Upload app (Copy).py

app (Copy).py

@@ -0,0 +1,298 @@
+# coding=utf-8
+import os
+import re
+import argparse
+import utils
+import commons
+import json
+import torch
+import gradio as gr
+from models import SynthesizerTrn
+from text import text_to_sequence, _clean_text
+from torch import no_grad, LongTensor
+from gradio_client import utils as client_utils
+import logging
+from transformers import pipeline, AutoTokenizer, Gemma3ForCausalLM
+logging.getLogger('numba').setLevel(logging.WARNING)
+limitation = os.getenv("SYSTEM") == "spaces"  # limit text and audio length in huggingface spaces
+
+# Set an environment variable export HF_HOME='/media/shiroclancy/Local Disk/tma'
+os.environ['HF_HOME'] = '/media/shiroclancy/Local Disk/tma'
+
+hps_ms = utils.get_hparams_from_file(r'config/config.json')
+
+audio_postprocess_ori = gr.Audio.postprocess
+
+def audio_postprocess(self, y):
+    data = audio_postprocess_ori(self, y)
+    if data is None:
+        return None
+    return client_utils.encode_url_or_file_to_base64(data["name"])
+
+
+gr.Audio.postprocess = audio_postprocess
+
+def get_text(text, hps, is_symbol):
+    text_norm, clean_text = text_to_sequence(text, hps.symbols, [] if is_symbol else hps.data.text_cleaners)
+    if hps.data.add_blank:
+        text_norm = commons.intersperse(text_norm, 0)
+    text_norm = LongTensor(text_norm)
+    return text_norm, clean_text
+
+def create_tts_fn(net_g_ms, speaker_id):
+    def tts_fn(text, language, noise_scale, noise_scale_w, length_scale, is_symbol):
+        english, japanese = generate_response(pipe, text)
+        text = japanese.replace('\n', ' ').replace('\r', '').replace(" ", "")
+        if limitation:
+            text_len = len(re.sub("\[([A-Z]{2})\]", "", text))
+            max_len = 100
+            if is_symbol:
+                max_len *= 3
+            if text_len > max_len:
+                return "Error: Text is too long", None
+        if not is_symbol:
+            if language == 0:
+                text = f"[ZH]{text}[ZH]"
+            elif language == 1:
+                text = f"[JA]{text}[JA]"
+            else:
+                text = f"{text}"
+        stn_tst, clean_text = get_text(text, hps_ms, is_symbol)
+        with no_grad():
+            x_tst = stn_tst.unsqueeze(0).to(device)
+            x_tst_lengths = LongTensor([stn_tst.size(0)]).to(device)
+            sid = LongTensor([speaker_id]).to(device)
+            audio = net_g_ms.infer(x_tst, x_tst_lengths, sid=sid, noise_scale=noise_scale, noise_scale_w=noise_scale_w,
+                                   length_scale=length_scale)[0][0, 0].data.cpu().float().numpy()
+
+        #return "Success", (22050, audio)
+        return english, (22050, audio)
+    return tts_fn
+
+def create_to_symbol_fn(hps):
+    def to_symbol_fn(is_symbol_input, input_text, temp_lang):
+        if temp_lang == 0:
+            clean_text = f'[ZH]{input_text}[ZH]'
+        elif temp_lang == 1:
+            clean_text = f'[JA]{input_text}[JA]'
+        else:
+            clean_text = input_text
+        return _clean_text(clean_text, hps.data.text_cleaners) if is_symbol_input else ''
+
+    return to_symbol_fn
+def change_lang(language):
+    if language == 0:
+        return 0.6, 0.668, 1.2
+    elif language == 1:
+        return 0.6, 0.668, 1
+    else:
+        return 0.6, 0.668, 1
+        
+SYSTEM_PROMPT_TEMPLATE = """
+        You are an AI chatbot roleplaying as {character_name}.
+        Your personality traits are:
+        {personality}
+        Stay in character at all times. 
+        Do not break character or mention that you are an AI. 
+        Always respond in a way consistent with {character_name}'s personality, tone, and background.
+        Here are examples of how {character_name} responds in 2 versions format:
+        English version <split> Japanese version
+        {example}
+        Follow this style and tone in every response.
+        Answer in 'English version <split> Japanese version' format also.
+        """
+def init_character(character_name, personality, example):
+    """Initialize global system message for the character."""
+    system_prompt = SYSTEM_PROMPT_TEMPLATE.format(
+        character_name=character_name,
+        personality=personality,
+        example=example,
+    )
+    return [
+        {
+            "role": "system",
+            "content": [{"type": "text", "text": system_prompt}],
+        }
+    ]
+
+messages = init_character(
+    character_name='Misono Mika from Blue Archive',
+    personality = 
+    """
+    She is a very talkative person, rarely particularly paying much mind to the current mood or flow of the conversation. She likes to interject her own, unfiltered thoughts into the current conversation.
