Update app.py

app.py

@@ -16,46 +16,42 @@ openai_key = os.environ.get("OPENAI_API_KEY")
 search_tool = DuckDuckGoSearchTool()
 
 ##Tool 2 
-class ExcelAnalysisTool:
-    def __init__(self):
-        self.name = "ExcelAnalysisTool"
-        self.description = (
-            "Loads an Excel file from the GAIA dataset on Hugging Face and calculates "
-            "the total sales for items labeled as 'food', excluding drinks. "
-            "Provide input as a string with the filename, e.g., 'sales_data.xlsx'."
-        )
-        self.repo_id = "gaia-benchmark/GAIA"
-
-    def __call__(self, filename: str) -> str:
-        """
-        Loads and processes the Excel file.
-
-        Args:
-            filename (str): The name of the Excel file (e.g., 'sales_data.xlsx').
+from smolagents import Tool
+from huggingface_hub import hf_hub_download
+import pandas as pd
 
-        Returns:
-            str: Total food sales in USD, or an error message.
-        """
+class ExcelAnalysisTool(Tool):
+    name = "excel_analysis"
+    description = (
+        "Loads an Excel file from the GAIA dataset on Hugging Face and calculates "
+        "the total sales for items labeled as 'food', excluding drinks. "
+        "Provide input as a string with the filename, e.g., 'sales_data.xlsx'."
+    )
+
+    inputs = {
+        "filename": {
+            "type": "string",
+            "description": "The name of the Excel file (e.g., 'sales_data.xlsx')"
+        }
+    }
+
+    output_type = "string"
+    repo_id = "gaia-benchmark/GAIA"
+
+    def forward(self, filename: str) -> str:
         try:
-            # Download the file from Hugging Face Hub
             file_path = hf_hub_download(
                 repo_id=self.repo_id,
                 filename=filename,
                 repo_type="dataset"
             )
-
-            # Load the Excel file into a DataFrame
             df = pd.read_excel(file_path)
-
-            # Filter rows: category == 'food' and item != 'drinks'
             food_sales = df[
                 (df['category'].str.lower() == 'food') &
                 (df['item'].str.lower() != 'drinks')
             ]
-
             total_sales = food_sales['sales'].sum()
             return f"Total sales for food items: ${total_sales:.2f}"
-
         except FileNotFoundError:
             return "Error: The specified file was not found."
         except KeyError as e:
@@ -64,48 +60,57 @@ class ExcelAnalysisTool:
             return f"An unexpected error occurred: {str(e)}"
 
 ##Tool 3
-class WikiTool:
-    def __init__(self):
-        self.name = "WikiTool"
-        self.description = (
-            "Performs Wikipedia lookups. Supports actions: 'summary' and 'is_historical_country'.\n"
-            "Usage:\n"
-            "- {'action': 'summary', 'topic': 'France'}\n"
-            "- {'action': 'is_historical_country', 'country_name': 'Yugoslavia'}"
-        )
+import wikipedia
+from smolagents import Tool
+
+class WikiTool(Tool):
+    name = "wiki_tool"
+    description = (
+        "Performs Wikipedia lookups. Actions supported: 'summary' and 'is_historical_country'."
+    )
+
+    inputs = {
+        "action": {
+            "type": "string",
+            "description": "The action to perform: 'summary' or 'is_historical_country'"
+        },
+        "topic": {
+            "type": "string",
+            "description": "The topic or country name to look up"
+        }
+    }
+
+    output_type = "string"
+
+    def forward(self, action: str, topic: str) -> str:
+        if action == "summary":
+            return self.fetch_summary(topic)
+        elif action == "is_historical_country":
+            return self.is_historical_country(topic)
+        else:
+            return "Error: Unknown action. Use 'summary' or 'is_historical_country'."
 
     def fetch_summary(self, topic: str) -> str:
         try:
-            summary = wikipedia.summary(topic, sentences=3)
-            return summary
+            return wikipedia.summary(topic, sentences=3)
         except wikipedia.DisambiguationError as e:
-            return f"Disambiguation error: The topic '{topic}' is ambiguous. Suggestions: {e.options[:5]}"
+            return f"Disambiguation: {e.options[:5]}"
         except wikipedia.PageError:
-            return f"Page error: The topic '{topic}' does not exist on Wikipedia."
+            return "No page found."
         except Exception as e:
-            return f"An unexpected error occurred: {str(e)}"
+            return f"Unexpected error: {str(e)}"
 
-    def is_historical_country(self, country_name: str) -> bool:
+    def is_historical_country(self, topic: str) -> str:
         try:
-            summary = wikipedia.summary(country_name, sentences=2).lower()
+            summary = wikipedia.summary(topic, sentences=2).lower()
             keywords = [
                 "former country", "no longer exists", "historical country",
                 "was a country", "defunct", "dissolved", "existed until",
                 "disestablished", "merged into"
             ]
-            return any(keyword in summary for keyword in keywords)
-        except Exception:
-            return False
-
-    def __call__(self, args: dict):
-        action = args.get("action")
-
-        if action == "summary":
-            return self.fetch_summary(args.get("topic", ""))
-        elif action == "is_historical_country":
-            return self.is_historical_country(args.get("country_name", ""))
-        else:
-            return "Error: Unknown action. Use 'summary' or 'is_historical_country'."
+            return "yes" if any(k in summary for k in keywords) else "no"
+        except:
+            return "no"
 
 wiki_tool = WikiTool()
 excel_tool = ExcelAnalysisTool()
@@ -118,7 +123,7 @@ async def run_and_submit_all(profile: gr.OAuthProfile | None):
         agent = ToolCallingAgent(
             tools=[search_tool, wiki_tool, excel_tool],
                         model=OpenAIServerModel(
-                    model_id="gpt-4.1",            # ✅ valid OpenAI model name
+                    model_id="gpt-4o",            # ✅ valid OpenAI model name
                     api_key=os.environ["OPENAI_API_KEY"] # ✅ securely load from environment
                 ),
             max_steps=20,