agent logic

agent.py

@@ -176,7 +176,7 @@ class BoomBot:
 
         # Modify the system prompt
         modified_prompt = replace_tool_mentions(agent.system_prompt)
-        agent.system_prompt = modified_prompt + self._get_system_prompt()
+        agent.system_prompt = modified_prompt
 
         return agent
 
@@ -258,12 +258,20 @@ class BoomBot:
         Returns:
             str: The agent's response
         """
-        print(f"BoomBot running with question (first 50 chars): {question[:50]}...")
+        prompt = self._get_system_prompt()
+        # Task introduction
+        prompt += "\nHere is the Task you need to solve:\n\n"
+        prompt += f"Task: {question}\n\n"
 
-        # Configure any task-specific settings based on the parameters
+        # Include download instructions if applicable
         if to_download:
-            # You could set up specific agent configurations here for download tasks
-            pass
+            link = f"https://agents-course-unit4-scoring.hf.space/files/{task_id}"
+            prompt += (
+                "IMPORTANT: Before solving the task, you must download a required file.\n"
+                f"Use the `download_file_from_link` tool with this link: {link}\n"
+                "After downloading, use the appropriate tool to read or process the file "
+                "before attempting to solve the task.\n\n"
+            )
 
         # Run the agent with the given question
         result = self.agent.generate_response(question)

app.py

@@ -4,7 +4,6 @@ import os
 import gradio as gr
 import pandas as pd
 import requests
-from traitlets import Bool  # type: ignore
 
 from agent import BoomBot
 
@@ -17,9 +16,9 @@ DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
 class BasicAgent:
     def __init__(self):
         print("BasicAgent initialized.")
-        self.agent = BoomBot(provider="groq")
+        self.agent = BoomBot(provider="deepinfra")
 
-    def __call__(self, question: str, task_id: str, to_download: Bool) -> str:
+    def __call__(self, question: str, task_id: str, to_download) -> str:
         print(f"Agent received question (first 50 chars): {question[:50]}...")
         return self.agent.run(question, task_id, to_download)