legolasyiu commited on
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0757831
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1 Parent(s): 0a48bf2

Update app.py

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  1. app.py +3 -41
app.py CHANGED
@@ -2,46 +2,8 @@ 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 Agemt ChatBot"
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- description = "A State-of-the-Art Agent Chatbot"
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- examples = [["How are you?"]]
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-
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-
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- tokenizer = AutoTokenizer.from_pretrained("EpistemeAI/Fireball-Meta-Llama-3.1-8B-Instruct-Agent-0.003-128K")
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- model = AutoModelForCausalLM.from_pretrained("EpistemeAI/Fireball-Meta-Llama-3.1-8B-Instruct-Agent-0.003-128K")
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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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- 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()
 
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  import gradio as gr
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  import torch
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+ import gradio as gr
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+ demo = gr.load("EpistemeAI/Fireball-Meta-Llama-3.1-8B-Instruct-Agent-0.003-128K-code", src="models")
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ demo.launch()