fix: documentation OpenAI

README.md

@@ -13,6 +13,7 @@ All packages are extensions to the [UiPath Python SDK](https://github.com/UiPath
 
 Build agents using the [LlamaIndex SDK](https://www.llamaindex.ai/):
 
+- [README](packages/uipath-llamaindex/README.md)
 - [Docs](https://uipath.github.io/uipath-python/llamaindex/quick_start/)
 - [Samples](packages/uipath-llamaindex/samples/)
 
@@ -23,6 +24,7 @@ Build agents using the [LlamaIndex SDK](https://www.llamaindex.ai/):
 
 Build agents using the [OpenAI Agents SDK](https://github.com/openai/openai-agents-python):
 
+- [README](packages/uipath-openai-agents/README.md)
 - [Docs](https://uipath.github.io/uipath-python/openai-agents/quick_start/)
 - [Samples](packages/uipath-openai-agents/samples/)
 

packages/uipath-openai-agents/README.md

@@ -1,32 +1,125 @@
-# UiPath OpenAI Agents SDK
+# UiPath OpenAI Agents Python SDK
 
-Build intelligent AI agents with OpenAI's Agents framework and UiPath.
+[![PyPI - Version](https://img.shields.io/pypi/v/uipath-openai-agents)](https://pypi.org/project/uipath-openai-agents/)
+[![PyPI downloads](https://img.shields.io/pypi/dm/uipath-openai-agents.svg)](https://pypi.org/project/uipath-openai-agents/)
+[![Python versions](https://img.shields.io/pypi/pyversions/uipath-openai-agents.svg)](https://pypi.org/project/uipath-openai-agents/)
+
+A Python SDK that enables developers to build and deploy OpenAI Agents to the UiPath Cloud Platform. It provides programmatic interaction with UiPath Cloud Platform services.
+
+This package is an extension to the [UiPath Python SDK](https://github.com/UiPath/uipath-python) and implements the [UiPath Runtime Protocol](https://github.com/UiPath/uipath-runtime-python).
+
+Check out these [sample projects](https://github.com/UiPath/uipath-integrations-python/tree/main/packages/uipath-openai-agents/samples) to see the SDK in action.
+
+## Requirements
+
+-   Python 3.11 or higher
+-   UiPath Automation Cloud account
 
 ## Installation
 
 ```bash
 pip install uipath-openai-agents
 ```
 
-## Quick Start
+using `uv`:
+
+```bash
+uv add uipath-openai-agents
+```
+
+## Configuration
+
+### Environment Variables
+
+Create a `.env` file in your project root with the following variables:
+
+```
+UIPATH_URL=https://cloud.uipath.com/ACCOUNT_NAME/TENANT_NAME
+UIPATH_ACCESS_TOKEN=YOUR_TOKEN_HERE
+```
+
+## Command Line Interface (CLI)
+
+The SDK provides a command-line interface for creating, packaging, and deploying OpenAI Agents:
+
+### Authentication
+
+```bash
+uipath auth
+```
+
+This command opens a browser for authentication and creates/updates your `.env` file with the proper credentials.
+
+### Initialize a Project
+
+```bash
+uipath init
+```
+
+Running `uipath init` will process the agent definitions in the `openai_agents.json` file and create the corresponding `entry-points.json` file needed for deployment.
+
+For more details on the configuration format, see the [UiPath configuration specifications](https://github.com/UiPath/uipath-python/blob/main/specs/README.md).
+
+### Debug a Project
+
+```bash
+uipath run AGENT [INPUT]
+```
+
+Executes the agent with the provided JSON input arguments.
+
+### Package a Project
+
+```bash
+uipath pack
+```
+
+Packages your project into a `.nupkg` file that can be deployed to UiPath.
+
+**Note:** Your `pyproject.toml` must include:
+
+-   A description field (avoid characters: &, <, >, ", ', ;)
+-   Author information
+
+Example:
+
+```toml
+description = "Your package description"
+authors = [{name = "Your Name", email = "your.email@example.com"}]
+```
+
+### Publish a Package
+
+```bash
+uipath publish
+```
+
+Publishes the most recently created package to your UiPath Orchestrator.
+
+## Project Structure
+
+To properly use the CLI for packaging and publishing, your project should include:
 
-See the [main repository documentation](../../docs/) for getting started guides and examples.
+-   A `pyproject.toml` file with project metadata
+-   A `openai_agents.json` file with your agent definitions (e.g., `"agents": {"agent": "main.py:agent"}`)
+-   A `entry-points.json` file (generated by `uipath init`)
+-   A `bindings.json` file (generated by `uipath init`) to configure resource overrides
+-   Any Python files needed for your automation
 
-## Features
+## Development
 
-- **OpenAI Agents Integration**: Build agents using OpenAI's native Agents framework
-- **Agent Orchestration**: Multi-agent coordination and communication
-- **State Management**: Persistent agent state with SQLite sessions
-- **UiPath Integration**: Seamless integration with UiPath runtime and tooling
+### Developer Tools
 
-## Status
+Check out [uipath-dev](https://github.com/uipath/uipath-dev-python) - an interactive terminal application for building, testing, and debugging UiPath Python runtimes, agents, and automation scripts.
 
