openai[minor]: implement langchain-openai package

libs/community/langchain_community/chat_models/azure_openai.py

@@ -6,6 +6,7 @@
 import warnings
 from typing import Any, Callable, Dict, List, Union
 
+from langchain_core._api.deprecation import deprecated
 from langchain_core.outputs import ChatResult
 from langchain_core.pydantic_v1 import BaseModel, Field, root_validator
 from langchain_core.utils import get_from_dict_or_env
@@ -16,6 +17,9 @@
 logger = logging.getLogger(__name__)
 
 
+@deprecated(
+    since="0.1.0", removal="0.2.0", alternative="langchain_openai.AzureChatOpenAI"
+)
 class AzureChatOpenAI(ChatOpenAI):
     """`Azure OpenAI` Chat Completion API.
 

libs/community/langchain_community/chat_models/openai.py

@@ -20,6 +20,7 @@
     Union,
 )
 
+from langchain_core._api.deprecation import deprecated
 from langchain_core.callbacks import (
     AsyncCallbackManagerForLLMRun,
     CallbackManagerForLLMRun,
@@ -143,6 +144,7 @@ def _convert_delta_to_message_chunk(
         return default_class(content=content)
 
 
+@deprecated(since="0.1.0", removal="0.2.0", alternative="langchain_openai.ChatOpenAI")
 class ChatOpenAI(BaseChatModel):
     """`OpenAI` Chat large language models API.
 

libs/community/langchain_community/embeddings/azure_openai.py

@@ -5,13 +5,17 @@
 import warnings
 from typing import Callable, Dict, Optional, Union
 
+from langchain_core._api.deprecation import deprecated
 from langchain_core.pydantic_v1 import Field, root_validator
 from langchain_core.utils import get_from_dict_or_env
 
 from langchain_community.embeddings.openai import OpenAIEmbeddings
 from langchain_community.utils.openai import is_openai_v1
 
 
+@deprecated(
+    since="0.1.0", removal="0.2.0", alternative="langchain_openai.AzureOpenAIEmbeddings"
+)
 class AzureOpenAIEmbeddings(OpenAIEmbeddings):
     """`Azure OpenAI` Embeddings API."""
 

libs/community/langchain_community/embeddings/openai.py

@@ -19,6 +19,7 @@
 )
 
 import numpy as np
+from langchain_core._api.deprecation import deprecated
 from langchain_core.embeddings import Embeddings
 from langchain_core.pydantic_v1 import BaseModel, Extra, Field, root_validator
 from langchain_core.utils import get_from_dict_or_env, get_pydantic_field_names
@@ -137,6 +138,11 @@ async def _async_embed_with_retry(**kwargs: Any) -> Any:
     return await _async_embed_with_retry(**kwargs)
 
 
+@deprecated(
+    since="0.1.0",
+    removal="0.2.0",
+    alternative="langchain_openai.OpenAIEmbeddings",
+)
 class OpenAIEmbeddings(BaseModel, Embeddings):
     """OpenAI embedding models.
 

libs/community/langchain_community/llms/openai.py

@@ -21,6 +21,7 @@
     Union,
 )
 
+from langchain_core._api.deprecation import deprecated
 from langchain_core.callbacks import (
     AsyncCallbackManagerForLLMRun,
     CallbackManagerForLLMRun,
@@ -724,6 +725,7 @@ def max_tokens_for_prompt(self, prompt: str) -> int:
         return self.max_context_size - num_tokens
 
 
+@deprecated(since="0.1.0", removal="0.2.0", alternative="langchain_openai.OpenAI")
 class OpenAI(BaseOpenAI):
     """OpenAI large language models.
 
@@ -750,6 +752,7 @@ def _invocation_params(self) -> Dict[str, Any]:
         return {**{"model": self.model_name}, **super()._invocation_params}
 
 
+@deprecated(since="0.1.0", removal="0.2.0", alternative="langchain_openai.AzureOpenAI")
 class AzureOpenAI(BaseOpenAI):
     """Azure-specific OpenAI large language models.
 
@@ -953,6 +956,7 @@ def lc_attributes(self) -> Dict[str, Any]:
         }
 
 
+@deprecated(since="0.1.0", removal="0.2.0", alternative="langchain_openai.ChatOpenAI")
 class OpenAIChat(BaseLLM):
     """OpenAI Chat large language models.
 

libs/community/langchain_community/utils/openai_functions.py

@@ -1,51 +1,15 @@
-from typing import Literal, Optional, Type, TypedDict
-
-from langchain_core.pydantic_v1 import BaseModel
-from langchain_core.utils.json_schema import dereference_refs
-
-
-class FunctionDescription(TypedDict):
-    """Representation of a callable function to the OpenAI API."""
-
-    name: str
-    """The name of the function."""
-    description: str
-    """A description of the function."""
-    parameters: dict
-    """The parameters of the function."""
-
-
-class ToolDescription(TypedDict):
-    """Representation of a callable function to the OpenAI API."""
-
-    type: Literal["function"]
-    function: FunctionDescription
-
-
-def convert_pydantic_to_openai_function(
-    model: Type[BaseModel],
-    *,
-    name: Optional[str] = None,
-    description: Optional[str] = None,
-) -> FunctionDescription:
-    """Converts a Pydantic model to a function description for the OpenAI API."""
-    schema = dereference_refs(model.schema())
-    schema.pop("definitions", None)
-    return {
-        "name": name or schema["title"],
-        "description": description or schema["description"],
-        "parameters": schema,
-    }
-
-
-def convert_pydantic_to_openai_tool(
-    model: Type[BaseModel],
-    *,
-    name: Optional[str] = None,
-    description: Optional[str] = None,
-) -> ToolDescription:
-    """Converts a Pydantic model to a function description for the OpenAI API."""
-    function = convert_pydantic_to_openai_function(
-        model, name=name, description=description
-    )
-    return {"type": "function", "function": function}
+# these stubs are just for backwards compatibility
+
+from langchain_core.utils.function_calling import (
+    FunctionDescription,
+    ToolDescription,
+    convert_pydantic_to_openai_function,
+    convert_pydantic_to_openai_tool,
+)
+
+__all__ = [
+    "FunctionDescription",
+    "ToolDescription",
+    "convert_pydantic_to_openai_function",
+    "convert_pydantic_to_openai_tool",
+]