Update app.py

app.py

@@ -1,26 +1,116 @@
 # app.py
+
+from wordcloud import WordCloud  ## Mr.Shen: Using a wordcloud library to show the key-words of the article 
 import streamlit as st
 from utils import * 
 
-st.header("AI Output: Summarizer")
 
-txt = st.text_area('Copy and paste your text here', 
-                   max_chars = 4000,
-                   key="input_text")
-st.write(txt)
+#### Define some sidebar functions and layouts here ####
+with st.sidebar: 
+    openai_api_key = st.text_input("OpenAI API Key", key="chatbot_api_key", type="password")
+    "[How to get your openai API key?](https://elephas.app/blog/how-to-get-chatgpt-api-key-clh93ii2e1642073tpacu6w934j)" ## Mr.Shen: Add a superlink to show how to get an Openai API key
+    "[![Visit out Huggingface Space](https://huggingface.co/datasets/huggingface/badges/raw/main/powered-by-huggingface-light.svg)](https://huggingface.co/TGSAI)"
+
+
+#### The main layouts start here ####
+
+### Input section start ###
+    
+st.title("📝 Summarizer")
+
+txt = st.text_area('Copy and paste your text here',
+                   height = 20,
+                   max_chars = 3000,
+                   key="txt")
+
+topics = st.text_input('Choose topics, seperated by ,', value= '', key='topics')
+
+word_count = st.slider('The maximum number of words of summary.', min_value = 10, max_value = 200, value = 20, key = 'word_count')
+
+## We will need two buttons, one for chat with ChatGPT, another for the free hugchat with lower quality. ##
+col1, col2 = st.columns(2)  ## This is how we put widgets in one row.
+
+with col1:
+    st.button('with ChatGPT', key='chatgpt')
+with col2:
+    st.button('with HugChat', key='hugchat')
+
+### Input section end ###
+
+### Function section Start ###
+    
+## Now we need to pass those input variables to our prompt ##
+prompt = f"""
+Your task is to generate a short summary from text below, delimited by triple backticks, in at most {word_count} words,\
+Firstly, extract relevant information and create a list of keywords without response,\
+Then, check if {topics} is in your list, if not, just response no relevent topics about {topics} to summarise,\
+if it is in your list, focusing on any aspects that mention {topics},
+```{txt}```
+"""  
+response = ''  ## Initilise the response as an empty string
+
+# Handling the "chat with ChatGPT" button clicked
+if st.session_state.chatgpt:
+
+    # Making sure user entering the OpenaAI API Key
+    if not st.session_state.chatbot_api_key:
+        st.info("Please add your OpenAI API key to continue.")
+        st.stop()
+        
+    openai.api_key = st.session_state.chatbot_api_key
+    response, token_dic, moderation = get_completion(prompt) ## Get the moderation, cost, and response from one function
+
+    # Compute cost
+    input_cost = token_dic['prompt_tokens']*0.0015/1000; 
+    output_cost=token_dic['completion_tokens']*0.002/1000
+    total_cost = input_cost + output_cost
+
+    # Moderation
+    mod = pd.DataFrame(moderation)
+    fig_r = get_radar(mod)  ## Generate the moderation radar graph
+
+# Wordcloud and sentiment analysis:
+if txt:
+    wordcloud = WordCloud(background_color='white', min_font_size=3, mode ='RGBA',min_word_length=1).generate(txt)
+    df, fig_s = get_sentiment(txt)
+    
+### Function section End ###
+
+### Output section Start ###
+
+## Wordcloud ##
+st.markdown(":violet[Wordcloud: ]")
+if wordcloud:
+    st.pyplot(plot_wordcloud(wordcloud))
+
+st.write("##")
 
-topics = st.text_input('Choose topics, seperated by ,', '')
-st.write(topics)
+## Sentiment Analysis ##
+st.markdown(":violet[Sentiment Analysis: ]")
+if df:
+    st.plotly_chart(fig_s)
+    st.dataframe(df)
 
+st.markdown("##### :blue[Summarizer with ChatGPT: ]")
+st.markdown(f"###### :black[{response}]")
+    
+## Moderation ##
+st.markdown("##### :blue[Content moderation: ]")
+if fig_r:
+    st.plotly_chart(fig)    
 
-st.subheader("Word count")
-word_count = st.slider("How long would you like your summary?", 10, 200)
-st.write("Word count:", word_count)
+## Cost of summarisation ## 
+if total_cost:
+    st.text("Total cost for this query: " + "$" + str(total_cost))
 
-password = st.text_input('Enter your password', max_chars=50, type="password")  # changed st.text_input with type="password"
-st.write(password)
+st.divider()
 
+### Summarise with ChatGPT ###
+if st.session_state.chatgpt:
+    st.markdown("##### :blue[Summarizer with ChatGPT: ]")
+    st.markdown(f"###### :black[{response}]")
+if st.session_state.hugchat:
+    st.write("coming soon ...")
 
-## st.header("Output:", divider=True ## seems like a version conflict here, to-do
+### Output section End ###
 
-st.button("ChatGPT summariser")