Fix/fix OpenAI clients for responses API at invocation time

.env.example

@@ -54,7 +54,9 @@ LLMGW_ACCESS_TOKEN=""
 LLMGW_CLIENT_ID=""
 LLMGW_CLIENT_SECRET=""
 
-# Optional tracking and tracing
+# Optional for tracking and BYOM
 LLMGW_SEMANTIC_USER_ID=""
+
 LLMGW_ACTION_ID=""
-LLMGW_ADDITIONAL_HEADERS=""
+LLMGW_OPERATION_CODE=""
+LlMGW_ADDITIONAL_HEADERS=""

packages/uipath_langchain_client/CHANGELOG.md

@@ -2,6 +2,11 @@
 
 All notable changes to `uipath_langchain_client` will be documented in this file.
 
+## [1.1.2] - 2026-02-12
+
+### Refactor
+- Rename normalized client for better comaptibility with other packages
+
 ## [1.1.1] - 2026-02-11
 
 ### Fixes
@@ -135,15 +140,15 @@ All notable changes to `uipath_langchain_client` will be documented in this file
 - `UiPathChatBedrock` - AWS Bedrock models
 - `UiPathChatBedrockConverse` - AWS Bedrock Converse API
 - `UiPathAzureAIChatCompletionsModel` - Azure AI models (non-OpenAI)
-- `UiPathNormalizedChatModel` - Provider-agnostic normalized API
+- `UiPathChat` - Provider-agnostic normalized API
 
 ### Embeddings Classes
 - `UiPathOpenAIEmbeddings` - OpenAI embeddings via direct API
 - `UiPathAzureOpenAIEmbeddings` - OpenAI embeddings via Azure
 - `UiPathGoogleGenerativeAIEmbeddings` - Google embeddings
 - `UiPathBedrockEmbeddings` - AWS Bedrock embeddings
 - `UiPathAzureAIEmbeddingsModel` - Azure AI embeddings
-- `UiPathNormalizedEmbeddings` - Provider-agnostic normalized API
+- `UiPathEmbeddings` - Provider-agnostic normalized API
 
 ### Features
 - Support for BYO (Bring Your Own) model connections

packages/uipath_langchain_client/README.md

@@ -56,7 +56,7 @@ For more control, instantiate provider-specific classes directly:
 from uipath_langchain_client.openai.chat_models import UiPathAzureChatOpenAI
 from uipath_langchain_client.google.chat_models import UiPathChatGoogleGenerativeAI
 from uipath_langchain_client.anthropic.chat_models import UiPathChatAnthropic
-from uipath_langchain_client.normalized.chat_models import UiPathNormalizedChatModel
+from uipath_langchain_client.normalized.chat_models import UiPathChat
 from uipath_langchain_client.settings import get_default_client_settings
 
 settings = get_default_client_settings()
@@ -75,7 +75,7 @@ claude_chat = UiPathChatAnthropic(
 )
 
