diff --git a/examples/data_interpreter/README.md b/examples/data_interpreter_mulit-agent/README.md
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rename from examples/data_interpreter/README.md
rename to examples/data_interpreter_mulit-agent/README.md
index d058d5d2b..6675ec29f 100644
--- a/examples/data_interpreter/README.md
+++ b/examples/data_interpreter_mulit-agent/README.md
@@ -24,7 +24,9 @@ By orchestrating these agents, the system can handle complex tasks that require
 
 These models are tested in this example. For other models, some modifications may be needed.
 
-- **Anthropic Claude** (`claude-3-5-sonnet-20240620`) accessed via the `litellm` package configuration.
+- **Anthropic Claude:** `claude-3-5-sonnet-20240620`, `claude-3-5-sonnet-20241022`, `claude-3-5-haiku-20241022` (accessed via the `litellm` package configuration).
+- **OpenAI:** `GPT4-o`,  `GPT4-o-mini`.
+- **DashScope:** `qwen-max`, `qwen-max-1201`.
 
 ## Prerequisites
 
@@ -102,7 +104,7 @@ Ensure that you have the necessary API access and that your environment is corre
 
 ## Examples
 
-This section demonstrates the pipeline's effectiveness on two different complex tasks.
+This section demonstrates the pipeline's effectiveness on two different complex tasks. For your own task, replace `"Your task description here."` with your task in `input_task` in `di_multiagent.py` script.
 
 ### Task 1: Mathematical Problem Solving
 
diff --git a/examples/data_interpreter/di_agents.py b/examples/data_interpreter_mulit-agent/di_agents.py
similarity index 100%
rename from examples/data_interpreter/di_agents.py
rename to examples/data_interpreter_mulit-agent/di_agents.py
diff --git a/examples/data_interpreter/di_multiagent.py b/examples/data_interpreter_mulit-agent/di_multiagent.py
similarity index 100%
rename from examples/data_interpreter/di_multiagent.py
rename to examples/data_interpreter_mulit-agent/di_multiagent.py