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Final fixes
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SiddhantH1512 committed Feb 27, 2024
1 parent 0ed8757 commit 510d65a
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Showing 4 changed files with 9 additions and 10 deletions.
9 changes: 4 additions & 5 deletions Capstone/streamlit-app/main_app.py
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Expand Up @@ -5,9 +5,9 @@
import base64
import os

# Ensure your AWS credentials are set in your environment or in ~/.aws/credentials
st.set_page_config(page_title="Welcome to the World of Homes", layout="wide")

local_image_path = '/app/files/pickled_image.pkl' # Path inside Docker
local_image_path = '/app/files/pickled_image.pkl'

def s3_download(s3_bucket, s3_file_key, local_file_path):
try:
Expand Down Expand Up @@ -61,10 +61,9 @@ def add_bg_from_local(image_file):
'''
st.markdown(page_bg_img, unsafe_allow_html=True)

add_bg_from_local(local_image_path) # Adjust the path to the image
add_bg_from_local(local_image_path)


# Additional Streamlit app content
st.set_page_config(page_title="Welcome to the World of Homes", layout="wide")
st.markdown("""
<div>
<h1>Welcome to the World of Homes</h1>
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4 changes: 2 additions & 2 deletions Capstone/streamlit-app/pages/1_Predictor.py
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Expand Up @@ -51,10 +51,10 @@ def download_file_from_s3(bucket_name, s3_key, local_path):

if pipeline is not None and df is not None:
# Your code here
st.title("Enter your requirements to get a quote")
st.title("Price Estimate 💸")


st.header("Enter your input")
st.header("Enter your inputs to get a quote")

# TYPE OF PROPERTY
property_type = st.selectbox('Property Type', df["property_type"].unique().tolist())
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2 changes: 1 addition & 1 deletion Capstone/streamlit-app/pages/2_Analytics.py
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Expand Up @@ -58,7 +58,7 @@ def s3_download(s3_bucket, s3_file_path, local_file):
wordcloud_data = pickle.load(file)


st.title("Analysis")
st.title("Analysis 📈")

# STREAMLIT LAYOUT
st.header("Sector wise price per sqft map")
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4 changes: 2 additions & 2 deletions Capstone/streamlit-app/pages/3_Recommender.py
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Expand Up @@ -55,7 +55,7 @@ def s3_download(s3_bucket, s3_file_path, local_file):


# DROP DOWN FOR LOCATIONS
st.title("Select a location and radius")
st.title("Select a location and radius 📍")
location = st.selectbox("Locations", sorted(locationdf.columns.tolist()))
radius = st.number_input("Radius (kms)")

Expand Down Expand Up @@ -91,7 +91,7 @@ def recommend_properties_with_scores2(property_name, top_n=5):
return new_recommendations_df

# DROP DOWN FOR APARTMENTS
st.title("Select an apartment")
st.title("Select an apartment 🏠")
apartment = st.selectbox("Apartments", sorted(locationdf.index.tolist()))

if st.button("Recommend"):
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