BioVibe_v2

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kevcipher commited on Apr 18

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.gitattributes +18 -0
Dockerfile +24 -0
__pycache__/main.cpython-311.pyc +0 -0
__pycache__/main.cpython-313.pyc +0 -0
biovibe_brain.pth +3 -0
index.html +219 -0
main.py +193 -0
mapping_dict.pkl +3 -0
music/ai_vibe_101.mid +0 -0
music/ai_vibe_101.wav +3 -0
music/ai_vibe_107.mid +0 -0
music/ai_vibe_107.wav +3 -0
music/ai_vibe_115.mid +0 -0
music/ai_vibe_115.wav +3 -0
music/ai_vibe_75.mid +0 -0
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music/ai_vibe_92.mid +0 -0
music/ai_vibe_92.wav +3 -0
notes_corpus.pkl +3 -0
requirements.txt +6 -0
soundfonts/Piano.SF2 +3 -0
stems/pad_ambient.wav +3 -0
stems/piano.wav +3 -0
stems/rain.wav +3 -0
stems/violin.wav +3 -0

.gitattributes CHANGED Viewed

@@ -33,3 +33,21 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text

 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
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+music/ai_vibe_86.wav filter=lfs diff=lfs merge=lfs -text
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+music/ai_vibe_90.wav filter=lfs diff=lfs merge=lfs -text
+music/ai_vibe_92.wav filter=lfs diff=lfs merge=lfs -text
+soundfonts/Piano.SF2 filter=lfs diff=lfs merge=lfs -text
+stems/pad_ambient.wav filter=lfs diff=lfs merge=lfs -text
+stems/piano.wav filter=lfs diff=lfs merge=lfs -text
+stems/rain.wav filter=lfs diff=lfs merge=lfs -text
+stems/violin.wav filter=lfs diff=lfs merge=lfs -text

Dockerfile ADDED Viewed

	@@ -0,0 +1,24 @@

+# 1. Chọn hệ điều hành gốc là Linux với Python 3.10
+FROM python:3.10-slim
+# 2. Cài đặt "nhạc công" FluidSynth sâu vào hệ điều hành
+RUN apt-get update && apt-get install -y \
+    fluidsynth \
+    && rm -rf /var/lib/apt/lists/*
+# 3. Tạo không gian làm việc
+WORKDIR /app
+# 4. Copy file danh sách thư viện và cài đặt
+COPY requirements.txt .
+# Cài đặt PyTorch bản CPU để tiết kiệm dung lượng và tránh lỗi
+RUN pip install --no-cache-dir -r requirements.txt --extra-index-url https://download.pytorch.org/whl/cpu
+# 5. Bê toàn bộ code của bạn bỏ vào container
+COPY . .
+# 6. Mở cửa số 7860 (Hugging Face bắt buộc dùng port này)
+EXPOSE 7860
+# 7. Ra lệnh bật server FastAPI khi hệ thống chạy
+CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "7860"]

__pycache__/main.cpython-311.pyc ADDED Viewed

Binary file (8.92 kB). View file

__pycache__/main.cpython-313.pyc ADDED Viewed

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biovibe_brain.pth ADDED Viewed

	@@ -0,0 +1,3 @@

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+oid sha256:c7ca670b7a2de2c65271cf0d021381f1ecfd4f894292c818257a1f7edc0a7a46
+size 15971033

