Allowing additional params for OpenAIEmbeddings. (langchain-ai#7752)

(langchain-ai#7654)

---------

Co-authored-by: Bagatur <[email protected]>

langchain/chat_models/jinachat.py

@@ -36,7 +36,7 @@
     HumanMessage,
     SystemMessage,
 )
-from langchain.utils import get_from_dict_or_env
+from langchain.utils import get_from_dict_or_env, get_pydantic_field_names
 
 logger = logging.getLogger(__name__)
 
@@ -155,7 +155,7 @@ class Config:
     @root_validator(pre=True)
     def build_extra(cls, values: Dict[str, Any]) -> Dict[str, Any]:
         """Build extra kwargs from additional params that were passed in."""
-        all_required_field_names = cls._all_required_field_names()
+        all_required_field_names = get_pydantic_field_names(cls)
         extra = values.get("model_kwargs", {})
         for field_name in list(values):
             if field_name in extra:

langchain/chat_models/openai.py

@@ -41,7 +41,7 @@
     HumanMessage,
     SystemMessage,
 )
-from langchain.utils import get_from_dict_or_env
+from langchain.utils import get_from_dict_or_env, get_pydantic_field_names
 
 if TYPE_CHECKING:
     import tiktoken
@@ -205,7 +205,7 @@ class Config:
     @root_validator(pre=True)
     def build_extra(cls, values: Dict[str, Any]) -> Dict[str, Any]:
         """Build extra kwargs from additional params that were passed in."""
-        all_required_field_names = cls._all_required_field_names()
+        all_required_field_names = get_pydantic_field_names(cls)
         extra = values.get("model_kwargs", {})
         for field_name in list(values):
             if field_name in extra:

langchain/embeddings/openai.py

@@ -2,6 +2,7 @@
 from __future__ import annotations
 
 import logging
+import warnings
 from typing import (
     Any,
     Callable,
@@ -16,7 +17,7 @@
 )
 
 import numpy as np
-from pydantic import BaseModel, Extra, root_validator
+from pydantic import BaseModel, Extra, Field, root_validator
 from tenacity import (
     AsyncRetrying,
     before_sleep_log,
@@ -27,7 +28,7 @@
 )
 
 from langchain.embeddings.base import Embeddings
-from langchain.utils import get_from_dict_or_env
+from langchain.utils import get_from_dict_or_env, get_pydantic_field_names
 
 logger = logging.getLogger(__name__)
 
@@ -193,12 +194,40 @@ class OpenAIEmbeddings(BaseModel, Embeddings):
     when tiktoken is called, you can specify a model name to use here."""
     show_progress_bar: bool = False
     """Whether to show a progress bar when embedding."""
+    model_kwargs: Dict[str, Any] = Field(default_factory=dict)
+    """Holds any model parameters valid for `create` call not explicitly specified."""
 
     class Config:
         """Configuration for this pydantic object."""
 
         extra = Extra.forbid
 
+    @root_validator(pre=True)
+    def build_extra(cls, values: Dict[str, Any]) -> Dict[str, Any]:
+        """Build extra kwargs from additional params that were passed in."""
+        all_required_field_names = get_pydantic_field_names(cls)
+        extra = values.get("model_kwargs", {})
+        for field_name in list(values):
+            if field_name in extra:
+                raise ValueError(f"Found {field_name} supplied twice.")
+            if field_name not in all_required_field_names:
+                warnings.warn(
+                    f"""WARNING! {field_name} is not default parameter.
+                    {field_name} was transferred to model_kwargs.
+                    Please confirm that {field_name} is what you intended."""
+                )
+                extra[field_name] = values.pop(field_name)
+
+        invalid_model_kwargs = all_required_field_names.intersection(extra.keys())
+        if invalid_model_kwargs:
+            raise ValueError(
+                f"Parameters {invalid_model_kwargs} should be specified explicitly. "
+                f"Instead they were passed in as part of `model_kwargs` parameter."
+            )
+
+        values["model_kwargs"] = extra
+        return values
+
     @root_validator()
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate that api key and python package exists in environment."""
@@ -261,6 +290,7 @@ def _invocation_params(self) -> Dict:
             "api_base": self.openai_api_base,
             "api_type": self.openai_api_type,
             "api_version": self.openai_api_version,
+            **self.model_kwargs,
         }
         if self.openai_api_type in ("azure", "azure_ad", "azuread"):
             openai_args["engine"] = self.deployment

langchain/llms/openai.py

@@ -28,7 +28,7 @@
 )
 from langchain.llms.base import BaseLLM, create_base_retry_decorator
 from langchain.schema import Generation, LLMResult
-from langchain.utils import get_from_dict_or_env
+from langchain.utils import get_from_dict_or_env, get_pydantic_field_names
 
 logger = logging.getLogger(__name__)
 
