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import streamlit as st | |
import pandas as pd | |
from appStore.prep_data import process_giz_worldwide, remove_duplicates | |
from appStore.prep_utils import create_documents, get_client | |
from appStore.embed import hybrid_embed_chunks | |
from appStore.search import hybrid_search | |
from appStore.region_utils import load_region_data, get_country_name, get_regions | |
from appStore.tfidf_extraction import extract_top_keywords | |
from torch import cuda | |
import json | |
from datetime import datetime | |
# get the device to be used eithe gpu or cpu | |
device = 'cuda' if cuda.is_available() else 'cpu' | |
st.set_page_config(page_title="SEARCH IATI",layout='wide') | |
st.title("GIZ Project Database") | |
var = st.text_input("Enter Search Query") | |
# Load the region lookup CSV | |
region_lookup_path = "docStore/regions_lookup.csv" | |
region_df = load_region_data(region_lookup_path) | |
#################### Create the embeddings collection and save ###################### | |
# the steps below need to be performed only once and then commented out any unnecssary compute over-run | |
##### First we process and create the chunks for relvant data source | |
#chunks = process_giz_worldwide() | |
##### Convert to langchain documents | |
#temp_doc = create_documents(chunks,'chunks') | |
##### Embed and store docs, check if collection exist then you need to update the collection | |
collection_name = "giz_worldwide" | |
#hybrid_embed_chunks(docs= temp_doc, collection_name = collection_name) | |
################### Hybrid Search ###################################################### | |
client = get_client() | |
print(client.get_collections()) | |
# Get all unique sub-regions | |
_, unique_sub_regions = get_regions(region_df) | |
# Fetch unique country codes and map to country names | |
def get_country_name_and_region_mapping(_client, collection_name, region_df): | |
results = hybrid_search(_client, "", collection_name) | |
country_set = set() | |
for res in results[0] + results[1]: | |
countries = res.payload.get('metadata', {}).get('countries', "[]") | |
try: | |
country_list = json.loads(countries.replace("'", '"')) | |
# Only add codes of length 2 | |
two_digit_codes = [code.upper() for code in country_list if len(code) == 2] | |
country_set.update(two_digit_codes) | |
except json.JSONDecodeError: | |
pass | |
# Create a mapping of {CountryName -> ISO2Code} and {ISO2Code -> SubRegion} | |
country_name_to_code = {} | |
iso_code_to_sub_region = {} | |
for code in country_set: | |
name = get_country_name(code, region_df) | |
sub_region_row = region_df[region_df['alpha-2'] == code] | |
sub_region = sub_region_row['sub-region'].values[0] if not sub_region_row.empty else "Not allocated" | |
country_name_to_code[name] = code | |
iso_code_to_sub_region[code] = sub_region | |
return country_name_to_code, iso_code_to_sub_region | |
# Get country name and region mappings | |
client = get_client() | |
country_name_mapping, iso_code_to_sub_region = get_country_name_and_region_mapping(client, collection_name, region_df) | |
unique_country_names = sorted(country_name_mapping.keys()) # List of country names | |
# Layout filters in columns | |
col1, col2, col3, col4 = st.columns([1, 1, 1, 4]) | |
# Region filter | |
with col1: | |
region_filter = st.selectbox("Region", ["All/Not allocated"] + sorted(unique_sub_regions)) # Display region names | |
# Dynamically filter countries based on selected region | |
if region_filter == "All/Not allocated": | |
filtered_country_names = unique_country_names # Show all countries if no region is selected | |
else: | |
filtered_country_names = [ | |
name for name, code in country_name_mapping.items() if iso_code_to_sub_region.get(code) == region_filter | |
] | |
# Country filter | |
with col2: | |
country_filter = st.selectbox("Country", ["All/Not allocated"] + filtered_country_names) # Display filtered country names | |
# Year range slider | |
with col3: | |
current_year = datetime.now().year | |
default_start_year = current_year - 5 # Default to 5 years ago | |
end_year_range = st.slider( | |
"Project End Year", | |
min_value=2010, | |
max_value=2030, | |
value=(default_start_year, current_year) | |
) | |
# Checkbox to control whether to show only exact matches | |
show_exact_matches = st.checkbox("Show only exact matches", value=False) | |
button = st.button("Refresh Search") | |
def filter_results(results, country_filter, region_filter, end_year_range): | |
filtered = [] | |
for r in results: | |
metadata = r.payload.get('metadata', {}) | |
countries = metadata.get('countries', "[]") | |
end_year_val = float(metadata.get('end_year', 0)) | |
# Convert countries to a list | |
try: | |
c_list = json.loads(countries.replace("'", '"')) | |
c_list = [code.upper() for code in c_list if len(code) == 2] | |
except json.JSONDecodeError: | |
c_list = [] | |
