Upload 3 files

app/main.py

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+from fastapi import FastAPI
+from pydantic import BaseModel
+from app.model.model import predict_pipeline
+from app.model.model import __version__ as model_version
+
+
+app = FastAPI()
+
+
+class TextIn(BaseModel):
+    text: str
+
+
+class PredictionOut(BaseModel):
+    language: str
+
+
+@app.get("/")
+def home():
+    return {"health_check": "OK", "model_version": model_version}
+
+
+@app.post("/predict", response_model=PredictionOut)
+def predict(payload: TextIn):
+    language = predict_pipeline(payload.text)
+    return {"language": language}

app/model/model.py

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+import pickle
+import re
+from pathlib import Path
+
+__version__ = "0.1.0"
+
+BASE_DIR = Path(__file__).resolve(strict=True).parent
+
+
+with open(f"{BASE_DIR}/trained_pipeline-{__version__}.pkl", "rb") as f:
+    model = pickle.load(f)
+
+
+classes = [
+    "Arabic",
+    "Danish",
+    "Dutch",
+    "English",
+    "French",
+    "German",
+    "Greek",
+    "Hindi",
+    "Italian",
+    "Kannada",
+    "Malayalam",
+    "Portugeese",
+    "Russian",
+    "Spanish",
+    "Sweedish",
+    "Tamil",
+    "Turkish",
+]
+
+
+def predict_pipeline(text):
+    text = re.sub(r'[!@#$(),\n"%^*?\:;~`0-9]', " ", text)
+    text = re.sub(r"[[]]", " ", text)
+    text = text.lower()
+    pred = model.predict([text])
+    return classes[pred[0]]

app/model/trained_pipeline-0.1.0.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:ab7135c7421b2636cd9fe030d05b883c5ba19ccd13e57195e755a9e43df2bc53
+size 10251835