 # Normalized (provider-agnostic)
-normalized_chat = UiPathNormalizedChatModel(model="gpt-4o-2024-11-20", settings=settings)
+normalized_chat = UiPathChat(model="gpt-4o-2024-11-20", settings=settings)
 ```
 
 ## Available Client Types
@@ -99,8 +99,8 @@ Uses UiPath's normalized API for a consistent interface across all providers.
 
 | Class | Description |
 |-------|-------------|
-| `UiPathNormalizedChatModel` | Provider-agnostic chat completions |
-| `UiPathNormalizedEmbeddings` | Provider-agnostic embeddings |
+| `UiPathChat` | Provider-agnostic chat completions |
+| `UiPathEmbeddings` | Provider-agnostic embeddings |
 
 ## Features
 

packages/uipath_langchain_client/src/uipath_langchain_client/__version__.py

@@ -1,3 +1,3 @@
 __title__ = "UiPath LangChain Client"
 __description__ = "A Python client for interacting with UiPath's LLM services via LangChain."
-__version__ = "1.1.1"
+__version__ = "1.1.2"

packages/uipath_langchain_client/src/uipath_langchain_client/clients/anthropic/chat_models.py

@@ -33,19 +33,21 @@ class UiPathChatAnthropic(UiPathBaseLLMClient, ChatAnthropic):
         vendor_type="anthropic",
         freeze_base_url=True,
     )
-    vendor_type: Literal["anthropic", "azure", "vertexai", "awsbedrock"] = "awsbedrock"
+    vendor_type: Literal["anthropic", "azure", "vertexai", "awsbedrock"] = "anthropic"
 
     @model_validator(mode="after")
     def setup_api_flavor_and_version(self) -> Self:
+        self.api_config.vendor_type = self.vendor_type
         match self.vendor_type:
             case "vertexai":
                 self.api_config.api_flavor = "anthropic-claude"
                 self.api_config.api_version = "v1beta1"
             case "awsbedrock":
                 self.api_config.api_flavor = "invoke"
             case _:
-                raise ValueError("Those vendors are currently not supported")
-        self.api_config.vendor_type = self.vendor_type
+                raise ValueError(
+                    "anthropic and azure vendors are currently not supported by UiPath"
+                )
         return self
 
     # Override fields to avoid typing issues and fix stuff

packages/uipath_langchain_client/src/uipath_langchain_client/clients/normalized/__init__.py

@@ -1,4 +1,4 @@
-from uipath_langchain_client.clients.normalized.chat_models import UiPathNormalizedChatModel
-from uipath_langchain_client.clients.normalized.embeddings import UiPathNormalizedEmbeddings
+from uipath_langchain_client.clients.normalized.chat_models import UiPathChat
+from uipath_langchain_client.clients.normalized.embeddings import UiPathEmbeddings
 
-__all__ = ["UiPathNormalizedChatModel", "UiPathNormalizedEmbeddings"]
+__all__ = ["UiPathChat", "UiPathEmbeddings"]

packages/uipath_langchain_client/src/uipath_langchain_client/clients/normalized/chat_models.py

@@ -12,11 +12,11 @@
 - Extended thinking/reasoning parameters for supported models
 
 Example:
-    >>> from uipath_langchain_client.normalized.chat_models import UiPathNormalizedChatModel
+    >>> from uipath_langchain_client.normalized.chat_models import UiPathChat
     >>> from uipath_langchain_client.settings import get_default_client_settings
     >>>
     >>> settings = get_default_client_settings()
-    >>> chat = UiPathNormalizedChatModel(
+    >>> chat = UiPathChat(
     ...     model="gpt-4o-2024-11-20",
     ...     settings=settings,
     ... )
@@ -60,7 +60,7 @@
 from uipath_langchain_client.settings import UiPathAPIConfig
 
 
-class UiPathNormalizedChatModel(UiPathBaseLLMClient, BaseChatModel):
+class UiPathChat(UiPathBaseLLMClient, BaseChatModel):
     """LangChain chat model using UiPath's normalized (provider-agnostic) API.
 
     This model provides a consistent interface across all LLM providers supported
@@ -86,7 +86,7 @@ class UiPathNormalizedChatModel(UiPathBaseLLMClient, BaseChatModel):
         include_thoughts: Whether to include thinking in Gemini responses.
 
     Example:
-        >>> chat = UiPathNormalizedChatModel(
+        >>> chat = UiPathChat(
         ...     model="gpt-4o-2024-11-20",
         ...     settings=settings,
         ...     temperature=0.7,

packages/uipath_langchain_client/src/uipath_langchain_client/clients/normalized/embeddings.py

@@ -3,7 +3,7 @@
 from uipath_langchain_client.settings import UiPathAPIConfig
 
 
-class UiPathNormalizedEmbeddings(UiPathBaseLLMClient, Embeddings):
+class UiPathEmbeddings(UiPathBaseLLMClient, Embeddings):
     """LangChain embeddings using the UiPath's normalized embeddings API.
 
     Provides a consistent interface for generating text embeddings across all

packages/uipath_langchain_client/src/uipath_langchain_client/clients/openai/chat_models.py

@@ -1,6 +1,7 @@
 from collections.abc import Awaitable, Callable
