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app.py

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+import os
+import gradio as gr
+from glm_huggingface import run_glm
+from open_ai import run_openai
+from  prompt_loader import get_prompt
+
+from dotenv import load_dotenv
+
+load_dotenv()
+
+if os.getenv("OPENAI_API_KEY",False):
+    print ("using OPENAI_API_KEY")
+    run_llm=run_openai
+else:
+    print ("using glm from huggingface")
+    run_llm=run_glm
+
+PROMPT_STYLE = get_prompt("PROMPT_STYLE")
+PROMPT_TEXT = get_prompt("PROMPT_TEXT")
+PROMPT_TEXT2 = get_prompt("PROMPT_TEXT2") 
+SYSPROMPT_STYLE = get_prompt("SYSPROMPT_STYLE")
+SYSPROMPT_TEXT = get_prompt("SYSPROMPT_TEXT")
+
+def get_song_output(artist, song_text):
+    try:
+        # Get style music from artist
+        style_glm = run_openai(f"Describe {artist}", sys_prompt=SYSPROMPT_STYLE)
+        if style_glm:
+            style = style_glm
+        else:
+            style = ''
+    except Exception as e:
+        print(f"ERROR infer llm: {e}")
+        style = ''
+
+    try:
+        text_glm = run_openai(f"{PROMPT_TEXT}\n{style}\n#Text song:\n{song_text}\n{PROMPT_TEXT2}", sys_prompt=SYSPROMPT_TEXT)
+        if text_glm:
+            text = text_glm
+        else:
+            text = ''
+    except Exception as e:
+        print(f"ERROR infer llm: {e}")
+        text = ''
+
+    return style, text
+
+# Define translatable strings
+english_strings = {
+    "title": "SUNO style generator and sound format",
+    "performer_label": "Performer Name",
+    "song_text_label": "Song Text",
+    "language_english": "English",
+    "language_russian": "Russian",
+    "generate_button": "Generate",
+    "style_label": "Style",
+    "song_result_label": "Song Text"
+}
+
+russian_strings = {
+    "title": "Название: SUNO стайл генератор и звуковой формат",
+    "performer_label": "Имя исполнителя: ",
+    "song_text_label": "Текст песни: ",
+    "language_english": "Английский: ",
+    "language_russian": "Русский: ",
+    "generate_button": "Сгенерировать: ",
+    "style_label": "Стиль: ",
+    "song_result_label": "Текст песни: "
+}
+
+current_language = "English"
+
+with gr.Blocks() as demo:
+    with gr.Row(elem_id="header", equal_height=True):
+    # Левая колонка (логотип 100x100)
+        with gr.Column(scale=0, min_width=100):
+            gr.Image(
+                value="splash.webp",
+                width=100,
+                height=100,
+                show_label=False,
+                interactive=False,
+                show_download_button=False,
+                show_fullscreen_button=False,
+                elem_id="logo"
+            )
+        # Правая колонка (markdown на всю ширину)
+        with gr.Column(scale=1):
+            gr.Markdown(f"# {english_strings['title']}\nby <a href='https://boosty.to/aicave/donate'>AiCave</a>")
+
+    with gr.Row():
+        with gr.Column():
+            # Input fields
+            name_input = gr.Textbox(label=english_strings["performer_label"],lines=5, max_lines=10)
+            text_input = gr.Textbox(label=english_strings["song_text_label"], lines=25, max_lines=25)
+            # language_radio = gr.Radio(["English", "Russian"], label=english_strings["language_english"] + "/" + english_strings["language_russian"])
+            generate_button = gr.Button(english_strings["generate_button"])
+
+        with gr.Column():
+            # Output fields
+            style_output = gr.Textbox(label=english_strings["style_label"],lines=5, max_lines=10,show_copy_button=True)
+            song_output = gr.Textbox(label=english_strings["song_result_label"], lines=28, max_lines=28,show_copy_button=True)
+
+    # Generate button click event - calls the get_song_output function
+    generate_button.click(
+        fn=get_song_output,
+        inputs=[name_input, text_input],
+        outputs=[style_output, song_output]
+    )
+
+demo.css = """
+#header {
+    align-items: center;
+    padding: 0px 0px;
+    border-bottom: 0px solid #ddd;
+}
+"""
+
+if __name__ == "__main__":
+    demo.launch(quiet = False)

