docs(sdk): add conversation model switching example

sdk/guides/llm-profile-store.mdx

@@ -12,7 +12,7 @@
 
 ## Benefits
 - **Persistence:** Saves model parameters (API keys, temperature, max tokens, ...) to a stable disk format.
 - **Reusability:** Import a defined profile into any script or session with a single identifier.
 - **Portability:** Simplifies the synchronization of model configurations across different machines or deployment environments.
 
 ## How It Works
@@ -170,8 +170,72 @@
 
 <RunExampleCode path_to_script="examples/01_standalone_sdk/37_llm_profile_store.py"/>
 
+## Mid-Conversation Model Switching
+
+You can use a saved profile to switch the active model on a running conversation between turns. This is useful when you want to start with one model, then switch to another for later user messages while keeping the same conversation history and combined usage metrics.
+
+<Note>
+This example is available on GitHub: [examples/01_standalone_sdk/44_model_switching_in_convo.py](https://github.com/OpenHands/software-agent-sdk/blob/main/examples/01_standalone_sdk/44_model_switching_in_convo.py)
+</Note>
+
+```python icon="python" expandable examples/01_standalone_sdk/44_model_switching_in_convo.py
+"""Mid-conversation model switching.
+
+Usage:
+    uv run examples/01_standalone_sdk/44_model_switching_in_convo.py
+"""
+
+import os
+
+from openhands.sdk import LLM, Agent, LocalConversation, Tool
+from openhands.sdk.llm.llm_profile_store import LLMProfileStore
+from openhands.tools.terminal import TerminalTool
+
+
+LLM_API_KEY = os.getenv("LLM_API_KEY")
+store = LLMProfileStore()
+
+store.save(
+    "gpt",
+    LLM(model="openhands/gpt-5.2", api_key=LLM_API_KEY),
+    include_secrets=True,
+)
+
+agent = Agent(
+    llm=LLM(
+        model=os.getenv("LLM_MODEL", "openhands/claude-sonnet-4-5-20250929"),
+        api_key=LLM_API_KEY,
+    ),
+    tools=[Tool(name=TerminalTool.name)],
+)
+conversation = LocalConversation(agent=agent, workspace=os.getcwd())
+
+# Send a message with the default model
+conversation.send_message("Say hello in one sentence.")
+conversation.run()
+
+# Switch to a different model and send another message
+conversation.switch_profile("gpt")
+print(f"Switched to: {conversation.agent.llm.model}")
+
+conversation.send_message("Say goodbye in one sentence.")
+conversation.run()
+
+# Print metrics per model
+for usage_id, metrics in conversation.state.stats.usage_to_metrics.items():
+    print(f"  [{usage_id}] cost=${metrics.accumulated_cost:.6f}")
+
+combined = conversation.state.stats.get_combined_metrics()
+print(f"Total cost: ${combined.accumulated_cost:.6f}")
+print(f"EXAMPLE_COST: {combined.accumulated_cost}")
+
+store.delete("gpt")
+```
+
+<RunExampleCode path_to_script="examples/01_standalone_sdk/44_model_switching_in_convo.py"/>
+
 ## Next Steps
 
 - **[LLM Registry](/sdk/guides/llm-registry)** - Manage multiple LLMs in memory at runtime
 - **[LLM Routing](/sdk/guides/llm-routing)** - Automatically route to different models
 - **[Exception Handling](/sdk/guides/llm-error-handling)** - Handle LLM errors gracefully