-⚠️ **Early Development**: This package is in early development (v0.1.0). APIs may change as the OpenAI Agents framework evolves.
+### Setting Up a Development Environment
 
-## Documentation
+Please read our [contribution guidelines](https://github.com/UiPath/uipath-integrations-python/packages/uipath-openai-agents/blob/main/CONTRIBUTING.md) before submitting a pull request.
 
-Full documentation is available in the [main repository](https://github.com/UiPath/uipath-llamaindex-python).
+### Special Thanks
 
-## License
+A huge thank-you to the open-source community and the maintainers of the libraries that make this project possible:
 
-See [LICENSE](../../LICENSE) in the repository root.
+- [OpenAI](https://github.com/openai/openai-python) for providing a powerful framework for building AI agents.
+- [OpenInference](https://github.com/Arize-ai/openinference) for observability and instrumentation support.
+- [Pydantic](https://github.com/pydantic/pydantic) for reliable, typed configuration and validation.

packages/uipath-openai-agents/docs/quick_start.md

@@ -106,7 +106,7 @@ Generate your first UiPath OpenAI agent:
 ✓  Created 'pyproject.toml' file.
 🔧  Please ensure to define OPENAI_API_KEY in your .env file.
 💡  Initialize project: uipath init
-💡  Run agent: uipath run agent '{"message": "Hello"}'
+💡  Run agent: uipath run agent '{"messages": "Hello"}'
 ```
 
 This command creates the following files:
@@ -173,7 +173,7 @@ Execute the agent with a sample input:
 <!-- termynal -->
 
 ```shell
-> uipath run agent '{"message": "Hello"}'
+> uipath run agent '{"messages": "Hello"}'
 {'response': 'Hello! How can I help you today?', 'agent_used': 'main'}
 ✓  Successful execution.
 ```
@@ -185,19 +185,19 @@ Depending on the shell you are using, it may be necessary to escape the input js
 
 /// tab | Bash/ZSH/PowerShell
 ```console
-uipath run agent '{"message": "Hello"}'
+uipath run agent '{"messages": "Hello"}'
 ```
 ///
 
 /// tab | Windows CMD
 ```console
-uipath run agent "{""message"": ""Hello""}"
+uipath run agent "{""messages"": ""Hello""}"
 ```
 ///
 
 /// tab | Windows PowerShell
 ```console
-uipath run agent '{\"message\":\"Hello\"}'
+uipath run agent '{\"messages\":\"Hello\"}'
 ```
 ///
 
@@ -215,7 +215,7 @@ The `run` command can also take a .json file as an input. You can create a file
 
 ```json
 {
-  "message": "Hello"
+  "messages": "Hello"
 }
 ```
 
@@ -275,7 +275,7 @@ Set the environment variables using the provided link.
 <!-- termynal -->
 
 ```shell
-> uipath invoke agent '{"message": "Hello"}'
+> uipath invoke agent '{"messages": "Hello"}'
 ⠴ Loading configuration ...
 ⠴ Starting job ...
 ✨ Job started successfully!

packages/uipath-openai-agents/pyproject.toml

@@ -70,7 +70,8 @@ plugins = [
   "pydantic.mypy"
 ]
 exclude = [
-    "samples/.*"
+    "samples/.*",
+    "testcases/.*"
 ]
 follow_imports = "silent"
 warn_redundant_casts = true

packages/uipath-openai-agents/samples/agent-as-tools/input.json

@@ -1,3 +1,3 @@
 {
-  "message": "Tell me a joke"
+  "messages": "Tell me a joke"
 }

packages/uipath-openai-agents/samples/agent-as-tools/main.py

@@ -3,6 +3,7 @@
 from pydantic import BaseModel, Field
 
 from uipath_openai_agents.chat import UiPathChatOpenAI
+from uipath_openai_agents.chat.supported_models import OpenAIModels
 
 """
 This example shows the agents-as-tools pattern adapted for UiPath coded agents.
@@ -32,7 +33,7 @@ def main() -> Agent:
     """Configure UiPath OpenAI client and return the orchestrator agent."""
     # Configure UiPath OpenAI client for agent execution
     # This routes all OpenAI API calls through UiPath's LLM Gateway
-    MODEL = "gpt-4o-2024-11-20"
+    MODEL = OpenAIModels.gpt_5_1_2025_11_13
     uipath_openai_client = UiPathChatOpenAI(model_name=MODEL)
     _openai_shared.set_default_openai_client(uipath_openai_client.async_client)
 

packages/uipath-openai-agents/samples/rag-assistant/.agent/CLI_REFERENCE.md

@@ -59,8 +59,10 @@ uv run uipath init --infer-bindings
 | `--input-file` | value | `Sentinel.UNSET` | Alias for '-f/--file' arguments |
 | `--output-file` | value | `Sentinel.UNSET` | File path where the output will be written |
 | `--trace-file` | value | `Sentinel.UNSET` | File path where the trace spans will be written (JSON Lines format) |
+| `--state-file` | value | `Sentinel.UNSET` | File path where the state file is stored for persisting execution state. If not provided, a temporary file will be used. |
 | `--debug` | flag | false | Enable debugging with debugpy. The process will wait for a debugger to attach. |
 | `--debug-port` | value | `5678` | Port for the debug server (default: 5678) |
+| `--keep-state-file` | flag | false | Keep the temporary state file even when not resuming and no job id is provided |
 
