community only

libs/community/Makefile

@@ -41,7 +41,7 @@ lint lint_diff lint_package lint_tests:
 	poetry run ruff .
 	[ "$(PYTHON_FILES)" = "" ] || poetry run ruff format $(PYTHON_FILES) --diff
 	[ "$(PYTHON_FILES)" = "" ] || poetry run ruff --select I $(PYTHON_FILES)
-	[ "$(PYTHON_FILES)" = "" ] || mkdir -p $(MYPY_CACHE) || poetry run mypy $(PYTHON_FILES) --cache-dir $(MYPY_CACHE)
+	[ "$(PYTHON_FILES)" = "" ] || mkdir -p $(MYPY_CACHE) && poetry run mypy $(PYTHON_FILES) --cache-dir $(MYPY_CACHE)
 
 format format_diff:
 	poetry run ruff format $(PYTHON_FILES)

libs/community/langchain_community/agent_toolkits/sql/base.py

@@ -4,9 +4,17 @@ from __future__ import annotations
 import warnings
 from typing import TYPE_CHECKING, Any, Dict, List, Literal, Optional, Sequence, Union
 
-from langchain_core.messages import AIMessage, SystemMessage
-from langchain_core.prompts import BasePromptTemplate, PromptTemplate
+from langchain_core.messages import (
+    AIMessage,
+    BaseMessage,
+    SystemMessage,
+)
+from langchain_core.prompts import (
+    BasePromptTemplate,
+    PromptTemplate,
+)
 from langchain_core.prompts.chat import (
+    BaseMessagePromptTemplate,
     ChatPromptTemplate,
     HumanMessagePromptTemplate,
     MessagesPlaceholder,
@@ -132,6 +140,7 @@ def create_sql_agent(
     toolkit = toolkit or SQLDatabaseToolkit(llm=llm, db=db)
     agent_type = agent_type or AgentType.ZERO_SHOT_REACT_DESCRIPTION
     tools = toolkit.get_tools() + list(extra_tools)
+    prefix = prefix or ""
     if prompt is None:
         prefix = prefix or SQL_PREFIX
         prefix = prefix.format(dialect=toolkit.dialect, top_k=top_k)
@@ -152,6 +161,8 @@ def create_sql_agent(
                 tool for tool in tools if not isinstance(tool, ListSQLDatabaseTool)
             ]
 
+    messages: List[Union[BaseMessage, BaseMessagePromptTemplate]] = []
+
     if agent_type == AgentType.ZERO_SHOT_REACT_DESCRIPTION:
         if prompt is None:
             from langchain.agents.mrkl import prompt as react_prompt

libs/community/langchain_community/cache.py

@@ -931,7 +931,7 @@ class CassandraCache(BaseCache):
         self.table_name = table_name
         self.ttl_seconds = ttl_seconds
 
-        self.kv_cache = ElasticCassandraTable(
+        self.kv_cache: Any = ElasticCassandraTable(
             session=self.session,
             keyspace=self.keyspace,
             table=self.table_name,
@@ -1067,7 +1067,7 @@ class CassandraSemanticCache(BaseCache):
         self._get_embedding = _cache_embedding
         self.embedding_dimension = self._get_embedding_dimension()
 
-        self.table = MetadataVectorCassandraTable(
+        self.table: Any = MetadataVectorCassandraTable(
             session=self.session,
             keyspace=self.keyspace,
             table=self.table_name,

libs/community/langchain_community/chat_models/anyscale.py

@@ -117,13 +117,13 @@ class ChatAnyscale(ChatOpenAI):
                 "ANYSCALE_API_KEY",
             )
         )
-        values["openai_api_base"] = get_from_dict_or_env(
+        values["openai_api_base"] = get_from_dict_or_env(  # type: ignore
             values,
             "anyscale_api_base",
             "ANYSCALE_API_BASE",
             default=DEFAULT_API_BASE,
         )
-        values["openai_proxy"] = get_from_dict_or_env(
+        values["openai_proxy"] = get_from_dict_or_env(  # type: ignore
             values,
             "anyscale_proxy",
             "ANYSCALE_PROXY",
@@ -141,7 +141,7 @@ class ChatAnyscale(ChatOpenAI):
             if is_openai_v1():
                 client_params = {
                     "api_key": values["openai_api_key"],
-                    "base_url": values["openai_api_base"],
+                    "base_url": values["openai_api_base"],  # type: ignore
                     # To do: future support
                     # "organization": values["openai_organization"],
                     # "timeout": values["request_timeout"],
@@ -152,7 +152,7 @@ class ChatAnyscale(ChatOpenAI):
                 }
                 values["client"] = openai.OpenAI(**client_params).chat.completions
             else:
-                values["client"] = openai.ChatCompletion
+                values["client"] = openai.ChatCompletion  # type: ignore
         except AttributeError as exc:
             raise ValueError(
                 "`openai` has no `ChatCompletion` attribute, this is likely "
@@ -167,7 +167,7 @@ class ChatAnyscale(ChatOpenAI):
 
         available_models = cls.get_available_models(
             values["openai_api_key"],
-            values["openai_api_base"],
+            values["openai_api_base"],  # type: ignore
         )
 
         if model_name not in available_models:

libs/community/langchain_community/chat_models/azure_openai.py

@@ -96,7 +96,7 @@ class AzureChatOpenAI(ChatOpenAI):
     openai_api_type: str = ""
     """Legacy, for openai<1.0.0 support."""
     validate_base_url: bool = True
-    """For backwards compatibility. If legacy val openai_api_base is passed in, try to 
+    """For backwards compatibility. If legacy val openai_api_base is passed in, try to  
         infer if it is a base_url or azure_endpoint and update accordingly.
     """
 
@@ -121,7 +121,7 @@ class AzureChatOpenAI(ChatOpenAI):
             or os.getenv("AZURE_OPENAI_API_KEY")
             or os.getenv("OPENAI_API_KEY")
         )
-        values["openai_api_base"] = values["openai_api_base"] or os.getenv(
+        values["openai_api_base"] = values["openai_api_base"] or os.getenv(  # type: ignore
             "OPENAI_API_BASE"
         )
         values["openai_api_version"] = values["openai_api_version"] or os.getenv(
@@ -143,8 +143,11 @@ class AzureChatOpenAI(ChatOpenAI):
         values["openai_api_type"] = get_from_dict_or_env(
             values, "openai_api_type", "OPENAI_API_TYPE", default="azure"
         )
-        values["openai_proxy"] = get_from_dict_or_env(
-            values, "openai_proxy", "OPENAI_PROXY", default=""
+        values["openai_proxy"] = get_from_dict_or_env(  # type: ignore
+            values,
+            "openai_proxy",
+            "OPENAI_PROXY",
+            default="",  # type: ignore
         )
 
         try:
@@ -157,37 +160,37 @@ class AzureChatOpenAI(ChatOpenAI):
             )
         if is_openai_v1():
             # For backwards compatibility. Before openai v1, no distinction was made
-            # between azure_endpoint and base_url (openai_api_base).
-            openai_api_base = values["openai_api_base"]
-            if openai_api_base and values["validate_base_url"]:
-                if "/openai" not in openai_api_base:
-                    values["openai_api_base"] = (
-                        values["openai_api_base"].rstrip("/") + "/openai"
+            # between azure_endpoint and base_url (openai_api_base).  # type: ignore
+            openai_api_base = values["openai_api_base"]  # type: ignore
+            if openai_api_base and values["validate_base_url"]:  # type: ignore
+                if "/openai" not in openai_api_base:  # type: ignore
+                    values["openai_api_base"] = (  # type: ignore
+                        values["openai_api_base"].rstrip("/") + "/openai"  # type: ignore
                     )
                     warnings.warn(
                         "As of openai>=1.0.0, Azure endpoints should be specified via "
-                        f"the `azure_endpoint` param not `openai_api_base` "
-                        f"(or alias `base_url`). Updating `openai_api_base` from "
-                        f"{openai_api_base} to {values['openai_api_base']}."
+                        f"the `azure_endpoint` param not `openai_api_base` "  # type: ignore
+                        f"(or alias `base_url`). Updating `openai_api_base` from "  # type: ignore
+                        f"{openai_api_base} to {values['openai_api_base']}."  # type: ignore
                     )
                 if values["deployment_name"]:
                     warnings.warn(
                         "As of openai>=1.0.0, if `deployment_name` (or alias "
                         "`azure_deployment`) is specified then "
-                        "`openai_api_base` (or alias `base_url`) should not be. "
+                        "`openai_api_base` (or alias `base_url`) should not be. "  # type: ignore
                         "Instead use `deployment_name` (or alias `azure_deployment`) "
                         "and `azure_endpoint`."
                     )
-                    if values["deployment_name"] not in values["openai_api_base"]:
+                    if values["deployment_name"] not in values["openai_api_base"]:  # type: ignore
                         warnings.warn(
-                            "As of openai>=1.0.0, if `openai_api_base` "
+                            "As of openai>=1.0.0, if `openai_api_base` "  # type: ignore
                             "(or alias `base_url`) is specified it is expected to be "
                             "of the form "
                             "https://example-resource.azure.openai.com/openai/deployments/example-deployment. "  # noqa: E501
-                            f"Updating {openai_api_base} to "
-                            f"{values['openai_api_base']}."
+                            f"Updating {openai_api_base} to "  # type: ignore
+                            f"{values['openai_api_base']}."  # type: ignore
                         )
-                        values["openai_api_base"] += (
+                        values["openai_api_base"] += (  # type: ignore
                             "/deployments/" + values["deployment_name"]
                         )
                     values["deployment_name"] = None
@@ -199,7 +202,7 @@ class AzureChatOpenAI(ChatOpenAI):
                 "azure_ad_token": values["azure_ad_token"],
                 "azure_ad_token_provider": values["azure_ad_token_provider"],
                 "organization": values["openai_organization"],
-                "base_url": values["openai_api_base"],
+                "base_url": values["openai_api_base"],  # type: ignore
                 "timeout": values["request_timeout"],
                 "max_retries": values["max_retries"],
                 "default_headers": values["default_headers"],
@@ -211,7 +214,7 @@ class AzureChatOpenAI(ChatOpenAI):
                 **client_params
             ).chat.completions
         else:
-            values["client"] = openai.ChatCompletion
+            values["client"] = openai.ChatCompletion  # type: ignore
         return values
 
