AIMessage, HumanMessage, SystemMessage
@@ -12,7 +12,7 @@ from embedchain.llm.base import BaseLlm
 
 @register_deserializable
 class OpenAILlm(BaseLlm):
-    def __init__(self, config: Optional[BaseLlmConfig] = None, functions: Optional[Dict[str, Any]] = None):
+    def __init__(self, config: Optional[BaseLlmConfig] = None, functions: Optional[dict[str, Any]] = None):
         self.functions = functions
         super().__init__(config=config)