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 solving GAIA benchmark questions. "
            "If given a table, analyze it and extract relevant facts to answer accurately. "
            "Provide only the final answer. Do not explain."
        )
        self.api_url = "https://agents-course-unit4-scoring.hf.space"

    def summarize_csv(self, csv_text: str) -> str:
        try:
            df = pd.read_csv(io.StringIO(csv_text))
            summary = f"Rows: {len(df)}, Columns: {len(df.columns)}\n"
            summary += f"Columns: {', '.join(df.columns[:10])}\n"
            sample_row = df.iloc[0].to_dict()
            summary += f"Sample row: {sample_row}"
            return summary
        except Exception as e:
            return f"[Failed to parse CSV: {e}]"

    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 "csv" in content_type or url.endswith(".csv"):
                return self.summarize_csv(response.text)
            elif "json" in content_type:
                return f"JSON Sample: {response.text[:1000]}"
            elif "text/plain" in content_type:
                return f"Text Sample: {response.text[:1000]}"
            elif "pdf" in content_type:
                return "[PDF detected. OCR not supported in this version.]"
            else:
                return f"[Unsupported file type: {content_type}]"

        except Exception as e:
            return f"[File fetch error: {e}]"

    def __call__(self, question: str, task_id: str = None) -> str:
        context = ""
        if task_id:
            context = self.fetch_file_context(task_id)
            context = f"FILE DATA:\n{context}\n"

        prompt = f"{self.instructions}\n\n{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()