import os
import sys
import google.generativeai as genai
from tenacity import retry, stop_after_attempt, wait_exponential, retry_if_exception_type

# Define a retry decorator
# Waits 2^x * 1 seconds between retries (1s, 2s, 4s, 8s, 16s, 32s...)
# With max=60, it will cap at waiting 60s per try.
# Stop after 15 attempts (approx 15 minutes of trying before giving up)
retry_policy = retry(
    stop=stop_after_attempt(15),
    wait=wait_exponential(multiplier=1, min=2, max=60),
    retry=retry_if_exception_type(Exception),
    reraise=True
)

@retry_policy
def _generate_with_retry(model, prompt):
    """Internal function to wrap the API call with retry logic."""
    try:
        return model.generate_content(prompt)
    except Exception as e:
        if "429" in str(e) or "Resource has been exhausted" in str(e):
            print(f"  [Rate Limit Hit] Waiting for quota reset... ({e})")
        raise e

def get_best_available_model():
    """
    Queries the API to find the best available model for text generation.
    Priority: gemini-1.5-flash > gemini-1.5-pro > gemini-pro > any 'generateContent' model
    """
    try:
        available_models = []
        for m in genai.list_models():
            if 'generateContent' in m.supported_generation_methods:
                available_models.append(m.name)
        
        # Priority list
        priorities = [
            "models/gemini-1.5-flash",
            "models/gemini-1.5-pro",
            "models/gemini-pro"
        ]
        
        # Check for priorities first
        for p in priorities:
            if p in available_models:
                return p
        
        # Fallback: check for aliases without 'models/' prefix just in case
        for p in priorities:
            short_name = p.replace("models/", "")
            # Some libraries might return short names, or custom handling
            # But genai.list_models() usually returns 'models/name'
            pass

        # If priority not found, pick the first available gemini model
        for m in available_models:
            if "gemini" in m:
                return m
                
        if available_models:
            return available_models[0]
            
    except Exception as e:
        print(f"Warning: Could not list models ({e}). Defaulting to 'gemini-pro'.")
    
    return "gemini-pro"

def translate_srt(srt_content, target_language="English", api_key=None):
    """
    Translates SRT subtitle content using the Gemini API, preserving timestamps.

    Args:
        srt_content (str): The raw text content of the SRT file.
        target_language (str): The target language for translation.
        api_key (str): Google Gemini API key. If None, checks env var GEMINI_API_KEY.

    Returns:
        str: The translated SRT content.
    """
    if not srt_content:
        return ""

    key = api_key or os.getenv("GEMINI_API_KEY")
    if not key:
        print("Error: GEMINI_API_KEY not found. Please set the environment variable or pass the key.")
        sys.exit(1)

    genai.configure(api_key=key)

    # Automatically select the best model
    model_name = get_best_available_model()
    print(f"Using Gemini Model: {model_name}")

    model = genai.GenerativeModel(model_name)

    prompt = (
        "You are a professional subtitle translator. Your task is to translate the following SRT subtitle file "
        f"into {target_language}.\n\n"
        "RULES:\n"
        "1. PRESERVE the SRT format exactly. Do not modify timestamps (e.g., 00:00:01,000 --> 00:00:04,000) or sequence numbers.\n"
        "2. Only translate the dialogue text.\n"
        "3. Maintain the original tone and context.\n"
        "4. Output ONLY the translated SRT content, no markdown code blocks or explanations.\n\n"
        "SRT Content:\n"
        f"{srt_content}"
    )

    print(f"Translating subtitles to {target_language} (with retries)...")
    try:
        # Call the retried internal function
        response = _generate_with_retry(model, prompt)
        print("Translation complete.")
        
        # Cleanup: sometimes models wrap output in ```srt ... ``` or ``` ... ```
        cleaned_text = response.text.strip()
        if cleaned_text.startswith("```"):
            # Remove first line (```srt or ```) and last line (```)
            lines = cleaned_text.split('\n')
            if len(lines) >= 2:
                cleaned_text = '\n'.join(lines[1:-1])
        
        return cleaned_text
    except Exception as e:
        print(f"Error during translation after retries: {e}")
        return None