 **Usage Examples:**
 
@@ -102,6 +104,7 @@ uv run uipath run --resume
         trace_file: File path where traces will be written in JSONL format
         max_llm_concurrency: Maximum concurrent LLM requests
         input_overrides: Input field overrides mapping (direct field override with deep merge)
+        resume: Resume execution from a previous suspended state
 
 
 **Arguments:**
@@ -124,6 +127,7 @@ uv run uipath run --resume
 | `--model-settings-id` | value | `"default"` | Model settings ID from evaluation set to override agent settings (default: 'default') |
 | `--trace-file` | value | `Sentinel.UNSET` | File path where traces will be written in JSONL format |
 | `--max-llm-concurrency` | value | `20` | Maximum concurrent LLM requests (default: 20) |
+| `--resume` | flag | false | Resume execution from a previous suspended state |
 
 **Usage Examples:**
 

packages/uipath-openai-agents/samples/rag-assistant/.agent/SDK_REFERENCE.md

@@ -16,6 +16,25 @@ sdk = UiPath()
 sdk = UiPath(base_url="https://cloud.uipath.com/...", secret="your_token")
 ```
 
+### Agenthub
+
+Agenthub service
+
+```python
+# Fetch available models from LLM Gateway discovery endpoint.
+sdk.agenthub.get_available_llm_models(headers: dict[str, Any] | None=None) -> list[uipath.platform.agenthub.agenthub.LlmModel]
+
+# Asynchronously fetch available models from LLM Gateway discovery endpoint.
+sdk.agenthub.get_available_llm_models_async(headers: dict[str, Any] | None=None) -> list[uipath.platform.agenthub.agenthub.LlmModel]
+
+# Start a system agent job.
+sdk.agenthub.invoke_system_agent(agent_name: str, entrypoint: str, input_arguments: dict[str, Any] | None=None, folder_key: str | None=None, folder_path: str | None=None, headers: dict[str, Any] | None=None) -> str
+
+# Asynchronously start a system agent and return the job.
+sdk.agenthub.invoke_system_agent_async(agent_name: str, entrypoint: str, input_arguments: dict[str, Any] | None=None, folder_key: str | None=None, folder_path: str | None=None, headers: dict[str, Any] | None=None) -> str
+
+```
+
 ### Api Client
 
 Api Client service
@@ -31,6 +50,12 @@ service = sdk.api_client
 Assets service
 
 ```python
+# List assets using OData API with offset-based pagination.
+sdk.assets.list(folder_path: Optional[str]=None, folder_key: Optional[str]=None, filter: Optional[str]=None, orderby: Optional[str]=None, skip: int=0, top: int=100) -> uipath.platform.common.paging.PagedResult[uipath.platform.orchestrator.assets.Asset]
+
+# Asynchronously list assets using OData API with offset-based pagination.
+sdk.assets.list_async(folder_path: Optional[str]=None, folder_key: Optional[str]=None, filter: Optional[str]=None, orderby: Optional[str]=None, skip: int=0, top: int=100) -> uipath.platform.common.paging.PagedResult[uipath.platform.orchestrator.assets.Asset]
+
 # Retrieve an asset by its name.
 sdk.assets.retrieve(name: str, folder_key: Optional[str]=None, folder_path: Optional[str]=None) -> uipath.platform.orchestrator.assets.UserAsset | uipath.platform.orchestrator.assets.Asset
 
@@ -505,7 +530,7 @@ Llm service
 
 ```python
 # Generate chat completions using UiPath's normalized LLM Gateway API.
-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.chat.llm_gateway.ToolDefinition] | None=None, tool_choice: Union[uipath.platform.chat.llm_gateway.AutoToolChoice, uipath.platform.chat.llm_gateway.RequiredToolChoice, uipath.platform.chat.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")
+sdk.llm.chat_completions(messages: list[dict[str, str]] | list[tuple[str, str]], model: str="gpt-4.1-mini-2025-04-14", 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.chat.llm_gateway.ToolDefinition] | None=None, tool_choice: Union[uipath.platform.chat.llm_gateway.AutoToolChoice, uipath.platform.chat.llm_gateway.RequiredToolChoice, uipath.platform.chat.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")
 
 ```
 
@@ -515,7 +540,7 @@ 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: dict[str, Any] | type[pydantic.main.BaseModel] | None=None, api_version: str="2024-10-21")
+sdk.llm_openai.chat_completions(messages: list[dict[str, str]], model: str="gpt-4.1-mini-2025-04-14", 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")