Add first attempt agent code

app.py

@@ -3,21 +3,68 @@ import gradio as gr
 import requests
 import inspect
 import pandas as pd
+import asyncio
+import sys
+from llama_index.llms.google_genai import GoogleGenAI
+from llama_index.tools.duckduckgo import DuckDuckGoSearchToolSpec
+from llama_index.core.agent.workflow import AgentWorkflow
+from llama_index.core.workflow import Context
+from llama_index.core.tools import FunctionTool
+from llama_index.core.llms import ChatMessage, ImageBlock, TextBlock
+
 
 # (Keep Constants as is)
 # --- Constants ---
 DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
 
+SYSTEM_PROMPT = "You are a general AI assistant. I will ask you a question. Reply only with YOUR FINAL ANSWER. YOUR FINAL ANSWER should be a number OR as few words as possible OR a comma separated list of numbers and/or strings. If you are asked for a number, don't use comma to write your number neither use units such as $ or percent sign unless specified otherwise. If you are asked for a string, don't use articles, neither abbreviations (e.g. for cities), and write the digits in plain text unless specified otherwise. If you are asked for a comma separated list, apply the above rules depending of whether the element to be put in the list is a number or a string."
 # --- Basic Agent Definition ---
 # ----- THIS IS WERE YOU CAN BUILD WHAT YOU WANT ------
 class BasicAgent:
     def __init__(self):
-        print("BasicAgent initialized.")
-    def __call__(self, question: str) -> str:
+        gemini_api_key = os.getenv("GEMINI_API_KEY")
+        if not gemini_api_key:
+            raise ValueError("GEMINI_API_KEY not set in environment variables.")
+
+        self.model = GoogleGenAI(
+            model="gemini-2.0-flash",
+            api_key=gemini_api_key
+        )
+
+        tool_list = DuckDuckGoSearchToolSpec().to_tool_list()
+        tool_list.append(FunctionTool.from_defaults(fn=reversed_string))
+        tool_list.append(FunctionTool.from_defaults(fn=download_file))
+        self.agent = AgentWorkflow.from_tools_or_functions(
+            tool_list,
+            llm=self.model,
+            system_prompt=SYSTEM_PROMPT,
+            verbose=True,
+        )
+        self.ctx = Context(agent);
+        self.api_url = DEFAULT_API_URL
+        self.download_url = f"{self.api_url}/files/"
+
+    def create_block(self, item):
+        if item.endswith(".png"):
+            return ImageBlock(url=self.download_url + item.replace(".png", ""))
+        else:
+            return TextBlock(text=item)
+
+    def __call__(self, messages) -> str:
         print(f"Agent received question (first 50 chars): {question[:50]}...")
-        fixed_answer = "This is a default answer."
-        print(f"Agent returning fixed answer: {fixed_answer}")
-        return fixed_answer
+        blocks = list(map(create_block, messages))
+        request = ChatMessage(role="user", blocks=blocks)
+        response = await agent.run(request, ctx=ctx)
+        print(f"Agent returning fixed answer: {response}")
+        return response
+
+def reversed_string(a_string: str):
+    """Reverses a string"""
+    return a_string[::-1]
+
+def download_file(file_name: str):
+    """Get the contents of a file."""
+    return requests.get(download_url + file_name).content
 
 def run_and_submit_all( profile: gr.OAuthProfile | None):
     """
@@ -37,6 +84,7 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
     api_url = DEFAULT_API_URL
     questions_url = f"{api_url}/questions"
     submit_url = f"{api_url}/submit"
+    download_url = f"{api_url}/files/"
 
     # 1. Instantiate Agent ( modify this part to create your agent)
     try:
@@ -76,11 +124,16 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
     for item in questions_data:
         task_id = item.get("task_id")
         question_text = item.get("question")
+        file_name = item.get("file_name")
         if not task_id or question_text is None:
             print(f"Skipping item with missing task_id or question: {item}")
             continue
         try:
-            submitted_answer = agent(question_text)
+            messages = [question_text]
+            if file_name:
+                file_url = download_url + file_name
+                messages.append(file_url)
+            submitted_answer = asyncio.run(agent(messages))
             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:
@@ -91,7 +144,7 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
         print("Agent did not produce any answers to submit.")
         return "Agent did not produce any answers to submit.", pd.DataFrame(results_log)
 
-    # 4. Prepare Submission 
+    # 4. Prepare Submission
     submission_data = {"username": username.strip(), "agent_code": agent_code, "answers": answers_payload}
     status_update = f"Agent finished. Submitting {len(answers_payload)} answers for user '{username}'..."
     print(status_update)

requirements.txt

@@ -1,2 +1,4 @@
 gradio
-requests
+requests
+llama-index-llms-google-genai
+llama-index-tools-duckduckgo