     @property

libs/community/langchain_community/chat_models/everlyai.py

@@ -83,7 +83,7 @@ class ChatEverlyAI(ChatOpenAI):
             "everlyai_api_key",
             "EVERLYAI_API_KEY",
         )
-        values["openai_api_base"] = DEFAULT_API_BASE
+        values["openai_api_base"] = DEFAULT_API_BASE  # type: ignore
 
         try:
             import openai
@@ -94,7 +94,7 @@ class ChatEverlyAI(ChatOpenAI):
                 "Please install it with `pip install openai`.",
             ) from e
         try:
-            values["client"] = openai.ChatCompletion
+            values["client"] = openai.ChatCompletion  # type: ignore
         except AttributeError as exc:
             raise ValueError(
                 "`openai` has no `ChatCompletion` attribute, this is likely "

libs/community/langchain_community/chat_models/gpt_router.py

@@ -39,7 +39,11 @@ from langchain_community.adapters.openai import (
 from langchain_community.chat_models.openai import _convert_delta_to_message_chunk
 
 if TYPE_CHECKING:
-    from gpt_router.models import ChunkedGenerationResponse, GenerationResponse
+    from gpt_router.models import (
+        ChunkedGenerationResponse,
+        GenerationResponse,
+        ModelGenerationRequest,
+    )
 
 
 logger = logging.getLogger(__name__)
@@ -57,8 +61,8 @@ class GPTRouterModel(BaseModel):
 
 
 def get_ordered_generation_requests(
-    models_priority_list: List[GPTRouterModel], **kwargs
-):
+    models_priority_list: List[GPTRouterModel], **kwargs: Any
+) -> List[ModelGenerationRequest]:
     """
     Return the body for the model router input.
     """
@@ -100,7 +104,7 @@ def completion_with_retry(
     models_priority_list: List[GPTRouterModel],
     run_manager: Optional[CallbackManagerForLLMRun] = None,
     **kwargs: Any,
-) -> Union[GenerationResponse, Generator[ChunkedGenerationResponse]]:
+) -> Union[GenerationResponse, Generator[ChunkedGenerationResponse, None, None]]:
     """Use tenacity to retry the completion call."""
     retry_decorator = _create_retry_decorator(llm, run_manager=run_manager)
 
@@ -122,7 +126,7 @@ async def acompletion_with_retry(
     models_priority_list: List[GPTRouterModel],
     run_manager: Optional[AsyncCallbackManagerForLLMRun] = None,
     **kwargs: Any,
-) -> Union[GenerationResponse, AsyncGenerator[ChunkedGenerationResponse]]:
+) -> Union[GenerationResponse, AsyncGenerator[ChunkedGenerationResponse, None]]:
     """Use tenacity to retry the async completion call."""
 
     retry_decorator = _create_retry_decorator(llm, run_manager=run_manager)
@@ -283,8 +287,8 @@ class GPTRouter(BaseChatModel):
         return self._create_chat_result(response)
 
     def _create_chat_generation_chunk(
-        self, data: Mapping[str, Any], default_chunk_class
-    ):
+        self, data: Mapping[str, Any], default_chunk_class: Any
+    ) -> Tuple[ChatGenerationChunk, Any]:
         chunk = _convert_delta_to_message_chunk(
             {"content": data.get("text", "")}, default_chunk_class
         )
@@ -293,8 +297,8 @@ class GPTRouter(BaseChatModel):
             dict(finish_reason=finish_reason) if finish_reason is not None else None
         )
         default_chunk_class = chunk.__class__
-        chunk = ChatGenerationChunk(message=chunk, generation_info=generation_info)
-        return chunk, default_chunk_class
+        chunk_ = ChatGenerationChunk(message=chunk, generation_info=generation_info)
+        return chunk_, default_chunk_class
 
     def _stream(
         self,

libs/community/langchain_community/chat_models/jinachat.py

@@ -68,11 +68,11 @@ def _create_retry_decorator(llm: JinaChat) -> Callable[[Any], Any]:
         stop=stop_after_attempt(llm.max_retries),
         wait=wait_exponential(multiplier=1, min=min_seconds, max=max_seconds),
         retry=(
-            retry_if_exception_type(openai.error.Timeout)
-            | retry_if_exception_type(openai.error.APIError)
-            | retry_if_exception_type(openai.error.APIConnectionError)
-            | retry_if_exception_type(openai.error.RateLimitError)
-            | retry_if_exception_type(openai.error.ServiceUnavailableError)
+            retry_if_exception_type(openai.error.Timeout)  # type: ignore
+            | retry_if_exception_type(openai.error.APIError)  # type: ignore
+            | retry_if_exception_type(openai.error.APIConnectionError)  # type: ignore
+            | retry_if_exception_type(openai.error.RateLimitError)  # type: ignore
+            | retry_if_exception_type(openai.error.ServiceUnavailableError)  # type: ignore
         ),
         before_sleep=before_sleep_log(logger, logging.WARNING),
     )
@@ -232,7 +232,7 @@ class JinaChat(BaseChatModel):
                 "Please install it with `pip install openai`."
             )
         try:
-            values["client"] = openai.ChatCompletion
+            values["client"] = openai.ChatCompletion  # type: ignore
         except AttributeError:
             raise ValueError(
                 "`openai` has no `ChatCompletion` attribute, this is likely "
@@ -264,11 +264,11 @@ class JinaChat(BaseChatModel):
             stop=stop_after_attempt(self.max_retries),
             wait=wait_exponential(multiplier=1, min=min_seconds, max=max_seconds),
             retry=(
-                retry_if_exception_type(openai.error.Timeout)
-                | retry_if_exception_type(openai.error.APIError)
-                | retry_if_exception_type(openai.error.APIConnectionError)
-                | retry_if_exception_type(openai.error.RateLimitError)
-                | retry_if_exception_type(openai.error.ServiceUnavailableError)
+                retry_if_exception_type(openai.error.Timeout)  # type: ignore
+                | retry_if_exception_type(openai.error.APIError)  # type: ignore
+                | retry_if_exception_type(openai.error.APIConnectionError)  # type: ignore
+                | retry_if_exception_type(openai.error.RateLimitError)  # type: ignore
+                | retry_if_exception_type(openai.error.ServiceUnavailableError)  # type: ignore
             ),
             before_sleep=before_sleep_log(logger, logging.WARNING),
         )

libs/community/langchain_community/chat_models/openai.py

@@ -84,11 +84,11 @@ def _create_retry_decorator(
     import openai
 
     errors = [
-        openai.error.Timeout,
-        openai.error.APIError,
-        openai.error.APIConnectionError,
-        openai.error.RateLimitError,
-        openai.error.ServiceUnavailableError,
+        openai.error.Timeout,  # type: ignore
+        openai.error.APIError,  # type: ignore
+        openai.error.APIConnectionError,  # type: ignore
+        openai.error.RateLimitError,  # type: ignore
+        openai.error.ServiceUnavailableError,  # type: ignore
     ]
     return create_base_retry_decorator(
         error_types=errors, max_retries=llm.max_retries, run_manager=run_manager
@@ -179,11 +179,11 @@ class ChatOpenAI(BaseChatModel):
         if self.openai_organization:
             attributes["openai_organization"] = self.openai_organization
 
-        if self.openai_api_base:
-            attributes["openai_api_base"] = self.openai_api_base
+        if self.openai_api_base:  # type: ignore
+            attributes["openai_api_base"] = self.openai_api_base  # type: ignore
 
