fix: add chat agent with hitl middleware

pyproject.toml

@@ -1,13 +1,11 @@
 [project]
 name = "uipath-langchain"
-version = "0.1.13"
+version = "0.1.14"
 description = "UiPath Langchain"
 readme = { file = "README.md", content-type = "text/markdown" }
 requires-python = ">=3.11"
 dependencies = [
-    "uipath-core>=0.0.6, <0.1.0",
-    "uipath-runtime>=0.1.2, <0.2.0",
-    "uipath>=2.2.11, <2.3.0",
+    "uipath>=2.2.16, <2.3.0",
     "langgraph>=1.0.0, <2.0.0",
     "langchain-core>=1.0.0, <2.0.0",
     "langgraph-checkpoint-sqlite>=3.0.0, <4.0.0",
@@ -110,3 +108,4 @@ name = "testpypi"
 url = "https://test.pypi.org/simple/"
 publish-url = "https://test.pypi.org/legacy/"
 explicit = true
+

samples/chat-agent/.agent/SDK_REFERENCE.md

@@ -259,37 +259,37 @@ Documents service
 # Classify a document using a DU Modern project.
 sdk.documents.classify(project_type: <enum 'ProjectType, tag: Optional[str]=None, project_name: Optional[str]=None, file: Union[IO[bytes], bytes, str, NoneType]=None, file_path: Optional[str]=None) -> typing.List[uipath.platform.documents.documents.ClassificationResult]
 
-# Asynchronously version of the [`classify`][uipath._services.documents_service.DocumentsService.classify] method.
+# Asynchronously version of the [`classify`][uipath.platform.documents._documents_service.DocumentsService.classify] method.
 sdk.documents.classify_async(project_type: <enum 'ProjectType, tag: Optional[str]=None, project_name: Optional[str]=None, file: Union[IO[bytes], bytes, str, NoneType]=None, file_path: Optional[str]=None) -> typing.List[uipath.platform.documents.documents.ClassificationResult]
 
 # Create a validate classification action for a document based on the classification results. More details about validation actions can be found in the [official documentation](https://docs.uipath.com/ixp/automation-cloud/latest/user-guide/validating-classifications).
 sdk.documents.create_validate_classification_action(action_title: str, action_priority: <enum 'ActionPriority, action_catalog: str, action_folder: str, storage_bucket_name: str, storage_bucket_directory_path: str, classification_results: List[uipath.platform.documents.documents.ClassificationResult]) -> uipath.platform.documents.documents.ValidateClassificationAction
 
-# Asynchronous version of the [`create_validation_action`][uipath._services.documents_service.DocumentsService.create_validate_classification_action] method.
+# Asynchronous version of the [`create_validation_action`][uipath.platform.documents._documents_service.DocumentsService.create_validate_classification_action] method.
 sdk.documents.create_validate_classification_action_async(action_title: str, action_priority: <enum 'ActionPriority, action_catalog: str, action_folder: str, storage_bucket_name: str, storage_bucket_directory_path: str, classification_results: List[uipath.platform.documents.documents.ClassificationResult]) -> uipath.platform.documents.documents.ValidateClassificationAction
 
 # Create a validate extraction action for a document based on the extraction response. More details about validation actions can be found in the [official documentation](https://docs.uipath.com/ixp/automation-cloud/latest/user-guide/validating-extractions).
 sdk.documents.create_validate_extraction_action(action_title: str, action_priority: <enum 'ActionPriority, action_catalog: str, action_folder: str, storage_bucket_name: str, storage_bucket_directory_path: str, extraction_response: uipath.platform.documents.documents.ExtractionResponse) -> uipath.platform.documents.documents.ValidateExtractionAction
 
-# Asynchronous version of the [`create_validation_action`][uipath._services.documents_service.DocumentsService.create_validate_extraction_action] method.
+# Asynchronous version of the [`create_validation_action`][uipath.platform.documents._documents_service.DocumentsService.create_validate_extraction_action] method.
 sdk.documents.create_validate_extraction_action_async(action_title: str, action_priority: <enum 'ActionPriority, action_catalog: str, action_folder: str, storage_bucket_name: str, storage_bucket_directory_path: str, extraction_response: uipath.platform.documents.documents.ExtractionResponse) -> uipath.platform.documents.documents.ValidateExtractionAction
 
