Delete destination-folder-name

destination-folder-name/Dockerfile

@@ -1,43 +0,0 @@
-FROM python:3.11-slim-bookworm
-
-ENV DEBIAN_FRONTEND=noninteractive \
-    PYTHONUNBUFFERED=1 \
-    PYTHONDONTWRITEBYTECODE=1 \
-    PIP_NO_CACHE_DIR=1 \
-    HF_HOME=/opt/models \
-    TRANSFORMERS_CACHE=/opt/models \
-    HUGGINGFACE_HUB_CACHE=/opt/models
-
-WORKDIR /code
-
-RUN apt-get update && apt-get install -y --no-install-recommends \
-        git \
-        wget \
-        curl \
-        libsndfile1 \
-        ffmpeg \
-        gcc \
-        g++ \
-        build-essential \
-        python3-dev \
-    && apt-get clean && rm -rf /var/lib/apt/lists/*
-
-COPY requirements.txt .
-RUN pip install --no-cache-dir -r requirements.txt
-
-# Pre-download model
-RUN python - <<EOF
-from huggingface_hub import snapshot_download
-snapshot_download(
-    repo_id="LiquidAI/LFM2.5-Audio-1.5B",
-    local_dir="/opt/models/LiquidAI/LFM2.5-Audio-1.5B",
-    local_dir_use_symlinks=False
-)
-print("Model downloaded successfully.")
-EOF
-
-COPY . .
-
-EXPOSE 7860
-
-CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "7860"]

destination-folder-name/app/main.py

@@ -1,179 +0,0 @@
-
-
-import asyncio
-import json
-import torch
-import numpy as np
-from fastapi import FastAPI, WebSocket, WebSocketDisconnect
-from pydantic import BaseModel
-from liquid_audio import (
-    LFM2AudioModel,
-    LFM2AudioProcessor,
-    ChatState,
-)
-
-
-HF_REPO = "LiquidAI/LFM2.5-Audio-1.5B"
-DEVICE = "cuda" if torch.cuda.is_available() else "cpu"
-SAMPLE_RATE = 24_000
-CHUNK_SIZE = 6
-
-if DEVICE == "cuda" and torch.cuda.is_bf16_supported():
-    DTYPE = torch.bfloat16
-else:
-    DTYPE = torch.float32
-
-torch.backends.cuda.matmul.allow_tf32 = True
-
-
-
-
-
-processor = LFM2AudioProcessor.from_pretrained(HF_REPO)
-model = LFM2AudioModel.from_pretrained(
-    HF_REPO,
-    torch_dtype=DTYPE,
-).to(DEVICE).eval()
-
-print(f"[BOOT]  LFM2.5 Loaded on {DEVICE}")
-
-
-
-
-
-app = FastAPI(title="LFM2.5 WebSocket TTS", version="2.0.0")
-
-
-# WAV HEADER
-
-
-def wav_header(sample_rate: int, channels: int = 1, bits: int = 16) -> bytes:
-    byte_rate = sample_rate * channels * bits // 8
-    block_align = channels * bits // 8
-    return (
-        b"RIFF"
-        + (b"\xff\xff\xff\xff")
-        + b"WAVEfmt "
-        + (16).to_bytes(4, "little")
-        + (1).to_bytes(2, "little")
-        + channels.to_bytes(2, "little")
-        + sample_rate.to_bytes(4, "little")
-        + byte_rate.to_bytes(4, "little")
-        + block_align.to_bytes(2, "little")
-        + bits.to_bytes(2, "little")
-        + b"data"
-        + (b"\xff\xff\xff\xff")
-    )
-
-
-# STREAM CORE
-
-
-async def stream_lfm_tts(websocket: WebSocket, text: str):
-    chat = ChatState(processor)
-
-    chat.new_turn("system")
-    chat.add_text("Respond with interleaved text and audio.")
-    chat.end_turn()
-
-    chat.new_turn("user")
-    chat.add_text(text)
-    chat.end_turn()
-
-    chat.new_turn("assistant")
-
-    await websocket.send_bytes(wav_header(SAMPLE_RATE))
-
-    audio_buffer = []
-    stop_flag = False
-
-    async def listen_for_stop():
-        nonlocal stop_flag
-        try:
-            while True:
-                msg = await websocket.receive_text()
-                data = json.loads(msg)
-                if data.get("type") == "stop":
-                    stop_flag = True
-                    break
-        except:
-            stop_flag = True
-
-    listener_task = asyncio.create_task(listen_for_stop())
-
-    try:
-        with torch.inference_mode():
-            for token in model.generate_interleaved(
-                **chat,
-                max_new_tokens=4096,
-                audio_temperature=0.8,
-                audio_top_k=4,
-            ):
-                if stop_flag:
-                    break
-
-                if token.numel() == 1:
-                    continue
-
-                audio_buffer.append(token)
-
-                if len(audio_buffer) >= CHUNK_SIZE:
-                    audio_codes = (
-                        torch.stack(audio_buffer, dim=1)
-                        .unsqueeze(0)
-                        .to(DEVICE)
-                    )
-
-                    waveform = processor.decode(audio_codes)
-                    waveform = waveform.squeeze().cpu().numpy()
-                    waveform = np.clip(waveform, -1.0, 1.0)
-                    audio_int16 = (waveform * 32767.0).astype(np.int16)
-
-                    await websocket.send_bytes(audio_int16.tobytes())
-                    audio_buffer.clear()
-
-        # flush
-        if not stop_flag and len(audio_buffer) > 1:
-            audio_codes = (
-                torch.stack(audio_buffer[:-1], dim=1)
-                .unsqueeze(0)
-                .to(DEVICE)
-            )
-            waveform = processor.decode(audio_codes)
-            waveform = waveform.squeeze().cpu().numpy()
-            waveform = np.clip(waveform, -1.0, 1.0)
-            audio_int16 = (waveform * 32767.0).astype(np.int16)
-
-            await websocket.send_bytes(audio_int16.tobytes())
-
-        await websocket.send_text(json.dumps({"type": "done"}))
-
-    finally:
-        listener_task.cancel()
-
-
-# WEBSOCKET ENDPOINT
-
-
-@app.websocket("/ws/tts")
-async def websocket_tts(websocket: WebSocket):
-    await websocket.accept()
-
-    try:
-        while True:
-            message = await websocket.receive_text()
-            payload = json.loads(message)
-
-            if payload.get("type") == "start":
-                text = payload.get("text", "").strip()
-                if not text:
-                    await websocket.send_text(json.dumps({
-                        "type": "error",
-                        "message": "Text is empty"
-                    }))
-                    continue
-
-                await stream_lfm_tts(websocket, text)
-
-    except WebSocketDisconnect:
-        print("Client disconnected")

destination-folder-name/requirements.txt

@@ -1,13 +0,0 @@
-torchaudio
-soundfile
-accelerate
-huggingface_hub==0.23.2
-sentencepiece
-tokenizers
-fastapi==0.110.0
-uvicorn[standard]==0.27.1
-torch==2.1.2
-numpy==1.26.4
-pydantic==2.6.4
-transformers==4.40.2
-liquid-audio