index.html ADDED Viewed

	@@ -0,0 +1,219 @@

+<!DOCTYPE html>
+<html lang="vi">
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>Bio-Vibe Web</title>
+    <link rel="icon" href="data:,">
+    <style>
+        body {
+            font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif;
+            background-color: #1a1a2e;
+            color: #e94560;
+            display: flex;
+            flex-direction: column;
+            align-items: center;
+            justify-content: center;
+            height: 100vh;
+            margin: 0;
+        }
+        .container {
+            background-color: #16213e;
+            padding: 40px;
+            border-radius: 15px;
+            text-align: center;
+            box-shadow: 0 10px 30px rgba(0,0,0,0.5);
+        }
+        h1 { color: #fff; margin-bottom: 5px; }
+        p { color: #a2a2bd; margin-bottom: 30px; }
+        #bpm-display {
+            font-size: 80px;
+            font-weight: bold;
+            margin: 20px 0;
+            text-shadow: 0 0 15px #e94560;
+            transition: color 0.3s ease;
+        }
+        @keyframes pulse {
+            0% { transform: scale(1); opacity: 1; }
+            50% { transform: scale(1.05); opacity: 0.8; }
+            100% { transform: scale(1); opacity: 1; }
+        }
+        .button-group {
+            display: flex;
+            justify-content: center;
+            flex-wrap: wrap;
+            gap: 15px;
+            max-width: 600px;
+        }
+        button {
+            background-color: #0f3460;
+            color: white;
+            border: none;
+            padding: 15px 25px;
+            font-size: 16px;
+            border-radius: 8px;
+            cursor: pointer;
+            transition: 0.3s;
+            font-weight: bold;
+        }
+        button:hover { background-color: #4ecca3; color: #1a1a2e; }
+        button:disabled { background-color: #333; cursor: not-allowed; color: #777; }
+        /* CSS riêng cho nút Dừng nhạc */
+        #btn-stop { background-color: #8b0000; }
+        #btn-stop:hover { background-color: #ff4d4d; color: white; }
+        #btn-stop:disabled { background-color: #333; }
+        #status { margin-top: 20px; color: #4ecca3; font-style: italic; font-size: 14px;}
+    </style>
+</head>
+<body>
+    <div class="container">
+        <h1>Bio-Vibe 🎧</h1>
+        <p>Âm nhạc trị liệu AI theo Nhịp tim</p>
+        <div id="bpm-display">-- BPM</div>
+        <div class="button-group">
+            <button id="btn-connect">1. Bắt tay Đồng hồ</button>
+            <button id="btn-generate">2. Sinh nhạc AI</button>
+            <button id="btn-stop" disabled>3. Dừng nhạc</button>
+        </div>
+        <div id="status">Chưa kết nối... Mở nRF Connect trên điện thoại để chuẩn bị!</div>
+    </div>
+    <script>
+        let currentBpm = 0;
+        let currentAudio = null; // Biến toàn cục để quản lý file âm thanh
+        const bpmDisplay = document.getElementById('bpm-display');
+        const statusText = document.getElementById('status');
+        const btnConnect = document.getElementById('btn-connect');
+        const btnGenerate = document.getElementById('btn-generate');
+        const btnStop = document.getElementById('btn-stop');
+        // ==========================================
+        // 1. BLUETOOTH LOGIC
+        // ==========================================
+        btnConnect.addEventListener('click', async () => {
+            try {
+                statusText.innerText = "Đang mở máy quét Bluetooth...";
+                const device = await navigator.bluetooth.requestDevice({
+                    acceptAllDevices: true,
+                    optionalServices: ['heart_rate']
+                });
+                statusText.innerText = `Đã chọn: ${device.name}. Đang kết nối...`;
+                const server = await device.gatt.connect();
+                const service = await server.getPrimaryService('heart_rate');
+                const characteristic = await service.getCharacteristic('heart_rate_measurement');
+                await characteristic.startNotifications();
+                characteristic.addEventListener('characteristicvaluechanged', handleHeartRateData);
