Create app.py

app.py

@@ -0,0 +1,92 @@
+import os
+import tempfile
+import asyncio
+from fastapi import FastAPI, WebSocket, WebSocketDisconnect
+from fastapi.middleware.cors import CORSMiddleware
+from faster_whisper import WhisperModel
+
+app = FastAPI()
+
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["*"],
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+
+# ─── Model Load ───────────────────────────────────────────────────────────────
+print("Loading Whisper model...")
+model = WhisperModel("large-v3", device="cpu", compute_type="int8")
+print("Whisper model ready!")
+
+# ─── Health ───────────────────────────────────────────────────────────────────
+@app.get("/health")
+async def health():
+    return {"status": "ok", "message": "SubFlow backend is running"}
+
+# ─── WebSocket Transcribe ─────────────────────────────────────────────────────
+@app.websocket("/transcribe")
+async def transcribe(websocket: WebSocket):
+    await websocket.accept()
+    tmp_path = None
+
+    try:
+        # مرحله ۱ — دریافت فایل صوتی
+        await websocket.send_json({"status": "receiving"})
+        audio_bytes = await websocket.receive_bytes()
+
+        # مرحله ۲ — ذخیره موقت روی دیسک
+        with tempfile.NamedTemporaryFile(suffix=".wav", delete=False) as tmp:
+            tmp.write(audio_bytes)
+            tmp_path = tmp.name
+
+        # مرحله ۳ — transcription
+        await websocket.send_json({"status": "transcribing"})
+
+        segments, info = model.transcribe(
+            tmp_path,
+            language="en",
+            word_timestamps=True,
+            vad_filter=True,
+        )
+
+        # مرحله ۴ — ساخت SRT
+        await websocket.send_json({"status": "processing"})
+
+        srt_entries = []
+        index = 1
+
+        for segment in segments:
+            words = list(segment.words)
+            if not words:
+                continue
+
+            start = words[0].start
+            end = words[-1].end
+            text = segment.text.strip()
+
+            srt_entries.append({
+                "index": index,
+                "start": start,
+                "end": end,
+                "text": text,
+                "words": [{"word": w.word, "start": w.start, "end": w.end} for w in words]
+            })
+            index += 1
+
+        # مرحله ۵ — ارسال نتیجه
+        await websocket.send_json({
+            "status": "done",
+            "segments": srt_entries,
+            "language": info.language,
+            "duration": info.duration,
+        })
+
+    except WebSocketDisconnect:
+        pass
+    except Exception as e:
+        await websocket.send_json({"status": "error", "message": str(e)})
+    finally:
+        if tmp_path and os.path.exists(tmp_path):
+            os.remove(tmp_path)
+        await websocket.close()