Update app.py
Browse files
app.py
CHANGED
@@ -54,42 +54,41 @@ units = st.slider(
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# for message in st.session_state.messages:
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# with st.chat_message(message["role"]):
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# st.markdown(message["content"])
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assistant = st.chat_message("assistant")
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initial_message = "How can I help you today?"
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def assistant_response(response):
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message_placeholder = assistant.empty()
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full_response = ""
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assistant_response = response
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# Simulate stream of response with milliseconds delay
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for chunk in assistant_response.split():
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full_response += chunk + " "
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time.sleep(0.05)
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# Add a blinking cursor to simulate typing
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message_placeholder.markdown(full_response + "▌")
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message_placeholder.markdown(full_response)
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# Add assistant response to chat history
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st.session_state.messages.append({"role": "assistant", "content": full_response})
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if "messages" not in st.session_state:
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st.session_state.messages = []
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if prompt := st.chat_input("What kind of class are you looking for?"):
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st.session_state.messages.append({"role": "user", "content": prompt})
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for message in st.session_state.messages:
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with st.chat_message(message["role"]):
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st.markdown(message["content"])
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)
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assistant = st.chat_message("assistant")
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initial_message = "How can I help you today?"
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if "messages" not in st.session_state:
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st.session_state.messages = []
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with st.chat_message("assistant"):
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st.markdown(initial_message)
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st.session_state.messages.append({"role": "assistant", "content": initial_message})
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if prompt := st.chat_input("What kind of class are you looking for?"):
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st.session_state.messages.append({"role": "user", "content": prompt})
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with st.chat_message("user"):
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st.markdown(message["content"])
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with st.chat_message("assistant"):
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message_placeholder = st.empty()
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full_response = ""
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response = filter_agent(prompt, OPENAI_API)
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query = response
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response = index.query(
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vector = embeddings.embed_query(query),
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top_k = 25,
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include_metadata = True
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)
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response = reranker(query, response)
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result_query = 'Original Query:' + query + 'Query Results:' + str(response)
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assistant_response = results_agent(result_query, OPENAI_API)
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for chunk in assistant_response.split():
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full_response += chunk + " "
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time.sleep(0.05)
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message_placeholder.markdown(full_response + "▌")
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message_placeholder.markdown(full_response)
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st.session_state.messages.append({"role": "assistant", "content": full_response})
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