-        if self.openai_proxy:
-            attributes["openai_proxy"] = self.openai_proxy
+        if self.openai_proxy:  # type: ignore
+            attributes["openai_proxy"] = self.openai_proxy  # type: ignore
 
         return attributes
 
@@ -205,13 +205,13 @@ class ChatOpenAI(BaseChatModel):
     # may assume openai_api_key is a str)
     openai_api_key: Optional[str] = Field(default=None, alias="api_key")
     """Automatically inferred from env var `OPENAI_API_KEY` if not provided."""
-    openai_api_base: Optional[str] = Field(default=None, alias="base_url")
+    openai_api_base: Optional[str] = Field(default=None, alias="base_url")  # type: ignore
     """Base URL path for API requests, leave blank if not using a proxy or service 
         emulator."""
     openai_organization: Optional[str] = Field(default=None, alias="organization")
     """Automatically inferred from env var `OPENAI_ORG_ID` if not provided."""
     # to support explicit proxy for OpenAI
-    openai_proxy: Optional[str] = None
+    openai_proxy: Optional[str] = None  # type: ignore
     request_timeout: Union[float, Tuple[float, float], Any, None] = Field(
         default=None, alias="timeout"
     )
@@ -290,12 +290,12 @@ class ChatOpenAI(BaseChatModel):
             or os.getenv("OPENAI_ORG_ID")
             or os.getenv("OPENAI_ORGANIZATION")
         )
-        values["openai_api_base"] = values["openai_api_base"] or os.getenv(
+        values["openai_api_base"] = values["openai_api_base"] or os.getenv(  # type: ignore
             "OPENAI_API_BASE"
         )
-        values["openai_proxy"] = get_from_dict_or_env(
+        values["openai_proxy"] = get_from_dict_or_env(  # type: ignore
             values,
-            "openai_proxy",
+            "openai_proxy",  # type: ignore
             "OPENAI_PROXY",
             default="",
         )
@@ -312,7 +312,7 @@ class ChatOpenAI(BaseChatModel):
             client_params = {
                 "api_key": values["openai_api_key"],
                 "organization": values["openai_organization"],
-                "base_url": values["openai_api_base"],
+                "base_url": values["openai_api_base"],  # type: ignore
                 "timeout": values["request_timeout"],
                 "max_retries": values["max_retries"],
                 "default_headers": values["default_headers"],
@@ -327,7 +327,7 @@ class ChatOpenAI(BaseChatModel):
                     **client_params
                 ).chat.completions
         elif not values.get("client"):
-            values["client"] = openai.ChatCompletion
+            values["client"] = openai.ChatCompletion  # type: ignore
         else:
             pass
         return values
@@ -547,14 +547,14 @@ class ChatOpenAI(BaseChatModel):
             openai_creds.update(
                 {
                     "api_key": self.openai_api_key,
-                    "api_base": self.openai_api_base,
+                    "api_base": self.openai_api_base,  # type: ignore
                     "organization": self.openai_organization,
                 }
             )
-        if self.openai_proxy:
+        if self.openai_proxy:  # type: ignore
             import openai
 
-            openai.proxy = {"http": self.openai_proxy, "https": self.openai_proxy}  # type: ignore[assignment]  # noqa: E501
+            openai.proxy = {"http": self.openai_proxy, "https": self.openai_proxy}  # type: ignore  # noqa: E501
         return {**self._default_params, **openai_creds}
 
     def _get_invocation_params(

libs/community/langchain_community/document_loaders/gcs_directory.py

@@ -35,7 +35,7 @@ class GCSDirectoryLoader(BaseLoader):
     def load(self) -> List[Document]:
         """Load documents."""
         try:
-            from google.cloud import storage
+            from google.cloud import storage  # type: ignore
         except ImportError:
             raise ImportError(
                 "Could not import google-cloud-storage python package. "

libs/community/langchain_community/document_loaders/gcs_file.py

@@ -51,7 +51,7 @@ class GCSFileLoader(BaseLoader):
     def load(self) -> List[Document]:
         """Load documents."""
         try:
-            from google.cloud import storage
+            from google.cloud import storage  # type: ignore
         except ImportError:
             raise ImportError(
                 "Could not import google-cloud-storage python package. "

libs/community/langchain_community/document_loaders/parsers/audio.py

@@ -73,7 +73,7 @@ class OpenAIWhisperParser(BaseBlobParser):
                             model="whisper-1", file=file_obj
                         )
                     else:
-                        transcript = openai.Audio.transcribe("whisper-1", file_obj)
+                        transcript = openai.Audio.transcribe("whisper-1", file_obj)  # type: ignore
                     break
                 except Exception as e:
                     attempts += 1

libs/community/langchain_community/document_transformers/google_translate.py

@@ -27,7 +27,7 @@ class GoogleTranslateTransformer(BaseDocumentTransformer):
         """
         try:
             from google.api_core.client_options import ClientOptions
-            from google.cloud import translate
+            from google.cloud import translate  # type: ignore
         except ImportError as exc:
             raise ImportError(
                 "Install Google Cloud Translate to use this parser."
@@ -70,7 +70,7 @@ class GoogleTranslateTransformer(BaseDocumentTransformer):
                 Options: `text/plain`, `text/html`
         """
         try:
-            from google.cloud import translate
+            from google.cloud import translate  # type: ignore
         except ImportError as exc:
             raise ImportError(
                 "Install Google Cloud Translate to use this parser."

libs/community/langchain_community/embeddings/azure_openai.py

@@ -64,7 +64,7 @@ class AzureOpenAIEmbeddings(OpenAIEmbeddings):
             or os.getenv("AZURE_OPENAI_API_KEY")
             or os.getenv("OPENAI_API_KEY")
         )
-        values["openai_api_base"] = values["openai_api_base"] or os.getenv(
+        values["openai_api_base"] = values["openai_api_base"] or os.getenv(  # type: ignore
             "OPENAI_API_BASE"
         )
         values["openai_api_version"] = values["openai_api_version"] or os.getenv(
@@ -78,9 +78,9 @@ class AzureOpenAIEmbeddings(OpenAIEmbeddings):
             or os.getenv("OPENAI_ORG_ID")
             or os.getenv("OPENAI_ORGANIZATION")
         )
-        values["openai_proxy"] = get_from_dict_or_env(
+        values["openai_proxy"] = get_from_dict_or_env(  # type: ignore
             values,
-            "openai_proxy",
+            "openai_proxy",  # type: ignore
             "OPENAI_PROXY",
             default="",
         )
@@ -104,35 +104,35 @@ class AzureOpenAIEmbeddings(OpenAIEmbeddings):
             )
         if is_openai_v1():
             # For backwards compatibility. Before openai v1, no distinction was made
-            # between azure_endpoint and base_url (openai_api_base).
-            openai_api_base = values["openai_api_base"]
-            if openai_api_base and values["validate_base_url"]:
-                if "/openai" not in openai_api_base:
-                    values["openai_api_base"] += "/openai"
+            # between azure_endpoint and base_url (openai_api_base).  # type: ignore
+            openai_api_base = values["openai_api_base"]  # type: ignore
+            if openai_api_base and values["validate_base_url"]:  # type: ignore
+                if "/openai" not in openai_api_base:  # type: ignore
+                    values["openai_api_base"] += "/openai"  # type: ignore
                     warnings.warn(
                         "As of openai>=1.0.0, Azure endpoints should be specified via "
-                        f"the `azure_endpoint` param not `openai_api_base` "
-                        f"(or alias `base_url`). Updating `openai_api_base` from "
-                        f"{openai_api_base} to {values['openai_api_base']}."
+                        f"the `azure_endpoint` param not `openai_api_base` "  # type: ignore
+                        f"(or alias `base_url`). Updating `openai_api_base` from "  # type: ignore
+                        f"{openai_api_base} to {values['openai_api_base']}."  # type: ignore
                     )
                 if values["deployment"]:
                     warnings.warn(
                         "As of openai>=1.0.0, if `deployment` (or alias "
                         "`azure_deployment`) is specified then "
-                        "`openai_api_base` (or alias `base_url`) should not be. "
+                        "`openai_api_base` (or alias `base_url`) should not be. "  # type: ignore
                         "Instead use `deployment` (or alias `azure_deployment`) "
                         "and `azure_endpoint`."
                     )
-                    if values["deployment"] not in values["openai_api_base"]:
+                    if values["deployment"] not in values["openai_api_base"]:  # type: ignore
                         warnings.warn(
-                            "As of openai>=1.0.0, if `openai_api_base` "
+                            "As of openai>=1.0.0, if `openai_api_base` "  # type: ignore
                             "(or alias `base_url`) is specified it is expected to be "
                             "of the form "
                             "https://example-resource.azure.openai.com/openai/deployments/example-deployment. "  # noqa: E501
-                            f"Updating {openai_api_base} to "
-                            f"{values['openai_api_base']}."
+                            f"Updating {openai_api_base} to "  # type: ignore
+                            f"{values['openai_api_base']}."  # type: ignore
                         )
-                        values["openai_api_base"] += (
+                        values["openai_api_base"] += (  # type: ignore
                             "/deployments/" + values["deployment"]
                         )
                     values["deployment"] = None
@@ -144,7 +144,7 @@ class AzureOpenAIEmbeddings(OpenAIEmbeddings):
                 "azure_ad_token": values["azure_ad_token"],
                 "azure_ad_token_provider": values["azure_ad_token_provider"],
                 "organization": values["openai_organization"],
-                "base_url": values["openai_api_base"],
+                "base_url": values["openai_api_base"],  # type: ignore
                 "timeout": values["request_timeout"],
                 "max_retries": values["max_retries"],
                 "default_headers": values["default_headers"],
@@ -154,7 +154,7 @@ class AzureOpenAIEmbeddings(OpenAIEmbeddings):
             values["client"] = openai.AzureOpenAI(**client_params).embeddings
             values["async_client"] = openai.AsyncAzureOpenAI(**client_params).embeddings
         else:
-            values["client"] = openai.Embedding
+            values["client"] = openai.Embedding  # type: ignore
         return values
 
