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SVM.joblib

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+version https://git-lfs.github.com/spec/v1
+oid sha256:7880a1538dd9a9e3d2e149235dd956fb1a53c2a54bc81c051699de599adff943
+size 4475227

app.py

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+from fastapi import FastAPI
+import joblib
+import numpy as np
+
+app = FastAPI()
+
+# Load your trained model
+model = joblib.load("SVM.joblib")  # Ensure this file is in the correct directory
+
+@app.get("/")
+def home():
+    return {"message": "AMP Classifier API is running!"}
+
+@app.post("/predict")
+def predict(sequence: str):
+    # Convert sequence to features (modify if needed)
+    features = np.array([len(sequence)])  # Example: length of sequence
+    prediction = model.predict([features])
+    
+    return {"sequence": sequence, "is_AMP": bool(prediction[0])}

requirements.txt

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+fastapi
+uvicorn
+scikit-learn
+joblib
+numpy
+pandas
+gradio