glm_huggingface.py

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+from __future__ import annotations
+import os
+import sys
+import html
+import re
+from typing import Any, List, Optional
+from paths import get_project_root
+from gradio_client import Client  # type: ignore
+
+
+def run_glm(prompt: str, sys_prompt: str) -> str:
+    """
+    Run LLM using the GLM Gradio Space via gradio_client.
+
+    Environment variables (loaded from .env at the repo root if available):
+      - GLM_GRADIO_SPACE      (default: "zai-org/GLM-4.5-Space")
+      - GLM_SYS_PROMPT        (default mirrors the system prompt used in test_gradio.py)
+      - GLM_TEMPERATURE       (float; default: 1)
+      - GLM_THINKING_ENABLED  (bool; "1"/"true"/"yes" => True; default: False)
+      - GLM_API_NAME          (default: "/chat_wrapper")
+    """
+    text = (prompt or "").strip()
+    if not text:
+        return prompt
+
+    _load_env()
+
+    space = os.getenv("GLM_GRADIO_SPACE", "zai-org/GLM-4.5-Space").strip() or "zai-org/GLM-4.5-Space"
+    sys_prompt = sys_prompt or ""
+
+    api_name = os.getenv("GLM_API_NAME", "/chat_wrapper").strip() or "/chat_wrapper"
+    temperature = _coerce_float(os.getenv("GLM_TEMPERATURE", "1"), default=1.0)
+    thinking_enabled = _coerce_bool(os.getenv("GLM_THINKING_ENABLED", "0"))
+
+    try:
+        client = Client(space)
+        result = client.predict(
+            msg=text,
+            sys_prompt=sys_prompt,
+            thinking_enabled=thinking_enabled,
+            temperature=temperature,
+            api_name=api_name,
+        )
+        content = _extract_clean_assistant_text(result).strip()
+        return content if content else prompt
+    except Exception as e:
+        _warn(f"GLM infer filed: {type(e).__name__}")
+        return prompt
+
+
+# --- Internal helpers ---------------------------------------------------------
+
+
+def _warn(msg: str) -> None:
+    print(f"[llm_refiner_glm] {msg}", file=sys.stderr)
+
+
+def _load_env() -> None:
+    """
+    Attempt to load .env from the project root (best-effort).
+    """
+    env_path = get_project_root() / ".env"
+    try:
+        from dotenv import load_dotenv  # type: ignore
+        load_dotenv(dotenv_path=env_path)
+    except Exception:
+        # If python-dotenv isn't installed, silently rely on existing process env
+        pass
+
+
+def _coerce_bool(val: Any) -> bool:
+    s = str(val).strip().lower()
+    return s in {"1", "true", "yes", "on"}
+
+
+def _coerce_float(val: Any, default: float) -> float:
+    try:
+        return float(val)
+    except Exception:
+        return default
+
+
+def _clean_html_to_text(html_content: Any) -> str:
+    """
+    Convert HTML (possibly with entities) to plain text with minimal structure preserved via newlines.
+    Mirrors the robust cleaning approach used in test_gradio.py.
+    """
+    if not isinstance(html_content, str):
+        html_content = str(html_content)
+    # Unescape entities first to normalize both raw and escaped HTML
+    text = html.unescape(html_content)
+    # Convert common block/line-break tags to newlines
+    text = re.sub(r"(?is)<br\s*/?>|</p>|</div>", "\n", text)
+    text = re.sub(r"(?is)<(script|style)\b.*?>.*?</\1>", "", text)
+    # Remove all remaining HTML tags (raw)
+    text = re.sub(r"(?s)<[^>]+>", "", text)
+    # Normalize whitespace: CRLF->LF, but don't remove empty lines or collapse whitespace
+    text = text.replace("\r\n", "\n").replace("\r", "\n")
+    # Preserve all lines including empty ones and whitespace
+    lines = text.splitlines()
+    # Join lines with single newlines, but keep existing whitespace
+    return "\n".join(lines)
+
+
+def _extract_clean_assistant_text(result: Any) -> str:
+    """
+    Extract 'assistant' messages from a Gradio chat result and return plain text without HTML.
+
+    Supports result formats:
+      - (messages, *rest)
+      - messages
+    Each message is a dict with 'role' and 'content'.
+    """
+    # Normalize to a list of messages
+    if isinstance(result, tuple) and result:
+        messages = result[0]
+    else:
+        messages = result
+
+    clean_segments: List[str] = []
+    if isinstance(messages, list):
+        for m in messages:
+            if isinstance(m, dict) and m.get("role") == "assistant":
+                content = m.get("content", "")
+                clean_segments.append(_clean_html_to_text(content))
+
+    if not clean_segments:
+        return ""
+    return "\n\n".join(s for s in clean_segments if s)

