fix: try #2

app.py

@@ -2,8 +2,9 @@ import os
 import gradio as gr
 import requests
 import inspect
+import nest_asyncio
 from llama_index.llms.ollama import Ollama
-from llama_index.llms.huggingface_api import HuggingFaceInferenceAPI
+from llama_index.tools.wikipedia import WikipediaToolSpec
 from llama_index.readers.youtube_transcript import YoutubeTranscriptReader
 from llama_index.core.tools import FunctionTool
 from llama_index.tools.duckduckgo import DuckDuckGoSearchToolSpec
@@ -19,6 +20,8 @@ from llama_index.core import get_response_synthesizer
 import pandas as pd
 import asyncio
 
+nest_asyncio.apply()
+
 # (Keep Constants as is)
 # --- Constants ---
 DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
@@ -77,13 +80,39 @@ class BasicAgent:
                 name="duck_duck_go_search_tool",
                 description="Searches the web and refines the result into a high-quality answer."
             )
+        
+        def wikipedia_search(query: str) -> str:
+            try:
+                text = WikipediaToolSpec().search_data(query)
+                documents = [Document(text)]
 
-        agent = AgentWorkflow.from_tools_or_functions([duckduckgo_search_tool, youtube_transcript_answer_tool], llm=self.llm)
+                splitter = SentenceSplitter(chunk_size=256)
+                nodes = splitter.get_nodes_from_documents(documents)
+
+                retriever = BM25Retriever(nodes=nodes, similarity_top_k=10)
+                synthesizer = get_response_synthesizer(response_mode="refine", llm=self.llm)
+                query_engine = RetrieverQueryEngine(retriever=retriever, response_synthesizer=synthesizer)
+
+                response = query_engine.query(query)
+                return response.response
+
+            except Exception as e:
+                return f"An error occurred: {e}"
+
+
+        wikipedia_search_tool = FunctionTool.from_defaults(
+                wikipedia_search,
+                name="wikipedia_search",
+                description="Searches anything on wikipedia and converts results into a high quality answer"
+            )
+
+        agent = AgentWorkflow.from_tools_or_functions([duckduckgo_search_tool, youtube_transcript_answer_tool, wikipedia_search_tool], llm=self.llm)
 
         async def run_agent():
             return await agent.run(question)
         
         response = asyncio.run(run_agent())
+
         final_answer = response.response.blocks[0].text
         print(f"Agent returning fixed answer: {final_answer}")
         return final_answer