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.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+hub_model/variables/variables.data-00000-of-00001 filter=lfs diff=lfs merge=lfs -text

app.py

@@ -0,0 +1,101 @@
+from flask import Flask
+from flask import request
+from flask import render_template
+from flask import redirect
+from flask import jsonify
+from flask import send_from_directory
+import json
+import numpy as np
+import moduli
+#from hugchat import hugchat
+#from hugchat.login import Login
+from numpy.linalg import norm
+import datetime
+import tensorflow as tf
+import tensorflow_hub as hub
+import tensorflow_text
+from functools import wraps
+import os
+import pickle
+
+model_url = "./hub_model/"
+hub_layer = hub.load(model_url)
+
+app = Flask(__name__)
+
+def support_jsonp(func):
+    """Wraps JSONified output for JSONP requests."""
+    @wraps(func)
+    def decorated_function(*args, **kwargs):
+        callback = request.args.get('callback', False)
+        if callback:
+            resp = func(*args, **kwargs)
+            resp.set_data('{}({})'.format(
+                str(callback),
+                resp.get_data(as_text=True)
+            ))
+            resp.mimetype = 'application/javascript'
+            return resp
+        else:
+            return func(*args, **kwargs)
+    return decorated_function
+
+@app.route("/")
+def flask_app():
+    return '<br>' \
+    '<h3><a href="http://18.102.72.47:5000" target="_blank">Hai acceso il server! Bene!&#128521 Adesso vai alla pagina La7 DEMO!!</a></h3>' \
+   
+
+@app.route('/broadcast_labels',methods=['POST','GET'])
+@support_jsonp
+def broadcast_labels():
+    #if request.method == 'GET':
+    s=request.args.get('S')
+    dati=moduli.la7_labels(s)
+    output=dati
+    response = jsonify(output)
+    return response
+
+@app.route('/requestsSearch',methods=['POST','GET'])
+@support_jsonp
+def tasksSearch():
+    domanda=request.args.get('frase').strip()
+    s=request.args.get('S').strip()
+    path=s
+    #dati=moduli.la7_Search(s,domanda,hub_layer)
+    print('domanda',domanda)
+    dati=[]
+    with open ('static/dati/'+str(path)+'/db_relatori_finale_emb', 'rb') as fp:
+        word = pickle.load(fp) 
+    word_orig=np.array(word, dtype="object")
+    message_embeddings = hub_layer(domanda)[0].numpy()
+    ris=[]
+    for n,w in enumerate(word):
+        contesto_embeddings=np.array(w[6])
+        cosine = np.dot(message_embeddings,contesto_embeddings)/(norm(message_embeddings)*norm(contesto_embeddings))
+        ris.append(cosine)
+    ris_sort=np.argsort(ris)[::-1]
+    l=0
+    for n in ris_sort:
+        if l==0:
+          testo=str(word[n][5])
+          testo_chi=str(word[n][2])+':'+str(word[n][1])
+        else:
+          testo=testo+' '+word[n][5]
+          testo_chi=testo_chi+' --- '+str(word[n][2])+' '+str(word[n][1])
+        l=len(testo)
+        if l>800:
+          break
+
+    d={}
+    d['text']=str(testo)
+    d['chi']=str(testo_chi)
+    dati.append(d)
+    output=dati
+    response = jsonify(output)
+    return response
+
+
+
+if __name__ == "__main__":
+    app.run(host='0.0.0.0',  port=7860)

hub_model/saved_model.pb

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:aea05ab4f38b378ed33359e7ae9b759b388c27a7267e26ee1fabf1f12a15caaf
+size 9339616

hub_model/variables/variables.data-00000-of-00001

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:6dcbc87e48438f803b0237fbb0941e8dec12f1c28ef5fc738ed7ba0a9a1ec182
+size 341194862

requirements.txt

@@ -0,0 +1,4 @@
+flask
+numpy==1.23.5
+tensorflow
+tensorflow_text

static/encodedT.npy

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:aab9e3ca8499a2f0e5094c483395bfddb9ef9e06c7b56b7d9d5193123a9a419f
+size 5949924

static/textT.npy

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+oid sha256:13891832587f8a6a450a471370bccc08e121cb6476078888679ee7af5d21b85c
+size 6458662