# app.py
import display_gloss as dg
import synonyms_preprocess as sp
from NLP_Spacy_base_translator import NlpSpacyBaseTranslator 
from flask import Flask, render_template, Response, request, send_file
import io
import cv2
import numpy as np
import os
import requests
from urllib.parse import quote, unquote
import tempfile

app = Flask(__name__, static_folder='static')
app.config['TITLE'] = 'Sign Language Translate'

nlp, dict_docs_spacy = sp.load_spacy_values()
dataset, list_2000_tokens = dg.load_data()

def translate_korean_to_english(text):
    try:
        url = "https://translate.googleapis.com/translate_a/single"
        params = {
            "client": "gtx", 
            "sl": "ko",
            "tl": "en",
            "dt": "t",
            "q": text.strip()
        }
        response = requests.get(url, params=params)
        if response.status_code == 200:
            translated_text = ' '.join(item[0] for item in response.json()[0] if item[0])
            return translated_text
        else:
            raise Exception(f"Translation API returned status code: {response.status_code}")
    except Exception as e:
        print(f"Translation error: {e}")
        return text

def generate_complete_video(gloss_list, dataset, list_2000_tokens):
    try:
        frames = []
        for frame in dg.generate_video(gloss_list, dataset, list_2000_tokens):
            frame_data = frame.split(b'\r\n\r\n')[1]
            nparr = np.frombuffer(frame_data, np.uint8)
            img = cv2.imdecode(nparr, cv2.IMREAD_COLOR)
            frames.append(img)
        
        if not frames:
            raise Exception("No frames generated")

        height, width = frames[0].shape[:2]
        fourcc = cv2.VideoWriter_fourcc(*'mp4v')
        
        with tempfile.NamedTemporaryFile(suffix='.mp4', delete=False) as temp_file:
            temp_path = temp_file.name
            
        out = cv2.VideoWriter(temp_path, fourcc, 25, (width, height))
        
        for frame in frames:
            out.write(frame)
        out.release()
        
        with open(temp_path, 'rb') as f:
            video_bytes = f.read()
        
        os.remove(temp_path)
        return video_bytes
    except Exception as e:
        print(f"Error generating video: {str(e)}")
        raise

@app.route('/')
def index():
    return render_template('index.html', title=app.config['TITLE'])

@app.route('/translate/', methods=['POST'])
def result():
    if request.method == 'POST':
        input_text = request.form['inputSentence'].strip()
        if not input_text:
            return render_template('error.html', error="Please enter text to translate")
        
        try:
            english_text = translate_korean_to_english(input_text)
            if not english_text:
                raise Exception("Translation failed")
                
            eng_to_asl_translator = NlpSpacyBaseTranslator(sentence=english_text)
            generated_gloss = eng_to_asl_translator.translate_to_gloss()
            
            gloss_list_lower = [gloss.lower() for gloss in generated_gloss.split() if gloss.isalnum()]
            gloss_sentence_before_synonym = " ".join(gloss_list_lower)
            
            gloss_list = [sp.find_synonyms(gloss, nlp, dict_docs_spacy, list_2000_tokens) 
                         for gloss in gloss_list_lower]
            gloss_sentence_after_synonym = " ".join(gloss_list)
            
            return render_template('result.html',
                                title=app.config['TITLE'],
                                original_sentence=input_text,
                                english_translation=english_text,
                                gloss_sentence_before_synonym=gloss_sentence_before_synonym,
                                gloss_sentence_after_synonym=gloss_sentence_after_synonym)
        except Exception as e:
            return render_template('error.html', error=f"Translation error: {str(e)}")

@app.route('/video_feed')
def video_feed():
    sentence = request.args.get('gloss_sentence_to_display', '')
    gloss_list = sentence.split()
    return Response(dg.generate_video(gloss_list, dataset, list_2000_tokens), 
                   mimetype='multipart/x-mixed-replace; boundary=frame')

@app.route('/download_video/<path:gloss_sentence>')
def download_video(gloss_sentence):
    try:
        decoded_sentence = unquote(gloss_sentence)
        gloss_list = decoded_sentence.split()
        
        if not gloss_list:
            return "No gloss provided", 400
            
        video_bytes = generate_complete_video(gloss_list, dataset, list_2000_tokens)
        
        if not video_bytes:
            return "Failed to generate video", 500
            
        return send_file(
            io.BytesIO(video_bytes),
            mimetype='video/mp4',
            as_attachment=True,
            download_name='sign_language.mp4'
        )
    except Exception as e:
        print(f"Download error: {str(e)}")
        return f"Error downloading video: {str(e)}", 500

if __name__ == "__main__":
    app.run(host="0.0.0.0", port=7860, debug=True)