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Upload app_working.py
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app_working.py
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import streamlit as st
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from llama_cpp import Llama
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llm = Llama.from_pretrained(
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repo_id="Mykes/med_gemma7b_gguf",
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filename="*Q4_K_M.gguf",
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verbose=False
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)
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basic_prompt = "Below is the context which is your conversation history and the last user question. Write a response according the context and question. ### Context: user: Ответь мне на вопрос о моем здоровье. assistant: Конечно! Какой у Вас вопрос? ### Question: {question} ### Response:"
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def generate_response(question):
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model_input = basic_prompt.format(question=input_text)
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if question:
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output = llm(
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model_input, # Prompt
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max_tokens=32, # Generate up to 32 tokens, set to None to generate up to the end of the context window
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stop=["<end_of_turn>"],
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echo=False # Echo the prompt back in the output
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) # Generate a completion, can also call create_completion
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st.write(output["choices"][0]["text"])
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else:
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st.write("Please enter a question to get a response.")
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input_text = st.text_input('Задайте мне медицинский вопрос...')
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# Button to trigger response generation
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if st.button('Generate Response'):
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generate_response(input_text)
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