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| import streamlit as st | |
| # from models_api import get_answer, get_hugging_face_answer | |
| from models_api import get_answer_from_context | |
| # Define Streamlit app | |
| def main(): | |
| st.title("Document Analysis Tool") | |
| # File upload | |
| uploaded_file = st.file_uploader("Upload a text file", type=["txt"]) | |
| if uploaded_file: | |
| file_contents = uploaded_file.read().decode("utf-8") | |
| st.text_area("File Content", file_contents, height=200) | |
| # User input question | |
| question = st.text_input("Enter your question") | |
| if st.button("Generate Llama 3 8b Response"): | |
| if question: | |
| st.write("Response from Llama3 8b:") | |
| answer_llama3 = get_answer_from_context(model_name="llama3-8b-8192",context= file_contents, question=question) | |
| # answer_llama3 = get_answer("llama3", file_contents, question) | |
| # answer_llama3 = get_hugging_face_answer("meta-llama/Meta-Llama-3-8B-Instruct", file_contents, question) | |
| st.write(answer_llama3) | |
| if st.button("Generate Mistral 7b Response"): | |
| if question: | |
| st.write("Response from Mistral 7b:") | |
| answer_mistral8x7b = get_answer_from_context(model_name="mixtral-8x7b-32768",context= file_contents, question=question) | |
| # answer_mistral7b = get_answer("mistral", file_contents, question) | |
| # # answer_mistral7b = get_hugging_face_answer("mistralai/Mistral-7B-Instruct-v0.1", file_contents, question) | |
| st.write(answer_mistral8x7b) | |
| if st.button("Generate Gemma 7b Response"): | |
| if question: | |
| st.write("Response from Gemma 7b:") | |
| # # answer_gemma7b = get_answer("gemma", file_contents, question) | |
| answer_gemma7b = get_answer_from_context(model_name="gemma-7b-it",context= file_contents, question=question) | |
| # answer_gemma7b = get_hugging_face_answer("google/gemma-7b-it", file_contents, question) | |
| st.write(answer_gemma7b) | |
| # Run Streamlit app | |
| if __name__ == "__main__": | |
| main() |