Upload 7 files

Dockefile.txt

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+FROM python:3.10-slim
+
+WORKDIR /app
+
+COPY requirements.txt .
+RUN pip install --no-cache-dir -r requirements.txt
+
+COPY . .
+
+EXPOSE 7860
+
+CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "7860"]

acceleration.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:f4ed75c52585a15c752132a593588f3d5fb4f180c1d25a7c64ef892bd0d92ab0
+size 953

app.py

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+from fastapi import FastAPI
+import joblib
+import pandas as pd
+
+app = FastAPI()
+
+# Load models once at startup
+future_spend_model = joblib.load("future_spend_7d.pkl")
+spike_model = joblib.load("spike_probability.pkl")
+acc_model = joblib.load("acceleration.pkl")
+FEATURES = joblib.load("model_features.pkl")
+
+@app.get("/")
+def root():
+    return {"status": "ML backend running"}
+
+@app.post("/predict")
+def predict(payload: dict):
+    X = pd.DataFrame([payload], columns=FEATURES)
+
+    future_spend = future_spend_model.predict(X)[0]
+    spike_prob = spike_model.predict_proba(X)[0][1]
+    acceleration = acc_model.predict(X)[0]
+
+    return {
+        "future_7d_spend": round(float(future_spend), 2),
+        "spike_probability": round(float(spike_prob), 3),
+        "acceleration": round(float(acceleration), 2)
+    }

future_spend_7d.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:31b0529daec826eafe8adfdd15bd61ea237b8e6747f8718356964e2c3231d607
+size 318177

model_features.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:7ed6118cb1dd9cc034817aca085764f0cf2d9aa49182b2bae5207f78bfaf86e7
+size 112

requirements.txt

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

spike_probability.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:ef336462e09127807cc10265ccefb29548a85d584306aa0a9bbdc810973f7fa3
+size 1263