Merge branch 'dev' of http://gitlab.pmf.kg.ac.rs/igrannonica/neuronstellar into dev

1 files changed, 42 insertions, 0 deletions

diff --git a/backend/microservice/api/controller.py b/backend/microservice/api/controller.py
new file mode 100644
index 00000000..ceed02ad
--- /dev/null
+++ b/backend/microservice/api/controller.py
@@ -0,0 +1,42 @@
+import flask
+from flask import request, jsonify
+import ml_socket
+import ml_service
+import tensorflow as tf
+import pandas as pd
+
+app = flask.Flask(__name__)
+app.config["DEBUG"] = True
+app.config["SERVER_NAME"] = "127.0.0.1:5543"
+  
+class train_callback(tf.keras.callbacks.Callback):
+    def __init__(self, x_test, y_test):
+        self.x_test = x_test
+        self.y_test = y_test
+    #
+    def on_epoch_end(self, epoch, logs=None):
+        print(epoch)
+        #print('Evaluation: ', self.model.evaluate(self.x_test,self.y_test),"\n") #broj parametara zavisi od izabranih metrika loss je default
+
+@app.route('/train', methods = ['POST'])
+def train():
+    print("******************************TRAIN*************************************************")
+    f = request.json["dataset"]
+    dataset = pd.read_csv(f)
+    #
+    result = ml_service.train(dataset, request.json["model"], train_callback)
+    print(result)
+    return jsonify(result)
+
+@app.route('/predict', methods = ['POST'])
+def predict():
+    f = request.json['filepath']
+    dataset = pd.read_csv(f)
+    m = request.json['modelpath']
+    #model = tf.keras.models.load_model(m)
+    #
+    #model.predict?
+
+print("App loaded.")
+ml_socket.start()
+app.run()
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