 from typing import Self
 
+from httpx import Request
 from pydantic import Field, SecretStr, model_validator
 from uipath_langchain_client.base_client import UiPathBaseLLMClient
 from uipath_langchain_client.settings import UiPathAPIConfig
@@ -21,25 +22,36 @@ class UiPathChatOpenAI(UiPathBaseLLMClient, ChatOpenAI):  # type: ignore[overrid
         api_type="completions",
         client_type="passthrough",
         vendor_type="openai",
-        freeze_base_url=True,
+        api_version="2025-03-01-preview",
+        freeze_base_url=False,
     )
 
     # Override fields to avoid errors when instantiating the class
     openai_api_key: SecretStr | None | Callable[[], str] | Callable[[], Awaitable[str]] = Field(
         alias="api_key", default=SecretStr("PLACEHOLDER")
     )
 
-    @model_validator(mode="after")
-    def setup_uipath_api_flavor_and_version(self) -> Self:
-        self.api_config.api_version = "2025-03-01-preview"
-        if self._use_responses_api({}):
-            self.api_config.api_flavor = "responses"
-        else:
-            self.api_config.api_flavor = "chat-completions"
-        return self
-
     @model_validator(mode="after")
     def setup_uipath_client(self) -> Self:
+        def fix_url_and_api_flavor_header(request: Request):
+            url_suffix = str(request.url).split(str(self.uipath_sync_client.base_url))[-1]
+            if "responses" in url_suffix:
+                request.headers["X-UiPath-LlmGateway-ApiFlavor"] = "responses"
+            else:
+                request.headers["X-UiPath-LlmGateway-ApiFlavor"] = "chat-completions"
+            request.url = self.uipath_sync_client.base_url
+
+        async def fix_url_and_api_flavor_header_async(request: Request):
+            url_suffix = str(request.url).split(str(self.uipath_async_client.base_url))[-1]
+            if "responses" in url_suffix:
+                request.headers["X-UiPath-LlmGateway-ApiFlavor"] = "responses"
+            else:
+                request.headers["X-UiPath-LlmGateway-ApiFlavor"] = "chat-completions"
+            request.url = self.uipath_async_client.base_url
+
+        self.uipath_sync_client.event_hooks["request"].append(fix_url_and_api_flavor_header)
+        self.uipath_async_client.event_hooks["request"].append(fix_url_and_api_flavor_header_async)
+
         self.root_client = OpenAI(
             api_key="PLACEHOLDER",
             timeout=None,  # handled by the UiPath client
@@ -62,25 +74,35 @@ class UiPathAzureChatOpenAI(UiPathBaseLLMClient, AzureChatOpenAI):  # type: igno
         api_type="completions",
         client_type="passthrough",
         vendor_type="openai",
-        freeze_base_url=True,
+        api_version="2025-03-01-preview",
+        freeze_base_url=False,
     )
 
     # Override fields to avoid errors when instantiating the class
     azure_endpoint: str | None = Field(default="PLACEHOLDER")
     openai_api_version: str | None = Field(default="PLACEHOLDER", alias="api_version")
     openai_api_key: SecretStr | None = Field(default=SecretStr("PLACEHOLDER"), alias="api_key")
 
-    @model_validator(mode="after")
-    def setup_uipath_api_flavor_and_version(self) -> Self:
-        self.api_config.api_version = "2025-03-01-preview"
-        if self._use_responses_api({}):
-            self.api_config.api_flavor = "responses"
-        else:
-            self.api_config.api_flavor = "chat-completions"
-        return self
-
     @model_validator(mode="after")
     def setup_uipath_client(self) -> Self:
+        def fix_url_and_api_flavor_header(request: Request):
+            url_suffix = str(request.url).split(str(self.uipath_sync_client.base_url))[-1]
+            if "responses" in url_suffix:
+                request.headers["X-UiPath-LlmGateway-ApiFlavor"] = "responses"
+            else:
+                request.headers["X-UiPath-LlmGateway-ApiFlavor"] = "chat-completions"
+            request.url = self.uipath_sync_client.base_url
+
+        async def fix_url_and_api_flavor_header_async(request: Request):
+            url_suffix = str(request.url).split(str(self.uipath_async_client.base_url))[-1]
+            if "responses" in url_suffix:
+                request.headers["X-UiPath-LlmGateway-ApiFlavor"] = "responses"
+            else:
+                request.headers["X-UiPath-LlmGateway-ApiFlavor"] = "chat-completions"
+            request.url = self.uipath_async_client.base_url
+
+        self.uipath_sync_client.event_hooks["request"].append(fix_url_and_api_flavor_header)
+        self.uipath_async_client.event_hooks["request"].append(fix_url_and_api_flavor_header_async)
         self.root_client = AzureOpenAI(
             azure_endpoint="PLACEHOLDER",
