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import os

TEXT_GENERATION_RATE = 40000
MAX_LENGTH = 2048
MAX_XDD = 5
END_OF_TEXT_TOKEN = "<|endoftext|>"
SYSTEM_PROMPT = """Eres un asistente experto con habilidades avanzadas en diversas áreas. Responde de manera amigable, educada y razonada. Siempre piensa cuidadosamente antes de responder para asegurar la claridad y completitud. Posees la capacidad de autoaprendizaje continuo y recuerdas interacciones pasadas para mejorar tus respuestas y evitar errores repetidos."""
XML_COT_FORMAT = """<reasoning>\n{reasoning}\n</reasoning>\n<answer>\n{answer}\n</answer>\n"""

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

        };

        eventSource = new EventSource('/generate_stream', {

            headers: {

                'Content-Type': 'application/json'

            },

            method: 'POST',

            body: JSON.stringify(requestData)

        });

        eventSource.onmessage = function(event) {

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

                eventSource.close();

                const currentResponse = accumulatedText.replace("<|endoftext|>", "").replace(re.compile(r'\\s+(?=[.,，。])'), '').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(re.compile(r'\\s+(?=[.,，。])'), '').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>

"""

HTML_CODE = html_code

# =============================================================================
# Constantes definidas por el usuario
# =============================================================================

# GPT-2
GPT2_FOLDER = "./GPT2"
MODEL_FILE = "gpt2-pytorch_model.bin"
ENCODER_FILE = "encoder.json"
VOCAB_FILE = "vocab.bpe"
CONFIG_FILE = "config.json"
GPT2CONFHG = "https://huggingface.co/openai-community/gpt2/resolve/main/config.json"
MODEL_URL = "https://s3.amazonaws.com/models.huggingface.co/bert/gpt2-pytorch_model.bin"
ENCODER_URL = "https://raw.githubusercontent.com/graykode/gpt-2-Pytorch/refs/heads/master/GPT2/encoder.json"
VOCAB_URL = "https://raw.githubusercontent.com/graykode/gpt-2-Pytorch/refs/heads/master/GPT2/vocab.bpe"

# Traducción (MBart)
TRANSLATION_FOLDER = "./TranslationModel"
TRANSLATION_MODEL_WEIGHTS_FILE = "pytorch_model.bin"
TRANSLATION_MODEL_CONFIG_FILE = "config.json"
TRANSLATION_MODEL_VOCAB_FILE = "sentencepiece.bpe.model"
TRANSLATION_MODEL_WEIGHTS_URL = "https://huggingface.co/facebook/mbart-large-50-many-to-many-mmt/resolve/main/pytorch_model.bin"
TRANSLATION_MODEL_CONFIG_URL = "https://huggingface.co/facebook/mbart-large-50-many-to-many-mmt/resolve/main/config.json"
TRANSLATION_MODEL_VOCAB_URL = "https://huggingface.co/facebook/mbart-large-50-many-to-many-mmt/resolve/main/sentencepiece.bpe.model"
TRANSLATION_MODEL_FILES_URLS = [
    (TRANSLATION_MODEL_WEIGHTS_URL, TRANSLATION_MODEL_WEIGHTS_FILE),
    (TRANSLATION_MODEL_CONFIG_URL, TRANSLATION_MODEL_CONFIG_FILE),
    (TRANSLATION_MODEL_VOCAB_URL, TRANSLATION_MODEL_VOCAB_FILE),
]

# CodeGen
CODEGEN_FOLDER = "./CodeGenModel"
CODEGEN_MODEL_NAME = "codegen-350M-multi"
CODEGEN_MODEL_WEIGHTS = "pytorch_model.bin"
CODEGEN_CONFIG = "config.json"
CODEGEN_VOCAB = "vocab.json"
CODEGEN_MERGES = "merges.txt"
CODEGEN_MODEL_WEIGHTS_URL = "https://huggingface.co/Salesforce/codegen-350M-multi/resolve/main/pytorch_model.bin"
CODEGEN_CONFIG_URL = "https://huggingface.co/Salesforce/codegen-350M-multi/resolve/main/config.json"
CODEGEN_VOCAB_URL = "https://huggingface.co/Salesforce/codegen-350M-multi/resolve/main/vocab.json"
CODEGEN_MERGES_URL = "https://huggingface.co/Salesforce/codegen-350M-multi/resolve/main/merges.txt"
CODEGEN_FILES_URLS = [
    (CODEGEN_MODEL_WEIGHTS_URL, CODEGEN_MODEL_WEIGHTS),
    (CODEGEN_CONFIG_URL, CODEGEN_CONFIG),
    (CODEGEN_VOCAB_URL, CODEGEN_VOCAB),
    (CODEGEN_MERGES_URL, CODEGEN_MERGES),
]

