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import os
import io
import pandas as pd
import requests
from openai import OpenAI
class GaiaAgent:
def __init__(self):
self.client = OpenAI(api_key=os.getenv("OPENAI_API_KEY"))
self.instructions = (
"You are an expert assistant solving GAIA benchmark questions. "
"You analyze file contents (like CSV), reason step-by-step, and respond with a single factual answer."
)
self.api_url = "https://agents-course-unit4-scoring.hf.space"
def fetch_file_context(self, task_id: str) -> str:
try:
url = f"{self.api_url}/files/{task_id}"
response = requests.get(url, timeout=10)
response.raise_for_status()
content_type = response.headers.get("Content-Type", "")
if "text/csv" in content_type or url.endswith(".csv"):
df = pd.read_csv(io.StringIO(response.text))
if df.shape[1] <= 15 and df.shape[0] <= 30:
return f"CSV table preview:\n{df.to_markdown(index=False)}"
else:
return f"CSV summary: {df.shape[0]} rows, {df.shape[1]} columns.\nColumns: {', '.join(df.columns[:10])}"
elif "application/json" in content_type:
return f"JSON content:\n{response.text[:2000]}"
elif "application/pdf" in content_type:
return "[PDF detected. You may need to request OCR summary.]"
elif "text/plain" in content_type:
return f"File preview:\n{response.text[:2000]}"
else:
return f"[Unsupported file type: {content_type}]"
except Exception as e:
return f"[Error downloading or processing file: {e}]"
def __call__(self, question: str, task_id: str = None) -> str:
file_context = ""
if task_id:
file_context = self.fetch_file_context(task_id)
if file_context:
file_context = f"FILE CONTEXT:\n{file_context}\n"
prompt = f"{self.instructions}\n\n{file_context}QUESTION:\n{question}\nANSWER:"
response = self.client.chat.completions.create(
model="gpt-4-turbo",
messages=[
{"role": "system", "content": self.instructions},
{"role": "user", "content": prompt}
],
temperature=0.0,
)
return response.choices[0].message.content.strip()
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