+                statusText.innerText = "Kết nối thành công! Đang đợi nhịp tim truyền lên...";
+                btnConnect.innerText = "✓ Đã kết nối Bluetooth";
+                btnConnect.style.backgroundColor = "#4ecca3";
+                btnConnect.style.color = "#1a1a2e";
+            } catch (error) {
+                console.error("Bluetooth Error:", error);
+                statusText.innerText = "Hủy kết nối hoặc lỗi thiết bị!";
+                statusText.style.color = "#ff4d4d";
+            }
+        });
+        function handleHeartRateData(event) {
+            const value = event.target.value;
+            const flags = value.getUint8(0);
+            if ((flags & 0x01) === 0) {
+                currentBpm = value.getUint8(1);
+            } else {
+                currentBpm = value.getUint16(1, true);
+            }
+            bpmDisplay.innerText = `${currentBpm} BPM`;
+            bpmDisplay.style.color = "#e94560";
+            statusText.innerText = "Đang đọc nhịp tim thành công. Sẵn sàng tạo nhạc!";
+            statusText.style.color = "#4ecca3";
+        }
+        // ==========================================
+        // 2. TẠO VÀ PHÁT NHẠC
+        // ==========================================
+        btnGenerate.addEventListener('click', async () => {
+            if (currentBpm === 0) {
+                alert("Bạn chưa kết nối Bluetooth hoặc chưa gửi số nhịp tim từ nRF Connect!");
+                return;
+            }
+            // TÍNH NĂNG MỚI: Tắt ngay bài nhạc cũ (nếu có) trước khi tạo bài mới
+            if (currentAudio) {
+                currentAudio.pause();
+                currentAudio.currentTime = 0; // Tua lại từ đầu
+                bpmDisplay.style.animation = "none";
+            }
+            statusText.innerText = `Đang gửi ${currentBpm} BPM cho bộ não AI xử lý...`;
+            btnGenerate.innerText = "AI đang sáng tác...";
+            btnGenerate.disabled = true;
+            btnStop.disabled = true;
+            try {
+                const response = await fetch('/generate-vibe', {
+                    method: 'POST',
+                    headers: { 'Content-Type': 'application/json' },
+                    body: JSON.stringify({ bpm: currentBpm })
+                });
+                const data = await response.json();
+                if (data.status === "success") {
+                    statusText.innerText = "Sáng tác xong! Đang phát nhạc 🎵";
+                    // Gắn file nhạc mới vào biến toàn cục
+                    currentAudio = new Audio(data.audio_url);
+                    currentAudio.play();
+                    bpmDisplay.style.animation = "pulse 1s infinite";
+                    btnStop.disabled = false; // Mở khóa nút Dừng
+                    // Xử lý khi nhạc tự chạy hết
+                    currentAudio.onended = () => {
+                        bpmDisplay.style.animation = "none";
+                        statusText.innerText = "Bản nhạc đã kết thúc. Sẵn sàng tạo trải nghiệm mới!";
+                        btnStop.disabled = true;
+                    };
+                } else {
+                    statusText.innerText = `Lỗi từ Server: ${data.message}`;
+                }
+            } catch (error) {
+                console.error("API Error:", error);
+                statusText.innerText = "Mất kết nối với máy chủ AI!";
+            } finally {
+                btnGenerate.innerText = "2. Sinh nhạc AI";
+                btnGenerate.disabled = false;
+            }
+        });
+        // ==========================================
+        // 3. DỪNG NHẠC THỦ CÔNG
+        // ==========================================
+        btnStop.addEventListener('click', () => {
+            if (currentAudio) {
+                currentAudio.pause(); // Cắt âm thanh
+                currentAudio.currentTime = 0; // Xóa cache phát
+                bpmDisplay.style.animation = "none"; // Tắt nhấp nháy
+                statusText.innerText = "Đã dừng phát nhạc.";
+                btnStop.disabled = true; // Khóa lại nút dừng
+            }
+        });
+    </script>
+</body>
+</html>

