Update app.py

app.py

@@ -86,138 +86,6 @@ def process(audio_path, in_lang_label, out_lang_label, progress=gr.Progress()):
         return None, f"Error: {e}", "", traceback.format_exc(), "Failed"
 
 
-# ── UI ───────────────────────────────────────────────────────────────
-with gr.Blocks(title="ClearWave AI", theme=gr.themes.Soft()) as demo:
-    gr.Markdown("# 🎵 ClearWave AI\n**Denoise · Transcribe · Translate**")
-
-    with gr.Row():
-        with gr.Column(scale=1):
-            audio_in = gr.Audio(
-                label="Upload Audio",
-                type="filepath",
-                sources=["upload", "microphone"],
-            )
-            in_lang  = gr.Dropdown(INPUT_LANGS,  value="Auto Detect", label="Input Language")
-            out_lang = gr.Dropdown(OUTPUT_LANGS, value="Telugu",      label="Output Language")
-            run_btn  = gr.Button("Process Audio", variant="primary", size="lg")
-            status   = gr.Markdown("Upload audio and click Process.")
-
-        with gr.Column(scale=2):
-            with gr.Tabs():
-                with gr.Tab("Text"):
-                    with gr.Row():
-                        with gr.Column():
-                            gr.Markdown("#### Transcript")
-                            transcript_out = gr.Markdown("...")
-                        with gr.Column():
-                            gr.Markdown("#### Translation")
-                            translation_out = gr.Markdown("...")
-                with gr.Tab("Clean Audio"):
-                    audio_out = gr.Audio(
-                        label="Denoised",
-                        type="filepath",
-                        interactive=False,
-                    )
-                with gr.Tab("Timings"):
-                    timing_out = gr.Markdown("...")
-
-    run_btn.click(
-        fn=process,
-        inputs=[audio_in, in_lang, out_lang],
-        outputs=[audio_out, transcript_out, translation_out, timing_out, status],
-        show_progress=True,
-        api_name=False,
-    )
-
-print("ClearWave AI ready!")
-demo.launch()import sys
-import types
-_a = types.ModuleType('audioop')
-_a.ratecv = lambda *a, **k: (b'', 0)
-sys.modules['audioop'] = _a
-sys.modules['pyaudioop'] = _a
-
-import gradio as gr
-import os
-import time
-import tempfile
-import shutil
-import subprocess
-import numpy as np
-
-print("ClearWave AI starting...")
-
-# ── Services (flat structure - all files in root) ────────────────────
-from denoiser    import Denoiser
-from transcriber import Transcriber
-from translator  import Translator
-
-_denoiser    = Denoiser()
-_transcriber = Transcriber()
-_translator  = Translator()
-
-# ── Config ───────────────────────────────────────────────────────────
-INPUT_LANGS  = ["Auto Detect", "English", "Telugu", "Hindi", "Tamil", "Kannada"]
-OUTPUT_LANGS = ["Telugu", "Hindi", "Tamil", "English", "Kannada"]
-LANG_CODES   = {
-    "Auto Detect": "auto",
-    "English":     "en",
-    "Telugu":      "te",
-    "Hindi":       "hi",
-    "Tamil":       "ta",
-    "Kannada":     "kn",
-}
-
-# ── Pipeline ─────────────────────────────────────────────────────────
-def process(audio_path, in_lang_label, out_lang_label, progress=gr.Progress()):
-    if audio_path is None:
-        return None, "Please upload audio.", "", "", "No audio"
-
-    in_lang  = LANG_CODES.get(in_lang_label, "auto")
-    out_lang = LANG_CODES.get(out_lang_label, "te")
-    tmp      = tempfile.mkdtemp()
-    t_total  = time.time()
-
-    try:
-        # Dept 1 — Denoise
-        progress(0.1, desc="Dept 1: Denoising...")
-        t0    = time.time()
-        clean = _denoiser.process(audio_path, tmp)
-        t1    = time.time() - t0
-
-        # Dept 2 — Transcribe
-        progress(0.4, desc="Dept 2: Transcribing...")
-        t0                          = time.time()
-        transcript, detected, tx_m  = _transcriber.transcribe(clean, in_lang)
-        t2                          = time.time() - t0
-
-        # Dept 3 — Translate
-        progress(0.75, desc="Dept 3: Translating...")
-        src          = detected if in_lang == "auto" else in_lang
-        t0           = time.time()
-        translated, tr_m = _translator.translate(transcript, src, out_lang)
-        t3           = time.time() - t0
-
-        total = time.time() - t_total
-        progress(1.0, desc=f"Done in {total:.1f}s!")
-
-        timing = (
-            f"| Step | Time | Method |\n|---|---|---|\n"
-            f"| Denoise    | {t1:.1f}s | noisereduce |\n"
-            f"| Transcribe | {t2:.1f}s | {tx_m} |\n"
-            f"| Translate  | {t3:.1f}s | {tr_m} |\n"
-            f"| **Total**  | **{total:.1f}s** | |"
-        )
-
-        out_audio = os.path.join(tmp, "output.wav")
-        shutil.copy(clean, out_audio)
-        return out_audio, transcript, translated, timing, f"Done in {total:.1f}s"
-
-    except Exception as e:
-        import traceback
-        return None, f"Error: {e}", "", traceback.format_exc(), "Failed"
-
-
 # ── UI ───────────────────────────────────────────────────────────────
 with gr.Blocks(title="ClearWave AI", theme=gr.themes.Soft()) as demo:
     gr.Markdown("# 🎵 ClearWave AI\n**Denoise · Transcribe · Translate**")