Create app.py

app.py

@@ -0,0 +1,33 @@
+from fastapi import FastAPI, Request
+from fastapi.responses import HTMLResponse, PlainTextResponse
+from fastapi.staticfiles import StaticFiles
+from fastapi.templating import Jinja2Templates
+import uvicorn
+from transformers import pipeline
+
+
+app = FastAPI()
+app.mount("/static", StaticFiles(directory="static"), name="static")
+templates = Jinja2Templates(directory="templates")
+
+@app.get("/", response_class=HTMLResponse)
+async def read_item(request: Request):
+    return templates.TemplateResponse("index.html", context={'request': request})
+
+@app.get("/{content}", response_class=PlainTextResponse)
+async def read_item(request: Request, content: str):
+    return analyze_output(content)
+
+@app.post("/{content}", response_class=PlainTextResponse)
+async def read_item(request: Request, content: str):
+    return analyze_output(content)
+
+def analyze_output(input: str, pipe = pipeline("text-classification", model="Titeiiko/OTIS-Official-Spam-Model")):
+    x = pipe(input)[0]
+    if x["label"] == "LABEL_0":
+        return str({"type":"Not Spam", "probability":x["score"]})
+    else:
+        return str({"type":"Spam", "probability":x["score"]})
+    
+if __name__ == "__main__":
+    uvicorn.run(app, host="0.0.0.0", port=8000)