import os
import mimetypes
from transformers import pipeline
from tools.asr_tool import transcribe_audio
from tools.excel_tool import analyze_excel
from tools.search_tool import search_duckduckgo

class GaiaAgent:
    def __init__(self):
        token = os.getenv("HUGGINGFACEHUB_API_TOKEN")
        if not token:
            raise ValueError("Missing HUGGINGFACEHUB_API_TOKEN environment variable.")

        self.llm = pipeline(
            "text-generation",
            model="mistralai/Mistral-7B-Instruct-v0.2",
            token=token,
            device="cpu",
            max_new_tokens=512,
            do_sample=False
        )

    def __call__(self, question: str):
        trace_log = ""

        if "http" in question or "www." in question:
            trace_log += "Detected URL or web reference. Performing search...\n"
            result = search_duckduckgo(question)
            trace_log += f"Search result: {result}\n"
            return result, trace_log

        if question.lower().endswith(".mp3") or question.lower().endswith(".wav"):
            trace_log += "Detected audio file. Performing transcription...\n"
            result = transcribe_audio(question)
            trace_log += f"Transcription result: {result}\n"
            return result, trace_log

        if question.lower().endswith(".xlsx") or question.lower().endswith(".xls"):
            trace_log += "Detected Excel file. Performing analysis...\n"
            result = analyze_excel(question)
            trace_log += f"Excel analysis result: {result}\n"
            return result, trace_log

        trace_log += "General question. Using local model...\n"
        response = self.llm(question)[0]["generated_text"]
        trace_log += f"LLM response: {response}\n"

        return response.strip(), trace_log