diff --git a/examples/data/di/dog.jpg b/examples/data/di/dog.jpg
new file mode 100644
index 000000000..679a932e8
Binary files /dev/null and b/examples/data/di/dog.jpg differ
diff --git a/examples/data/di/receipt_shopping.jpg b/examples/data/di/receipt_shopping.jpg
new file mode 100644
index 000000000..3368eb42f
Binary files /dev/null and b/examples/data/di/receipt_shopping.jpg differ
diff --git a/examples/data/omniparse/test01.docx b/examples/data/omniparse/test01.docx
index 7b6251799..87b37a8ee 100644
Binary files a/examples/data/omniparse/test01.docx and b/examples/data/omniparse/test01.docx differ
diff --git a/examples/di/ocr_receipt.py b/examples/di/ocr_receipt.py
index af54d519b..bf32f5722 100644
--- a/examples/di/ocr_receipt.py
+++ b/examples/di/ocr_receipt.py
@@ -1,17 +1,17 @@
+from metagpt.const import EXAMPLE_DATA_PATH
 from metagpt.roles.di.data_interpreter import DataInterpreter
 
 
 async def main():
     # Notice: pip install metagpt[ocr] before using this example
-    image_path = "image.jpg"
+    image_path = EXAMPLE_DATA_PATH / "di/receipt_shopping.jpg"
     language = "English"
     requirement = f"""This is a {language} receipt image.
     Your goal is to perform OCR on images using PaddleOCR, output text content from the OCR results and discard 
-    coordinates and confidence levels, then recognize the total amount from ocr text content, and finally save as table. 
+    coordinates and confidence levels, then recognize the total amount from ocr text content, and finally save as csv table. 
     Image path: {image_path}.
     NOTE: The environments for Paddle and PaddleOCR are all ready and has been fully installed."""
-    di = DataInterpreter()
-
+    di = DataInterpreter(react_mode="react")
     await di.run(requirement)
 
 
diff --git a/examples/di/rm_image_background.py b/examples/di/rm_image_background.py
index cb7900a0a..e28778241 100644
--- a/examples/di/rm_image_background.py
+++ b/examples/di/rm_image_background.py
@@ -1,5 +1,6 @@
 import asyncio
 
+from metagpt.const import DEFAULT_WORKSPACE_ROOT, EXAMPLE_DATA_PATH
 from metagpt.roles.di.data_interpreter import DataInterpreter
 
 
@@ -9,7 +10,7 @@ async def main(requirement: str = ""):
 
 
 if __name__ == "__main__":
-    image_path = "/your/path/to/the/image.jpeg"
-    save_path = "/your/intended/save/path/for/image_rm_bg.png"
+    image_path = EXAMPLE_DATA_PATH / "di/dog.jpg"
+    save_path = DEFAULT_WORKSPACE_ROOT / "image_rm_bg.png"
     requirement = f"This is a image, you need to use python toolkit rembg to remove the background of the image and save the result. image path:{image_path}; save path:{save_path}."
     asyncio.run(main(requirement))