Delete app0.py

app0.py

@@ -1,71 +0,0 @@
-import os
-from fastapi import FastAPI, File, UploadFile
-from pydantic import BaseModel
-from transformers import pipeline
-from PIL import Image
-import joblib
-import re
-import string
-import io
-import uvicorn
-
-# ✅ Define Hugging Face Cache Directory
-CACHE_DIR = "./hf_cache"
-os.makedirs(CACHE_DIR, exist_ok=True)
-
-# ✅ Initialize FastAPI
-app = FastAPI()
-
-# ✅ Load NSFW Image Classification Model with custom cache
-pipe = pipeline("image-classification", model="LukeJacob2023/nsfw-image-detector", cache_dir=CACHE_DIR)
-
-# ✅ Load Toxic Text Classification Model
-try:
-    model = joblib.load("toxic_classifier.pkl")
-    vectorizer = joblib.load("vectorizer.pkl")
-    print("✅ Model & Vectorizer Loaded Successfully!")
-except Exception as e:
-    print(f"❌ Error: {e}")
-    exit(1)
-
-# 📌 Text Input Data Model
-class TextInput(BaseModel):
-    text: str
-
-# 🔹 Text Preprocessing Function
-def preprocess_text(text):
-    text = text.lower()
-    text = re.sub(r'\d+', '', text)  # Remove numbers
-    text = text.translate(str.maketrans('', '', string.punctuation))  # Remove punctuation
-    return text.strip()
-
-# 📌 NSFW Image Classification API
-@app.post("/classify_image/")
-async def classify_image(file: UploadFile = File(...)):
-    try:
-        image = Image.open(io.BytesIO(await file.read()))
-        results = pipe(image)
-        
-        classification_label = max(results, key=lambda x: x['score'])['label']
-        nsfw_labels = {"sexy", "porn", "hentai"}
-        nsfw_status = "NSFW" if classification_label in nsfw_labels else "SFW"
-
-        return {"status": nsfw_status, "results": results}
-    except Exception as e:
-        return {"error": str(e)}
-
-# 📌 Toxic Text Classification API
-@app.post("/classify_text/")
-async def classify_text(data: TextInput):
-    try:
-        processed_text = preprocess_text(data.text)
-        text_vectorized = vectorizer.transform([processed_text])
-        prediction = model.predict(text_vectorized)
-        result = "Toxic" if prediction[0] == 1 else "Safe"
-        return {"prediction": result}
-    except Exception as e:
-        return {"error": str(e)}
-
-# ✅ Run FastAPI on Hugging Face
-if __name__ == "__main__":
-    uvicorn.run(app, host="0.0.0.0", port=7860)