main.py ADDED Viewed

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+from fastapi import FastAPI, Request
+from fastapi.staticfiles import StaticFiles
+from fastapi.responses import FileResponse
+from pydantic import BaseModel
+from pydub import AudioSegment
+import torch
+import torch.nn as nn
+import pickle
+import numpy as np
+from music21 import note, chord, stream, instrument
+import os
+os.environ['KMP_DUPLICATE_LIB_OK'] = 'True'
+import random
+import subprocess
+app = FastAPI(title="Bio-Vibe AI Inference")
+os.makedirs("music", exist_ok=True)
+app.mount("/music", StaticFiles(directory="music"), name="music")
+@app.get("/")
+async def serve_frontend():
+    return FileResponse("index.html")
+class HeartRateData(BaseModel):
+    bpm: int
+# ==========================================
+# 1. KHÔI PHỤC "BỘ NÃO" (PYTORCH MODEL)
+# ==========================================
+# Cấu trúc class phải y hệt lúc train
+class BioVibeAI(nn.Module):
+    def __init__(self, vocab_size, embed_size=256, hidden_size=512, num_layers=2):
+        super(BioVibeAI, self).__init__()
+        self.embedding = nn.Embedding(vocab_size, embed_size)
+        self.lstm = nn.LSTM(embed_size, hidden_size, num_layers, batch_first=True)
+        self.fc = nn.Linear(hidden_size, vocab_size)
+    def forward(self, x):
+        embedded = self.embedding(x)
+        out, _ = self.lstm(embedded)
+        out = self.fc(out[:, -1, :])
+        return out
+# Nạp từ điển
+with open('mapping_dict.pkl', 'rb') as f:
+    int_to_note = pickle.load(f)
+note_to_int = {note: number for number, note in int_to_note.items()}
+vocab_size = len(int_to_note)
+# Load trọng số mô hình
+device = torch.device("cpu") # Server chạy CPU cho nhẹ
+model = BioVibeAI(vocab_size=vocab_size)
+model.load_state_dict(torch.load("biovibe_brain.pth", map_location=device))
+model.eval() # Chuyển sang chế độ suy luận
+# Nạp kho dữ liệu cũ để lấy Seed (đoạn nhạc mồi)
+with open('notes_corpus.pkl', 'rb') as f:
+    corpus = pickle.load(f)
+# ==========================================
+# 2. HÀM SÁNG TÁC BẰNG NHIỆT ĐỘ (TEMPERATURE)
+# ==========================================
+def generate_ai_midi(bpm: int, output_file: str, num_notes: int = 60):
+    # Logic phản hồi sinh học
+    if bpm > 80:
+        temperature = 0.7  # An toàn, ổn định
+        base_offset = 1.0  # Nốt đánh chậm
+    else:
+        temperature = 1.0  # Bay bổng, ngẫu hứng
+        base_offset = 0.5  # Nốt đánh nhanh hơn một chút
+    # Chọn bừa 100 nốt từ kho dữ liệu để làm "mồi" cho AI
+    start_idx = random.randint(0, len(corpus) - 100)
+    seed_sequence = corpus[start_idx:start_idx + 100]
+    pattern = [note_to_int[char] for char in seed_sequence]
+    generated_notes = []
+    print(f"Đang sáng tác với Temp={temperature}...")
+    # AI bắt đầu dự đoán
+    for i in range(num_notes):
+        sequence_tensor = torch.tensor([pattern], dtype=torch.long).to(device)
+        with torch.no_grad():
+            prediction = model(sequence_tensor)
+        # ÁP DỤNG TEMPERATURE
+        prediction = prediction / temperature
+        probabilities = torch.softmax(prediction, dim=1).numpy()[0]
+        # Chọn nốt dựa trên phân phối xác suất
+        index = np.random.choice(len(probabilities), p=probabilities)
+        result_note = int_to_note[index]
+        generated_notes.append(result_note)
+        # Cập nhật cửa sổ trượt (thêm nốt mới, xóa nốt cũ nhất)
+        pattern.append(index)
+        pattern = pattern[1:]
+    # ==========================================
+    # 3. CHUYỂN NGỮ AI THÀNH FILE MIDI
+    # ==========================================
