fix(structs): simplify Agent initialization example in index.md

- Remove explicit OpenAIChat import and llm setup
- Show passing temperature, model_name, and max_tokens directly to Agent
- Remove dotenv/env loading instructions

docs/swarms/structs/index.md

@@ -40,28 +40,10 @@ Features:
 ✅ Long term memory database with RAG (ChromaDB, Pinecone, Qdrant)
 
 ```python
-import os
-
-from dotenv import load_dotenv
-
-# Import the OpenAIChat model and the Agent struct
 from swarms import Agent
-from swarm_models import OpenAIChat
-
-# Load the environment variables
-load_dotenv()
-
-# Get the API key from the environment
-api_key = os.environ.get("OPENAI_API_KEY")
-
-# Initialize the language model
-llm = OpenAIChat(
-    temperature=0.5, model_name="gpt-4", openai_api_key=api_key, max_tokens=4000
-)
-
 
 ## Initialize the workflow
-agent = Agent(llm=llm, max_loops=1, autosave=True, dashboard=True)
+agent = Agent(temperature=0.5, model_name="gpt-4o-mini", max_tokens=4000, max_loops=1, autosave=True, dashboard=True)
 
 # Run the workflow on a task
 agent.run("Generate a 10,000 word blog on health and wellness.")