 # Extract predicted data from a document using an DU Modern/IXP project.
 sdk.documents.extract(tag: Optional[str]=None, project_name: Optional[str]=None, file: Union[IO[bytes], bytes, str, NoneType]=None, file_path: Optional[str]=None, classification_result: Optional[uipath.platform.documents.documents.ClassificationResult]=None, project_type: Optional[uipath.platform.documents.documents.ProjectType]=None, document_type_name: Optional[str]=None) -> typing.Union[uipath.platform.documents.documents.ExtractionResponse, uipath.platform.documents.documents.ExtractionResponseIXP]
 
-# Asynchronously version of the [`extract`][uipath._services.documents_service.DocumentsService.extract] method.
+# Asynchronously version of the [`extract`][uipath.platform.documents._documents_service.DocumentsService.extract] method.
 sdk.documents.extract_async(tag: Optional[str]=None, project_name: Optional[str]=None, file: Union[IO[bytes], bytes, str, NoneType]=None, file_path: Optional[str]=None, classification_result: Optional[uipath.platform.documents.documents.ClassificationResult]=None, project_type: Optional[uipath.platform.documents.documents.ProjectType]=None, document_type_name: Optional[str]=None) -> typing.Union[uipath.platform.documents.documents.ExtractionResponse, uipath.platform.documents.documents.ExtractionResponseIXP]
 
 # Get the result of a validate classification action.
 sdk.documents.get_validate_classification_result(validation_action: uipath.platform.documents.documents.ValidateClassificationAction) -> typing.List[uipath.platform.documents.documents.ClassificationResult]
 
-# Asynchronous version of the [`get_validation_result`][uipath._services.documents_service.DocumentsService.get_validate_classification_result] method.
+# Asynchronous version of the [`get_validation_result`][uipath.platform.documents._documents_service.DocumentsService.get_validate_classification_result] method.
 sdk.documents.get_validate_classification_result_async(validation_action: uipath.platform.documents.documents.ValidateClassificationAction) -> typing.List[uipath.platform.documents.documents.ClassificationResult]
 
 # Get the result of a validate extraction action.
 sdk.documents.get_validate_extraction_result(validation_action: uipath.platform.documents.documents.ValidateExtractionAction) -> typing.Union[uipath.platform.documents.documents.ExtractionResponse, uipath.platform.documents.documents.ExtractionResponseIXP]
 
-# Asynchronous version of the [`get_validation_result`][uipath._services.documents_service.DocumentsService.get_validate_extraction_result] method.
+# Asynchronous version of the [`get_validation_result`][uipath.platform.documents._documents_service.DocumentsService.get_validate_extraction_result] method.
 sdk.documents.get_validate_extraction_result_async(validation_action: uipath.platform.documents.documents.ValidateExtractionAction) -> typing.Union[uipath.platform.documents.documents.ExtractionResponse, uipath.platform.documents.documents.ExtractionResponseIXP]
 
 ```
@@ -411,7 +411,7 @@ Llm service
 
 ```python
 # Generate chat completions using UiPath's normalized LLM Gateway API.
-sdk.llm.chat_completions(messages: Union[List[Dict[str, str]], List[tuple[str, str]]], model: str="gpt-4o-mini-2024-07-18", max_tokens: int=4096, temperature: float=0, n: int=1, frequency_penalty: float=0, presence_penalty: float=0, top_p: Optional[float]=1, top_k: Optional[int]=None, tools: Optional[List[uipath.platform.llm_gateway.llm_gateway.ToolDefinition]]=None, tool_choice: Union[uipath.platform.llm_gateway.llm_gateway.AutoToolChoice, uipath.platform.llm_gateway.llm_gateway.RequiredToolChoice, uipath.platform.llm_gateway.llm_gateway.SpecificToolChoice, Literal['auto', 'none'], NoneType]=None, response_format: Union[Dict[str, Any], type[pydantic.main.BaseModel], NoneType]=None, api_version: str="2024-08-01-preview")
+sdk.llm.chat_completions(messages: list[dict[str, str]] | list[tuple[str, str]], model: str="gpt-4o-mini-2024-07-18", max_tokens: int=4096, temperature: float=0, n: int=1, frequency_penalty: float=0, presence_penalty: float=0, top_p: float | None=1, top_k: int | None=None, tools: list[uipath.platform.llm_gateway.llm_gateway.ToolDefinition] | None=None, tool_choice: Union[uipath.platform.llm_gateway.llm_gateway.AutoToolChoice, uipath.platform.llm_gateway.llm_gateway.RequiredToolChoice, uipath.platform.llm_gateway.llm_gateway.SpecificToolChoice, Literal['auto', 'none'], NoneType]=None, response_format: dict[str, Any] | type[pydantic.main.BaseModel] | None=None, api_version: str="2024-08-01-preview")
 
 ```
 
@@ -421,7 +421,7 @@ Llm Openai service
 
