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Update app.py
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app.py
CHANGED
@@ -2,39 +2,85 @@ import streamlit as st
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from transformers import GPT2Tokenizer, GPT2LMHeadModel
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tokenizer = GPT2Tokenizer.from_pretrained(model_path)
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tokenizer.pad_token = tokenizer.eos_token
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model = GPT2LMHeadModel.from_pretrained(model_path)
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def generate_response(input_text):
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return response
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prompt = st.chat_input(placeholder="Say Something!",key=None, max_chars=None, disabled=False, on_submit=None, args=None, kwargs=None)
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if prompt:
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from transformers import GPT2Tokenizer, GPT2LMHeadModel
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# Function to generate a response
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def generate_response(input_text):
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# Adjusted input to include the [Bot] marker
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#adjusted_input = f"{input_text} [Bot]"
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# Encode the adjusted input
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inputs = tokenizer(input_text, return_tensors="pt")
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# Generate a sequence of text with a slightly increased max_length to account for the prompt length
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output_sequences = model.generate(
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input_ids=inputs['input_ids'],
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attention_mask=inputs['attention_mask'],
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max_length=100, # Adjusted max_length
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temperature=0.7,
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top_k=50,
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top_p=0.95,
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no_repeat_ngram_size=2,
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pad_token_id=tokenizer.eos_token_id,
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#early_stopping=True,
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do_sample=True
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# Decode the generated sequence
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full_generated_text = tokenizer.decode(output_sequences[0], skip_special_tokens=True)
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# Extract the generated response after the [Bot] marker
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bot_response_start = full_generated_text.find('[Bot]') + len('[Bot]')
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bot_response = full_generated_text[bot_response_start:]
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# Trim the response to end at the last period within the specified max_length
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last_period_index = bot_response.rfind('.')
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if last_period_index != -1:
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bot_response = bot_response[:last_period_index + 1]
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return bot_response.strip()
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# Load pre-trained model tokenizer (vocabulary) and model
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model_name = 'KhantKyaw/Chat_GPT-2'
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tokenizer = GPT2Tokenizer.from_pretrained(model_name)
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model = GPT2LMHeadModel.from_pretrained(model_name)
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# Chat loop
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print("Chatbot is ready. Type 'quit' to exit.")
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while True:
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user_input = input("You: ")
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if user_input.lower() == "quit":
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break
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response = generate_response(user_input)
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print("Chatbot:", response)
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st.title("Simple Streamlit Chatbot")
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# User input text box
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user_input = st.text_input("You: ", key="user_input")
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# Button to send the message
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if st.button("Send"):
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# Generating a response
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response = get_response(user_input)
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# Displaying the conversation
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# Here, we use st.session_state to keep track of the conversation
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if 'conversation' not in st.session_state:
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st.session_state.conversation = []
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# Append the user input and bot response to the conversation
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st.session_state.conversation.append("You: " + user_input)
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st.session_state.conversation.append("Bot: " + response)
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# Display each line in the conversation
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for line in st.session_state.conversation:
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st.text(line)
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#prompt = st.chat_input(placeholder="Say Something!",key=None, max_chars=None, disabled=False, on_submit=None, args=None, kwargs=None)
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#if prompt:
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# with st.chat_message(name="AI",avatar=None):
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# st.write(generate_response(prompt))
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