Update app.py

app.py

@@ -3,7 +3,11 @@ import gradio as gr
 import requests
 import inspect
 import pandas as pd
-from smolagents import CodeAgent, DuckDuckGoSearchTool, InferenceClientModel
+#from smolagents import CodeAgent, DuckDuckGoSearchTool, InferenceClientModel
+from langchain_community.llms import HuggingFaceHub
+from langchain.agents import initialize_agent, Tool
+from langchain.utilities import DuckDuckGoSearchAPIWrapper
+import os
 
 # (Keep Constants as is)
 # --- Constants ---
@@ -11,7 +15,51 @@ DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
 
 # --- Basic Agent Definition ---
 # ----- THIS IS WERE YOU CAN BUILD WHAT YOU WANT ------
+
 class BasicAgent:
+    def __init__(self):
+        print("BasicAgent initialized.")
+
+        # Load Hugging Face model via LangChain
+        self.llm = HuggingFaceHub(
+            repo_id="google/flan-t5-base",   # text2text model
+            huggingfacehub_api_token=os.getenv("HF_TOKEN"),
+            model_kwargs={"temperature": 0.2, "max_new_tokens": 256}
+        )
+
+        # Setup DuckDuckGo search tool
+        search = DuckDuckGoSearchAPIWrapper()
+        tools = [
+            Tool(
+                name="DuckDuckGo Search",
+                func=search.run,
+                description="Useful for answering questions about current events"
+            )
+        ]
+
+        # Initialize LangChain agent
+        self.agent = initialize_agent(
+            tools, self.llm, agent="zero-shot-react-description", verbose=True
+        )
+
+    def __call__(self, question: str) -> str:
+        print(f"Agent received question (first 50 chars): {question[:50]}...")
+        fixed_answer = self.agent.run(question)
+        print(f"Agent returning fixed answer: {fixed_answer}")
+        return fixed_answer
+
+
+    '''def __call__(self, question: str) -> str:
+        print(f"Agent received: {question[:50]}...")
+        try:
+            answer = self.agent.run(question)
+            print(f"Agent returning: {answer}")
+            return answer
+        except Exception as e:
+            return f"AGENT ERROR: {e}"'''
+
+
+'''class BasicAgent:
     def __init__(self):
         print("BasicAgent initialized.")
         model = InferenceClientModel(
@@ -30,7 +78,7 @@ class BasicAgent:
         print(f"Agent received question (first 50 chars): {question[:50]}...")
         fixed_answer = self.agent.run(question)
         print(f"Agent returning fixed answer: {fixed_answer}")
-        return fixed_answer
+        return fixed_answer'''
 
 def run_and_submit_all( profile: gr.OAuthProfile | None):
     """