Create app.py

app.py

@@ -0,0 +1,77 @@
+from fastapi import FastAPI, UploadFile, File, HTTPException
+from fastapi.responses import JSONResponse
+from faster_whisper import WhisperModel
+import tempfile
+import os
+import shutil
+import logging
+
+logging.basicConfig(level=logging.INFO)
+
+app = FastAPI(
+    title="Fast Whisper API",
+    version="1.0.0"
+)
+
+print("Loading Faster Whisper model...")
+
+model = WhisperModel(
+    "base",
+    device="cpu",
+    compute_type="int8",
+    cpu_threads=4,
+    num_workers=2
+)
+
+print("Model loaded successfully!")
+
+@app.get("/")
+def root():
+    return {
+        "status": "online",
+        "model": "faster-whisper-base",
+        "languages": [
+            "Hindi",
+            "English",
+            "Hinglish (Auto Detect)"
+        ]
+    }
+
+
+@app.post("/transcribe")
+async def transcribe(file: UploadFile = File(...)):
+    if not file.filename:
+        raise HTTPException(400, "No file uploaded.")
+
+    suffix = os.path.splitext(file.filename)[1]
+
+    with tempfile.NamedTemporaryFile(delete=False, suffix=suffix) as temp:
+        shutil.copyfileobj(file.file, temp)
+        temp_path = temp.name
+
+    try:
+        segments, info = model.transcribe(
+            temp_path,
+            beam_size=1,
+            vad_filter=True,
+            word_timestamps=False
+        )
+
+        text = " ".join(segment.text.strip() for segment in segments).strip()
+
+        return JSONResponse(
+            {
+                "success": True,
+                "language": info.language,
+                "language_probability": round(info.language_probability, 3),
+                "text": text
+            }
+        )
+
+    except Exception as e:
+        logging.exception(e)
+        raise HTTPException(500, str(e))
+
+    finally:
+        if os.path.exists(temp_path):
+            os.remove(temp_path)