Fixed Sequence Bug

Author: Joshua Mayanja

.vscode/settings.json

@@ -0,0 +1,3 @@
+{
+    "python.formatting.provider": "black"
+}

app/__init__.py

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+import json
+from multiprocessing.spawn import spawn_main
+import pathlib
+from typing import Optional
+from fastapi import FastAPI
+from keras.models import load_model
+from keras_preprocessing.text import tokenizer_from_json
+from keras_preprocessing.sequence import pad_sequences
+
+app = FastAPI(
+    version="1.0.0",
+    title="DrexSpam",
+    description="An Artificial Intelligence based Spam detector API using machine learning",
+)
+
+BASE_DIR = pathlib.Path(__file__).resolve().parent
+
+MODEL_DIR = BASE_DIR.parent / "models"
+SPAM_MODEL_DIR = MODEL_DIR / "spam"
+SPAM_MODEL_PATH = SPAM_MODEL_DIR / "spam-model.h5"
+SPAM_TOKENIZER_PATH = SPAM_MODEL_DIR / "spam-classifer-tokenizer.json"
+SPAM_METADATA_PATH = SPAM_MODEL_DIR / "spam-classifer-metadata.json"
+
+SPAM_MODEL = None
+SPAM_TOKENIZER = None
+SPAM_METADATA = {}
+LEGEND_INVERTED = {}
+
+@app.on_event("startup")
+def on_startup():
+    global SPAM_MODEL, SPAM_TOKENIZER, SPAM_METADATA, LEGEND_INVERTED
+    # Load model
+    if SPAM_MODEL_PATH.exists():
+        SPAM_MODEL = load_model(SPAM_MODEL_PATH)
+    if SPAM_TOKENIZER_PATH.exists():
+        t_json = SPAM_TOKENIZER_PATH.read_text()
+        SPAM_TOKENIZER = tokenizer_from_json(t_json)
+    if SPAM_METADATA_PATH.exists():
+        SPAM_METADATA = json.loads(SPAM_METADATA_PATH.read_text())
+        LEGEND_INVERTED = SPAM_METADATA["labels_legend_inverted"]
+
+def predict(query: str):
+    sequences = SPAM_TOKENIZER.texts_to_sequences([query])
+    maxlen = SPAM_METADATA.get("max_sequence") or 280
+    x_input = pad_sequences(sequences, maxlen=280)
+    preds_array = SPAM_MODEL.predict(x_input)
+    return {}
+
+
+@app.get("/")
+def read_index(q: Optional[str] = None):
+    global SPAM_MODEL, SPAM_METADATA
+    query = q or "Hello world"
+    print(SPAM_MODEL)
+    return {"query": query, **SPAM_METADATA}

app/__pycache__/__init__.cpython-37.pyc

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+{
+    "labels_legend_inverted": {
+        "0": "ham",
+        "1": "spam"
+    },
+    "legend": {
+        "ham": 0,
+        "spam": 1
+    },
+    "max_sequence": 300,
+    "max_words": 280
+}