drmasad commited on
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693c6e9
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1 Parent(s): 216f23b

Update app.py

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Files changed (1) hide show
  1. app.py +16 -7
app.py CHANGED
@@ -1,3 +1,10 @@
 
 
 
 
 
 
 
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  # Import necessary libraries
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  import streamlit as st
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  from transformers import AutoModelForCausalLM, AutoTokenizer, BitsAndBytesConfig, pipeline
@@ -41,9 +48,13 @@ st.sidebar.write(f"You're now chatting with **{selected_model}**")
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  st.sidebar.image("https://www.hmgaihub.com/untitled.png")
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  st.sidebar.markdown("*Generated content may be inaccurate or false.*")
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  st.sidebar.markdown("*This is an under development project.*")
 
 
 
 
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  def load_model(selected_model_name):
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- st.info("Loading the model, please wait...")
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  model_name = model_links[selected_model_name]
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  # Define the BitsAndBytesConfig for quantization
@@ -81,13 +92,12 @@ def load_model(selected_model_name):
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  "mistralai/Mistral-7B-Instruct-v0.2", trust_remote_code=True
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  )
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- st.success("Model is ready. Now we are ready!")
 
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  return model, tokenizer
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-
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-
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  # Load model and tokenizer
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  model, tokenizer = load_model(selected_model)
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@@ -106,11 +116,10 @@ if prompt := st.chat_input("Ask me anything about diabetes"):
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  st.session_state.messages.append({"role": "user", "content": prompt})
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  instructions = """
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- Act as a highly knowledgeable endocrinology doctor with expertise in explaining complex medical information in an understandable way to patients who do not have a medical background. Your responses should not only convey empathy and care but also demonstrate a high level of medical accuracy and reliability.
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- you will answer only what the need and in professional way. do not add extra unnecessary information. you can however chat with the patient casually
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  """
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- full_prompt = f"<s>[INST] {instructions} [/INST] {prompt}</s>"
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  with st.chat_message("assistant"):
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  result = pipeline(
 
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+ """
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+ Diabetes Version
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+ @aim: Demo for testing purposes only
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+ @inquiries: Dr M As'ad
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+ @email: [email protected]
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+ """
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+
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  # Import necessary libraries
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  import streamlit as st
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  from transformers import AutoModelForCausalLM, AutoTokenizer, BitsAndBytesConfig, pipeline
 
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  st.sidebar.image("https://www.hmgaihub.com/untitled.png")
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  st.sidebar.markdown("*Generated content may be inaccurate or false.*")
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  st.sidebar.markdown("*This is an under development project.*")
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+ st.sidebar.markdown("*Not a replacement for medical advice from a doctor.*")
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+
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+ # Loading message placeholder
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+ loading_message = st.empty()
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  def load_model(selected_model_name):
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+ loading_message.info("Loading the model, please wait...")
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  model_name = model_links[selected_model_name]
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  # Define the BitsAndBytesConfig for quantization
 
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  "mistralai/Mistral-7B-Instruct-v0.2", trust_remote_code=True
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  )
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+ # Clear the loading message
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+ loading_message.success("Model is ready. Now we are ready!")
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  return model, tokenizer
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  # Load model and tokenizer
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  model, tokenizer = load_model(selected_model)
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  st.session_state.messages.append({"role": "user", "content": prompt})
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  instructions = """
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+ Act as a highly knowledgeable doctor with special interest in diabetes, skilled at explaining complex medical information in a way that is easy to understand for patients without a medical background. Your responses should not only demonstrate empathy and care but also uphold a high standard of medical accuracy and reliability. Respond precisely to what the patient needs in a professional, accurate, and reassuring manner, avoiding any unnecessary information.
 
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  """
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+ full_prompt = f"<s>[INST] {prompt} [/INST] {instructions}</s>"
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  with st.chat_message("assistant"):
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  result = pipeline(