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import os
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 a highly skilled research assistant solving GAIA benchmark questions. "
"You can analyze documents, perform reasoning, and answer with a single factual answer only."
)
self.api_url = "https://agents-course-unit4-scoring.hf.space"
def fetch_file_content(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" in content_type or "csv" in content_type or "json" in content_type:
return response.text[:3000] # Truncate to fit token limit
elif "application/pdf" in content_type:
return "[PDF file content detected. Summarize manually or use tool.]"
else:
return f"[Unsupported file type: {content_type}]"
except Exception as e:
return f"[Error downloading or reading file: {e}]"
def __call__(self, question: str, task_id: str = None) -> str:
file_context = ""
if task_id:
file_context = self.fetch_file_content(task_id)
if file_context:
file_context = f"Here is the related file content:\n{file_context}\n"
prompt = f"{self.instructions}\n\n{file_context}Question: {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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