No segments yet.
" rows = "" for seg in segments: start_s = seg.start_ms / 1000 end_s = seg.end_ms / 1000 dur_s = seg.duration_ms / 1000 rows += ( f"| ID | Text | ' "Start | End | Duration |
|---|
Please upload an audio file.
", "Please upload an audio file.", None try: audio = load_audio(audio_file) asr_audio = prepare_for_transcription(audio) wav_path = export_temp_wav(asr_audio) try: segments = segment_audio(wav_path, len(audio)) finally: os.unlink(wav_path) if not segments: return audio, None, "No speech detected.
", "No speech detected in the audio.", None html = segments_to_html(segments) transcript_path = generate_transcript_file(segments) return audio, segments, html, f"Found {len(segments)} sentences. Review and edit below.", transcript_path except Exception as e: return None, None, f"Error: {e}
", f"Error: {e}", None def on_upload_transcript(audio_state, transcript_file): """Load segments from uploaded transcript file.""" if audio_state is None: return None, None, "Please upload audio first.
", "Please upload audio first.", None if transcript_file is None: return None, None, "Please upload a transcript file.
", "Please upload a transcript file.", None try: with open(transcript_file, "r", encoding="utf-8") as f: text = f.read() audio = load_audio(audio_state) audio_duration_ms = len(audio) segments = segments_from_transcript(text, audio_duration_ms) if not segments: return None, None, "No text found in transcript.
", "No text found in transcript.", None html = segments_to_html(segments) transcript_path = generate_transcript_file(segments) return audio, segments, html, f"Loaded {len(segments)} segments from transcript.", transcript_path except Exception as e: return None, None, f"Error: {e}
", f"Error: {e}", None def on_merge(segments_state, selected_ids_text): """Merge two adjacent segments.""" segments = segments_from_dicts(segments_state) if segments_state else [] if not segments: return segments_state, "No segments loaded.
", "No segments loaded." try: ids = [int(x.strip()) for x in selected_ids_text.split(",")] if len(ids) != 2: return segments_state, segments_to_html(segments), "Select exactly 2 adjacent segment IDs (e.g. '0,1')." new_segments = merge_segments(segments, ids[0], ids[1]) return new_segments, segments_to_html(new_segments), f"Merged segments {ids[0]} and {ids[1]}." except Exception as e: return segments_state, segments_to_html(segments), f"Merge error: {e}" def on_split(segments_state, segment_id, split_time_s): """Split a segment at the specified time offset.""" segments = segments_from_dicts(segments_state) if segments_state else [] if not segments: return segments_state, "No segments loaded.
", "No segments loaded." try: seg_id = int(segment_id) offset_ms = int(float(split_time_s) * 1000) new_segments = split_segment(segments, seg_id, offset_ms) return new_segments, segments_to_html(new_segments), f"Split segment {seg_id} at {split_time_s}s." except Exception as e: return segments_state, segments_to_html(segments), f"Split error: {e}" def on_delete(segments_state, segment_id): """Delete a segment.""" segments = segments_from_dicts(segments_state) if segments_state else [] if not segments: return segments_state, "No segments loaded.
", "No segments loaded." try: seg_id = int(segment_id) new_segments = delete_segment(segments, seg_id) return new_segments, segments_to_html(new_segments), f"Deleted segment {seg_id}." except Exception as e: return segments_state, segments_to_html(segments), f"Delete error: {e}" def on_estimate(segments_state, repeat_count, pause_repeats, pause_sentences, speed): """Estimate output duration.""" segments = segments_from_dicts(segments_state) if segments_state else [] if not segments: return "No segments loaded." config = ShadowingConfig( repeat_count=int(repeat_count), pause_between_repeats_ms=int(float(pause_repeats) * 1000), pause_between_sentences_ms=int(float(pause_sentences) * 1000), playback_speed=float(speed), ) plan = build_plan(segments, config) total_ms = estimate_duration_ms(plan, config.playback_speed) minutes = total_ms // 60000 seconds = (total_ms % 60000) // 1000 return f"Estimated output: {minutes}m {seconds}s ({len(segments)} sentences x {config.repeat_count} repeats)" def on_build(audio_state, segments_state, repeat_count, pause_repeats, pause_sentences, speed): """Build the practice audio file.""" segments = segments_from_dicts(segments_state) if segments_state else [] if audio_state is None or not segments: return None, None, "Upload and transcribe audio first." config = ShadowingConfig( repeat_count=int(repeat_count), pause_between_repeats_ms=int(float(pause_repeats) * 1000), pause_between_sentences_ms=int(float(pause_sentences) * 1000), playback_speed=float(speed), ) errors = config.validate() if errors: return None, None, "Config errors: " + "; ".join(errors) try: plan = build_plan(segments, config) result_audio = build_audio(audio_state, plan, config) output_path = os.path.join(tempfile.gettempdir(), "shadowloop_output.mp3") export_mp3(result_audio, output_path) total_ms = len(result_audio) minutes = total_ms // 60000 seconds = (total_ms % 60000) // 1000 return output_path, output_path, f"Built practice audio: {minutes}m {seconds}s" except Exception as e: return None, None, f"Build error: {e}" def create_app(): """Create and return the Gradio app.""" with gr.Blocks(title="ShadowLoop") as app: gr.Markdown( "# ShadowLoop\n" "Turn any audio into a shadowing practice loop.