Update initialization.py

initialization.py

@@ -27,70 +27,71 @@ def resume_reader(resume):
 
 def initialize_session_state(template=None, position=None):
     """ initialize session states """
+    print("Initializing session state...")
+
     if 'jd' in st.session_state:
+        print("Using job description for embedding...")
         st.session_state.docsearch = embedding(st.session_state.jd)
     else:
+        print("Using resume for embedding...")
         st.session_state.docsearch = embedding(resume_reader(st.session_state.resume))
 
-    #if 'retriever' not in st.session_state:
+    print("Creating retriever...")
     st.session_state.retriever = st.session_state.docsearch.as_retriever(search_type="similarity")
-    #if 'chain_type_kwargs' not in st.session_state:
+
     if 'jd' in st.session_state:
+        print("Using job description prompt template...")
         Interview_Prompt = PromptTemplate(input_variables=["context", "question"],
-                                              template=template)
+                                          template=template)
         st.session_state.chain_type_kwargs = {"prompt": Interview_Prompt}
     else:
-            st.session_state.chain_type_kwargs = prompt_sector(position, templates)
-    #if 'memory' not in st.session_state:
+        print("Using position-specific prompt template...")
+        st.session_state.chain_type_kwargs = prompt_sector(position, templates)
+
+    print("Creating memory...")
     st.session_state.memory = ConversationBufferMemory()
-    # interview history
-    #if "history" not in st.session_state:
+
+    print("Initializing history and token count...")
     st.session_state.history = []
-    # token count
-    #if "token_count" not in st.session_state:
     st.session_state.token_count = 0
-    #if "guideline" not in st.session_state:
-    llm = ChatOpenAI(
-            model_name="gpt-3.5-turbo",
-            temperature=0.6, )
-    st.session_state.guideline = RetrievalQA.from_chain_type(
-            llm=llm,
-            chain_type_kwargs=st.session_state.chain_type_kwargs, chain_type='stuff',
-            retriever=st.session_state.retriever, memory=st.session_state.memory).run(
-            "Create an interview guideline and prepare only one questions for each topic. Make sure the questions tests the technical knowledge")
-    # llm chain and memory
-    #if "screen" not in st.session_state:
-    llm = ChatOpenAI(
-            model_name="gpt-3.5-turbo",
-            temperature=0.8, )
-    PROMPT = PromptTemplate(
-            input_variables=["history", "input"],
-            template="""I want you to act as an interviewer strictly following the guideline in the current conversation.
 
-                            Ask me questions and wait for my answers like a real person.
-                            Do not write explanations.
-                            Ask question like a real person, only one question at a time.
-                            Do not ask the same question.
-                            Do not repeat the question.
-                            Do ask follow-up questions if necessary. 
-                            You name is GPTInterviewer.
-                            I want you to only reply as an interviewer.
-                            Do not write all the conversation at once.
-                            If there is an error, point it out.
+    print("Creating guideline...")
+    llm = ChatOpenAI(model_name="gpt-3.5-turbo", temperature=0.6)
+    st.session_state.guideline = RetrievalQA.from_chain_type(
+        llm=llm,
+        chain_type_kwargs=st.session_state.chain_type_kwargs,
+        chain_type='stuff',
+        retriever=st.session_state.retriever,
+        memory=st.session_state.memory
+    ).run("Create an interview guideline and prepare only one questions for each topic. Make sure the questions tests the technical knowledge")
 
-                            Current Conversation:
-                            {history}
+    print("Creating screen chain...")
+    llm = ChatOpenAI(model_name="gpt-3.5-turbo", temperature=0.8)
+    PROMPT = PromptTemplate(
+        input_variables=["history", "input"],
+        template="""I want you to act as an interviewer strictly following the guideline in the current conversation.
+                        Ask me questions and wait for my answers like a real person.
+                        Do not write explanations.
+                        Ask question like a real person, only one question at a time.
+                        Do not ask the same question.
+                        Do not repeat the question.
+                        Do ask follow-up questions if necessary. 
+                        You name is GPTInterviewer.
+                        I want you to only reply as an interviewer.
+                        Do not write all the conversation at once.
+                        If there is an error, point it out.
+                        Current Conversation:
+                        {history}
+                        Candidate: {input}
+                        AI: """)
+    st.session_state.screen = ConversationChain(prompt=PROMPT, llm=llm, memory=st.session_state.memory)
 
-                            Candidate: {input}
-                            AI: """)
-    st.session_state.screen = ConversationChain(prompt=PROMPT, llm=llm,
-                                                    memory=st.session_state.memory)
-    #if "feedback" not in st.session_state:
-    llm = ChatOpenAI(
-        model_name = "gpt-3.5-turbo",
-        temperature = 0.5,)
+    print("Creating feedback chain...")
+    llm = ChatOpenAI(model_name="gpt-3.5-turbo", temperature=0.5)
     st.session_state.feedback = ConversationChain(
-            prompt=PromptTemplate(input_variables = ["history", "input"], template = templates.feedback_template),
-            llm=llm,
-            memory = st.session_state.memory,
-        )
+        prompt=PromptTemplate(input_variables=["history", "input"], template=templates.feedback_template),
+        llm=llm,
+        memory=st.session_state.memory,
+    )
+
+    print("Session state initialized.")