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db72c4b
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Update app.py

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  1. app.py +44 -4
app.py CHANGED
@@ -1,7 +1,47 @@
 
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  import gradio as gr
 
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- def greet(name):
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- return "Hello " + name + "!!"
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- iface = gr.Interface(fn=greet, inputs="text", outputs="text")
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- iface.launch()
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ from transformers import AutoModelForCausalLM, AutoTokenizer
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  import gradio as gr
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+ import torch
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+ title = "????AI ChatBot"
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+ description = "A State-of-the-Art Large-scale Pretrained Response generation model (DialoGPT)"
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+ examples = [["How are you?"]]
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+
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+
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+ tokenizer = AutoTokenizer.from_pretrained("microsoft/DialoGPT-large")
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+ model = AutoModelForCausalLM.from_pretrained("microsoft/DialoGPT-large")
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+
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+
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+ def predict(input, history=[]):
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+ # tokenize the new input sentence
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+ new_user_input_ids = tokenizer.encode(
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+ input + tokenizer.eos_token, return_tensors="pt"
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+ )
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+
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+ # append the new user input tokens to the chat history
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+ bot_input_ids = torch.cat([torch.LongTensor(history), new_user_input_ids], dim=-1)
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+
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+ # generate a response
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+ history = model.generate(
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+ bot_input_ids, max_length=4000, pad_token_id=tokenizer.eos_token_id
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+ ).tolist()
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+
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+ # convert the tokens to text, and then split the responses into lines
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+ response = tokenizer.decode(history[0]).split("<|endoftext|>")
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+ # print('decoded_response-->>'+str(response))
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+ response = [
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+ (response[i], response[i + 1]) for i in range(0, len(response) - 1, 2)
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+ ] # convert to tuples of list
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+ # print('response-->>'+str(response))
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+ return response, history
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+
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+
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+ gr.Interface(
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+ fn=predict,
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+ title=title,
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+ description=description,
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+ examples=examples,
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+ inputs=["text", "state"],
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+ outputs=["chatbot", "state"],
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+ theme="finlaymacklon/boxy_violet",
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+ ).launch()