 ```python
 # Generate chat completions using UiPath's LLM Gateway service.
-sdk.llm_openai.chat_completions(messages: List[Dict[str, str]], model: str="gpt-4o-mini-2024-07-18", max_tokens: int=4096, temperature: float=0, response_format: Union[Dict[str, Any], type[pydantic.main.BaseModel], NoneType]=None, api_version: str="2024-10-21")
+sdk.llm_openai.chat_completions(messages: list[dict[str, str]], model: str="gpt-4o-mini-2024-07-18", max_tokens: int=4096, temperature: float=0, response_format: dict[str, Any] | type[pydantic.main.BaseModel] | None=None, api_version: str="2024-10-21")
 
 # Generate text embeddings using UiPath's LLM Gateway service.
 sdk.llm_openai.embeddings(input: str, embedding_model: str="text-embedding-ada-002", openai_api_version: str="2024-10-21")
@@ -434,16 +434,16 @@ Mcp service
 
 ```python
 # List all MCP servers.
-sdk.mcp.list(folder_path: Optional[str]=None) -> typing.List[uipath.platform.orchestrator.mcp.McpServer]
+sdk.mcp.list(folder_path: str | None=None) -> typing.List[uipath.platform.orchestrator.mcp.McpServer]
 
 # Asynchronously list all MCP servers.
-sdk.mcp.list_async(folder_path: Optional[str]=None) -> typing.List[uipath.platform.orchestrator.mcp.McpServer]
+sdk.mcp.list_async(folder_path: str | None=None) -> typing.List[uipath.platform.orchestrator.mcp.McpServer]
 
 # Retrieve a specific MCP server by its slug.
-sdk.mcp.retrieve(slug: str, folder_path: Optional[str]=None) -> uipath.platform.orchestrator.mcp.McpServer
+sdk.mcp.retrieve(slug: str, folder_path: str | None=None) -> uipath.platform.orchestrator.mcp.McpServer
 
 # Asynchronously retrieve a specific MCP server by its slug.
-sdk.mcp.retrieve_async(slug: str, folder_path: Optional[str]=None) -> uipath.platform.orchestrator.mcp.McpServer
+sdk.mcp.retrieve_async(slug: str, folder_path: str | None=None) -> uipath.platform.orchestrator.mcp.McpServer
 
 ```
 

samples/chat-agent/entry-points.json

@@ -4,7 +4,7 @@
     "entryPoints": [
         {
             "filePath": "agent",
-            "uniqueId": "f5a38c3c-199a-4c57-b49b-e8b8eb7319f7",
+            "uniqueId": "9c094a08-edb8-4e43-b4bd-94e4c1665d5f",
             "type": "agent",
             "input": {
                 "type": "object",
@@ -2142,26 +2142,38 @@
                     {
                         "id": "__start__",
                         "name": "__start__",
-                        "type": "Node",
-                        "subgraph": null
+                        "type": "__start__",
+                        "subgraph": null,
+                        "metadata": {}
                     },
                     {
                         "id": "model",
                         "name": "model",
-                        "type": "Node",
-                        "subgraph": null
+                        "type": "model",
+                        "subgraph": null,
+                        "metadata": {
+                            "model_name": "claude-3-7-sonnet-latest",
+                            "max_tokens": 64000
+                        }
                     },
                     {
                         "id": "tools",
                         "name": "tools",
-                        "type": "Node",
-                        "subgraph": null
+                        "type": "tool",
+                        "subgraph": null,
+                        "metadata": {
+                            "tool_names": [
+                                "tavily_search"
+                            ],
+                            "tool_count": 1
+                        }
                     },
                     {
                         "id": "__end__",
                         "name": "__end__",
-                        "type": "Node",
-                        "subgraph": null
+                        "type": "__end__",
+                        "subgraph": null,
+                        "metadata": {}
                     }
                 ],
                 "edges": [

samples/chat-agent/pyproject.toml

@@ -9,7 +9,7 @@ dependencies = [
     "langchain-anthropic>=1.2.0",
     "tavily-python>=0.7.13",
     "langchain-tavily>=0.2.13",
-    "uipath-langchain>=0.1.0, <0.2.0",
+    "uipath-langchain>=0.1.11, <0.2.0",
     "uipath>=2.2.0, <2.3.0",
 ]
 
@@ -49,5 +49,5 @@ lint.ignore = [
 
 [dependency-groups]
 dev = [
-    "uipath-dev>=0.0.5",
+     "uipath-dev==0.0.11",
 ]