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JanetBackEnd
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ahmed531998 2023-04-17 21:10:06 +02:00
parent 3b143e0f73
commit e705b0498c
3 changed files with 32 additions and 8 deletions
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4
ResponseGenerator.py
View File

@ -88,9 +88,9 @@ class ResponseGenerator:
return self.db[db_type].iloc[[I[0]][0]].reset_index(drop=True).loc[0]
def gen_response(self, action, utterance=None, username=None, state=None, consec_history=None, chitchat_history=None):
def gen_response(self, action, utterance=None, username=None, vrename=None, state=None, consec_history=None, chitchat_history=None):
if action == "Help":
return "Hey it's Janet! I am here to help you make use of the datasets and papers in the catalogue. I can answer questions whose answers may be inside the papers. I can summarize papers for you. I can also chat with you. So, whichever it is, I am ready to chat!"
return "Hey it's Janet! I am here to help you make use of the datasets and papers in the catalogue of the " + vrename +" VRE. I can answer questions whose answers may be inside the papers. I can summarize papers for you. I can also chat with you. So, whichever it is, I am ready to chat!"
elif action == "Recommend":
prompt = self.recommender.make_recommendation(username)
if prompt != "":

30
VRE.py
View File

@ -186,8 +186,19 @@ class VRE:
self.db['paper_db'] = paper_df.sort_values(by='metadata_created', ascending=True)
self.db['dataset_db'] = dataset_df.sort_values(by='metadata_created', ascending=True)
self.db['post_db'] = post_df.sort_values(by='time', ascending=True)
self.db['content_db'] = content_df
other_content_df = pd.DataFrame(columns=['id', 'paperid', 'content'])
for i, post in post_df.iterrows():
self.content_counter+=1
other_content_df.loc[str(self.content_counter)] = [self.content_counter, -1, post['author'] + ' posted: ' + post['content'] + ' It is about ' + ', '.join(post['tags'])]
for i, description in dataset_df.iterrows():
self.content_counter+=1
other_content_df.loc[str(self.content_counter)] = [self.content_counter, -2, description['title'] + ' is a dataset. ' + description['notes'] + ' It is about ' + ', '.join(description['tags']) ]
for i, description in paper_df.iterrows():
self.content_counter+=1
other_content_df.loc[str(self.content_counter)] = [self.content_counter, -3, description['title'] + ' is a paper. ' + description['notes'] + ' It is about ' + ', '.join(description['tags']) ]
self.db['content_db'] = pd.concat(content_df, other_content_df)
self.db['paper_db'].to_json(self.directory + self.name + '_paper.json')
self.db['dataset_db'].to_json(self.directory + self.name + '_dataset.json')
@ -271,9 +282,21 @@ class VRE:
self.db['post_db'] = pd.concat([self.db['post_db'], post_df.sort_values(by='time', ascending=True)])
self.db['post_db'].to_json(self.directory+self.name+'_post.json')
other_content_df = pd.DataFrame(columns=['id', 'paperid', 'content'])
for i, post in post_df.iterrows():
self.content_counter+=1
other_content_df.loc[str(self.content_counter)] = [self.content_counter, -1, post['author'] + ' posted: ' + post['content'] + ' It is about ' + ', '.join(post['tags'])]
for i, description in dataset_df.iterrows():
self.content_counter+=1
other_content_df.loc[str(self.content_counter)] = [self.content_counter, -2, description['title'] + ' is a dataset. ' + description['notes'] + ' It is about ' + ', '.join(description['tags']) ]
for i, description in paper_df.iterrows():
self.content_counter+=1
other_content_df.loc[str(self.content_counter)] = [self.content_counter, -3, description['title'] + ' is a paper. ' + description['notes'] + ' It is about ' + ', '.join(description['tags']) ]
self.db['paper_db'].to_json(self.directory + self.name + '_paper.json')
self.db['dataset_db'].to_json(self.directory + self.name + '_dataset.json')
self.db['content_db'] = pd.concat([self.db['content_db'], content_df])
self.db['content_db'] = pd.concat([self.db['content_db'], content_df, other_content_df])
self.db['content_db'].to_json(self.directory + self.name + '_content.json')
if not paper_df.empty or not dataset_df.empty or not content_df.empty or not post_df.empty:
self.new_income = True
@ -297,6 +320,7 @@ class VRE:
continue
modline+=line[i]
modline = re.sub(r'\.+', ".", modline)
modline = re.sub("\[.*?\]","", modline)
return modline
def check_if_sentence(self, sentence):

6
main.py
View File

@ -90,13 +90,13 @@ def predict():
state = {'help': True, 'inactive': False, 'modified_query':"", 'intent':""}
dm.update(state)
action = dm.next_action()
response = rg.gen_response(action)
response = rg.gen_response(action, vrename=vre.name)
message = {"answer": response}
elif text == "<RECOMMEND_ON_IDLE>":
state = {'help': False, 'inactive': True, 'modified_query':"recommed: ", 'intent':""}
dm.update(state)
action = dm.next_action()
response = rg.gen_response(action, username=user.username)
response = rg.gen_response(action, username=user.username, vrename=vre.name)
message = {"answer": response}
new_state = {'modified_query': response}
dm.update(new_state)
@ -117,7 +117,7 @@ def predict():
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())
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(), vrename=vre.name)
message = {"answer": response, "query": text, "cand": "candidate", "history": dm.get_consec_history(), "modQuery": state['modified_query']}
if state['intent'] == "QA":
response = response.split("_______ \n The answer is: ")[1]