Create tool_read_excel_as_json.py

tool_read_excel_as_json.py

@@ -0,0 +1,54 @@
+from smolagents import tool
+import os
+import requests
+import pandas as pd
+from io import BytesIO
+
+DEFAULT_API_URL = os.getenv("AGENT_API_URL", "https://agents-course-unit4-scoring.hf.space")
+
+@tool
+def read_excel_as_json(task_id: str) -> dict:
+    """
+    Fetches and parses an Excel file as structured JSON for a given task_id.
+    
+    Args:
+        task_id: The task ID to fetch.
+        
+    Returns:
+        {
+            "task_id": str,
+            "sheets": {
+                "SheetName1": [ {col1: val1, col2: val2, ...}, ... ],
+                ...
+            },
+            "status": "Success" | "Error"
+        }
+    """
+    url = f"{DEFAULT_API_URL}/files/{task_id}"
+
+    try:
+        response = requests.get(url, timeout=10)
+        if response.status_code != 200:
+            return {"task_id": task_id, "sheets": {}, "status": f"{response.status_code} - Failed"}
+
+        xls = pd.ExcelFile(BytesIO(response.content))
+        sheets_json = {}
+
+        for sheet in xls.sheet_names:
+            df = xls.parse(sheet)
+            df = df.dropna(how="all")  # Remove completely empty rows
+            rows = df.head(20).to_dict(orient="records")  # limit to first 20 rows
+            sheets_json[sheet] = rows
+
+        return {
+            "task_id": task_id,
+            "sheets": sheets_json,
+            "status": "Success"
+        }
+
+    except Exception as e:
+        return {
+            "task_id": task_id,
+            "sheets": {},
+            "status": f"Error: {str(e)}"
+        }