Update app.py

app.py

@@ -1,5 +1,4 @@
 import json
-from langchain_tavily import TavilySearch
 from langgraph.prebuilt import create_react_agent
 from langgraph_supervisor import create_supervisor
 from langchain_groq import ChatGroq
@@ -13,11 +12,12 @@ import pandas as pd
 import json
 import traceback
 import io
-import time
+from tavily import TavilyClient
+from langchain_core.tools import tool
 
 # --- Constants ---
 load_dotenv()
-
+client = TavilyClient(api_key=os.getenv("TAVILY_API_KEY"))
 DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
 groq_token = os.getenv("GROQ_API_KEY")
 tavily_token = os.getenv("TAVILY_API_KEY")
@@ -39,30 +39,20 @@ system_prompt = """
                     Route to agents/tools when it materially improves accuracy/recency (esp. factual/date/spec/list questions).
                     Answer directly for stable explanations/ideation. Keep meta minimal.
                 """
-
 prompt_search = """
-You are web_research_agent.
-
-You have one tool: web_search.
+You are a web research agent.
 
-IMPORTANT:
-When calling web_search use ONLY:
+You have one tool:
 
-{
-  "query": "<search query>"
-}
+web_search(query)
 
-Do not provide:
-topic,
-search_depth,
-include_images,
-time_range,
-exclude_domains,
-include_domains,
-start_date,
-end_date.
+Always use the tool when factual information is required.
 
-Answer using the tool results.
+After receiving search results:
+- Extract the answer.
+- Return only the final answer.
+- If multiple sources disagree, choose the most reliable source.
+- If the answer is numeric, return only the number.
 """
 
 prompt_python_execute = """You are a python code execution agent.
@@ -79,11 +69,7 @@ prompt_chess = """You are a chess position reviewing agent.
 
 
 # --- Tools ---
-web_search = TavilySearch(
-    max_results=5,
-    topic="general",
-    tavily_api_key=tavily_token
-)
+
 
 CHESSVISION_TO_FEN_URL = "http://app.chessvision.ai/predict"
 CHESS_MOVE_API = "https://chess-api.com/v1"
@@ -112,7 +98,31 @@ def download_file_as_string(task_id: str) -> str:
     else:
         raise Exception(f"Failed to download the file. Status code: {response.status_code}")
 
+@tool
+def web_search(query: str) -> str:
+    """
+    Search the web and return relevant results.
+    """
+    try:
+        result = client.search(
+            query=query,
+            max_results=5,
+            search_depth="advanced"
+        )
+
+        snippets = []
+
+        for item in result.get("results", []):
+            snippets.append(
+                f"Title: {item.get('title','')}\n"
+                f"Content: {item.get('content','')}\n"
+                f"URL: {item.get('url','')}\n"
+            )
 
+        return "\n\n".join(snippets)
+
+    except Exception as e:
+        return f"ERROR: {str(e)}"
 from langchain_core.tools import tool
 
 
@@ -223,7 +233,7 @@ groq_llm = ChatGroq(
     max_retries=2,
     api_key=groq_token,
 )
-
+print("Registered tool:", web_search.name)
 # --- Agents ---
 web_research_agent = create_react_agent(
     model=groq_llm,