     @property

libs/community/langchain_community/embeddings/localai.py

@@ -42,11 +42,11 @@ def _create_retry_decorator(embeddings: LocalAIEmbeddings) -> Callable[[Any], An
         stop=stop_after_attempt(embeddings.max_retries),
         wait=wait_exponential(multiplier=1, min=min_seconds, max=max_seconds),
         retry=(
-            retry_if_exception_type(openai.error.Timeout)
-            | retry_if_exception_type(openai.error.APIError)
-            | retry_if_exception_type(openai.error.APIConnectionError)
-            | retry_if_exception_type(openai.error.RateLimitError)
-            | retry_if_exception_type(openai.error.ServiceUnavailableError)
+            retry_if_exception_type(openai.error.Timeout)  # type: ignore
+            | retry_if_exception_type(openai.error.APIError)  # type: ignore
+            | retry_if_exception_type(openai.error.APIConnectionError)  # type: ignore
+            | retry_if_exception_type(openai.error.RateLimitError)  # type: ignore
+            | retry_if_exception_type(openai.error.ServiceUnavailableError)  # type: ignore
         ),
         before_sleep=before_sleep_log(logger, logging.WARNING),
     )
@@ -64,11 +64,11 @@ def _async_retry_decorator(embeddings: LocalAIEmbeddings) -> Any:
         stop=stop_after_attempt(embeddings.max_retries),
         wait=wait_exponential(multiplier=1, min=min_seconds, max=max_seconds),
         retry=(
-            retry_if_exception_type(openai.error.Timeout)
-            | retry_if_exception_type(openai.error.APIError)
-            | retry_if_exception_type(openai.error.APIConnectionError)
-            | retry_if_exception_type(openai.error.RateLimitError)
-            | retry_if_exception_type(openai.error.ServiceUnavailableError)
+            retry_if_exception_type(openai.error.Timeout)  # type: ignore
+            | retry_if_exception_type(openai.error.APIError)  # type: ignore
+            | retry_if_exception_type(openai.error.APIConnectionError)  # type: ignore
+            | retry_if_exception_type(openai.error.RateLimitError)  # type: ignore
+            | retry_if_exception_type(openai.error.ServiceUnavailableError)  # type: ignore
         ),
         before_sleep=before_sleep_log(logger, logging.WARNING),
     )
@@ -89,7 +89,7 @@ def _check_response(response: dict) -> dict:
     if any(len(d["embedding"]) == 1 for d in response["data"]):
         import openai
 
-        raise openai.error.APIError("LocalAI API returned an empty embedding")
+        raise openai.error.APIError("LocalAI API returned an empty embedding")  # type: ignore
     return response
 
 
@@ -132,7 +132,7 @@ class LocalAIEmbeddings(BaseModel, Embeddings):
             from langchain_community.embeddings import LocalAIEmbeddings
             openai = LocalAIEmbeddings(
                 openai_api_key="random-string",
-                openai_api_base="http://localhost:8080"
+                openai_api_base="http://localhost:8080"  # type: ignore
             )
 
     """
@@ -141,9 +141,9 @@ class LocalAIEmbeddings(BaseModel, Embeddings):
     model: str = "text-embedding-ada-002"
     deployment: str = model
     openai_api_version: Optional[str] = None
-    openai_api_base: Optional[str] = None
+    openai_api_base: Optional[str] = None  # type: ignore
     # to support explicit proxy for LocalAI
-    openai_proxy: Optional[str] = None
+    openai_proxy: Optional[str] = None  # type: ignore
     embedding_ctx_length: int = 8191
     """The maximum number of tokens to embed at once."""
     openai_api_key: Optional[str] = None
@@ -199,15 +199,15 @@ class LocalAIEmbeddings(BaseModel, Embeddings):
         values["openai_api_key"] = get_from_dict_or_env(
             values, "openai_api_key", "OPENAI_API_KEY"
         )
-        values["openai_api_base"] = get_from_dict_or_env(
+        values["openai_api_base"] = get_from_dict_or_env(  # type: ignore
             values,
-            "openai_api_base",
+            "openai_api_base",  # type: ignore
             "OPENAI_API_BASE",
             default="",
         )
-        values["openai_proxy"] = get_from_dict_or_env(
+        values["openai_proxy"] = get_from_dict_or_env(  # type: ignore
             values,
-            "openai_proxy",
+            "openai_proxy",  # type: ignore
             "OPENAI_PROXY",
             default="",
         )
@@ -228,7 +228,7 @@ class LocalAIEmbeddings(BaseModel, Embeddings):
         try:
             import openai
 
-            values["client"] = openai.Embedding
+            values["client"] = openai.Embedding  # type: ignore
         except ImportError:
             raise ImportError(
                 "Could not import openai python package. "
@@ -244,16 +244,16 @@ class LocalAIEmbeddings(BaseModel, Embeddings):
             "headers": self.headers,
             "api_key": self.openai_api_key,
             "organization": self.openai_organization,
-            "api_base": self.openai_api_base,
+            "api_base": self.openai_api_base,  # type: ignore
             "api_version": self.openai_api_version,
             **self.model_kwargs,
         }
-        if self.openai_proxy:
+        if self.openai_proxy:  # type: ignore
             import openai
 
-            openai.proxy = {
-                "http": self.openai_proxy,
-                "https": self.openai_proxy,
+            openai.proxy = {  # type: ignore
+                "http": self.openai_proxy,  # type: ignore
+                "https": self.openai_proxy,  # type: ignore
             }  # type: ignore[assignment]  # noqa: E501
         return openai_args
 

libs/community/langchain_community/embeddings/openai.py

@@ -54,11 +54,11 @@ def _create_retry_decorator(embeddings: OpenAIEmbeddings) -> Callable[[Any], Any
             max=embeddings.retry_max_seconds,
         ),
         retry=(
-            retry_if_exception_type(openai.error.Timeout)
-            | retry_if_exception_type(openai.error.APIError)
-            | retry_if_exception_type(openai.error.APIConnectionError)
-            | retry_if_exception_type(openai.error.RateLimitError)
-            | retry_if_exception_type(openai.error.ServiceUnavailableError)
+            retry_if_exception_type(openai.error.Timeout)  # type: ignore
+            | retry_if_exception_type(openai.error.APIError)  # type: ignore
+            | retry_if_exception_type(openai.error.APIConnectionError)  # type: ignore
+            | retry_if_exception_type(openai.error.RateLimitError)  # type: ignore
+            | retry_if_exception_type(openai.error.ServiceUnavailableError)  # type: ignore
         ),
         before_sleep=before_sleep_log(logger, logging.WARNING),
     )
@@ -81,11 +81,11 @@ def _async_retry_decorator(embeddings: OpenAIEmbeddings) -> Any:
             max=embeddings.retry_max_seconds,
         ),
         retry=(
-            retry_if_exception_type(openai.error.Timeout)
-            | retry_if_exception_type(openai.error.APIError)
-            | retry_if_exception_type(openai.error.APIConnectionError)
-            | retry_if_exception_type(openai.error.RateLimitError)
-            | retry_if_exception_type(openai.error.ServiceUnavailableError)
+            retry_if_exception_type(openai.error.Timeout)  # type: ignore
+            | retry_if_exception_type(openai.error.APIError)  # type: ignore
+            | retry_if_exception_type(openai.error.APIConnectionError)  # type: ignore
+            | retry_if_exception_type(openai.error.RateLimitError)  # type: ignore
+            | retry_if_exception_type(openai.error.ServiceUnavailableError)  # type: ignore
         ),
         before_sleep=before_sleep_log(logger, logging.WARNING),
     )
@@ -106,7 +106,7 @@ def _check_response(response: dict, skip_empty: bool = False) -> dict:
     if any(len(d["embedding"]) == 1 for d in response["data"]) and not skip_empty:
         import openai
 
