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from main import *
from tts_api import tts_api as tts_route
from stt_api import stt_api as stt_route
from sentiment_api import sentiment_api as sentiment_route
from imagegen_api import imagegen_api as imagegen_route
from musicgen_api import musicgen_api as musicgen_route
from translation_api import translation_api as translation_route
from codegen_api import codegen_api as codegen_route
from text_to_video_api import text_to_video_api as text_to_video_route
from summarization_api import summarization_api as summarization_route
from image_to_3d_api import image_to_3d_api as image_to_3d_route
from flask import Flask, request, jsonify, Response, send_file, stream_with_context
from flask_cors import CORS
import torch
import torch.nn.functional as F
import torchaudio
import numpy as np
from PIL import Image
import io
import tempfile
import queue
import json
import base64
from markupsafe import Markup
from markupsafe import escape

app = Flask(__name__)
CORS(app)

html_code = """<!DOCTYPE html>

<html lang="en">

<head>

    <meta charset="UTF-8">

    <meta name="viewport" content="width=device-width, initial-scale=1.0">

    <title>AI Text Generation</title>

    <link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/animate.css/4.1.1/animate.min.css"/>

    <link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/6.0.0/css/all.min.css" integrity="sha512-9usAa10IRO0HhonpyAIVpjrylPvoDwiPUiKdWk5t3PyolY1cOd4DSE0Ga+ri4AuTroPR5aQvXU9xC6qOPnzFeg==" crossorigin="anonymous" referrerpolicy="no-referrer" />

    <script src="https://cdn.jsdelivr.net/npm/marked/marked.min.js"></script>

    <style>

        body {

            font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif;

            background: #f0f0f0;

            color: #333;

            margin: 0;

            padding: 0;

            display: flex;

            flex-direction: column;

            align-items: center;

            min-height: 100vh;

        }

        .container {

            width: 95%;

            max-width: 900px;

            padding: 20px;

            background-color: #fff;

            box-shadow: 0 0 10px rgba(0, 0, 0, 0.1);

            border-radius: 8px;

            margin-top: 20px;

            margin-bottom: 20px;

            display: flex;

            flex-direction: column;

        }

        .header {

            text-align: center;

            margin-bottom: 20px;

        }

        .header h1 {

            font-size: 2em;

            color: #333;

        }

        .form-group {

            margin-bottom: 15px;

        }

        .form-group textarea {

            width: 100%;

            padding: 10px;

            border: 1px solid #ccc;

            border-radius: 5px;

            font-size: 16px;

            box-sizing: border-box;

            resize: vertical;

        }

        button {

            padding: 10px 15px;

            border: none;

            border-radius: 5px;

            background-color: #007bff;

            color: white;

            font-size: 18px;

            cursor: pointer;

            transition: background-color 0.3s ease;

        }

        button:hover {

            background-color: #0056b3;

        }

        #output {

            margin-top: 20px;

            padding: 15px;

            border: 1px solid #ddd;

            border-radius: 5px;

            background-color: #f9f9f9;

            white-space: pre-wrap;

            word-break: break-word;

            overflow-y: auto;

            max-height: 100vh;

        }

        #output strong {

            font-weight: bold;

        }

        .animated-text {

            position: fixed;

            top: 20px;

            left: 20px;

            font-size: 1.5em;

            color: rgba(0, 0, 0, 0.1);

            pointer-events: none;

            z-index: -1;

        }

        @media (max-width: 768px) {

            .container {

                width: 98%;

                margin-top: 10px;

                margin-bottom: 10px;

                padding: 15px;

            }

            .header h1 {

                font-size: 1.8em;

            }

            .form-group textarea, .form-group input[type="text"] {

                font-size: 14px;

                padding: 8px;

            }

            button {

                font-size: 16px;

                padding: 8px 12px;

            }

            #output {

                font-size: 14px;

                padding: 10px;

                margin-top: 15px;

            }

        }

    </style>

</head>

<body>

<div class="animated-text animate__animated animate__fadeIn animate__infinite infinite">AI POWERED</div>

<div class="container">

    <div class="header animate__animated animate__fadeInDown">

    </div>

    <div class="form-group animate__animated animate__fadeInLeft">

        <textarea id="text" rows="5" placeholder="Enter text"></textarea>

    </div>

    <button onclick="generateText()" class="animate__animated animate__fadeInUp">Generate Reasoning</button>

    <div id="output" class="animate__animated">

        <strong>Response:</strong><br>

        <span id="generatedText"></span>

    </div>

</div>

<script>

    let eventSource = null;

    let accumulatedText = "";

    let lastResponse = "";

    async function generateText() {

        const inputText = document.getElementById("text").value;

        document.getElementById("generatedText").innerText = "";

        accumulatedText = "";

        if (eventSource) {

            eventSource.close();

        }

        const temp = 0.7;

        const top_k_val = 40;

        const top_p_val = 0.0;

        const repetition_penalty_val = 1.2;

        const requestData = {

            text: inputText,

            temp: temp,

            top_k: top_k_val,

            top_p: top_p_val,

            reppenalty: repetition_penalty_val

        };

        const params = new URLSearchParams(requestData).toString();

        eventSource = new EventSource('/api/v1/generate_stream?' + params);

        eventSource.onmessage = function(event) {

            if (event.data === "<END_STREAM>") {

                eventSource.close();

                const currentResponse = accumulatedText.replace("<|endoftext|>", "").replace(/\s+(?=[.,，。])/g, '').trim();

                if (currentResponse === lastResponse.trim()) {

                    accumulatedText = "**Response is repetitive. Please try again or rephrase your query.**";