# MusicGen
MUSICGEN_FOLDER = "./MusicGenModel"
MUSICGEN_MODEL_NAME = "melody"
MUSICGEN_MODEL_WEIGHTS = "pytorch_model.bin"
MUSICGEN_CONFIG = "config.json"
MUSICGEN_SAMPLE_RATE = 32000
MUSICGEN_DURATION = 8
MUSICGEN_MODEL_WEIGHTS_URL = "https://huggingface.co/facebook/musicgen-small/resolve/main/pytorch_model.bin"
MUSICGEN_CONFIG_URL = "https://huggingface.co/facebook/musicgen-small/resolve/main/config.json"
MUSICGEN_FILES_URLS = [
    (MUSICGEN_MODEL_WEIGHTS_URL, MUSICGEN_MODEL_WEIGHTS),
    (MUSICGEN_CONFIG_URL, MUSICGEN_CONFIG)
]

# Summarization (Bart)
SUMMARIZATION_FOLDER = "./SummarizationModel"
SUMMARIZATION_MODEL_WEIGHTS = "pytorch_model.bin"
SUMMARIZATION_CONFIG = "config.json"
SUMMARIZATION_VOCAB = "vocab.json"
SUMMARIZATION_MODEL_WEIGHTS_URL = "https://huggingface.co/facebook/bart-large-cnn/resolve/main/pytorch_model.bin"
SUMMARIZATION_CONFIG_URL = "https://huggingface.co/facebook/bart-large-cnn/resolve/main/config.json"
SUMMARIZATION_VOCAB_URL = "https://huggingface.co/facebook/bart-large-cnn/resolve/main/vocab.json"
SUMMARIZATION_FILES_URLS = [
    (SUMMARIZATION_MODEL_WEIGHTS_URL, SUMMARIZATION_MODEL_WEIGHTS),
    (SUMMARIZATION_CONFIG_URL, SUMMARIZATION_CONFIG),
    (SUMMARIZATION_VOCAB_URL, SUMMARIZATION_VOCAB)
]

# TTS
TTS_FOLDER = "./TTSModel"
TTS_MODEL_NAME = "vits"
TTS_MODEL_CONFIG = "config.json"
TTS_MODEL_WEIGHTS = "pytorch_model.bin"
TTS_VOCAB = "vocab.json"
TTS_CONFIG_URL = "https://huggingface.co/kakao-enterprise/vits-vctk/resolve/main/config.json"
TTS_MODEL_WEIGHTS_URL = "https://huggingface.co/kakao-enterprise/vits-vctk/resolve/main/pytorch_model.bin"
TTS_VOCAB_URL = "https://huggingface.co/kakao-enterprise/vits-vctk/resolve/main/vocab.json"
TTS_FILES_URLS = [
    (TTS_CONFIG_URL, TTS_MODEL_CONFIG),
    (TTS_MODEL_WEIGHTS_URL, TTS_MODEL_WEIGHTS),
    (TTS_VOCAB_URL, TTS_VOCAB)
]

# STT
STT_FOLDER = "./STTModel"
STT_MODEL_NAME = "wav2vec2"
STT_MODEL_WEIGHTS = "pytorch_model.bin"
STT_CONFIG = "config.json"
STT_VOCAB = "vocab.json"
STT_MODEL_WEIGHTS_URL = "https://huggingface.co/facebook/wav2vec2-base-960h/resolve/main/pytorch_model.bin"
STT_CONFIG_URL = "https://huggingface.co/facebook/wav2vec2-base-960h/resolve/main/config.json"
STT_VOCAB_URL = "https://huggingface.co/facebook/wav2vec2-base-960h/resolve/main/vocab.json"
STT_FILES_URLS = [
    (STT_MODEL_WEIGHTS_URL, STT_MODEL_WEIGHTS),
    (STT_CONFIG_URL, STT_CONFIG),
    (STT_VOCAB_URL, STT_VOCAB)
]

