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JanetBackEnd
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fixes

This commit is contained in:
ahmed531998 2023-04-17 06:59:02 +02:00
parent 346cb31afd
commit 9412c10460
2 changed files with 43 additions and 35 deletions
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37
Recommender.py
View File

@ -4,51 +4,52 @@ import random
class Recommender:
def __init__(self, retriever):
self.curr_recommendations = []
self.recommended = []
self.curr_recommendations = {}
self.recommended = {}
self.retriever = retriever
self.rand_seed = 5
def _new(self, material):
for row in self.curr_recommendations:
print(row)
if username not in curr_recommendations:
return True
for row in self.curr_recommendations[username]:
if row['id'] == material['id'] and row['type'] == material['type']:
return False
return True
def _match_tags(self, material, interest):
def _match_tags(self, username, material, interest):
score = 0.7
for tag in material['tags']:
if cosine_similarity(np.array(self.retriever.encode([tag])),
np.array(self.retriever.encode([interest]))) > score:
if self._new(material):
print('hi')
self.curr_recommendations.append(material)
self.recommended.append(False)
self.curr_recommendations[username] = self.curr_recommendations[username].append(material) if username not in self.curr_recommendations else [material]
self.recommended[username] = self.recommended[username].append(False) if username not in self.recommended else [False]
def generate_recommendations(self, interests, new_material):
def generate_recommendations(self, username, interests, new_material):
for interest in interests:
for i, material in new_material.iterrows():
self._match_tags(material, interest)
self._match_tags(username, material, interest)
def make_recommendation(self, user):
if len(self.curr_recommendations) == 0:
def make_recommendation(self, username):
if len(self.curr_recommendations[username]) == 0:
return ""
to_consider = [idx for idx, value in enumerate(self.recommended) if value == False]
to_consider = [idx for idx, value in enumerate(self.recommended[username]) if value == False]
if len(to_consider) == 0:
return ""
index = random.choice(list(range(0, len(to_consider))))
index = self.recommended[index]
index = self.recommended[username][index]
#while self.recommended[index] == True:
# index = random.choice(list(range(0, len(self.curr_recommendations))))
recommendation = "Hey " + user + "! This " + self.curr_recommendations[index][
recommendation = "Hey " + username + "! This " + self.curr_recommendations[username][index][
'type'].lower() + " about " + ', '.join(
self.curr_recommendations[index]['tags']).lower() + " was posted recently by " + \
self.curr_recommendations[index][
self.curr_recommendations[username][index]['tags']).lower() + " was posted recently by " + \
self.curr_recommendations[username][index][
'author'].lower() + " on the catalogue. You may wanna check it out! It is titled " + \
self.curr_recommendations[index]['title'].lower() + ". Cheers, Janet"
self.curr_recommendations[username][index]['title'].lower() + ". Cheers, Janet"
# self.curr_recommendations.remove(self.curr_recommendations[index])
self.recommended[index] = True
self.recommended[username][index] = True
return recommendation

41
main.py
View File

@ -38,7 +38,6 @@ conn = psycopg2.connect(
cur = conn.cursor()
dms = {}
users = {}
def vre_fetch():
@ -50,12 +49,20 @@ def vre_fetch():
rg.update_index(vre.get_index())
rg.update_db(vre.get_db())
def user_interest_decay():
def user_interest_decay(user):
while True:
print("decaying interests after 3 minutes")
print("decaying interests after 3 minutes for " + user.username)
time.sleep(180)
user.decay_interests()
def clear_inactive():
while True:
time.sleep(1)
for user in users:
if user['activity'] > 3600:
del users[user['username']]
user['activity'] += 1
@app.route("/health", methods=['GET'])
def health():
return "Success", 200
@ -64,23 +71,20 @@ def health():
def init_dm():
username = request.get_json().get("username")
token = '2c1e8f88-461c-42c0-8cc1-b7660771c9a3-843339462'
i = 1
while username in dms:
username = username + str(i)
i+=1
dms[username] = DM()
user = User(username, token)
users[username] = user
threading.Thread(target=user_interest_decay, name='decayinterest_'+username).start()
message = {"answer": "your assigned name is " + username, "assignedname": username}
if username not in users:
users[username] = {'dm': DM(), 'activity': 0, 'user': User(username, token)}
threading.Thread(target=user_interest_decay, args=(users[username]['user'],), name='decayinterest_'+username).start()
message = {"answer": "your assigned name is " + username, "assignedname": username}
else:
message = {"answer": "welcome back " + username, "assignedname": username}
return message
@app.route("/api/predict", methods=['POST'])
def predict():
text = request.get_json().get("message")
username = request.get_json().get("username")
dm = dms[username]
user = users[username]
dm = users[username]['dm']
user = users[username]['user']
message = {}
if text == "<HELP_ON_START>":
state = {'help': True, 'inactive': False, 'modified_query':"", 'intent':""}
@ -110,7 +114,7 @@ def predict():
new_user_interests = user.get_user_interests()
new_vre_material = pd.concat([vre.db['paper_db'], vre.db['dataset_db']]).reset_index(drop=True)
if (new_user_interests != old_user_interests or len(old_vre_material) != len(new_vre_material)):
rec.generate_recommendations(new_user_interests, new_vre_material)
rec.generate_recommendations(username, new_user_interests, new_vre_material)
dm.update(state)
action = dm.next_action()
response = rg.gen_response(action=action, utterance=state['modified_query'], state=dm.get_recent_state(), consec_history=dm.get_consec_history(), chitchat_history=dm.get_chitchat_history())
@ -120,8 +124,9 @@ def predict():
new_state = {'modified_query': response, 'intent': state['intent']}
dm.update(new_state)
reply = jsonify(message)
dms[username] = dm
users[username] = user
users[username]['dm'] = dm
users[username]['user'] = user
users[username]['activity'] = 0
return reply
@app.route('/api/feedback', methods = ['POST'])
@ -174,6 +179,8 @@ if __name__ == "__main__":
threading.Thread(target=vre_fetch, name='updatevre').start()
threading.Thread(target=clear_inactive, name='clear').start()
rec = Recommender(retriever)
rg = ResponseGenerator(index,db, rec, generators, retriever)