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import os
import re
import requests
import tempfile
import pandas as pd
from openai import OpenAI
from duckduckgo_search import DDGS
PROMPT = (
"You are a general AI assistant. I will ask you a question. "
"Report your thoughts, and finish your 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."
)
class BasicAgent:
def __init__(self):
self.llm = OpenAI(api_key=os.getenv("OPENAI_API_KEY"))
print("BasicAgent initialized.")
def web_search(self, query: str, max_results: int = 5) -> str:
try:
with DDGS() as ddgs:
results = list(ddgs.text(query, max_results=max_results))
if not results:
return ""
formatted_results = ""
for i, result in enumerate(results, 1):
title = result.get('title', '')
body = result.get('body', '')
href = result.get('href', '')
formatted_results += f"{i}. {title}\n URL: {href}\n Description: {body}\n\n"
return formatted_results
except Exception as e:
return ""
def excel_tool(self, file_url: str) -> str:
try:
r = requests.get(file_url, timeout=20)
r.raise_for_status()
with tempfile.NamedTemporaryFile(suffix=".xlsx", delete=False) as f:
f.write(r.content)
f.flush()
excel_path = f.name
df = pd.read_excel(excel_path)
# Simple heuristic: try to sum 'Sales' where 'Type' == 'food'
if "Type" in df.columns and "Sales" in df.columns:
total = df[df["Type"].str.lower() == "food"]["Sales"].sum()
return f"{round(total, 2)}"
# Fallback: sum all numeric columns
total = df.select_dtypes(include='number').sum().sum()
return f"{round(total, 2)}"
except Exception as e:
return "Unable to read Excel file"
def fetch_file_url(self, task_id):
DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
try:
url = f"{DEFAULT_API_URL}/files/{task_id}"
r = requests.head(url, timeout=5)
if r.status_code == 200:
return url
except Exception:
pass
return None
def __call__(self, question: str, task_id: str = None) -> str:
# If there is a file, and question looks like Excel/data, use excel_tool
file_url = self.fetch_file_url(task_id) if task_id else None
answer = None
if file_url and ("excel" in question.lower() or "spreadsheet" in question.lower() or "file" in question.lower()):
try:
excel_result = self.excel_tool(file_url)
if excel_result and "unable" not in excel_result.lower():
return excel_result
except Exception:
pass # Fall back to search+llm
# Otherwise, use web search + LLM
search_snippet = self.web_search(question)
prompt = PROMPT + f"\n\nWeb search results:\n{search_snippet}\n\nQuestion: {question}"
response = self.llm.chat.completions.create(
model="gpt-4o",
messages=[{"role": "system", "content": prompt}],
temperature=0.0,
max_tokens=512,
)
answer = response.choices[0].message.content.strip()
final_line = ""
for line in answer.splitlines():
if line.strip().lower().startswith("final answer:"):
final_line = line.split(":", 1)[-1].strip(" .\"'")
break
return final_line or answer |