nfl_tool Added

app.py

@@ -3,7 +3,10 @@ import datetime
 import requests
 import pytz
 import yaml
+
 from tools.final_answer import FinalAnswerTool
+from duckduckgo_search import DDGS
+
 
 from Gradio_UI import GradioUI
 
@@ -18,9 +21,36 @@ def my_custom_tool(arg1:str, arg2:int)-> str: #it's import to specify the return
     """
     return "What magic will you build ?"
 
-from datasets import load_dataset
+#from datasets import load_dataset
+#ds = load_dataset("nfliu/decontextualization")
 
-ds = load_dataset("nfliu/decontextualization")
+@tool
+def nfl_tool(question: str ) -> str:
+    
+    """
+    A tool to answer all questions about the NFL rules, tactics and players.
+    
+    Args:
+    question: The user question to lookup the answer
+    """
+    
+    # Prepare the duckduckgo query
+    query = f"{question}"
+    print(f"🔍 Searching DuckDuckGo with query: {query}")  # Debug
+    with DDGS() as ddgs:
+        results = list(ddgs.text(query, max_results=5))  # Otteniamo i primi 5 risultati
+    
+    print(f"📊 Found {len(results)} results")  # Debug
+    
+    if not results:
+        return ["❌ We haven't founded answers to this question."]
+    
+    # SHow results
+    for r in results:
+        print(f"📌 {r['title']} - {r['href']}")
+    
+    return [f"{r['title']} - {r['href']}" for r in results]
+    
 
 @tool
 def tool_calculator(num1: int, num2: int, operation: str) -> int:
@@ -90,7 +120,7 @@ with open("prompts.yaml", 'r') as stream:
     
 agent = CodeAgent(
     model=model,
-    tools=[final_answer,tool_calculator], ## add your tools here (don't remove final answer)
+    tools=[final_answer,tool_calculator,nfl_tool], ## add your tools here (don't remove final answer)
     max_steps=6,
     verbosity_level=1,
     grammar=None,