initial commit

Dockerfile

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+FROM python:3.10
+
+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"]

app.py

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+import pickle
+import os
+from fastapi import FastAPI
+from pydantic import BaseModel
+
+# -----------------------------
+# FastAPI initialization
+# -----------------------------
+app = FastAPI(
+    title="RTL Log Severity Classifier",
+    description="Machine learning API that predicts severity of RTL verification logs.",
+    version="1.0"
+)
+
+# -----------------------------
+# Model paths
+# -----------------------------
+VECTORIZER_PATH = "vectorizer.pkl"
+MODEL_PATH = "severity_model.pkl"
+
+# -----------------------------
+# Severity mapping
+# -----------------------------
+REVERSE_MAP = {
+    0: "INFO",
+    1: "WARNING",
+    2: "ERROR",
+    3: "CRITICAL"
+}
+
+# -----------------------------
+# Load artifacts safely
+# -----------------------------
+if not os.path.exists(VECTORIZER_PATH):
+    raise RuntimeError("vectorizer.pkl not found")
+
+if not os.path.exists(MODEL_PATH):
+    raise RuntimeError("severity_model.pkl not found")
+
+with open(VECTORIZER_PATH, "rb") as f:
+    vectorizer = pickle.load(f)
+
+with open(MODEL_PATH, "rb") as f:
+    model = pickle.load(f)
+
+# -----------------------------
+# Request schema
+# -----------------------------
+class LogRequest(BaseModel):
+    module: str
+    message: str
+
+
+# -----------------------------
+# Health check
+# -----------------------------
+@app.get("/")
+def health_check():
+    return {
+        "status": "running",
+        "model": "RTL Severity Classifier",
+        "classes": ["INFO", "WARNING", "ERROR", "CRITICAL"]
+    }
+
+
+# -----------------------------
+# Prediction endpoint
+# -----------------------------
+@app.post("/predict")
+def predict_severity(request: LogRequest):
+
+    text = request.module + " " + request.message
+
+    vector = vectorizer.transform([text])
+
+    pred = model.predict(vector)[0]
+
+    severity = REVERSE_MAP[pred]
+
+    return {
+        "module": request.module,
+        "message": request.message,
+        "predicted_severity": severity
+    }

requirements.txt

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

severity_model.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:bf37966b8f9f795dc7a81828f1151498019f76807b58a76b9bc03f9856c02d8f
+size 320785

vectorizer.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:cf04a2c840257e4a158b1be2a77f01b356fde06f27b1b65d6cceac08d45de11d
+size 428212