-        raise openai.error.APIError("OpenAI API returned an empty embedding")
+        raise openai.error.APIError("OpenAI API returned an empty embedding")  # type: ignore
     return response
 
 
@@ -194,13 +194,13 @@ class OpenAIEmbeddings(BaseModel, Embeddings):
     openai_api_version: Optional[str] = Field(default=None, alias="api_version")
     """Automatically inferred from env var `OPENAI_API_VERSION` if not provided."""
     # to support Azure OpenAI Service custom endpoints
-    openai_api_base: Optional[str] = Field(default=None, alias="base_url")
+    openai_api_base: Optional[str] = Field(default=None, alias="base_url")  # type: ignore
     """Base URL path for API requests, leave blank if not using a proxy or service 
         emulator."""
     # to support Azure OpenAI Service custom endpoints
     openai_api_type: Optional[str] = None
     # to support explicit proxy for OpenAI
-    openai_proxy: Optional[str] = None
+    openai_proxy: Optional[str] = None  # type: ignore
     embedding_ctx_length: int = 8191
     """The maximum number of tokens to embed at once."""
     openai_api_key: Optional[str] = Field(default=None, alias="api_key")
@@ -288,7 +288,7 @@ class OpenAIEmbeddings(BaseModel, Embeddings):
         values["openai_api_key"] = get_from_dict_or_env(
             values, "openai_api_key", "OPENAI_API_KEY"
         )
-        values["openai_api_base"] = values["openai_api_base"] or os.getenv(
+        values["openai_api_base"] = values["openai_api_base"] or os.getenv(  # type: ignore
             "OPENAI_API_BASE"
         )
         values["openai_api_type"] = get_from_dict_or_env(
@@ -297,9 +297,9 @@ class OpenAIEmbeddings(BaseModel, Embeddings):
             "OPENAI_API_TYPE",
             default="",
         )
-        values["openai_proxy"] = get_from_dict_or_env(
+        values["openai_proxy"] = get_from_dict_or_env(  # type: ignore
             values,
-            "openai_proxy",
+            "openai_proxy",  # type: ignore
             "OPENAI_PROXY",
             default="",
         )
@@ -340,7 +340,7 @@ class OpenAIEmbeddings(BaseModel, Embeddings):
                 client_params = {
                     "api_key": values["openai_api_key"],
                     "organization": values["openai_organization"],
-                    "base_url": values["openai_api_base"],
+                    "base_url": values["openai_api_base"],  # type: ignore
                     "timeout": values["request_timeout"],
                     "max_retries": values["max_retries"],
                     "default_headers": values["default_headers"],
@@ -354,7 +354,7 @@ class OpenAIEmbeddings(BaseModel, Embeddings):
                         **client_params
                     ).embeddings
             elif not values.get("client"):
-                values["client"] = openai.Embedding
+                values["client"] = openai.Embedding  # type: ignore
             else:
                 pass
         return values
@@ -370,7 +370,7 @@ class OpenAIEmbeddings(BaseModel, Embeddings):
                 "headers": self.headers,
                 "api_key": self.openai_api_key,
                 "organization": self.openai_organization,
-                "api_base": self.openai_api_base,
+                "api_base": self.openai_api_base,  # type: ignore
                 "api_type": self.openai_api_type,
                 "api_version": self.openai_api_version,
                 **self.model_kwargs,
@@ -378,7 +378,7 @@ class OpenAIEmbeddings(BaseModel, Embeddings):
             if self.openai_api_type in ("azure", "azure_ad", "azuread"):
                 openai_args["engine"] = self.deployment
             # TODO: Look into proxy with openai v1.
-            if self.openai_proxy:
+            if self.openai_proxy:  # type: ignore
                 try:
                     import openai
                 except ImportError:
@@ -387,9 +387,9 @@ class OpenAIEmbeddings(BaseModel, Embeddings):
                         "Please install it with `pip install openai`."
                     )
 
-                openai.proxy = {
-                    "http": self.openai_proxy,
-                    "https": self.openai_proxy,
+                openai.proxy = {  # type: ignore
+                    "http": self.openai_proxy,  # type: ignore
+                    "https": self.openai_proxy,  # type: ignore
                 }  # type: ignore[assignment]  # noqa: E501
         return openai_args
 

libs/community/langchain_community/llms/anyscale.py

@@ -107,7 +107,7 @@ class Anyscale(BaseOpenAI):
             import openai
 
             ## Always create ChatComplete client, replacing the legacy Complete client
-            values["client"] = openai.ChatCompletion
+            values["client"] = openai.ChatCompletion  # type: ignore
         except ImportError:
             raise ImportError(
                 "Could not import openai python package. "

libs/community/langchain_community/llms/gooseai.py

@@ -97,8 +97,8 @@ class GooseAI(LLM):
             import openai
 
             openai.api_key = gooseai_api_key.get_secret_value()
-            openai.api_base = "https://api.goose.ai/v1"
-            values["client"] = openai.Completion
+            openai.api_base = "https://api.goose.ai/v1"  # type: ignore
+            values["client"] = openai.Completion  # type: ignore
         except ImportError:
             raise ImportError(
                 "Could not import openai python package. "

libs/community/langchain_community/llms/openai.py

@@ -94,11 +94,11 @@ def _create_retry_decorator(
     import openai
 
     errors = [
-        openai.error.Timeout,
-        openai.error.APIError,
-        openai.error.APIConnectionError,
-        openai.error.RateLimitError,
-        openai.error.ServiceUnavailableError,
+        openai.error.Timeout,  # type: ignore
+        openai.error.APIError,  # type: ignore
+        openai.error.APIConnectionError,  # type: ignore
+        openai.error.RateLimitError,  # type: ignore
+        openai.error.ServiceUnavailableError,  # type: ignore
     ]
     return create_base_retry_decorator(
         error_types=errors, max_retries=llm.max_retries, run_manager=run_manager
@@ -157,14 +157,14 @@ class BaseOpenAI(BaseLLM):
     @property
     def lc_attributes(self) -> Dict[str, Any]:
         attributes: Dict[str, Any] = {}
-        if self.openai_api_base:
-            attributes["openai_api_base"] = self.openai_api_base
+        if self.openai_api_base:  # type: ignore
+            attributes["openai_api_base"] = self.openai_api_base  # type: ignore
 
         if self.openai_organization:
             attributes["openai_organization"] = self.openai_organization
 
-        if self.openai_proxy:
-            attributes["openai_proxy"] = self.openai_proxy
+        if self.openai_proxy:  # type: ignore
+            attributes["openai_proxy"] = self.openai_proxy  # type: ignore
 
         return attributes
 
@@ -199,13 +199,13 @@ class BaseOpenAI(BaseLLM):
     # may assume openai_api_key is a str)
     openai_api_key: Optional[str] = Field(default=None, alias="api_key")
     """Automatically inferred from env var `OPENAI_API_KEY` if not provided."""
-    openai_api_base: Optional[str] = Field(default=None, alias="base_url")
+    openai_api_base: Optional[str] = Field(default=None, alias="base_url")  # type: ignore
     """Base URL path for API requests, leave blank if not using a proxy or service 
         emulator."""
     openai_organization: Optional[str] = Field(default=None, alias="organization")
     """Automatically inferred from env var `OPENAI_ORG_ID` if not provided."""
     # to support explicit proxy for OpenAI
-    openai_proxy: Optional[str] = None
+    openai_proxy: Optional[str] = None  # type: ignore
     batch_size: int = 20
     """Batch size to use when passing multiple documents to generate."""
     request_timeout: Union[float, Tuple[float, float], Any, None] = Field(
@@ -282,12 +282,12 @@ class BaseOpenAI(BaseLLM):
         values["openai_api_key"] = get_from_dict_or_env(
             values, "openai_api_key", "OPENAI_API_KEY"
         )
-        values["openai_api_base"] = values["openai_api_base"] or os.getenv(
+        values["openai_api_base"] = values["openai_api_base"] or os.getenv(  # type: ignore
             "OPENAI_API_BASE"
         )
-        values["openai_proxy"] = get_from_dict_or_env(
+        values["openai_proxy"] = get_from_dict_or_env(  # type: ignore
             values,
-            "openai_proxy",
+            "openai_proxy",  # type: ignore
             "OPENAI_PROXY",
             default="",
         )
@@ -308,7 +308,7 @@ class BaseOpenAI(BaseLLM):
             client_params = {
                 "api_key": values["openai_api_key"],
                 "organization": values["openai_organization"],
-                "base_url": values["openai_api_base"],
+                "base_url": values["openai_api_base"],  # type: ignore
                 "timeout": values["request_timeout"],
                 "max_retries": values["max_retries"],
                 "default_headers": values["default_headers"],
@@ -320,7 +320,7 @@ class BaseOpenAI(BaseLLM):
             if not values.get("async_client"):
                 values["async_client"] = openai.AsyncOpenAI(**client_params).completions
         elif not values.get("client"):
-            values["client"] = openai.Completion
+            values["client"] = openai.Completion  # type: ignore
         else:
             pass
 