@@ -186,13 +186,13 @@ class Config:
     @root_validator(pre=True)
     def build_extra(cls, values: Dict[str, Any]) -> Dict[str, Any]:
         """Build extra kwargs from additional params that were passed in."""
-        all_required_field_names = cls._all_required_field_names()
+        all_required_field_names = get_pydantic_field_names(cls)
         extra = values.get("model_kwargs", {})
         for field_name in list(values):
             if field_name in extra:
                 raise ValueError(f"Found {field_name} supplied twice.")
             if field_name not in all_required_field_names:
-                logger.warning(
+                warnings.warn(
                     f"""WARNING! {field_name} is not default parameter.
                     {field_name} was transferred to model_kwargs.
                     Please confirm that {field_name} is what you intended."""

langchain/schema/language_model.py

@@ -7,6 +7,7 @@
 from langchain.schema.messages import BaseMessage, get_buffer_string
 from langchain.schema.output import LLMResult
 from langchain.schema.prompt import PromptValue
+from langchain.utils import get_pydantic_field_names
 
 if TYPE_CHECKING:
     from langchain.callbacks.manager import Callbacks
@@ -246,9 +247,8 @@ def get_num_tokens_from_messages(self, messages: List[BaseMessage]) -> int:
 
     @classmethod
     def _all_required_field_names(cls) -> Set:
-        all_required_field_names = set()
-        for field in cls.__fields__.values():
-            all_required_field_names.add(field.name)
-            if field.has_alias:
-                all_required_field_names.add(field.alias)
-        return all_required_field_names
+        """DEPRECATED: Kept for backwards compatibility.
+
+        Use get_pydantic_field_names.
+        """
+        return get_pydantic_field_names(cls)

langchain/utils.py

@@ -4,7 +4,7 @@
 import importlib
 import os
 from importlib.metadata import version
-from typing import Any, Callable, Dict, List, Optional, Tuple
+from typing import Any, Callable, Dict, List, Optional, Set, Tuple
 
 from packaging.version import parse
 from requests import HTTPError, Response
@@ -183,3 +183,16 @@ def check_package_version(
             f"Expected {package} version to be >= {gte_version}. Received "
             f"{imported_version}."
         )
+
+
+def get_pydantic_field_names(pydantic_cls: Any) -> Set:
+    """Get field names, including aliases, for a pydantic class.
+
+    Args:
+        pydantic_cls: Pydantic class."""
+    all_required_field_names = set()
+    for field in pydantic_cls.__fields__.values():
+        all_required_field_names.add(field.name)
+        if field.has_alias:
+            all_required_field_names.add(field.alias)
+    return all_required_field_names

pyproject.toml

@@ -362,6 +362,7 @@ extended_testing = [
  "openai",
  "sympy",
  "rapidfuzz",
+ "openai",
  "rank_bm25",
 ]
 

tests/unit_tests/embeddings/test_openai.py

@@ -0,0 +1,20 @@
+import os
+
+import pytest
+
+from langchain.embeddings.openai import OpenAIEmbeddings
+
+os.environ["OPENAI_API_KEY"] = "foo"
+
+
+@pytest.mark.requires("openai")
+def test_openai_invalid_model_kwargs() -> None:
+    with pytest.raises(ValueError):
+        OpenAIEmbeddings(model_kwargs={"model": "foo"})
+
+
+@pytest.mark.requires("openai")
+def test_openai_incorrect_field() -> None:
+    with pytest.warns(match="not default parameter"):
+        llm = OpenAIEmbeddings(foo="bar")
+    assert llm.model_kwargs == {"foo": "bar"}

tests/unit_tests/llms/test_openai.py

@@ -0,0 +1,28 @@
+import os
+
+import pytest
+
+from langchain.llms.openai import OpenAI
+
+os.environ["OPENAI_API_KEY"] = "foo"
+
+
+@pytest.mark.requires("openai")
+def test_openai_model_param() -> None:
+    llm = OpenAI(model="foo")
+    assert llm.model_name == "foo"
+    llm = OpenAI(model_name="foo")
+    assert llm.model_name == "foo"
+
+
+@pytest.mark.requires("openai")
+def test_openai_invalid_model_kwargs() -> None:
+    with pytest.raises(ValueError):
+        OpenAI(model_kwargs={"model_name": "foo"})
+
+
+@pytest.mark.requires("openai")
+def test_openai_incorrect_field() -> None:
+    with pytest.warns(match="not default parameter"):
+        llm = OpenAI(foo="bar")
+    assert llm.model_kwargs == {"foo": "bar"}