first commit

utils/audio.py

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+"""
+NovaAi – TTS-Engine-Hub
+utils/audio.py
+Version: v0.0.1
+
+Description:
+  Audio processing utilities: concat, merging chunks, etc.
+
+Author: Abby (ChatGPT)
+Date: 2025-07-23
+Canvas: utils/audio.py
+"""
+
+import tempfile
+import os
+import ffmpeg
+import shutil
+
+def check_ffmpeg():
+    """Check if ffmpeg is installed and available in the system's PATH."""
+    return shutil.which("ffmpeg") is not None
+
+def concat_audio(files, fmt):
+    """
+    Concatenate a list of audio files into a single file of the given format.
+    Supports: wav, ogg, mp3
+    """
+    if len(files) == 1:
+        # If there's only one file, just return it, no cleanup needed here.
+        return files[0]
+
+    # Securely create a temporary file for the output
+    with tempfile.NamedTemporaryFile(suffix=f'.{fmt}', prefix="chunked_", delete=False) as temp_output_file:
+        output_file_path = temp_output_file.name
+
+    try:
+        if fmt == "wav":
+            import wave
+            data = []
+            params = None
+            for f in files:
+                with wave.open(f, 'rb') as wf:
+                    if params is None:
+                        params = wf.getparams()
+                    data.append(wf.readframes(wf.getnframes()))
+            with wave.open(output_file_path, 'wb') as wf:
+                wf.setparams(params)
+                for d in data:
+                    wf.writeframes(d)
+        else:
+            if not check_ffmpeg():
+                raise RuntimeError("ffmpeg not found. Please install ffmpeg and ensure it is in your PATH.")
+
+            with tempfile.NamedTemporaryFile("w", delete=False) as tf:
+                list_file_path = tf.name
+                for f in files:
+                    tf.write(f"file '{os.path.abspath(f)}'\\n")
+                tf.flush()
+            
+            try:
+                (
+                    ffmpeg
+                    .input(list_file_path, format='concat', safe=0)
+                    .output(output_file_path, acodec='copy')
+                    .run(overwrite_output=True, quiet=True)
+                )
+            finally:
+                os.unlink(list_file_path)
+
+    finally:
+        # Clean up the input chunk files
+        for f in files:
+            if os.path.exists(f):
+                os.remove(f)
+
+    return output_file_path

utils/cache.py

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+"""
+NovaAi – TTS-Engine-Hub
+utils/cache.py
+Version: v0.0.1
+
+Description:
+  Caching utilities for TTS requests (cache key generation, etc).
+
+Author: Abby (ChatGPT)
+Date: 2025-07-23
+Canvas: utils/cache.py
+"""
+
+import hashlib
+
+# Für die API: Wichtig! req muss mindestens die Felder .text, .engine, .model, .speaker, .format, .chunking haben.
+def build_cache_key(req) -> str:
+    """
+    Build a cache key from all relevant TTS request parameters.
+    """
+    data = f"{req.text}|{req.engine}|{req.model}|{req.speaker}|{req.format}|{getattr(req, 'chunking', False)}"
+    return hashlib.sha256(data.encode()).hexdigest()

utils/text.py

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+"""
+NovaAi – TTS-Engine-Hub
+utils/text.py
+Version: v0.0.1
+
+Description:
+  Text processing utilities: chunking, splitting, etc.
+
+Author: Abby (ChatGPT)
+Date: 2025-07-23
+Canvas: utils/text.py
+"""
+
+def chunk_text(text, maxlen=250):
+    """
+    Split text into chunks of roughly maxlen (split at sentence boundaries if possible).
+    """
+    import re
+    sentences = re.split(r'([.!?]\s)', text)
+    chunks = []
+    buf = ""
+    for s in sentences:
+        if len(buf) + len(s) > maxlen:
+            if buf:
+                chunks.append(buf.strip())
+                buf = ""
+        buf += s
+    if buf.strip():
+        chunks.append(buf.strip())
+    return [c for c in chunks if c.strip()]