Update app.py

app.py

@@ -1,3 +1,6 @@
+import time
+print('1')
+print(time.time())
 
 #__import__('pysqlite3')
 #import sys
@@ -66,7 +69,7 @@ print(len(docs))
 def load_model():
     #embeddings = HuggingFaceInstructEmbeddings(model_name="hkunlp/instructor-large",model_kwargs={"device":DEVICE})
     embeddings = HuggingFaceInstructEmbeddings(model_name="sentence-transformers/all-MiniLM-L6-v2",model_kwargs={"device":DEVICE})
-
+    print(DEVICE)
 
     text_splitter = RecursiveCharacterTextSplitter(chunk_size=1024, chunk_overlap=256)
     texts = text_splitter.split_documents(docs)
@@ -134,7 +137,7 @@ def load_model():
     qa_chain = RetrievalQA.from_chain_type(
         llm=llm,
         chain_type="stuff",
-        retriever=db.as_retriever(search_kwargs={"k": 2}),
+        retriever=db.as_retriever(search_kwargs={"k": 5}),
         return_source_documents=True,
         chain_type_kwargs={"prompt": prompt,
                            "verbose": False,
@@ -181,6 +184,8 @@ def get_message_history():
 
 qa_chain = load_model()
 
+print('2')
+print(time.time())
 if prompt := st.chat_input("How can I help you today?"):
     st.session_state.messages.append({"role": "user", "content": prompt})
     with st.chat_message("user"):
@@ -192,7 +197,11 @@ if prompt := st.chat_input("How can I help you today?"):
         logger.info(f"{user_session_id} Message History: {message_history}")
         # question = st.text_input("Ask your question", placeholder="Try to include context in your question",
         # disabled=not uploaded_file,)
+        print('3')
+        print(time.time())
         result = qa_chain(prompt)
+        print('4')
+        print(time.time())
         sound_file = BytesIO()
         tts = gTTS(result['result'], lang='en')
         tts.write_to_fp(sound_file)
@@ -205,7 +214,8 @@ if prompt := st.chat_input("How can I help you today?"):
     #st.write(repr(result['source_documents'][0].metadata['page']))
     #st.write(repr(result['source_documents'][0]))
 
-
+    print('5')
+    print(time.time())
     ### READ IN PDF
     page_number = int(result['source_documents'][0].metadata['page'])
     doc = fitz.open(str(result['source_documents'][0].metadata['source']))
@@ -296,18 +306,18 @@ if prompt := st.chat_input("How can I help you today?"):
     # """
     # message_placeholder.markdown(html_string, unsafe_allow_html=True)  # will display a st.audio with the sound you specified in the "src" of the html_string and autoplay it
     # #time.sleep(5)  # wait for 2 seconds to finish the playing of the audio
-    response_sentiment = st.radio(
-        "How was the Assistant's response?",
-        ["😁", "😕", "😢"],
-        key="response_sentiment",
-        disabled=st.session_state.disabled,
-        horizontal=True,
-        index=1,
-        help="This helps us improve the model.",
-        # hide the radio button on click
-        on_change=on_select(),
-    )
-    logger.info(f"{user_session_id} | {full_response} | {response_sentiment}")
+    #response_sentiment = st.radio(
+    #    "How was the Assistant's response?",
+    #    ["😁", "😕", "😢"],
+    #    key="response_sentiment",
+    #    disabled=st.session_state.disabled,
+    #    horizontal=True,
+    #    index=1,
+    #    help="This helps us improve the model.",
+    #    # hide the radio button on click
+    #   on_change=on_select(),
+    #)
+    #logger.info(f"{user_session_id} | {full_response} | {response_sentiment}")
 
     # # Logging to FastAPI Endpoint
     # headers = {"Authorization": f"Bearer {secret_token}"}