@@ -597,14 +597,14 @@ class BaseOpenAI(BaseLLM):
             openai_creds.update(
                 {
                     "api_key": self.openai_api_key,
-                    "api_base": self.openai_api_base,
+                    "api_base": self.openai_api_base,  # type: ignore
                     "organization": self.openai_organization,
                 }
             )
-        if self.openai_proxy:
+        if self.openai_proxy:  # type: ignore
             import openai
 
-            openai.proxy = {"http": self.openai_proxy, "https": self.openai_proxy}  # type: ignore[assignment]  # noqa: E501
+            openai.proxy = {"http": self.openai_proxy, "https": self.openai_proxy}  # type: ignore  # noqa: E501
         return {**openai_creds, **self._default_params}
 
     @property
@@ -807,7 +807,7 @@ class AzureOpenAI(BaseOpenAI):
     openai_api_type: str = ""
     """Legacy, for openai<1.0.0 support."""
     validate_base_url: bool = True
-    """For backwards compatibility. If legacy val openai_api_base is passed in, try to 
+    """For backwards compatibility. If legacy val openai_api_base is passed in, try to  
         infer if it is a base_url or azure_endpoint and update accordingly.
     """
 
@@ -841,12 +841,12 @@ class AzureOpenAI(BaseOpenAI):
         values["azure_ad_token"] = values["azure_ad_token"] or os.getenv(
             "AZURE_OPENAI_AD_TOKEN"
         )
-        values["openai_api_base"] = values["openai_api_base"] or os.getenv(
+        values["openai_api_base"] = values["openai_api_base"] or os.getenv(  # type: ignore
             "OPENAI_API_BASE"
         )
-        values["openai_proxy"] = get_from_dict_or_env(
+        values["openai_proxy"] = get_from_dict_or_env(  # type: ignore
             values,
-            "openai_proxy",
+            "openai_proxy",  # type: ignore
             "OPENAI_PROXY",
             default="",
         )
@@ -870,37 +870,37 @@ class AzureOpenAI(BaseOpenAI):
             )
         if is_openai_v1():
             # For backwards compatibility. Before openai v1, no distinction was made
-            # between azure_endpoint and base_url (openai_api_base).
-            openai_api_base = values["openai_api_base"]
-            if openai_api_base and values["validate_base_url"]:
-                if "/openai" not in openai_api_base:
-                    values["openai_api_base"] = (
-                        values["openai_api_base"].rstrip("/") + "/openai"
+            # between azure_endpoint and base_url (openai_api_base).  # type: ignore
+            openai_api_base = values["openai_api_base"]  # type: ignore
+            if openai_api_base and values["validate_base_url"]:  # type: ignore
+                if "/openai" not in openai_api_base:  # type: ignore
+                    values["openai_api_base"] = (  # type: ignore
+                        values["openai_api_base"].rstrip("/") + "/openai"  # type: ignore
                     )
                     warnings.warn(
                         "As of openai>=1.0.0, Azure endpoints should be specified via "
-                        f"the `azure_endpoint` param not `openai_api_base` "
-                        f"(or alias `base_url`). Updating `openai_api_base` from "
-                        f"{openai_api_base} to {values['openai_api_base']}."
+                        f"the `azure_endpoint` param not `openai_api_base` "  # type: ignore
+                        f"(or alias `base_url`). Updating `openai_api_base` from "  # type: ignore
+                        f"{openai_api_base} to {values['openai_api_base']}."  # type: ignore
                     )
                 if values["deployment_name"]:
                     warnings.warn(
                         "As of openai>=1.0.0, if `deployment_name` (or alias "
                         "`azure_deployment`) is specified then "
-                        "`openai_api_base` (or alias `base_url`) should not be. "
+                        "`openai_api_base` (or alias `base_url`) should not be. "  # type: ignore
                         "Instead use `deployment_name` (or alias `azure_deployment`) "
                         "and `azure_endpoint`."
                     )
-                    if values["deployment_name"] not in values["openai_api_base"]:
+                    if values["deployment_name"] not in values["openai_api_base"]:  # type: ignore
                         warnings.warn(
-                            "As of openai>=1.0.0, if `openai_api_base` "
+                            "As of openai>=1.0.0, if `openai_api_base` "  # type: ignore
                             "(or alias `base_url`) is specified it is expected to be "
                             "of the form "
                             "https://example-resource.azure.openai.com/openai/deployments/example-deployment. "  # noqa: E501
-                            f"Updating {openai_api_base} to "
-                            f"{values['openai_api_base']}."
+                            f"Updating {openai_api_base} to "  # type: ignore
+                            f"{values['openai_api_base']}."  # type: ignore
                         )
-                        values["openai_api_base"] += (
+                        values["openai_api_base"] += (  # type: ignore
                             "/deployments/" + values["deployment_name"]
                         )
                     values["deployment_name"] = None
@@ -912,7 +912,7 @@ class AzureOpenAI(BaseOpenAI):
                 "azure_ad_token": values["azure_ad_token"],
                 "azure_ad_token_provider": values["azure_ad_token_provider"],
                 "organization": values["openai_organization"],
-                "base_url": values["openai_api_base"],
+                "base_url": values["openai_api_base"],  # type: ignore
                 "timeout": values["request_timeout"],
                 "max_retries": values["max_retries"],
                 "default_headers": values["default_headers"],
@@ -925,7 +925,7 @@ class AzureOpenAI(BaseOpenAI):
             ).completions
 
         else:
-            values["client"] = openai.Completion
+            values["client"] = openai.Completion  # type: ignore
 
         return values
 
@@ -993,11 +993,11 @@ class OpenAIChat(BaseLLM):
     # may assume openai_api_key is a str)
     openai_api_key: Optional[str] = Field(default=None, alias="api_key")
     """Automatically inferred from env var `OPENAI_API_KEY` if not provided."""
-    openai_api_base: Optional[str] = Field(default=None, alias="base_url")
+    openai_api_base: Optional[str] = Field(default=None, alias="base_url")  # type: ignore
     """Base URL path for API requests, leave blank if not using a proxy or service 
         emulator."""
     # to support explicit proxy for OpenAI
-    openai_proxy: Optional[str] = None
+    openai_proxy: Optional[str] = None  # type: ignore
     max_retries: int = 6
     """Maximum number of retries to make when generating."""
     prefix_messages: List = Field(default_factory=list)
@@ -1029,15 +1029,15 @@ class OpenAIChat(BaseLLM):
         openai_api_key = get_from_dict_or_env(
             values, "openai_api_key", "OPENAI_API_KEY"
         )
-        openai_api_base = get_from_dict_or_env(
+        openai_api_base = get_from_dict_or_env(  # type: ignore
             values,
-            "openai_api_base",
+            "openai_api_base",  # type: ignore
             "OPENAI_API_BASE",
             default="",
         )
-        openai_proxy = get_from_dict_or_env(
+        openai_proxy = get_from_dict_or_env(  # type: ignore
             values,
-            "openai_proxy",
+            "openai_proxy",  # type: ignore
             "OPENAI_PROXY",
             default="",
         )
@@ -1048,19 +1048,19 @@ class OpenAIChat(BaseLLM):
             import openai
 
             openai.api_key = openai_api_key
-            if openai_api_base:
-                openai.api_base = openai_api_base
+            if openai_api_base:  # type: ignore
+                openai.api_base = openai_api_base  # type: ignore
             if openai_organization:
                 openai.organization = openai_organization
-            if openai_proxy:
-                openai.proxy = {"http": openai_proxy, "https": openai_proxy}  # type: ignore[assignment]  # noqa: E501
+            if openai_proxy:  # type: ignore
+                openai.proxy = {"http": openai_proxy, "https": openai_proxy}  # type: ignore  # noqa: E501
         except ImportError:
             raise ImportError(
                 "Could not import openai python package. "
                 "Please install it with `pip install openai`."
             )
         try:
-            values["client"] = openai.ChatCompletion
+            values["client"] = openai.ChatCompletion  # type: ignore
         except AttributeError:
             raise ValueError(
                 "`openai` has no `ChatCompletion` attribute, this is likely "

libs/community/langchain_community/llms/vllm.py

@@ -164,7 +164,7 @@ class VLLMOpenAI(BaseOpenAI):
             params.update(
                 {
                     "api_key": self.openai_api_key,
-                    "api_base": self.openai_api_base,
+                    "api_base": self.openai_api_base,  # type: ignore
                 }
             )
 

libs/community/langchain_community/tools/amadeus/closest_airport.py

@@ -51,6 +51,8 @@ class AmadeusClosestAirport(AmadeusBaseTool):
         location: str,
         run_manager: Optional[CallbackManagerForToolRun] = None,
     ) -> str:
+        if not self.llm:
+            raise ValueError("No language model (llm) has been set for this tool.")
         content = (
             f" What is the nearest airport to {location}? Please respond with the "
             " airport's International Air Transport Association (IATA) Location "

