Update app.py

app.py

@@ -15,13 +15,10 @@ import numpy as np
 
 print("ClearWave AI starting...")
 
-# ── Services ────────────────────────────────────────────────────────
-from services.denoiser     import Denoiser
-from services.transcriber  import Transcriber
-# ✅ FIX: Now using the full Translator class (NLLB-1.3B + Google fallback)
-#         Previously app.py had its own inline translate() that only used
-#         Google Translate and completely ignored translator.py
-from services.translator   import Translator
+# ── Services (flat structure - all files in root) ────────────────────
+from denoiser    import Denoiser
+from transcriber import Transcriber
+from translator  import Translator
 
 _denoiser    = Denoiser()
 _transcriber = Transcriber()
@@ -133,4 +130,136 @@ with gr.Blocks(title="ClearWave AI", theme=gr.themes.Soft()) as demo:
     )
 
 print("ClearWave AI ready!")
-demo.launch()
+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**")
+
+    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()