Create app.py

app.py

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+# filename: elegant_arabic_transcriber.py
+
+import streamlit as st
+import nemo.collections.asr as nemo_asr
+import soundfile as sf
+import tempfile
+import os
+from pydub import AudioSegment
+import time
+
+# Custom CSS for gloomy elegant styling
+st.markdown("""
+    <style>
+        :root {
+            --primary: #3a506b;
+            --secondary: #5bc0be;
+            --accent: #e55934;
+            --background: #1c2541;
+            --card: #0b132b;
+            --text: #e0e0e0;
+            --text-secondary: #b8b8b8;
+        }
+        
+        .stApp {
+            background-color: var(--background);
+            color: var(--text);
+        }
+        
+        .main .block-container {
+            max-width: 1200px;
+            padding: 2rem 3rem;
+        }
+        
+        .card {
+            background-color: var(--card);
+            border-radius: 8px;
+            padding: 1.5rem;
+            margin-bottom: 1.5rem;
+            border-left: 3px solid var(--secondary);
+        }
+        
+        .header {
+            background: linear-gradient(135deg, #0b132b, #1c2541);
+            color: white;
+            padding: 2rem 3rem;
+            margin: -2rem -3rem 2rem -3rem;
+            border-bottom: 1px solid rgba(91, 192, 190, 0.2);
+        }
+        
+        .stButton>button {
+            background: var(--primary);
+            color: white;
+            border: none;
+            border-radius: 6px;
+            padding: 0.7rem 1.5rem;
+            font-weight: 500;
+            transition: all 0.2s ease;
+            border: 1px solid rgba(91, 192, 190, 0.3);
+        }
+        
+        .stButton>button:hover {
+            background: #2c3e5a;
+            color: white;
+        }
+        
+        .stDownloadButton>button {
+            background: var(--secondary);
+            color: #0b132b;
+        }
+        
+        .stDownloadButton>button:hover {
+            background: #4aa8a6;
+            color: #0b132b;
+        }
+        
+        .transcript-container {
+            background-color: rgba(11, 19, 43, 0.7);
+            border-radius: 8px;
+            padding: 1.5rem;
+            margin-top: 1rem;
+            border: 1px solid rgba(91, 192, 190, 0.1);
+        }
+        
+        .transcript-box {
+            background-color: transparent;
+            font-size: 1.1rem;
+            line-height: 1.8;
+            min-height: 150px;
+            direction: rtl;
+            font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif;
+            color: var(--text);
+            white-space: pre-wrap;
+        }
+        
+        .stats {
+            display: flex;
+            gap: 1rem;
+            margin-top: 1rem;
+        }
+        
+        .stat-box {
+            background-color: rgba(58, 80, 107, 0.5);
+            padding: 0.8rem 1rem;
+            border-radius: 6px;
+            flex: 1;
+            min-width: 100px;
+            text-align: center;
+            border: 1px solid rgba(91, 192, 190, 0.1);
+        }
+        
+        .stat-value {
+            font-size: 1.2rem;
+            font-weight: bold;
+            color: var(--secondary);
+        }
+        
+        .progress-container {
+            height: 6px;
+            background-color: rgba(58, 80, 107, 0.5);
+            border-radius: 3px;
+            margin: 1.5rem 0;
+            overflow: hidden;
+        }
+        
+        .progress-bar {
+            height: 100%;
+            background: linear-gradient(90deg, var(--secondary), #4aa8a6);
+            border-radius: 3px;
+            transition: width 0.4s ease;
+        }
+        
+        h1, h2, h3 {
+            color: var(--text) !important;
+        }
+        
+        .file-uploader {
+            border: 2px dashed var(--secondary);
+            border-radius: 8px;
+            padding: 2rem;
+            text-align: center;
+            background-color: rgba(91, 192, 190, 0.05);
+            margin-bottom: 1.5rem;
+        }
+        
+        .feature-icon {
+            color: var(--secondary);
+            margin-right: 0.5rem;
+        }
+        
+        .stSpinner > div {
+            border-color: var(--secondary) transparent transparent transparent !important;
+        }
+    </style>
+""", unsafe_allow_html=True)
+
+SUPPORTED_TYPES = ['wav', 'mp3', 'ogg', 'flac', 'm4a']
+
+# Load NeMo model once
+@st.cache_resource
+def load_model():
+    model = nemo_asr.models.EncDecHybridRNNTCTCBPEModel.from_pretrained(
+        model_name="nvidia/stt_ar_fastconformer_hybrid_large_pcd_v1.0"