libs/community/langchain_community/tools/google_cloud/texttospeech.py

@@ -9,12 +9,12 @@ from langchain_core.tools import BaseTool
 from langchain_community.utilities.vertexai import get_client_info
 
 if TYPE_CHECKING:
-    from google.cloud import texttospeech
+    from google.cloud import texttospeech  # type: ignore
 
 
 def _import_google_cloud_texttospeech() -> Any:
     try:
-        from google.cloud import texttospeech
+        from google.cloud import texttospeech  # type: ignore
     except ImportError as e:
         raise ImportError(
             "Cannot import google.cloud.texttospeech, please install "

libs/community/langchain_community/utilities/dalle_image_generator.py

@@ -31,13 +31,13 @@ class DallEAPIWrapper(BaseModel):
     model_kwargs: Dict[str, Any] = Field(default_factory=dict)
     openai_api_key: Optional[str] = Field(default=None, alias="api_key")
     """Automatically inferred from env var `OPENAI_API_KEY` if not provided."""
-    openai_api_base: Optional[str] = Field(default=None, alias="base_url")
+    openai_api_base: Optional[str] = Field(default=None, alias="base_url")  # type: ignore
     """Base URL path for API requests, leave blank if not using a proxy or service 
         emulator."""
     openai_organization: Optional[str] = Field(default=None, alias="organization")
     """Automatically inferred from env var `OPENAI_ORG_ID` if not provided."""
     # to support explicit proxy for OpenAI
-    openai_proxy: Optional[str] = None
+    openai_proxy: Optional[str] = None  # type: ignore
     request_timeout: Union[float, Tuple[float, float], Any, None] = Field(
         default=None, alias="timeout"
     )
@@ -102,12 +102,12 @@ class DallEAPIWrapper(BaseModel):
             or os.getenv("OPENAI_ORGANIZATION")
             or None
         )
-        values["openai_api_base"] = values["openai_api_base"] or os.getenv(
+        values["openai_api_base"] = values["openai_api_base"] or os.getenv(  # type: ignore
             "OPENAI_API_BASE"
         )
-        values["openai_proxy"] = get_from_dict_or_env(
+        values["openai_proxy"] = get_from_dict_or_env(  # type: ignore
             values,
-            "openai_proxy",
+            "openai_proxy",  # type: ignore
             "OPENAI_PROXY",
             default="",
         )
@@ -125,7 +125,7 @@ class DallEAPIWrapper(BaseModel):
             client_params = {
                 "api_key": values["openai_api_key"],
                 "organization": values["openai_organization"],
-                "base_url": values["openai_api_base"],
+                "base_url": values["openai_api_base"],  # type: ignore
                 "timeout": values["request_timeout"],
                 "max_retries": values["max_retries"],
                 "default_headers": values["default_headers"],
@@ -138,7 +138,7 @@ class DallEAPIWrapper(BaseModel):
             if not values.get("async_client"):
                 values["async_client"] = openai.AsyncOpenAI(**client_params).images
         elif not values.get("client"):
-            values["client"] = openai.Image
+            values["client"] = openai.Image  # type: ignore
         else:
             pass
         return values

libs/community/langchain_community/utilities/vertexai.py

@@ -111,7 +111,7 @@ def get_client_info(module: Optional[str] = None) -> "ClientInfo":
 def load_image_from_gcs(path: str, project: Optional[str] = None) -> "Image":
     """Loads im Image from GCS."""
     try:
-        from google.cloud import storage
+        from google.cloud import storage  # type: ignore
     except ImportError:
         raise ImportError("Could not import google-cloud-storage python package.")
     from vertexai.preview.generative_models import Image

libs/community/langchain_community/vectorstores/astradb.py

@@ -15,7 +15,6 @@ from typing import (
     Optional,
     Set,
     Tuple,
-    Type,
     TypeVar,
 )
 
@@ -33,7 +32,6 @@ if TYPE_CHECKING:
     from astrapy.db import AstraDB as LibAstraDB
     from astrapy.db import AsyncAstraDB
 
-ADBVST = TypeVar("ADBVST", bound="AstraDB")
 T = TypeVar("T")
 U = TypeVar("U")
 DocDict = Dict[str, Any]  # dicts expressing entries to insert
@@ -1142,10 +1140,10 @@ class AstraDB(VectorStore):
 
     @classmethod
     def _from_kwargs(
-        cls: Type[ADBVST],
+        cls,
         embedding: Embeddings,
         **kwargs: Any,
-    ) -> ADBVST:
+    ) -> "AstraDB":
         known_kwargs = {
             "collection_name",
             "token",
@@ -1197,13 +1195,13 @@ class AstraDB(VectorStore):
 
     @classmethod
     def from_texts(
-        cls: Type[ADBVST],
+        cls,
         texts: List[str],
         embedding: Embeddings,
         metadatas: Optional[List[dict]] = None,
         ids: Optional[List[str]] = None,
         **kwargs: Any,
-    ) -> ADBVST:
+    ) -> "AstraDB":
         """Create an Astra DB vectorstore from raw texts.
 
         Args:
@@ -1232,13 +1230,13 @@ class AstraDB(VectorStore):
 
     @classmethod
     async def afrom_texts(
-        cls: Type[ADBVST],
+        cls,
         texts: List[str],
         embedding: Embeddings,
         metadatas: Optional[List[dict]] = None,
         ids: Optional[List[str]] = None,
         **kwargs: Any,
-    ) -> ADBVST:
+    ) -> "AstraDB":
         """Create an Astra DB vectorstore from raw texts.
 
         Args:
@@ -1267,11 +1265,11 @@ class AstraDB(VectorStore):
 
     @classmethod
     def from_documents(
-        cls: Type[ADBVST],
+        cls,
         documents: List[Document],
         embedding: Embeddings,
         **kwargs: Any,
-    ) -> ADBVST:
+    ) -> "AstraDB":
         """Create an Astra DB vectorstore from a document list.
 
         Utility method that defers to 'from_texts' (see that one).

libs/community/langchain_community/vectorstores/matching_engine.py

@@ -13,7 +13,7 @@ from langchain_core.vectorstores import VectorStore
 from langchain_community.utilities.vertexai import get_client_info
 
 if TYPE_CHECKING:
-    from google.cloud import storage
+    from google.cloud import storage  # type: ignore
     from google.cloud.aiplatform import MatchingEngineIndex, MatchingEngineIndexEndpoint
     from google.cloud.aiplatform.matching_engine.matching_engine_index_endpoint import (
         Namespace,
@@ -103,7 +103,7 @@ class MatchingEngine(VectorStore):
     def _validate_google_libraries_installation(self) -> None:
         """Validates that Google libraries that are needed are installed."""
         try:
-            from google.cloud import aiplatform, storage  # noqa: F401
+            from google.cloud import aiplatform, storage  # type: ignore # noqa: F401
             from google.oauth2 import service_account  # noqa: F401
         except ImportError:
             raise ImportError(
@@ -545,7 +545,7 @@ class MatchingEngine(VectorStore):
             A configured GCS client.
         """
 
-        from google.cloud import storage
+        from google.cloud import storage  # type: ignore
 
         return storage.Client(
             credentials=credentials,

libs/community/tests/integration_tests/adapters/test_openai.py

@@ -6,8 +6,8 @@ from langchain_community.adapters import openai as lcopenai
 def _test_no_stream(**kwargs: Any) -> None:
     import openai
 
-    result = openai.ChatCompletion.create(**kwargs)
-    lc_result = lcopenai.ChatCompletion.create(**kwargs)
+    result = openai.ChatCompletion.create(**kwargs)  # type: ignore
+    lc_result = lcopenai.ChatCompletion.create(**kwargs)  # type: ignore
     if isinstance(lc_result, dict):
         if isinstance(result, dict):
             result_dict = result["choices"][0]["message"].to_dict_recursive()
@@ -20,11 +20,11 @@ def _test_stream(**kwargs: Any) -> None:
     import openai
 
     result = []
-    for c in openai.ChatCompletion.create(**kwargs):
+    for c in openai.ChatCompletion.create(**kwargs):  # type: ignore
         result.append(c["choices"][0]["delta"].to_dict_recursive())
 
     lc_result = []
-    for c in lcopenai.ChatCompletion.create(**kwargs):
+    for c in lcopenai.ChatCompletion.create(**kwargs):  # type: ignore
         lc_result.append(c["choices"][0]["delta"])
     assert result == lc_result
 
@@ -32,8 +32,8 @@ def _test_stream(**kwargs: Any) -> None:
 async def _test_async(**kwargs: Any) -> None:
     import openai
 
