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from flask import Flask, request, jsonify
from transformers import pipeline
app = Flask(__name__)
labels = {
"LABEL_0": "not_bullying",
"LABEL_1": "bullying",
}
# Load the text classification pipeline with label mappings
classifier = pipeline(
"text-classification",
model="Davephoenix/bert-bullying-detector",
)
@app.route("/classify/text", methods=["POST"])
def classify_text():
data = request.get_json()
if not data or "text" not in data:
return jsonify({"error": "Missing 'text' in request body"}), 400
try:
result = classifier(data["text"])
# Map the labels to their meanings
for item in result:
item["label"] = labels.get(item["label"], item["label"])
return jsonify(result)
except Exception as e:
return jsonify({"error": str(e)}), 500
@app.route("/classify/audio", methods=["POST"])
def classify_audio():
return jsonify({"error": "Audio classification not implemented yet"}), 501
@app.route("/classify/image", methods=["POST"])
def classify_image():
return jsonify({"error": "Image classification not implemented yet"}), 501
if __name__ == "__main__":
app.run(host="0.0.0.0", port=7860)
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