             api_version="PLACEHOLDER",

packages/uipath_langchain_client/src/uipath_langchain_client/factory.py

@@ -96,10 +96,10 @@ def get_chat_model(
 
     if client_type == "normalized":
         from uipath_langchain_client.clients.normalized.chat_models import (
-            UiPathNormalizedChatModel,
+            UiPathChat,
         )
 
-        return UiPathNormalizedChatModel(
+        return UiPathChat(
             model=model_name,
             settings=client_settings,
             byo_connection_id=byo_connection_id,
@@ -239,10 +239,10 @@ def get_embedding_model(
 
     if client_type == "normalized":
         from uipath_langchain_client.clients.normalized.embeddings import (
-            UiPathNormalizedEmbeddings,
+            UiPathEmbeddings,
         )
 
-        return UiPathNormalizedEmbeddings(
+        return UiPathEmbeddings(
             model=model_name,
             settings=client_settings,
             byo_connection_id=byo_connection_id,

src/uipath_llm_client/httpx_client.py

@@ -219,7 +219,7 @@ class UiPathHttpxAsyncClient(AsyncClient):
 
     _streaming_header: str = "X-UiPath-Streaming-Enabled"
     _default_headers: Mapping[str, str] = {
-        "X-UiPath-LLMGateway-TimeoutSeconds": "30",  # server side timeout, default is 10, maximum is 300
+        "X-UiPath-LLMGateway-TimeoutSeconds": "295",  # server side timeout, default is 10, maximum is 300
         "X-UiPath-LLMGateway-AllowFull4xxResponse": "true",  # allow full 4xx responses (default is false)
     }
 

tests/langchain/conftest.py

@@ -12,7 +12,7 @@
 from uipath_langchain_client.clients.bedrock.embeddings import UiPathBedrockEmbeddings
 from uipath_langchain_client.clients.google.chat_models import UiPathChatGoogleGenerativeAI
 from uipath_langchain_client.clients.google.embeddings import UiPathGoogleGenerativeAIEmbeddings
-from uipath_langchain_client.clients.normalized.chat_models import UiPathNormalizedChatModel
+from uipath_langchain_client.clients.normalized.chat_models import UiPathChat
 from uipath_langchain_client.clients.openai.chat_models import (
     UiPathAzureChatOpenAI,
     UiPathChatOpenAI,
@@ -28,7 +28,7 @@
 GPT_MODELS_NON_REASONING_CONFIGS = [
     {"model_class": UiPathAzureChatOpenAI},
     {"model_class": UiPathAzureChatOpenAI, "model_kwargs": {"use_responses_api": True}},
-    # {"model_class": UiPathNormalizedChatModel},
+    # {"model_class": UiPathChat},
 ]
 
 GPT_MODELS_WITH_REASONING_CONFIGS = [
@@ -43,7 +43,7 @@
             "verbosity": "low",
         },
     },
-    # {"model_class": UiPathNormalizedChatModel, "model_kwargs": {"reasoning_effort": "low"}},
+    # {"model_class": UiPathChat, "model_kwargs": {"reasoning_effort": "low"}},
 ]
 
 GEMINI_2_5_CONFIGS = [
@@ -56,7 +56,7 @@
         "model_kwargs": {"thinking_budget": 128, "include_thoughts": True},
     },
     # {
-    #     "model_class": UiPathNormalizedChatModel,
+    #     "model_class": UiPathChat,
     #     "model_kwargs": {"thinking_budget": 128, "include_thoughts": True},
     # },
 ]
@@ -71,7 +71,7 @@
         "model_kwargs": {"thinking_level": "low", "include_thoughts": True},
     },
     # {
-    #     "model_class": UiPathNormalizedChatModel,
+    #     "model_class": UiPathChat,
     #     "model_kwargs": {"thinking_level": "low", "include_thoughts": True},
     # },
 ]
@@ -101,7 +101,7 @@
             "thinking": {"type": "enabled", "budget_tokens": 1024},
         },
     },
-    # {"model_class": UiPathNormalizedChatModel},
+    # {"model_class": UiPathChat},
 ]
 
 CLAUDE_MODELS_AWSBEDROCK_CONFIGS = [
@@ -139,7 +139,7 @@
             "thinking": {"type": "enabled", "budget_tokens": 1024},
         },
     },
-    # {"model_class": UiPathNormalizedChatModel},
+    # {"model_class": UiPathChat},
 ]
 
 COMPLETIONS_MODELS_WITH_CONFIGS = {
@@ -164,7 +164,7 @@
 
 
 COMPLETION_CLIENTS_CLASSES = [
-    UiPathNormalizedChatModel,
+    UiPathChat,
     UiPathChatOpenAI,
     UiPathAzureChatOpenAI,
     # UiPathAzureAIChatCompletionsModel,
@@ -175,7 +175,7 @@
     # UiPathChatBedrockConverse,
 ]
 EMBEDDINGS_CLIENTS_CLASSES = [
-    # UiPathNormalizedEmbeddings,
+    # UiPathEmbeddings,
     UiPathOpenAIEmbeddings,
     UiPathAzureOpenAIEmbeddings,
     # UiPathAzureAIEmbeddingsModel,
@@ -214,11 +214,11 @@ def completions_config(
 EMBEDDINGS_MODELS_WITH_CONFIGS = {
     "text-embedding-3-large": [
         {"model_class": UiPathAzureOpenAIEmbeddings},
-        # {"model_class": UiPathNormalizedEmbeddings},
+        # {"model_class": UiPathEmbeddings},
     ],
     "gemini-embedding-001": [
         {"model_class": UiPathGoogleGenerativeAIEmbeddings},
-        # {"model_class": UiPathNormalizedEmbeddings},
+        # {"model_class": UiPathEmbeddings},
     ],
 }