Update src/streamlit_app.py

src/streamlit_app.py

@@ -1,40 +1,42 @@
-import altair as alt
-import numpy as np
-import pandas as pd
 import streamlit as st
+from library_summarizer import llm_lib_summarizer_v1
+from command_generator import llm_lib_installer_v1
+
+st.title("📂 Compatible Library Summarizer")
+
+imported_libraries = st.text_area("Enter the libraries you are importing in your ipynb file:", height=200)
+api_key = st.text_input("Enter your Groq API Key:", type="password")
+task = st.text_input("Enter the task you are working on (e.g., data analysis, machine learning):", value="Basic ML task")
+python_version = st.selectbox("Select your Python version:", options=["3.7", "3.8", "3.9", "3.10", "3.11","3.12"], index=3)
+
+# File uploader widget
+uploaded_file = st.file_uploader("Choose a file", type=["txt"])
+
+if uploaded_file is not None:
+    st.success(f"File uploaded: {uploaded_file.name}")
+
+    # Read the file (decode for text files)
+    
+if st.button("Generate bash command"):
+    if imported_libraries and uploaded_file:
+        library = imported_libraries
+        libraries = uploaded_file.read().decode("utf-8")
+        with st.spinner("Summarizing imported libraries"):
+            try:
+                summary = llm_lib_summarizer_v1(import_string=library, api_key=api_key)
+                st.subheader("Summary of Libraries:")
+                st.code(summary)
+
+            except Exception as e:
+                st.error(f"An error occurred: {e}")
+                
+        with st.spinner("Generating ideal pip install command..."):    
+            try:
+                st.subheader(f"Generated pip install command for python version {python_version}")
+                command = llm_lib_installer_v1(imported_libs=summary, python_version=python_version, task=task, api_key=api_key, libraries=libraries)
+                st.markdown(command)
+            except Exception as e:
+                st.error(f"An error occurred: {e}")
+    else:
+        st.error("Please enter text or upload a file.")
 
-"""
-# Welcome to Streamlit!
-
-Edit `/streamlit_app.py` to customize this app to your heart's desire :heart:.
-If you have any questions, checkout our [documentation](https://docs.streamlit.io) and [community
-forums](https://discuss.streamlit.io).
-
-In the meantime, below is an example of what you can do with just a few lines of code:
-"""
-
-num_points = st.slider("Number of points in spiral", 1, 10000, 1100)
-num_turns = st.slider("Number of turns in spiral", 1, 300, 31)
-
-indices = np.linspace(0, 1, num_points)
-theta = 2 * np.pi * num_turns * indices
-radius = indices
-
-x = radius * np.cos(theta)
-y = radius * np.sin(theta)
-
-df = pd.DataFrame({
-    "x": x,
-    "y": y,
-    "idx": indices,
-    "rand": np.random.randn(num_points),
-})
-
-st.altair_chart(alt.Chart(df, height=700, width=700)
-    .mark_point(filled=True)
-    .encode(
-        x=alt.X("x", axis=None),
-        y=alt.Y("y", axis=None),
-        color=alt.Color("idx", legend=None, scale=alt.Scale()),
-        size=alt.Size("rand", legend=None, scale=alt.Scale(range=[1, 150])),
-    ))