docs(weave): Docs edits to /guides/integrations/openai_agents

docs/docs/guides/integrations/index.md

@@ -31,6 +31,7 @@ LLM providers are the vendors that offer access to large language models for gen
 
 Frameworks help orchestrate the actual execution pipelines in AI applications. They provide tools and abstractions for building complex workflows. Weave integrates with these frameworks to trace the entire pipeline:
 
+- **[OpenAI Agents SDK](/guides/integrations/openai_agents)**
 - **[LangChain](/guides/integrations/langchain)**
 - **[LlamaIndex](/guides/integrations/llamaindex)**
 - **[DSPy](/guides/integrations/dspy)**

docs/docs/guides/integrations/openai_agents.md

@@ -1,21 +1,26 @@
 
 # OpenAI Agents SDK
 
-The [OpenAI Agents SDK](https://github.com/openai/openai-agents-python) is a lightweight yet powerful framework for building multi-agent workflows.
+The [OpenAI Agents Python SDK](https://github.com/openai/openai-agents-python) is a lightweight and powerful framework for building multi-agent workflows. You can use W&B Weave with the OpenAI Agents SDK to track and monitor your agentic applications.
 
 ## Installation
 
+Install the required dependencies using `pip`: 
+
 ```bash
 pip install weave openai-agents
 ```
 
-## Getting Started
+## Get started
 
 To use the OpenAI Agents SDK with Weave, you'll need to:
+
 - Initialize Weave with your project name
 - Add the Weave tracing processor to your agents
 - Create and run your agents as usual
 
+In the following codes sample, an OpenAI Agent is created and integrated with Weave for traceability. First, a Weave project is initialized and the `WeaveTracingProcessor` is set up to capture execution traces. A `Weather` data model is created to represent weather information. The `get_weather` function is decorated as a tool the agent can use and returns a sample weather report. An agent named `Hello world` is configured with basic instructions and access to the weather tool. The main function asynchronously runs the agent with a sample input (`What's the weather in Tokyo?`) and outputs the final response.
+
 ```python
 from pydantic import BaseModel
 from agents import Agent, Runner, function_tool, set_trace_processors
@@ -50,6 +55,6 @@ if __name__ == "__main__":
     asyncio.run(main())
 ```
 
-## View your traces
+## View traces
 
-To see what happened during your agent execution, follow the link to your Weave dashboard and see your agent traces. 
+When the above code sample is run, a link to the Weave dashboard is generated. To see what happened during your agent execution, follow the link to see your agent traces.