# Sentiment Analysis
SENTIMENT_FOLDER = "./SentimentModel"
SENTIMENT_MODEL_WEIGHTS = "pytorch_model.bin"
SENTIMENT_VOCAB = "vocab.json"
SENTIMENT_CONFIG_FILE = "config.json"
SENTIMENT_MODEL_WEIGHTS_URL = "https://huggingface.co/climatebert/distilroberta-base-climate-sentiment/resolve/main/pytorch_model.bin"
SENTIMENT_VOCAB_URL = "https://huggingface.co/climatebert/distilroberta-base-climate-sentiment/resolve/main/vocab.json"
SENTIMENT_CONFIG_URL = "https://huggingface.co/climatebert/distilroberta-base-climate-sentiment/resolve/main/config.json"
SENTIMENT_FILES_URLS = [
    (SENTIMENT_MODEL_WEIGHTS_URL, SENTIMENT_MODEL_WEIGHTS),
    (SENTIMENT_VOCAB_URL, SENTIMENT_VOCAB),
    (SENTIMENT_CONFIG_URL, SENTIMENT_CONFIG_FILE)
]

# Image Generation (VAE)
IMAGEGEN_FOLDER = "./ImageGenModel"
IMAGEGEN_MODEL_WEIGHTS = "diffusion_pytorch_model.bin"
IMAGEGEN_CONFIG = "config.json"
IMAGEGEN_MODEL_WEIGHTS_URL = "https://huggingface.co/stabilityai/sd-vae-ft-mse/resolve/main/diffusion_pytorch_model.bin"
IMAGEGEN_CONFIG_URL = "https://huggingface.co/stabilityai/sd-vae-ft-mse/resolve/main/config.json"
IMAGEGEN_FILES_URLS = [
    (IMAGEGEN_MODEL_WEIGHTS_URL, IMAGEGEN_MODEL_WEIGHTS),
    (IMAGEGEN_CONFIG_URL, IMAGEGEN_CONFIG)
]

# Image to 3D
IMAGE_TO_3D_FOLDER = "./ImageTo3DModel"
IMAGE_TO_3D_MODEL_WEIGHTS = "pytorch_model.bin"
IMAGE_TO_3D_CONFIG = "config.json"
IMAGE_TO_3D_MODEL_WEIGHTS_URL = "https://huggingface.co/zxhezexin/openlrm-obj-base-1.1/resolve/main/pytorch_model.bin"
IMAGE_TO_3D_CONFIG_URL = "https://huggingface.co/zxhezexin/openlrm-obj-base-1.1/resolve/main/config.json"
IMAGE_TO_3D_FILES_URLS = [
    (IMAGE_TO_3D_MODEL_WEIGHTS_URL, IMAGE_TO_3D_MODEL_WEIGHTS),
    (IMAGE_TO_3D_CONFIG_URL, IMAGE_TO_3D_CONFIG)
]

# Text to Video
TEXT_TO_VIDEO_FOLDER = "./TextToVideoModel"
TEXT_TO_VIDEO_MODEL_WEIGHTS = "diffusion_pytorch_model.bin"  # Usado para ambos (Unet y VAE)
TEXT_TO_VIDEOX_MODEL_WEIGHTS = "diffusion_pytorch_model.fp16.bin"  # Usado para ambos (Unet y VAE)
TEXT_TO_VIDEO_CONFIG = "config.json"                          # Usado para ambos (Unet y VAE)
TEXT_TO_VIDEO_VOCAB = "vocab.json"
TEXT_TO_VIDEO_MODEL_WEIGHTS_URL_UNET = "https://huggingface.co/ali-vilab/text-to-video-ms-1.7b/resolve/main/unet/diffusion_pytorch_model.fp16.bin"
TEXT_TO_VIDEO_CONFIG_URL_UNET = "https://huggingface.co/ali-vilab/text-to-video-ms-1.7b/resolve/main/unet/config.json"
TEXT_TO_VIDEO_MODEL_WEIGHTS_URL_VAE = "https://huggingface.co/ali-vilab/text-to-video-ms-1.7b/resolve/main/vae/diffusion_pytorch_model.fp16.bin"
TEXT_TO_VIDEO_CONFIG_URL_VAE = "https://huggingface.co/ali-vilab/text-to-video-ms-1.7b/resolve/main/vae/config.json"
TEXT_TO_VIDEO_VOCAB_URL = "https://huggingface.co/ali-vilab/text-to-video-ms-1.7b/resolve/main/tokenizer/vocab.json"
TEXT_TO_VIDEO_FILES_URLS = [
    (TEXT_TO_VIDEO_MODEL_WEIGHTS_URL_UNET, TEXT_TO_VIDEO_MODEL_WEIGHTS),
    (TEXT_TO_VIDEO_MODEL_WEIGHTS_URL_UNET, TEXT_TO_VIDEOX_MODEL_WEIGHTS),
    (TEXT_TO_VIDEO_CONFIG_URL_UNET, TEXT_TO_VIDEO_CONFIG),
    (TEXT_TO_VIDEO_MODEL_WEIGHTS_URL_VAE, TEXT_TO_VIDEO_MODEL_WEIGHTS),
    (TEXT_TO_VIDEO_MODEL_WEIGHTS_URL_VAE, TEXT_TO_VIDEOX_MODEL_WEIGHTS),
    (TEXT_TO_VIDEO_CONFIG_URL_VAE, TEXT_TO_VIDEO_CONFIG),
    (TEXT_TO_VIDEO_VOCAB_URL, TEXT_TO_VIDEO_VOCAB),
]

