Update README.md

README.md

@@ -110,6 +110,12 @@ If needed, the Langchain's `RecursiveCharacterTextSplitter` function was used to
 Each `chunk_text` was embedded using the [**`BAAI/bge-m3`**](https://huggingface.co/BAAI/bge-m3) model. 
 The resulting embedding vector is stored in the `embeddings_bge-m3` column as a **string**, but can easily be parsed back into a `list[float]` or NumPy array.
 
+## 🔄 The chunking doesn't fit your use case?
+
+[**SOON AVAILABLE FOR THIS DATASET**] ~~If you need to reconstitute the original, un-chunked dataset, you can follow [this tutorial notebook available on our GitHub repository](https://github.com/etalab-ia/mediatech/blob/main/docs/reconstruct_vector_database.ipynb).~~
+
+⚠️ The tutorial is only relevant for datasets that were chunked **without overlap**.
+
 ## 📌 Embedding Use Notice
 
 ⚠️ The `embeddings_bge-m3` column is stored as a **stringified list** of floats (e.g., `"[-0.03062629,-0.017049594,...]"`).