install.sh

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+#!/bin/bash
+uv venv .venv --python=3.12
+source .venv/bin/activate
+uv pip install -r requirements.txt

open_ai.py

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+import os
+
+from openai import OpenAI
+from dotenv import load_dotenv
+
+load_dotenv()
+
+api_key = os.getenv("OPENAI_API_KEY","")
+url = os.getenv("OPENAI_API_URL","https://api.openai.com/v1/")
+model = os.getenv("OPENAI_API_MODEL","openai/gpt-oss-120b")
+client = OpenAI(
+    api_key=api_key,
+    base_url=url
+)
+def run_openai(prompt: str, sys_prompt: str) -> str:
+    try:
+        response = client.chat.completions.create(
+            model=model,
+            max_tokens=5000,
+            temperature=1,
+            presence_penalty=0,
+            top_p=0.95,
+            messages=[
+                {
+                    "role": "system",
+                    "content": sys_prompt
+                },
+                {
+                    "role": "user",
+                    "content": prompt
+                }
+            ]
+        )
+    except Exception as e:
+        return f"LLM infer filed: {type(e).__name__}"
+    return response.choices[0].message.content

paths.py

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+from __future__ import annotations
+
+from pathlib import Path
+
+__all__ = ["get_project_root", "get_data_dir", "data_file"]
+
+
+def get_project_root() -> Path:
+    """Return the absolute path to the repository root (directory containing this file)."""
+    return Path(__file__).resolve().parent
+
+
+def get_data_dir() -> Path:
+    """Return the absolute path to the data directory under the repository root."""
+    return get_project_root() / "data"
+
+
+def data_file(name: str) -> Path:
+    """Return the absolute path to a file inside the data directory."""
+    return get_data_dir() / name

prompt_loader.py

@@ -0,0 +1,25 @@
+from base64 import b64decode
+from cryptography.fernet import Fernet
+from dotenv import load_dotenv
+import os
+import prompts_enc
+
+load_dotenv()
+
+def get_prompt(name: str) -> str:
+    """Возвращает раскодированный промпт по имени."""
+    key = os.getenv("PROMPT_KEY")
+    if not key:
+        raise RuntimeError("PROMPT_KEY отсутствует в переменных окружения")
+
+    if not hasattr(prompts_enc, name):
+        raise KeyError(f"Промпт '{name}' не найден")
+
+    fernet = Fernet(key.encode())
+    encoded = getattr(prompts_enc, name)
+    decoded = fernet.decrypt(b64decode(encoded)).decode()
+    return decoded
+
+
+if __name__ == "__main__":
+    print(get_prompt("PROMPT_STYLE"))

prompts_enc.py

@@ -0,0 +1,7 @@
+# ⚠️ AUTO-GENERATED — DO NOT EDIT
+
+PROMPT_STYLE = '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'
+PROMPT_TEXT = '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'
+PROMPT_TEXT2 = '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'
+SYSPROMPT_STYLE = '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'
+SYSPROMPT_TEXT = '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'

requirements.txt

@@ -0,0 +1,6 @@
+gradio
+gradio_client
+openai
+python-dotenv
+requests
+cryptography