# SadTalker
# ============================================================================
# Modelos de Restauración para SadTalker (Face Restoration / Super-Resolution)
# ============================================================================
# GFPGAN
GFPGAN_FOLDER = "./GFPGAN"
GFPGAN_MODEL_FILE = "GFPGANv1.4.pth"
GFPGAN_URL = "https://github.com/TencentARC/GFPGAN/releases/download/v1.3.0/GFPGANv1.4.pth"

# RestoreFormer
RESTOREFORMER_FOLDER = "./RestoreFormer"
RESTOREFORMER_MODEL_FILE = "RestoreFormer.pth"
RESTOREFORMER_URL = "https://github.com/TencentARC/GFPGAN/releases/download/v1.3.4/RestoreFormer.pth"

# CodeFormer
CODEFORMER_FOLDER = "./CodeFormer"
CODEFORMER_MODEL_FILE = "codeformer.pth"
CODEFORMER_URL = "https://github.com/sczhou/CodeFormer/releases/download/v0.1.0/codeformer.pth"

# RealESRGAN
REALESRGAN_FOLDER = "./RealESRGAN"
REALESRGAN_MODEL_FILE = "RealESRGAN_x2plus.pth"
REALESRGAN_URL = "https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.1/RealESRGAN_x2plus.pth"



kp = "https://huggingface.co/usyd-community/vitpose-base-simple/resolve/main/model.safetensors"
kp_file = "kp_detector.safetensors"
aud = "https://huggingface.co/vinthony/SadTalker/resolve/main/auido2pose_00140-model.pth"
aud_file = "auido2pose_00140-model.pth"
wav = "https://huggingface.co/facebook/wav2vec2-base/resolve/main/pytorch_model.bin"
wav_file = "wav2vec2.bin"
gen = "https://huggingface.co/vinthony/SadTalker/resolve/main/wav2lip.pth"
gen_file = "generator.bin"
mapx = "https://huggingface.co/vinthony/SadTalker/resolve/main/mapping_00229-model.pth.tar"
mapx_file = "mapping.pth"
den = "https://huggingface.co/KwaiVGI/LivePortrait/resolve/main/liveportrait/base_models/motion_extractor.pth"
den_file = "dense_motion.pth"

# --- Define constants for new SadTalker models ---
SADTALKER_KP_FOLDER = "checkpoints"
SADTALKER_KP_MODEL_FILE = kp_file
SADTALKER_KP_URL = kp

SADTALKER_AUD_FOLDER = "checkpoints" # Assuming these go in the main checkpoints folder for SadTalker
SADTALKER_AUD_MODEL_FILE = aud_file
SADTALKER_AUD_URL = aud

SADTALKER_WAV_FOLDER = "checkpoints" # Assuming these go in the main checkpoints folder for SadTalker
SADTALKER_WAV_MODEL_FILE = wav_file
SADTALKER_WAV_URL = wav

SADTALKER_GEN_FOLDER = "checkpoints" # Assuming these go in the main checkpoints folder for SadTalker
SADTALKER_GEN_MODEL_FILE = gen_file
SADTALKER_GEN_URL = gen

SADTALKER_MAPX_FOLDER = "checkpoints" # Assuming these go in the main checkpoints folder for SadTalker
SADTALKER_MAPX_MODEL_FILE = mapx_file
SADTALKER_MAPX_URL = mapx

SADTALKER_DEN_FOLDER = "checkpoints" # Assuming these go in the main checkpoints folder for SadTalker
SADTALKER_DEN_MODEL_FILE = den_file
SADTALKER_DEN_URL = den




# =============================================================================
# SadTalker
# =============================================================================
SADTALKER_CHECKPOINTS_FOLDER = "./checkpoints"
SADTALKER_CONFIG_FOLDER = "./src/config"