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import streamlit as st | |
from utils import load_json, count_tokens | |
import json | |
# Set up the Streamlit page configuration | |
st.set_page_config(page_title="Cintra Code Chunker", layout="wide") | |
def main(): | |
# Streamlit widgets for file selection | |
st.title("Cintra Code Chunker") | |
uploaded_file = st.file_uploader("Choose a file") | |
if uploaded_file is not None: | |
# Displaying the original file content | |
file_content = uploaded_file.getvalue().decode("utf-8") | |
st.text_area("File content", value=file_content, height=250, max_chars=50000) | |
# Input for token chunk size target | |
token_chunk_size = st.slider( | |
"Select token chunk size target", min_value=10, max_value=500, value=100 | |
) | |
# Button to trigger chunking process | |
if st.button("Chunk Code"): | |
# Assuming the existence of a function to chunk code based on token size | |
# This is a placeholder for the actual chunking logic which would likely involve | |
# the 'count_tokens' function from utils.py and some logic to split the code into chunks | |
# For demonstration, we'll just show a message | |
st.success( | |
f"Code has been chunked with a target of {token_chunk_size} tokens per chunk." | |
) | |
# Displaying the chunked code - this would be replaced with actual chunked code display logic | |
st.text_area( | |
"Chunked Code", | |
value="Chunked code would appear here...", | |
height=250, | |
max_chars=50000, | |
) | |
if __name__ == "__main__": | |
main() |