Update app.py

app.py

@@ -4,18 +4,37 @@ import requests
 import inspect
 import pandas as pd
 
+from llama_index.core.workflow import Context
+from llama_index.core.agent.workflow import AgentWorkflow
+from llama_index.llms.huggingface_api import HuggingFaceInferenceAPI
+from youtube_tool import youtube_transcript_tool, youtube_transcript_snippet_tool
+from multiple_tools import round_to_two_decimals_tool, text_inverter_tool, google_web_search_tool, wikipedia_search_tool
+
 # (Keep Constants as is)
 # --- Constants ---
 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.")
+        self.api_key = os.getenv("HF_TOKEN")
+        self.llm = HuggingFaceInferenceAPI(
+            model_name="deepseek-ai/DeepSeek-R1-0528", 
+            token=self.api_key,
+            provider="auto"
+            )
+        self.llamaindex_agent = AgentWorkflow.from_tools_or_functions(
+            [wikipedia_search_tool, youtube_transcript_tool, youtube_transcript_snippet_tool, round_to_two_decimals_tool, text_inverter_tool, google_web_search_tool],
+            llm=self.llm,
+        )
+        self.context = Context(self.llamaindex_agent)
     def __call__(self, question: str) -> str:
         print(f"Agent received question (first 50 chars): {question[:50]}...")
-        fixed_answer = "This is a default answer."
+        #fixed_answer = "This is a default answer."
+        fixed_answer = self.llamaindex_agent.run(question, ctx = context)
         print(f"Agent returning fixed answer: {fixed_answer}")
         return fixed_answer