+    offset = 0
+    output_stream = stream.Stream()
+    output_stream.append(instrument.Piano()) # Chọn nhạc cụ
+    for pattern_note in generated_notes:
+        # Nếu là hợp âm (có dấu chấm, ví dụ '4.7.11')
+        try:
+            # Xử lý Hợp âm
+            if ('.' in pattern_note) or pattern_note.isdigit():
+                notes_in_chord = pattern_note.split('.')
+                chord_notes = []
+                for current_note in notes_in_chord:
+                    n = note.Note(int(current_note))
+                    # --- CAN THIỆP TẠI ĐÂY ---
+                    if n.pitch.ps > 72:  # Nếu nốt cao hơn C5
+                        n.pitch.ps -= 12  # Hạ xuống 1 quãng tám
+                    n.volume.velocity = random.randint(50, 70)  # Giảm độ đanh (Velocity)
+                    # -------------------------
+                    chord_notes.append(n)
+                new_obj = chord.Chord(chord_notes)
+            # Xử lý Nốt đơn
+            else:
+                new_obj = note.Note(pattern_note)
+                # --- CAN THIỆP TẠI ĐÂY ---
+                if new_obj.pitch.ps > 72:
+                    new_obj.pitch.ps -= 12
+                new_obj.volume.velocity = random.randint(50, 70)
+                # -------------------------
+            new_obj.offset = offset
+            output_stream.append(new_obj)
+            offset += base_offset
+        except:
+            continue
+    output_stream.write('midi', fp=output_file)
+# ==========================================
+# 4. API ENDPOINT
+# ==========================================
+# Low-pass filter
+def apply_audio_filters(wav_path):
+    # Đọc file âm thanh vừa render
+    sound = AudioSegment.from_wav(wav_path)
+    # 1. Áp dụng Low Pass Filter tại 2000Hz (Loại bỏ tiếng rít cao)
+    sound = sound.low_pass_filter(2000)
+    # 2. Fade in/Fade out nhẹ để âm thanh không bị ngắt đột ngột (tăng ADSR mượt)
+    sound = sound.fade_in(1000).fade_out(2000)
+    # Xuất đè lên file cũ
+    sound.export(wav_path, format="wav")
+@app.post("/generate-vibe")
+async def generate_vibe(data: HeartRateData, request: Request):
+    # Đường dẫn file
+    midi_file = f"music/ai_vibe_{data.bpm}.mid"
+    wav_file = f"music/ai_vibe_{data.bpm}.wav"
+    soundfont_path = "soundfonts/Piano.sf2" # Đường dẫn tới file sf2 bạn vừa tải
+    # Bước 1: PyTorch sinh ra cấu trúc nốt nhạc (MIDI)
+    # Bước 1: PyTorch sinh ra cấu trúc nốt nhạc (MIDI)
+    generate_ai_midi(data.bpm, midi_file)
+    # Bước 2: Tự viết lệnh Render bằng Subprocess chuẩn xác cho FluidSynth 2.5+
+    print("Đang render MIDI thành âm thanh Piano...")
+    try:
+        subprocess.run([
+            "fluidsynth",
+            "-ni",               # Chạy ẩn không cần giao diện
+            "-r", "44100",       # Chất lượng Sample rate
+            "-F", wav_file,      # Xuất ra file thay vì phát ra loa laptop!
+            soundfont_path,      # Dàn nhạc (Soundfont)
+            midi_file            # Kịch bản (MIDI)
+        ], check=True)
+        # --- BƯỚC MỚI: LỌC ÂM THANH NHỨC ÓC ---
+        apply_audio_filters(wav_file)
+        # -------------------------------------
+    except Exception as e:
+        print(f"Lỗi khi render âm thanh: {e}")
+        return {"status": "error", "message": "Render failed"}
+    server_url = str(request.base_url).rstrip("/")
+    # Bước 3: Trả về link file âm thanh xịn xò cho App Flutter
+    return {"status": "success", "audio_url": f"{server_url}/{wav_file}"}

mapping_dict.pkl ADDED Viewed

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+size 4327

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