+    )
+    return model
+
+model = load_model()
+
+# Helper: Convert any audio to 16kHz mono WAV
+def convert_audio(uploaded_file, target_sample_rate=16000):
+    with tempfile.NamedTemporaryFile(delete=False, suffix=".wav") as tmp_out:
+        audio = AudioSegment.from_file(uploaded_file)
+        audio = audio.set_frame_rate(target_sample_rate).set_channels(1)
+        audio.export(tmp_out.name, format="wav")
+        return tmp_out.name
+
+# App UI
+st.markdown("""
+    <div class="header">
+        <h1 style="margin-bottom: 0.5rem;">Arabic Transcriber</h1>
+        <p style="color: var(--text-secondary); margin-top: 0;">Convert speech to text with precision</p>
+    </div>
+""", unsafe_allow_html=True)
+
+# Main content - single wide column layout
+st.markdown("""
+    <div class="card">
+        <div style="display: flex; gap: 1rem; margin-bottom: 1rem;">
+            <span class="feature-icon">🔊</span>
+            <span>Supports WAV, MP3, OGG, FLAC, M4A</span>
+        </div>
+        <div style="display: flex; gap: 1rem; margin-bottom: 1rem;">
+            <span class="feature-icon">⚡</span>
+            <span>Fast processing with advanced AI</span>
+        </div>
+    </div>
+""", unsafe_allow_html=True)
+
+uploaded_file = st.file_uploader("Drag and drop audio file here", type=SUPPORTED_TYPES)
+
+if uploaded_file is not None:
+    # Convert to 16kHz mono wav
+    with st.spinner("Preparing audio for transcription..."):
+        processed_wav = convert_audio(uploaded_file)
+    
+    # Show audio info
+    data, sample_rate = sf.read(processed_wav)
+    channels = 1 if len(data.shape) == 1 else data.shape[1]
+    duration = len(data) / sample_rate
+    
+    # Show audio player and info
+    st.audio(processed_wav, format="audio/wav")
+    
+    st.markdown("### Audio Details")
+    st.markdown("""
+        <div class="stats">
+            <div class="stat-box">
+                <div>Duration</div>
+                <div class="stat-value">{:.1f}s</div>
+            </div>
+            <div class="stat-box">
+                <div>Sample Rate</div>
+                <div class="stat-value">{} Hz</div>
+            </div>
+            <div class="stat-box">
+                <div>Channels</div>
+                <div class="stat-value">{}</div>
+            </div>
+        </div>
+    """.format(duration, sample_rate, channels), unsafe_allow_html=True)
+    
+    # Transcription
+    if st.button("Transcribe Audio", type="primary"):
+        # Create a progress container
+        progress_container = st.empty()
+        progress_container.markdown("""
+            <div class="progress-container">
+                <div class="progress-bar" style="width: 30%;"></div>
+            </div>
+            <div style="text-align: center; margin-top: 5px; color: var(--secondary);">Processing audio...</div>
+        """, unsafe_allow_html=True)
+        
+        time.sleep(0.8)
+        progress_container.markdown("""
+            <div class="progress-container">
+                <div class="progress-bar" style="width: 70%;"></div>
+            </div>
+            <div style="text-align: center; margin-top: 5px; color: var(--secondary);">Transcribing content...</div>
+        """, unsafe_allow_html=True)
+        
+        # Actual transcription
+        with st.spinner(""):
+            result = model.transcribe([processed_wav])
+            transcript = result[0].text
+        
+        # Update progress to complete
+        progress_container.markdown("""
+            <div class="progress-container">
+                <div class="progress-bar" style="width: 100%;"></div>
+            </div>
+            <div style="text-align: center; margin-top: 5px; color: var(--secondary);">Transcription complete</div>
+        """, unsafe_allow_html=True)
+        
+        time.sleep(0.5)
+        progress_container.empty()
+        
+        st.markdown("### Transcription Results")
+        st.markdown(f"""
+            <div class="transcript-container">
+                <div class="transcript-box">{transcript}</div>
+            </div>
+        """, unsafe_allow_html=True)
+        
+        # Download button
+        st.download_button("Download Transcript", transcript, 
+                          file_name="arabic_transcript.txt")
+        
+        # Cleanup
+        os.remove(processed_wav)
+
+# Minimal footer
+st.markdown("""
+    <div style="text-align: center; color: var(--text-secondary); padding: 2rem 0; font-size: 0.8rem;">
+        <p>Powered by NeMo ASR • Secure local processing</p>
+    </div>
+""", unsafe_allow_html=True)