Update README.md

README.md

@@ -68,6 +68,66 @@ This file is a list of chunks used for document retrieval, which contains the fo
 - **Example**: `A molecule editor is a computer program for creating and modifying representations of chemical structures.`
 
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+## 🛠 How to Use with Python
+
+You can load and work with the mmRAG dataset using standard Python libraries like `json`. Below is a simple example of how to load and interact with the data files.
+
+### ✅ Step 1: Load the Dataset
+
+```python
+import json
+
+# Load query datasets
+with open("mmrag_train.json", "r", encoding="utf-8") as f:
+    train_data = json.load(f)
+
+with open("mmrag_dev.json", "r", encoding="utf-8") as f:
+    dev_data = json.load(f)
+
+with open("mmrag_test.json", "r", encoding="utf-8") as f:
+    test_data = json.load(f)
+
+# Load document chunks
+with open("processed_documents.json", "r", encoding="utf-8") as f:
+    documents = json.load(f)
+    # Load as dict if needed
+    documents = {doc["id"]: doc["text"] for doc in documents}
+```
+### ✅ Step 2: Access Query and Document Examples
+
+```python
+# Example query
+query_example = train_data[0]
+print("Query:", query_example["query"])
+print("Answer:", query_example["answer"])
+print("Relevant Chunks:", query_example["relevant_chunks"])
+
+# Get the text of a relevant chunk
+for chunk_id, relevance in query_example["relevant_chunks"].items():
+    if relevance > 0:
+        print(f"Chunk ID: {chunk_id}, Relevance label: {relevance}\nText: {documents[chunk_id]}")
+```
+### 📊 Example: Get Sorted Routing Scores
+The following example shows how to extract and sort the `dataset_score` field of a query to understand which dataset is most relevant to the query.
+
+```python
+# Choose a query from the dataset
+query_example = train_data[0]
+
+print("Query:", query_example["query"])
+print("Answer:", query_example["answer"])
+
+# Get dataset routing scores
+routing_scores = query_example["dataset_score"]
+
+# Sort datasets by relevance score (descending)
+sorted_routing = sorted(routing_scores.items(), key=lambda x: x[1], reverse=True)
+
+print("\nRouting Results (sorted):")
+for dataset, score in sorted_routing:
+    print(f"{dataset}: {score}")
+```
+
 
 ## 📄 License