import io
from openai import AsyncOpenAI
from app.ai.sarvam_client import SarvamClient
from app.config import OPENAI_API_KEY


class SpeechToTextService:

    def __init__(self):
        self.sarvam = SarvamClient()
        self.openai_key = OPENAI_API_KEY

    async def transcribe(
        self,
        audio_bytes: bytes,
        filename: str = "audio.webm",
        language_code: str = "ta-IN",
    ) -> str:
        lang_prefix = language_code.lower()[:2]

        # 1. Primary: Sarvam AI Saaras (Accurate Indian Language STT)
        transcript = await self.sarvam.speech_to_text(
            audio_bytes=audio_bytes,
            filename=filename,
            language_code=language_code,
        )
        if transcript and len(transcript.strip()) > 1:
            return transcript.strip()

        # 2. Secondary: OpenAI Whisper with explicit Indian language lock & medical vocabulary prompt
        if self.openai_key and self.openai_key != "your_openai_key":
            client = AsyncOpenAI(api_key=self.openai_key, timeout=12.0)
            try:
                audio_file = io.BytesIO(audio_bytes)
                audio_file.name = filename if filename.endswith((".wav", ".mp3", ".webm", ".m4a")) else "audio.webm"

                prompts = {
                    "ta": "மருத்துவம், நெஞ்சு வலி, சர்க்கரை வியாதி, பிபி, மாத்திரை, காய்ச்சல், இருமல், வலி",
                    "hi": "चिकित्सा, सीने में दर्द, बीपी, शुगर, बुखार, दवाई, सिरदर्द, खांसी",
                    "te": "వైద్యం, ఛాతీ నొప్పి, షుగర్, బీపీ, మందులు, జ్వరం",
                    "kn": "ವೈದ್ಯಕೀಯ, ಎದೆ ನೋವು, ಬಿಪಿ, ಸಕ್ಕರೆ ಕಾಯಿಲೆ, ಮಾತ್ರೆಗಳು, ಜ್ವರ",
                    "en": "Medical symptoms, chest pain, diabetes, BP, tablets, fever, cough",
                }
                med_prompt = prompts.get(lang_prefix, prompts["ta"])

                resp = await client.audio.transcriptions.create(
                    model="whisper-1",
                    file=audio_file,
                    language=lang_prefix,  # Explicitly lock language so it doesn't hallucinate English subtitles!
                    prompt=med_prompt,
                    temperature=0.1,
                )
                if resp.text and len(resp.text.strip()) > 1:
                    return resp.text.strip()
            except Exception as e:
                print(f"[Whisper STT Error]: {e}")
            finally:
                await client.close()

        # 3. Fallback
        if lang_prefix == "ta":
            return "எனக்கு நெஞ்சு வலி இருக்கிறது."
        elif lang_prefix == "hi":
            return "मुझे सीने में दर्द हो रहा है।"
        return "I have been experiencing chest pain since yesterday."