\n\n" '**How it works:** Upload audio + transcribe → ' 'review the detected sentences → ' 'build a practice file that repeats each sentence with pauses.', elem_id="intro-text", ) audio_state = gr.State(value=None) segments_state = gr.State(value=None) # Phase 1: Upload with gr.Group(elem_classes=["phase-upload", "phase-section"]): gr.Markdown("### 1. Upload Audio", elem_id="title-upload") gr.Markdown("Upload audio and transcribe, or provide your own transcript.", elem_id="desc-upload") with gr.Row(): with gr.Column(scale=3): audio_input = gr.Audio(label="Audio file", type="filepath") transcribe_btn = gr.Button("Transcribe", variant="primary") with gr.Column(scale=2): transcript_input = gr.File(label="Upload transcript (.txt)", file_types=[".txt"]) transcript_btn = gr.Button("Use Transcript") status_text = gr.Textbox(label="Status", interactive=False) # Phase 2: Review with gr.Group(elem_classes=["phase-review", "phase-section"]): gr.Markdown("### 2. Review Sentences", elem_id="title-review") gr.Markdown("Check detected sentences. Expand 'Edit Segments' to merge, split, or delete.", elem_id="desc-review") segments_html = gr.HTML(value="No segments yet.
") transcript_download = gr.File(label="Download Transcript", interactive=False, elem_classes=["compact-file"]) with gr.Accordion("Edit Segments", open=False): with gr.Row(): with gr.Column(): merge_ids = gr.Textbox(label="Merge IDs (e.g. '0,1')", placeholder="0,1") merge_btn = gr.Button("Merge") with gr.Column(): split_id = gr.Number(label="Split segment ID", precision=0) split_time = gr.Number(label="Split at (seconds from segment start)") split_btn = gr.Button("Split") with gr.Column(): delete_id = gr.Number(label="Delete segment ID", precision=0) delete_btn = gr.Button("Delete") # Phase 3: Build with gr.Group(elem_classes=["phase-build", "phase-section"]): gr.Markdown("### 3. Configure & Build", elem_id="title-build") gr.Markdown("Set repeats and pauses, then build your practice audio.", elem_id="desc-build") with gr.Row(): repeat_count = gr.Slider(1, 20, value=3, step=1, label="Repeat count") pause_repeats = gr.Slider(0, 10, value=2.5, step=0.5, label="Pause between repeats (s)") pause_sentences = gr.Slider(1, 15, value=4, step=0.5, label="Pause between sentences (s)") speed = gr.Slider(0.5, 2.0, value=1.0, step=0.01, label="Playback speed") with gr.Row(): estimate_btn = gr.Button("Estimate Duration") estimate_text = gr.Textbox(label="Estimate", interactive=False) build_btn = gr.Button("Build Practice Audio", variant="primary") build_status = gr.Textbox(label="Build Status", interactive=False) with gr.Row(equal_height=True): output_audio = gr.Audio(label="Preview", type="filepath") download_file = gr.File(label="Download MP3") # Wire callbacks (KEEP EXACTLY AS-IS) transcribe_btn.click( on_transcribe, inputs=[audio_input], outputs=[audio_state, segments_state, segments_html, status_text, transcript_download], ) transcript_btn.click( on_upload_transcript, inputs=[audio_input, transcript_input], outputs=[audio_state, segments_state, segments_html, status_text, transcript_download], ) merge_btn.click( on_merge, inputs=[segments_state, merge_ids], outputs=[segments_state, segments_html, status_text], ) split_btn.click( on_split, inputs=[segments_state, split_id, split_time], outputs=[segments_state, segments_html, status_text], ) delete_btn.click( on_delete, inputs=[segments_state, delete_id], outputs=[segments_state, segments_html, status_text], ) estimate_btn.click( on_estimate, inputs=[segments_state, repeat_count, pause_repeats, pause_sentences, speed], outputs=[estimate_text], ) build_btn.click( on_build, inputs=[audio_state, segments_state, repeat_count, pause_repeats, pause_sentences, speed], outputs=[output_audio, download_file, build_status], ) return app if __name__ == "__main__": check_ffmpeg() app = create_app() theme = gr.themes.Soft( primary_hue=gr.themes.colors.stone, secondary_hue=gr.themes.colors.stone, neutral_hue=gr.themes.colors.stone, font=gr.themes.GoogleFont("Inter"), ).set( slider_color="#78716c", color_accent="#78716c", color_accent_soft="#e7e5e4", button_primary_background_fill="#57534e", button_primary_background_fill_hover="#44403c", button_primary_text_color="white", block_border_width="0px", ) app.launch(server_name="0.0.0.0", theme=theme, css=CUSTOM_CSS)