-    result = await openai.ChatCompletion.acreate(**kwargs)
-    lc_result = await lcopenai.ChatCompletion.acreate(**kwargs)
+    result = await openai.ChatCompletion.acreate(**kwargs)  # type: ignore
+    lc_result = await lcopenai.ChatCompletion.acreate(**kwargs)  # type: ignore
     if isinstance(lc_result, dict):
         if isinstance(result, dict):
             result_dict = result["choices"][0]["message"].to_dict_recursive()
@@ -46,11 +46,11 @@ async def _test_astream(**kwargs: Any) -> None:
     import openai
 
     result = []
-    async for c in await openai.ChatCompletion.acreate(**kwargs):
+    async for c in await openai.ChatCompletion.acreate(**kwargs):  # type: ignore
         result.append(c["choices"][0]["delta"].to_dict_recursive())
 
     lc_result = []
-    async for c in await lcopenai.ChatCompletion.acreate(**kwargs):
+    async for c in await lcopenai.ChatCompletion.acreate(**kwargs):  # type: ignore
         lc_result.append(c["choices"][0]["delta"])
     assert result == lc_result
 

libs/community/tests/integration_tests/chat_models/test_openai.py

@@ -23,7 +23,7 @@ def test_chat_openai() -> None:
         temperature=0.7,
         base_url=None,
         organization=None,
-        openai_proxy=None,
+        openai_proxy=None,  # type: ignore
         timeout=10.0,
         max_retries=3,
         http_client=None,

libs/community/tests/integration_tests/embeddings/test_azure_openai.py

@@ -20,7 +20,7 @@ def _get_embeddings(**kwargs: Any) -> AzureOpenAIEmbeddings:
     return AzureOpenAIEmbeddings(
         azure_deployment=DEPLOYMENT_NAME,
         api_version=OPENAI_API_VERSION,
-        openai_api_base=OPENAI_API_BASE,
+        openai_api_base=OPENAI_API_BASE,  # type: ignore
         openai_api_key=OPENAI_API_KEY,
         **kwargs,
     )
@@ -104,7 +104,7 @@ def test_azure_openai_embedding_with_empty_string() -> None:
     output = embedding.embed_documents(document)
     assert len(output) == 2
     assert len(output[0]) == 1536
-    expected_output = openai.Embedding.create(input="", model="text-embedding-ada-002")[
+    expected_output = openai.Embedding.create(input="", model="text-embedding-ada-002")[  # type: ignore
         "data"
     ][0]["embedding"]
     assert np.allclose(output[0], expected_output)

libs/community/tests/integration_tests/embeddings/test_openai.py

@@ -70,7 +70,7 @@ def test_openai_embedding_with_empty_string() -> None:
     output = embedding.embed_documents(document)
     assert len(output) == 2
     assert len(output[0]) == 1536
-    expected_output = openai.Embedding.create(input="", model="text-embedding-ada-002")[
+    expected_output = openai.Embedding.create(input="", model="text-embedding-ada-002")[  # type: ignore
         "data"
     ][0]["embedding"]
     assert np.allclose(output[0], expected_output)

libs/community/tests/integration_tests/llms/test_azure_openai.py

@@ -22,7 +22,7 @@ def _get_llm(**kwargs: Any) -> AzureOpenAI:
     return AzureOpenAI(
         deployment_name=DEPLOYMENT_NAME,
         openai_api_version=OPENAI_API_VERSION,
-        openai_api_base=OPENAI_API_BASE,
+        openai_api_base=OPENAI_API_BASE,  # type: ignore
         openai_api_key=OPENAI_API_KEY,
         **kwargs,
     )

libs/community/tests/integration_tests/storage/test_astradb.py

@@ -1,10 +1,14 @@
 """Implement integration tests for AstraDB storage."""
 import os
+from typing import TYPE_CHECKING
 
 import pytest
 
 from langchain_community.storage.astradb import AstraDBByteStore, AstraDBStore
 
+if TYPE_CHECKING:
+    from astrapy.db import AstraDB
+
 
 def _has_env_vars() -> bool:
     return all(
@@ -16,7 +20,7 @@ def _has_env_vars() -> bool:
 
 
 @pytest.fixture
-def astra_db():
+def astra_db() -> AstraDB:
     from astrapy.db import AstraDB
 
     return AstraDB(
@@ -26,14 +30,14 @@ def astra_db():
     )
 
 
-def init_store(astra_db, collection_name: str):
+def init_store(astra_db: AstraDB, collection_name: str) -> AstraDBStore:
     astra_db.create_collection(collection_name)
     store = AstraDBStore(collection_name=collection_name, astra_db_client=astra_db)
     store.mset([("key1", [0.1, 0.2]), ("key2", "value2")])
     return store
 
 
-def init_bytestore(astra_db, collection_name: str):
+def init_bytestore(astra_db: AstraDB, collection_name: str) -> AstraDBByteStore:
     astra_db.create_collection(collection_name)
     store = AstraDBByteStore(collection_name=collection_name, astra_db_client=astra_db)
     store.mset([("key1", b"value1"), ("key2", b"value2")])
@@ -43,7 +47,7 @@ def init_bytestore(astra_db, collection_name: str):
 @pytest.mark.requires("astrapy")
 @pytest.mark.skipif(not _has_env_vars(), reason="Missing Astra DB env. vars")
 class TestAstraDBStore:
-    def test_mget(self, astra_db) -> None:
+    def test_mget(self, astra_db: AstraDB) -> None:
         """Test AstraDBStore mget method."""
         collection_name = "lc_test_store_mget"
         try:
@@ -52,7 +56,7 @@ class TestAstraDBStore:
         finally:
             astra_db.delete_collection(collection_name)
 
-    def test_mset(self, astra_db) -> None:
+    def test_mset(self, astra_db: AstraDB) -> None:
         """Test that multiple keys can be set with AstraDBStore."""
         collection_name = "lc_test_store_mset"
         try:
@@ -64,7 +68,7 @@ class TestAstraDBStore:
         finally:
             astra_db.delete_collection(collection_name)
 
-    def test_mdelete(self, astra_db) -> None:
+    def test_mdelete(self, astra_db: AstraDB) -> None:
         """Test that deletion works as expected."""
         collection_name = "lc_test_store_mdelete"
         try:
@@ -75,7 +79,7 @@ class TestAstraDBStore:
         finally:
             astra_db.delete_collection(collection_name)
 
-    def test_yield_keys(self, astra_db) -> None:
+    def test_yield_keys(self, astra_db: AstraDB) -> None:
         collection_name = "lc_test_store_yield_keys"
         try:
             store = init_store(astra_db, collection_name)
@@ -85,7 +89,7 @@ class TestAstraDBStore:
         finally:
             astra_db.delete_collection(collection_name)
 
-    def test_bytestore_mget(self, astra_db) -> None:
+    def test_bytestore_mget(self, astra_db: AstraDB) -> None:
         """Test AstraDBByteStore mget method."""
         collection_name = "lc_test_bytestore_mget"
         try:
@@ -94,7 +98,7 @@ class TestAstraDBStore:
         finally:
             astra_db.delete_collection(collection_name)
 
-    def test_bytestore_mset(self, astra_db) -> None:
+    def test_bytestore_mset(self, astra_db: AstraDB) -> None:
         """Test that multiple keys can be set with AstraDBByteStore."""
         collection_name = "lc_test_bytestore_mset"
         try:

libs/core/Makefile

@@ -42,7 +42,7 @@ lint lint_diff lint_package lint_tests:
 	[ "$(PYTHON_FILES)" = "" ] || poetry run ruff format $(PYTHON_FILES) --diff
 	[ "$(PYTHON_FILES)" = "" ] || poetry run ruff --select I $(PYTHON_FILES)
 	[ "$(PYTHON_FILES)" = "" ] || poetry run mypy $(PYTHON_FILES)
-	[ "$(PYTHON_FILES)" = "" ] || mkdir $(MYPY_CACHE) || poetry run mypy $(PYTHON_FILES) --cache-dir $(MYPY_CACHE)
+	[ "$(PYTHON_FILES)" = "" ] || mkdir -p $(MYPY_CACHE) && poetry run mypy $(PYTHON_FILES) --cache-dir $(MYPY_CACHE)
 
 format format_diff:
 	poetry run ruff format $(PYTHON_FILES)

libs/langchain/Makefile

@@ -62,7 +62,7 @@ lint lint_diff lint_package lint_tests:
 	poetry run ruff .
 	[ "$(PYTHON_FILES)" = "" ] || poetry run ruff format $(PYTHON_FILES) --diff
 	[ "$(PYTHON_FILES)" = "" ] || poetry run ruff --select I $(PYTHON_FILES)
-	[ "$(PYTHON_FILES)" = "" ] || mkdir $(MYPY_CACHE) || poetry run mypy $(PYTHON_FILES) --cache-dir $(MYPY_CACHE)
+	[ "$(PYTHON_FILES)" = "" ] || mkdir -p $(MYPY_CACHE) && poetry run mypy $(PYTHON_FILES) --cache-dir $(MYPY_CACHE)
 
 format format_diff:
 	[ "$(PYTHON_FILES)" = "" ] || poetry run ruff format $(PYTHON_FILES)