# Translate selected country name to iso2 | |
selected_iso_code = country_name_mapping.get(country_filter, None) | |
# Check if any country in the metadata matches the selected region | |
if region_filter != "All/Not allocated": | |
countries_in_region = [code for code in c_list if iso_code_to_sub_region.get(code) == region_filter] | |
else: | |
countries_in_region = c_list | |
# Filtering | |
if ( | |
(country_filter == "All/Not allocated" or selected_iso_code in c_list) | |
and (region_filter == "All/Not allocated" or countries_in_region) | |
and (end_year_range[0] <= end_year_val <= end_year_range[1]) | |
): | |
filtered.append(r) | |
return filtered | |
if button: | |
# 1) Use a bigger limit so we get more than 10 results | |
results = hybrid_search(client, var, collection_name, limit=500) # e.g., 100 or 200 | |
# results is a tuple: (semantic_results, lexical_results) | |
semantic_all = results[0] | |
lexical_all = results[1] | |
# 2) Filter the entire sets | |
filtered_semantic = filter_results(semantic_all, country_filter, region_filter, end_year_range) | |
filtered_lexical = filter_results(lexical_all, country_filter, region_filter, end_year_range) | |
filtered_semantic_no_dupe = remove_duplicates(filtered_semantic) | |
filtered_lexical_no_dupe = remove_duplicates(filtered_lexical) | |
# 3) Now we take the top 10 *after* filtering | |
# Check user preference | |
if show_exact_matches: | |
st.write(f"Showing **Top 10 Lexical Search results** for query: {var}") | |
# Show the top 10 from filtered_lexical | |
for res in filtered_lexical_no_dupe[:10]: | |
project_name = res.payload['metadata'].get('project_name', 'Project Link') | |
url = res.payload['metadata'].get('url', '#') | |
st.markdown(f"#### [{project_name}]({url})") | |
# Snippet logic (80 words) | |
full_text = res.payload['page_content'] | |
words = full_text.split() | |
preview_word_count = 80 | |
preview_text = " ".join(words[:preview_word_count]) | |
remainder_text = " ".join(words[preview_word_count:]) | |
st.write(preview_text + ("..." if remainder_text else "")) | |
# Keywords | |
top_keywords = extract_top_keywords(full_text, top_n=5) | |
if top_keywords: | |
st.markdown(f"_{' · '.join(top_keywords)}_") | |
# Metadata | |
metadata = res.payload.get('metadata', {}) | |
countries = metadata.get('countries', "[]") | |
client_name = metadata.get('client', 'Unknown Client') | |
start_year = metadata.get('start_year', None) | |
end_year_ = metadata.get('end_year', None) | |
try: | |
c_list = json.loads(countries.replace("'", '"')) | |
country_names = [get_country_name(code.upper(), region_df) for code in c_list if len(code) == 2] | |
except json.JSONDecodeError: | |
country_names = [] | |
start_year_str = f"{int(round(float(start_year)))}" if start_year else "Unknown" | |
end_year_str = f"{int(round(float(end_year_)))}" if end_year_ else "Unknown" | |
additional_text = ( | |
f"**{', '.join(country_names)}**, commissioned by **{client_name}**, **{start_year_str}-{end_year_str}**" | |
) | |
st.markdown(additional_text) | |
st.divider() | |
else: | |
st.write(f"Showing **Top 10 Semantic Search results** for query: {var}") | |
# Show the top 10 from filtered_semantic | |
for res in filtered_semantic_no_dupe[:10]: | |
project_name = res.payload['metadata'].get('project_name', 'Project Link') | |
url = res.payload['metadata'].get('url', '#') | |
st.markdown(f"#### [{project_name}]({url})") | |
# Snippet logic | |
full_text = res.payload['page_content'] | |
words = full_text.split() | |
preview_word_count = 80 | |
preview_text = " ".join(words[:preview_word_count]) | |
remainder_text = " ".join(words[preview_word_count:]) | |
st.write(preview_text + ("..." if remainder_text else "")) | |
# Keywords | |
top_keywords = extract_top_keywords(full_text, top_n=5) | |
if top_keywords: | |
st.markdown(f"_{' · '.join(top_keywords)}_") | |
# Metadata | |
metadata = res.payload.get('metadata', {}) | |
countries = metadata.get('countries', "[]") | |
client_name = metadata.get('client', 'Unknown Client') | |
start_year = metadata.get('start_year', None) | |
end_year_ = metadata.get('end_year', None) | |
try: | |
c_list = json.loads(countries.replace("'", '"')) | |
country_names = [get_country_name(code.upper(), region_df) for code in c_list if len(code) == 2] | |
except json.JSONDecodeError: | |
country_names = [] | |
start_year_str = f"{int(round(float(start_year)))}" if start_year else "Unknown" | |
end_year_str = f"{int(round(float(end_year_)))}" if end_year_ else "Unknown" | |
additional_text = ( | |
f"**{', '.join(country_names)}**, commissioned by **{client_name}**, **{start_year_str}-{end_year_str}**" | |
) | |
st.markdown(additional_text) | |
st.divider() | |
# for i in results: | |
# st.subheader(str(i.metadata['id'])+":"+str(i.metadata['title_main'])) | |
# st.caption(f"Status:{str(i.metadata['status'])}, Country:{str(i.metadata['country_name'])}") | |
# st.write(i.page_content) | |
# st.divider() | |