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import streamlit as st |
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from library_summarizer import llm_lib_summarizer_v1 |
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from command_generator import llm_lib_installer_v1 |
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st.title("📂 Compatible Library Version Generator") |
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imported_libraries = st.text_area("Enter the libraries you are importing in your ipynb file:", height=200) |
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api_key = st.text_input("Enter your Groq API Key:", type="password") |
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task = st.text_input("Enter the task you are working on (e.g., data analysis, machine learning):", value="Basic ML task") |
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python_version = st.selectbox("Select your Python version:", options=["3.7", "3.8", "3.9", "3.10", "3.11","3.12"], index=3) |
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with open('libraries.txt','r') as f: |
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libraries = f.read() |
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if st.button("Generate pip command"): |
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if imported_libraries: |
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library = imported_libraries |
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with st.spinner("Summarizing imported libraries"): |
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try: |
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summary = llm_lib_summarizer_v1(import_string=library, api_key=api_key) |
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st.subheader("Summary of Libraries:") |
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st.code(summary) |
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except Exception as e: |
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st.error(f"An error occurred: {e}") |
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with st.spinner("Generating ideal pip install command..."): |
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try: |
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st.subheader(f"Generated pip install command for python version {python_version}") |
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command = llm_lib_installer_v1(imported_libs=summary, python_version=python_version, task=task, api_key=api_key, libraries=libraries) |
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st.markdown(command) |
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except Exception as e: |
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st.error(f"An error occurred: {e}") |
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else: |
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st.error("Please enter the libraries you imported in the colab notebook.") |
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