new commits

app.py

@@ -43,7 +43,10 @@ def main():
     def example_submit(text):
         st.session_state["prompt_from_text"] = text   
 
-    st.session_state["celeb_name"] = st.sidebar.selectbox('Choose your celebrity crush', options=list(celeb_data.keys()))
+    def clear_chat_his():
+        st.session_state["messages"] = []
+
+    st.sidebar.selectbox('Choose your celebrity crush', key="celeb_name", options=sorted(list(celeb_data.keys())), on_change=clear_chat_his)
     model_id=st.sidebar.selectbox("Choose Your model",options=model_list)
 
     st.session_state["QA_model_path"] = f"google/{model_id}" if "flan-t5" in model_id else model_id
@@ -102,7 +105,11 @@ def main():
         st.session_state["messages"].append({"role": "user", "content": prompt})
 
         # Add assistant response to chat history
-        response = st.session_state["celeb_bot"].question_answer()
+        if len(st.session_state["messages"]) < 3:
+            response = st.session_state["celeb_bot"].question_answer()
+        else:
+            chat_his = "Question: {q}\n\nAnswer: {a}\n\n".format(q=st.session_state["messages"][-3]["content"], a=st.session_state["messages"][-2]["content"])
+            response = st.session_state["celeb_bot"].question_answer(chat_his=chat_his)            
         
         # disable autoplay to play in HTML
         b64 = st.session_state["celeb_bot"].text_to_speech(autoplay=False)

celebbot.py

@@ -97,7 +97,25 @@ class CelebBot():
 
     def third_to_first_person(self, text):
         text = text.replace(" ", "  ")
-        name = self.name.split(" ")[-1].lower()
+        possible_names = [name.lower() for name in self.name.split(" ")]
+        if "bundchen" in self.name.lower():
+            possible_names.append("bündchen")
+        if "beyonce" in self.name.lower():
+            possible_names.append("beyoncé")
+        if "adele" in self.name.lower():
+            possible_names.append("adkins") 
+        if "katy perry" in self.name.lower():
+            possible_names.append("hudson") 
+        if "lady gaga" in self.name.lower():
+            possible_names.append("germanotta") 
+        if "michelle obama" in self.name.lower():
+            possible_names.append("robinson")
+        if "natalie portman" in self.name.lower():
+            possible_names.append("hershlag") 
+        if "rihanna" in self.name.lower():
+            possible_names.append("fenty")   
+        if "victoria beckham" in self.name.lower():
+            possible_names.append("adams")                         
         doc = self.spacy_model(text)
         transformed_text = []
 
@@ -109,10 +127,14 @@ class CelebBot():
                     transformed_text.append("me")
                 elif token.text.lower() == "his":
                     transformed_text.append("my")
-                elif token.text.lower() == name and token.dep_ in ["nsubj", "nsubjpass"]:
+                elif token.text.lower() == "himself":
+                    transformed_text.append("myself")
+                elif token.text.lower() in possible_names and token.dep_ in ["nsubj", "nsubjpass"]:
                     transformed_text.append("I")
-                elif token.text in ["'s", "’s"] and doc[i-1].text.lower() == name:
+                elif token.text in ["'s", "’s"] and doc[i-1].text.lower() in possible_names:
                     transformed_text[-1] = "my"
+                elif token.text.lower() in possible_names and token.dep_ in ["dobj", "dative"]:
+                    transformed_text.append("me")                    
                 elif token.text.lower() == "their":
                     transformed_text.append("our")
                 elif token.text.lower() == "they":
@@ -127,10 +149,14 @@ class CelebBot():
                         transformed_text.append("my")
                     else:
                         transformed_text.append("me")
-                elif token.text.lower() == name and token.dep_ in ["nsubj", "nsubjpass"]:
+                elif token.text.lower() == "herself":
+                    transformed_text.append("myself")
+                elif token.text.lower() in possible_names and token.dep_ in ["nsubj", "nsubjpass"]:
                     transformed_text.append("I")
-                elif token.text in ["'s", "’s"] and doc[i-1].text.lower() == name:
+                elif token.text in ["'s", "’s"] and doc[i-1].text.lower() in possible_names:
                     transformed_text[-1] = "my"
+                elif token.text.lower() in possible_names and token.dep_ in ["dobj", "dative"]:
+                    transformed_text.append("me")    
                 elif token.text.lower() == "their":
                     transformed_text.append("our")
                 elif token.text.lower() == "they":
@@ -140,19 +166,18 @@ class CelebBot():
 
         return "".join(transformed_text)
 
-    def question_answer(self, instruction='', knowledge=''):
+    def question_answer(self, instruction='', knowledge='', chat_his=''):
         instruction = f"Your name is {self.name}. Always answer as helpfully as possible, while being safe. Your answers should not include any harmful, unethical, racist, sexist, toxic, dangerous, or illegal content. Please ensure that your responses are socially unbiased and positive in nature. If a question does not make any sense, or is not factually coherent, explain why instead of answering something not correct. If you don't know the answer to a question, please don't share false information."
         if self.text != "":
-            if re.search(re.compile(rf'\b(you|your|yours)\b', flags=re.IGNORECASE), self.text) != None:
-              knowledge = self.retrieve_knowledge_assertions()
-            else:
+            if re.search(re.compile(rf'\b({self.name})\b', flags=re.IGNORECASE), self.text) != None:
               knowledge = self.retrieve_knowledge_assertions(change_person=False)
+            else:
+              knowledge = self.retrieve_knowledge_assertions()
 
-            query = f"Context: {instruction} {knowledge}\n\nQuestion: {self.text}\n\nAnswer:"
+            query = f"Context: {instruction} {knowledge}\n\nChat History: {chat_his}Question: {self.text}\n\nAnswer:"
             input_ids = self.QA_tokenizer(f"{query}", return_tensors="pt").input_ids.to(self.QA_model.device)
             outputs = self.QA_model.generate(input_ids, max_length=1024, min_length=8, do_sample=True, temperature=0.2, repetition_penalty=2.5)
             self.text = self.QA_tokenizer.decode(outputs[0], skip_special_tokens=True)
-            # self.text = " ".join([i.text.strip().capitalize() for i in self.spacy_model(self.text).sents])
         return self.text
 
     @staticmethod