                } else {

                    lastResponse = currentResponse;

                }

                document.getElementById("generatedText").innerHTML = marked.parse(accumulatedText);

                return;

            }

            accumulatedText += event.data;

            let partialText = accumulatedText.replace("<|endoftext|>", "").replace(/\s+(?=[.,，。])/g, '').trim();

            document.getElementById("generatedText").innerHTML = marked.parse(partialText);

        };

        eventSource.onerror = function(error) {

            console.error("SSE error", error);

            eventSource.close();

        };

        const outputDiv = document.getElementById("output");

        outputDiv.classList.add("show");

    }

    function base64ToBlob(base64Data, contentType) {

        contentType = contentType || '';

        const sliceSize = 1024;

        const byteCharacters = atob(base64Data);

        const bytesLength = byteCharacters.length;

        const slicesCount = Math.ceil(bytesLength / sliceSize);

        const byteArrays = new Array(slicesCount);

        for (let sliceIndex = 0; sliceIndex < slicesCount; ++sliceIndex) {

            const begin = sliceIndex * sliceSize;

            const end = Math.min(begin + sliceSize, bytesLength);

            const bytes = new Array(end - begin);

            for (let offset = begin, i = 0; offset < end; ++i, ++offset) {

                bytes[i] = byteCharacters[offset].charCodeAt(0);

            }

            byteArrays[sliceIndex] = new Uint8Array(bytes);

        }

        return new Blob(byteArrays, { type: contentType });

    }

</script>

</body>

</html>

"""
feedback_queue = queue.Queue()


@app.route("/")
def index():
    return html_code

@app.route("/api/v1/generate_stream", methods=["GET"])
def generate_stream():
    text = request.args.get("text", "")
    temp = float(request.args.get("temp", 0.7))
    top_k = int(request.args.get("top_k", 40))
    top_p = float(request.args.get("top_p", 0.0))
    reppenalty = float(request.args.get("reppenalty", 1.2))
    response_queue = queue.Queue()
    reasoning_queue.put({
        'text_input': text,
        'temperature': temp,
        'top_k': top_k,
        'top_p': top_p,
        'repetition_penalty': reppenalty,
        'response_queue': response_queue
    })
    @stream_with_context
    def event_stream():
        while True:
            output = response_queue.get()
            if "error" in output:
                yield "data: <ERROR>\n\n"
                break
            text_chunk = output.get("text")
            if text_chunk:
                for word in text_chunk.split(' '):
                    clean_word = word.strip()
                    if clean_word:
                        yield "data: " + clean_word + "\n\n"
                yield "data: <END_STREAM>\n\n"
                break
    return Response(event_stream(), mimetype="text/event-stream")

@app.route("/api/v1/generate", methods=["POST"])
def generate():
    data = request.get_json()
    text = data.get("text", "")
    temp = float(data.get("temp", 0.7))
    top_k = int(data.get("top_k", 40))
    top_p = float(data.get("top_p", 0.0))
    reppenalty = float(data.get("reppenalty", 1.2))
    response_queue = queue.Queue()
    reasoning_queue.put({
        'text_input': text,
        'temperature': temp,
        'top_k': top_k,
        'top_p': top_p,
        'repetition_penalty': reppenalty,
        'response_queue': response_queue
    })
    output = response_queue.get()
    if "error" in output:
        return jsonify({"error": output["error"]}), 500
    result_text = output.get("text", "").strip()
    return jsonify({"response": result_text})

@app.route("/api/v1/feedback", methods=["POST"])
def feedback():
    data = request.get_json()
    feedback_text = data.get("feedback_text")
    correct_category = data.get("correct_category")
    if feedback_text and correct_category:
        feedback_queue.put((feedback_text, correct_category))
        return jsonify({"status": "feedback received"})
    return jsonify({"status": "feedback failed"}), 400

@app.route("/api/v1/tts", methods=["POST"])
def tts_api():
    return tts_route()

@app.route("/api/v1/stt", methods=["POST"])
def stt_api():
    return stt_route()

@app.route("/api/v1/sentiment", methods=["POST"])
def sentiment_api():
    return sentiment_route()

@app.route("/api/v1/imagegen", methods=["POST"])
def imagegen_api():
    return imagegen_route()

@app.route("/api/v1/musicgen", methods=["POST"])
def musicgen_api():
    return musicgen_route()

@app.route("/api/v1/translation", methods=["POST"])
def translation_api():
    return translation_route()

@app.route("/api/v1/codegen", methods=["POST"])
def codegen_api():
    return codegen_route()

@app.route("/api/v1/text_to_video", methods=["POST"])
def text_to_video_api():
    return text_to_video_route()

@app.route("/api/v1/summarization", methods=["POST"])
def summarization_api():
    return summarization_route()

@app.route("/api/v1/image_to_3d", methods=["POST"])
def image_to_3d_api():
    return image_to_3d_route()

@app.route("/api/v1/sadtalker", methods=["POST"])
def sadtalker():
    from sadtalker_api import router as sadtalker_router
    return sadtalker_router.create_video()

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