richardorama commited on
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61944f0
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1 Parent(s): f2ef415

Update app.py

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Files changed (1) hide show
  1. app.py +70 -30
app.py CHANGED
@@ -10,43 +10,83 @@ import ast
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  st.title("Assorted Language Tools - AI Craze")
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- ################ CHAT BOT #################
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- # Load the GPT model
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- generator = pipeline("text-generation", model="EleutherAI/gpt-neo-2.7B")
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- # Streamlit chat UI
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- #st.title("GPT-3 Chatbox")
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- # user_input = st.text_input("You: ", "Hello, how are you?")
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- # if user_input:
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- # response = generator(user_input, max_length=100, num_return_sequences=1)[0]['generated_text']
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- # st.write(f"GPT-3: {response}")
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- # Define the summarization function
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- def chat(txt):
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- st.write('\n\n')
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- #st.write(txt[:100]) # Display the first 100 characters of the article
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- #st.write('--------------------------------------------------------------')
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- #summary = summarizer(txt, max_length=500, min_length=30, do_sample=False)
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- #st.write(summary[0]['summary_text'])
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- response = generator(txt, max_length=500, num_return_sequences=1)[0]['generated_text']
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- st.write(f"GPT-3: {response}")
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- DEFAULT_CHAT = ""
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- # Create a text area for user input
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- CHAT = st.sidebar.text_area('Enter Chat (String)', DEFAULT_CHAT, height=150)
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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- # Enable the button only if there is text in the CHAT variable
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- if CHAT:
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- if st.sidebar.button('Chat Statement'):
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- # Call your Summarize function here
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- chat(CHAT) # Directly pass the your
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- else:
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- st.sidebar.button('Chat Statement', disabled=True)
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- st.warning('👈 Please enter Chat!')
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-
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  ################ STATEMENT SUMMARIZATION #################
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  st.title("Assorted Language Tools - AI Craze")
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+ # ################ CHAT BOT #################
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+ # # Load the GPT model
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+ # generator = pipeline("text-generation", model="EleutherAI/gpt-neo-2.7B")
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+ # # Streamlit chat UI
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+ # #st.title("GPT-3 Chatbox")
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+ # # user_input = st.text_input("You: ", "Hello, how are you?")
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+ # # if user_input:
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+ # # response = generator(user_input, max_length=100, num_return_sequences=1)[0]['generated_text']
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+ # # st.write(f"GPT-3: {response}")
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+ # # Define the summarization function
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+ # def chat(txt):
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+ # st.write('\n\n')
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+ # #st.write(txt[:100]) # Display the first 100 characters of the article
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+ # #st.write('--------------------------------------------------------------')
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+ # #summary = summarizer(txt, max_length=500, min_length=30, do_sample=False)
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+ # #st.write(summary[0]['summary_text'])
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+ # response = generator(txt, max_length=500, num_return_sequences=1)[0]['generated_text']
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+ # st.write(f"GPT-3: {response}")
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+ # DEFAULT_CHAT = ""
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+ # # Create a text area for user input
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+ # CHAT = st.sidebar.text_area('Enter Chat (String)', DEFAULT_CHAT, height=150)
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+
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+ # # Enable the button only if there is text in the CHAT variable
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+ # if CHAT:
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+ # if st.sidebar.button('Chat Statement'):
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+ # # Call your Summarize function here
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+ # chat(CHAT) # Directly pass the your
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+ # else:
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+ # st.sidebar.button('Chat Statement', disabled=True)
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+ # st.warning('👈 Please enter Chat!')
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+
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+
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+ import streamlit as st
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+ from transformers import pipeline, GPT2Tokenizer, GPT2LMHeadModel
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+
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+ # Load pre-trained GPT-2 model and tokenizer
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+ model_name = "gpt2" # Use "gpt-3.5-turbo" or another model from Hugging Face if needed
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+ model = GPT2LMHeadModel.from_pretrained(model_name)
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+ tokenizer = GPT2Tokenizer.from_pretrained(model_name)
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+
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+ # Initialize the text generation pipeline
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+ gpt_pipeline = pipeline("text-generation", model=model, tokenizer=tokenizer)
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+
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+ # Streamlit UI
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+ st.title("Chat with GPT-2")
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+
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+ if 'conversation' not in st.session_state:
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+ st.session_state.conversation = ""
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+
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+ def chat_with_gpt(user_input):
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+ # Append user input to the conversation
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+ st.session_state.conversation += f"User: {user_input}\n"
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+
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+ # Generate response
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+ response = gpt_pipeline(user_input, max_length=100, num_return_sequences=1)[0]['generated_text']
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+ response_text = response.replace(user_input, '') # Strip the user input part from response
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+
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+ # Append GPT's response to the conversation
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+ st.session_state.conversation += f"GPT: {response_text}\n"
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+ return response_text
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+
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+ # Text input for user query
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+ user_input = st.text_input("You:", "")
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+
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+ if st.button("Send"):
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+ if user_input:
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+ chat_with_gpt(user_input)
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+
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+ # Display conversation history
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+ st.text_area("Conversation", value=st.session_state.conversation, height=400)
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  ################ STATEMENT SUMMARIZATION #################
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