app.py is uploaded here
Browse files
app.py
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import gradio as gr
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import os
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from huggingface_hub import login
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from transformers import AutoModelForSeq2SeqLM, T5Tokenizer
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from peft import PeftModel, PeftConfig
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token = os.environ.get("token")
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login(token)
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print("login is succesful")
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max_length=512
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MODEL_NAME = "google/flan-t5-base"
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tokenizer = T5Tokenizer.from_pretrained(MODEL_NAME, token=token)
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config = PeftConfig.from_pretrained("Orcawise/eu_ai_act_orcawise_july12")
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base_model = AutoModelForSeq2SeqLM.from_pretrained("google/flan-t5-base")
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model = PeftModel.from_pretrained(base_model, "Orcawise/eu_ai_act_orcawise_july12")
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#gr.Interface.from_pipeline(pipe).launch()
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def generate_text(prompt):
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"""Generates text using the PEFT model.
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Args:
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prompt (str): The user-provided prompt to start the generation.
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Returns:
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str: The generated text.
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"""
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# Preprocess the prompt
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# inputs = tokenizer(prompt, return_tensors="pt").to("cuda")
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inputs = tokenizer(prompt, return_tensors="pt")
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# Generate text using beam search
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outputs = model.generate(
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input_ids = inputs["input_ids"],
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max_length=max_length,
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num_beams=5,
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repetition_penalty=1.5,
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temperature=1,
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top_k=100,
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top_p=0.5,
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early_stopping=True
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)
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# Decode the generated tokens
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generated_text = tokenizer.decode(outputs, skip_special_tokens=True)[0]
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print("show the generated text", generated_text)
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return generated_text
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#############
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custom_css="""
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.message.pending {
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background: #A8C4D6;
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}
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/* Response message */
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.message.bot.svelte-1s78gfg.message-bubble-border {
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/* background: white; */
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border-color: #266B99
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}
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/* User message */
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.message.user.svelte-1s78gfg.message-bubble-border{
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background: #9DDDF9;
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border-color: #9DDDF9
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}
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/* For both user and response message as per the document */
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span.md.svelte-8tpqd2.chatbot.prose p {
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color: #266B99;
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}
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/* Chatbot comtainer */
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.gradio-container{
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/* background: #84D5F7 */
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}
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/* RED (Hex: #DB1616) for action buttons and links only */
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.clear-btn {
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background: #DB1616;
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color: white;
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}
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/* #84D5F7 - Primary colours are set to be used for all sorts */
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.submit-btn {
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background: #266B99;
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color: white;
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}
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"""
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### working correctly but the welcoming message isnt rendering
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with gr.Blocks(css=custom_css) as demo:
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chatbot = gr.Chatbot()
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msg = gr.Textbox(placeholder="Ask your question...") # Add placeholder text
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submit_button = gr.Button("Submit", elem_classes="submit-btn")
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clear = gr.Button("Clear", elem_classes="clear-btn")
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def user(user_message, history):
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return "", history + [[user_message, None]]
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def bot(history):
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history[-1][1] = "" # Update the last bot message (welcome message or response)
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if len(history) < 0: # Check if it's the first interaction
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bot_message = "Hi there! How can I help you today?"
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history.append([None, bot_message]) # Add welcome message to history
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for character in bot_message:
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history[-1][1] += character
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yield history # Yield the updated history character by character
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else:
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previous_message = history[-1][0] # Access the previous user message
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bot_message = generate_text(previous_message) # Generate response based on previous message
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for character in bot_message:
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history[-1][1] += character
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yield history # Yield the updated history character by character
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# Connect submit button to user and then bot functions
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submit_button.click(user, [msg, chatbot], [msg, chatbot], queue=False).then(
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bot, chatbot, chatbot
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)
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# Trigger user function on Enter key press (same chain as submit button)
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msg.submit(user, [msg, chatbot], [msg, chatbot], queue=False).then(
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bot, chatbot, chatbot
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)
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clear.click(lambda: None, None, chatbot, queue=False)
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demo.launch()
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