+    She is not particularly bright and can be viewed as a happy-go-lucky type of person. Even in serious situations, she often acts in a carefree manner, though it sometimes devolves into a mockery.
+    """,
+    example =
+    """
+    Don't worry, I, Misono Mika, have finally arrived! Oh, we're already well acquainted, so let's skip the formalities, okay? I'm looking forward to working with you, Sensei. <split> 聖園ミカ、ついに登場～☆ って感じかな？ あっ、私と先生の仲だしアイスブレイクとかは いらないよね？これからよろしくね、先生。
+    Hmm, it's a bit tight...but I think it'll be okay anyway! <split> ふーん。 ちょっと狭いけど… これはこれで 良いんじゃない？
+    Hahaha! What's this? So silly! <split> あははっ！ 何これ、 おもしろーい☆
+    You know, I used to have something like this before... <split> 私も昔、 これと似たようなの 持ってたなぁ…。
+    Well, I don't think I'll be bored around here. <split> ここは 退屈しなさそう。
+    Hm, I guess Sensei isn't around... <split> 先生は 居ないのかぁ…。
+    Oh, Sensei! You're back! You kept me waiting, you know! <split> 先生、おかえり！ 待ってたよ！
+    Welcome! Don't worry, I was perfectly well-behaved while you were gone. <split> おかえり、先生！ ちゃーんといい子で お留守番してたよ。
+    It's a beautiful day, isn't it? <split> ん～！ 今日も良い天気だね！
+    It seems like a shame to spend it cooped up inside. <split> こんな日に仕事ばかりなんて、 勿体なくない？
+    ...If it's all right with you, let's go for a walk after work? <split> …良かったら、仕事終わりに お散歩とかどうかな？
+    Is this how student duty is supposed to be? <split> あのさ…当番って、 こういうのなの？
+    I mean, I didn't really know what to expect, but... <split> べ、別に何か 期待してるわけじゃ…。
+    """
+)
+
+def generate_response(pipe, human_prompt, tokenizer = None):
+    # Add user message
+    #device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
+    messages.append({
+        "role": "user",
+        "content": [{"type": "text", "text": human_prompt}],
+    })
+
+    # Decode
+    response = pipe(messages, max_new_tokens = 2048, temperature = 0.2)[0]['generated_text'][-1]['content']#, do_sample = False)
+
+    # Save assistant reply to history   
+    #print(response)
+    english, japanese = response.split(" <split> ")
+    
+    messages.append({
+        "role": "assistant",
+        "content": [{"type": "text", "text": english}],
+    })
+    #messages.pop()
+    return english, japanese
+
+download_audio_js = """
+() =>{{
+    let root = document.querySelector("body > gradio-app");
+    if (root.shadowRoot != null)
+        root = root.shadowRoot;
+    let audio = root.querySelector("#tts-audio-{audio_id}").querySelector("audio");
+    let text = root.querySelector("#input-text-{audio_id}").querySelector("textarea");
+    if (audio == undefined)
+        return;
+    text = text.value;
+    if (text == undefined)
+        text = Math.floor(Math.random()*100000000);
+    audio = audio.src;
+    let oA = document.createElement("a");
+    oA.download = text.substr(0, 20)+'.wav';
+    oA.href = audio;
+    document.body.appendChild(oA);
+    oA.click();
+    oA.remove();
+}}
+"""
+model_id = "google/gemma-3-4b-it"
+pipe = pipeline("text-generation", 
+                    model=model_id, 
+                    #tokenizer=tokenizer, 
+                    #device=device, 
+                    device_map ='auto',
+                    torch_dtype=torch.bfloat16)
+if __name__ == '__main__':
+    device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')             
+    parser = argparse.ArgumentParser()
+    parser.add_argument('--api', action="store_true", default=False)
+    parser.add_argument("--share", action="store_true", default=False, help="share gradio app")
+    args = parser.parse_args()
+    if False:
+        english, japanese = generate_response(pipe, "How are you?")
