Update app.py

app.py

@@ -11,7 +11,13 @@ from langchain_core.messages import AnyMessage, SystemMessage, HumanMessage, AIM
 from langgraph.graph.message import add_messages
 from langgraph.prebuilt import ToolNode, tools_condition
 from langchain_tavily import TavilySearch
-from tools import answer_excel_question, answer_python_question, extract_youtube_id, get_youtube_transcript
+from tools import (
+    download_task_file,
+    read_attached_text_file,
+    answer_excel_question,
+    answer_python_question,
+    get_youtube_transcript,
+)
 # (Keep Constants as is)
 # --- Constants ---
 DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
@@ -41,15 +47,17 @@ class BasicAgent:
             max_retries=1,
             max_tokens=128,
         )
-        self.tools = [answer_excel_question, 
-                      answer_python_question, 
-                      extract_youtube_id, 
-                      get_youtube_transcript,
-                      TavilySearch(
-                          max_results=5,
-                          topic="general",
-                          search_depth="basic",
-                      )
+        self.tools = [
+            download_task_file,
+            read_attached_text_file,
+            answer_excel_question,
+            answer_python_question,
+            get_youtube_transcript,
+            TavilySearch(
+                max_results=5,
+                topic="general",
+                search_depth="basic",
+            ),
         ]
 
         self.chat_with_tools = self.model.bind_tools(self.tools)
@@ -126,12 +134,22 @@ class BasicAgent:
             return "tools"
     
         return "final_process"
-        
-    def answer_question(self, question: str) -> str:
-        # TODO: 
-        messages = [HumanMessage(content=question)]
-        messages = self.react_graph.invoke({"messages" : messages})
-        return messages["messages"][-1].content
+
+    def answer_question(self, question: str, task_id: str | None = None) -> str:
+        user_content = question
+    
+        if task_id:
+            user_content += (
+                f"\n\nTask ID: {task_id}. "
+                "If the question mentions an attached file, spreadsheet, code file, audio, or image, "
+                "use the available tools with this task_id."
+            )
+    
+        messages = [HumanMessage(content=user_content)]
+        result = self.react_graph.invoke({"messages": messages})
+        return result["messages"][-1].content
+    
+
 
 def run_and_submit_all( profile: gr.OAuthProfile | None):
     """
@@ -194,7 +212,7 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
             print(f"Skipping item with missing task_id or question: {item}")
             continue
         try:
-            submitted_answer = agent(question_text)
+            submitted_answer = agent(question_text, task_id)
             answers_payload.append({"task_id": task_id, "submitted_answer": submitted_answer})
             results_log.append({"Task ID": task_id, "Question": question_text, "Submitted Answer": submitted_answer})
         except Exception as e: