First passing run, with 35 points

.gitignore

@@ -0,0 +1 @@
+.env

agent.py

@@ -1,15 +1,80 @@
-from smolagents import CodeAgent, HfApiModel, DuckDuckGoSearchTool
+import os
 
-model = HfApiModel("Qwen/Qwen2.5-Coder-32B-Instruct")
+from smolagents import (
+    CodeAgent,
+    HfApiModel,
+    OpenAIServerModel,
+    DuckDuckGoSearchTool,
+    ToolCallingAgent,
+    WikipediaSearchTool,
+)
+
+import logging
+import sys
+
+logging.basicConfig(stream=sys.stdout, level=logging.DEBUG)
+logging.getLogger().addHandler(logging.StreamHandler(stream=sys.stdout))
+
+from llama_index.core.agent.workflow import AgentWorkflow
+from llama_index.llms.gemini import Gemini
+from llama_index.tools.wikipedia import WikipediaToolSpec
+import asyncio
+
+# model = HfApiModel("Qwen/Qwen2.5-Coder-32B-Instruct")  # Limit is reached very fast
+# model = OpenAIServerModel(
+#     model_id="gemini-2.0-flash",
+#     api_base="https://generativelanguage.googleapis.com/v1beta/openai/",
+#     api_key=os.environ.get("GEMINI_API_KEY"),
+# )
+
+
+# agent = CodeAgent(
+#     tools=[
+#         DuckDuckGoSearchTool(),
+#         # WikipediaSearchTool(),
+#     ],
+#     additional_authorized_imports=["bs4", "pandas", "numpy", "csv", "json"],
+#     model=model,
+#     add_base_tools=True,
+# )
+# agent = ToolCallingAgent(
+#     tools=[
+#         DuckDuckGoSearchTool(),
+#         WikipediaSearchTool(),
+#     ],
+#     model=model,
+#     add_base_tools=True,
+# )
 
-agent = CodeAgent(
-    tools=[
-        DuckDuckGoSearchTool(),
+
+model = Gemini(
+    model="gemini-2.0-flash",
+)
+
+agent = AgentWorkflow.from_tools_or_functions(
+    [
+        *WikipediaToolSpec().to_tool_list(),
     ],
-    model=model,
+    llm=model,
 )
 
 
 def run_agent(question: str) -> str:
-    response = agent.run(question)
+    prompt = f"""
+You are a helpful assistant that answers requested questions using tools.
+I will give you a question at the end. Report your thoughts, and give the final answer with the following template:
+FINAL ANSWER: [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.
+
+Remember that your answer should start with "FINAL ANSWER: " and be followed by the answer.
+
+The question is:
+
+{question}
+"""
+
+    response = agent.run(prompt)
     return str(response)

agent_lc.py

@@ -0,0 +1,52 @@
+from langchain_google_genai import ChatGoogleGenerativeAI
+from langchain_community.tools.tavily_search import TavilySearchResults
+from langgraph.prebuilt import create_react_agent
+from langgraph.checkpoint.memory import MemorySaver
+from langchain_core.messages import HumanMessage, AIMessage
+import re
+
+model = ChatGoogleGenerativeAI(
+    model="gemini-2.0-flash",
+    temperature=0,
+)
+
+search_tool = TavilySearchResults(max_results=5)
+
+memory = MemorySaver()
+agent = create_react_agent(model, [search_tool], checkpointer=memory)
+
+
+def run_agent(question: str) -> str:
+    prompt = f"""
+You are a helpful assistant that answers requested questions using tools.
+I will give you a question at the end. Report your thoughts, and give the final answer with the following template:
+FINAL ANSWER: [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.
+
+Remember that your answer should start with "FINAL ANSWER: " and be followed by the answer.
+
+The question is:
+
+{question}
+"""
+    for step in agent.stream(
+        {"messages": [HumanMessage(content=prompt)]},
+        {"configurable": {"thread_id": "tid1"}},
+        stream_mode="values",
+    ):
+        step["messages"][-1].pretty_print()
+
+        # check if the step is a final answer
+        if isinstance(step["messages"][-1], AIMessage):
+            # check if the answer is final, and extract it
+            final_answer = re.search(
+                r"FINAL ANSWER: (.*)",
+                step["messages"][-1].content,
+            )
+            if final_answer:
+                return final_answer.group(1).strip()
+
+    return "No final answer found."

app.py

@@ -4,7 +4,7 @@ import requests
 import pandas as pd
 from concurrent.futures import ThreadPoolExecutor
 
-from agent import run_agent
+from agent_lc import run_agent
 
 # (Keep Constants as is)
 # --- Constants ---
@@ -103,7 +103,7 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
     results_log = []
     answers_payload = []
     print(f"Running agent on {len(questions_data)} questions...")
-    with ThreadPoolExecutor(max_workers=20) as executor:
+    with ThreadPoolExecutor(max_workers=1) as executor:
         futures = {
             executor.submit(process_item, agent, item): item for item in questions_data
         }

requirements.txt

@@ -1,3 +1,11 @@
 gradio
 requests
-smolagents
+smolagents[openai]
+wikipedia-api
+beautifulsoup4
+llama-index
+llama-index-tools-wikipedia
+llama-index-llms-gemini
+langchain-google-genai
+langchain-community
+langgraph