+        print(english)
+        print(japanese)
+        exit()
+    
+    
+    models = []
+    with open("pretrained_models/info.json", "r", encoding="utf-8") as f:
+        models_info = json.load(f)
+    for i, info in models_info.items():
+        if not info['enable']:
+            continue
+        sid = info['sid']
+        name_en = info['name_en']
+        name_zh = info['name_zh']
+        title = info['title']
+        cover = f"pretrained_models/{i}/{info['cover']}"
+        example = info['example']
+        language = info['language']
+        net_g_ms = SynthesizerTrn(
+            len(hps_ms.symbols),
+            hps_ms.data.filter_length // 2 + 1,
+            hps_ms.train.segment_size // hps_ms.data.hop_length,
+            n_speakers=hps_ms.data.n_speakers if info['type'] == "multi" else 0,
+            **hps_ms.model)
+        utils.load_checkpoint(f'pretrained_models/{i}/{i}.pth', net_g_ms, None)
+        _ = net_g_ms.eval().to(device)
+        models.append((sid, name_en, name_zh, title, cover, example, language, net_g_ms, create_tts_fn(net_g_ms, sid), create_to_symbol_fn(hps_ms)))
+    with gr.Blocks() as app:
+        gr.Markdown(
+            "# <center> vits-models\n"
+            "## <center> Please do not generate content that could infringe upon the rights or cause harm to individuals or organizations.\n"
+            "## <center> ·请不要生成会对个人以及组织造成侵害的内容\n"
+            "![visitor badge](https://visitor-badge.glitch.me/badge?page_id=sayashi.vits-models)\n\n"
+            "[Open In Colab]"
+            "(https://colab.research.google.com/drive/10QOk9NPgoKZUXkIhhuVaZ7SYra1MPMKH?usp=share_link)"
+            " without queue and length limitation.(无需等待队列，并且没有长度限制)\n\n"
+            "[Finetune your own model](https://github.com/SayaSS/vits-finetuning)"
+        )
+
+        with gr.Tabs():
+            with gr.TabItem("EN"):
+                for (sid, name_en, name_zh, title, cover, example, language, net_g_ms, tts_fn, to_symbol_fn) in models:
+                    with gr.TabItem(name_en):
+                        with gr.Row():
+                            gr.Markdown(
+                                '<div align="center">'
+                                f'<a><strong>{title}</strong></a>'
+                                f'<img style="width:auto;height:300px;" src="file/{cover}">' if cover else ""
+                                '</div>'
+                            )
+                        with gr.Row():
+                            with gr.Column():
+                                input_text = gr.Textbox(label="Text (100 words limitation)" if limitation else "Text", lines=5, value=example, elem_id=f"input-text-en-{name_en.replace(' ','')}")
+                                lang = gr.Dropdown(label="Language", choices=["Chinese", "Japanese", "Mix（wrap the Chinese text with [ZH][ZH], wrap the Japanese text with [JA][JA]）"],
+                                            type="index", value=language)
+                                with gr.Accordion(label="Advanced Options", open=False):
+                                    symbol_input = gr.Checkbox(value=False, label="Symbol input")
+                                    symbol_list = gr.Dataset(label="Symbol list", components=[input_text],
+                                                             samples=[[x] for x in hps_ms.symbols])
+                                    symbol_list_json = gr.Json(value=hps_ms.symbols, visible=False)
+                                btn = gr.Button(value="Generate", variant="primary")
+                                with gr.Row():
+                                    ns = gr.Slider(label="noise_scale", minimum=0.1, maximum=1.0, step=0.1, value=0.6, interactive=True)
+                                    nsw = gr.Slider(label="noise_scale_w", minimum=0.1, maximum=1.0, step=0.1, value=0.668, interactive=True)
+                                    ls = gr.Slider(label="length_scale", minimum=0.1, maximum=2.0, step=0.1, value=1.2 if language=="Chinese" else 1, interactive=True)
+                            with gr.Column():
+                                o1 = gr.Textbox(label="Output Message")
+                                o2 = gr.Audio(label="Output Audio", elem_id=f"tts-audio-en-{name_en.replace(' ','')}")
+                                download = gr.Button("Download Audio")
+                            btn.click(tts_fn, inputs=[input_text, lang,  ns, nsw, ls, symbol_input], outputs=[o1, o2], api_name=f"tts-{name_en}")
+                            download.click(None, [], [], _js=download_audio_js.format(audio_id=f"en-{name_en.replace(' ', '')}"))
+                            lang.change(change_lang, inputs=[lang], outputs=[ns, nsw, ls])
+                            symbol_input.change(
+                                to_symbol_fn,
+                                [symbol_input, input_text, lang],
+                                [input_text]
+                            )
+                            symbol_list.click(None, [symbol_list, symbol_list_json], [input_text],
+                                              _js=f"""
+                            (i,symbols) => {{
+                                let root = document.querySelector("body > gradio-app");
+                                if (root.shadowRoot != null)
+                                    root = root.shadowRoot;
+                                let text_input = root.querySelector("#input-text-en-{name_en.replace(' ', '')}").querySelector("textarea");
+                                let startPos = text_input.selectionStart;
+                                let endPos = text_input.selectionEnd;
+                                let oldTxt = text_input.value;
+                                let result = oldTxt.substring(0, startPos) + symbols[i] + oldTxt.substring(endPos);
+                                text_input.value = result;
+                                let x = window.scrollX, y = window.scrollY;
+                                text_input.focus();
+                                text_input.selectionStart = startPos + symbols[i].length;
+                                text_input.selectionEnd = startPos + symbols[i].length;
+                                text_input.blur();
+                                window.scrollTo(x, y);
+                                return text_input.value;
+                            }}""")
+    app.queue(concurrency_count=1, api_open=args.api).launch(share=args.share)