app.py

import streamlit as st
import pandas as pd
from appStore.prep_data import process_giz_worldwide, remove_duplicates, get_max_end_year, extract_year
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 either 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 (PROTOTYPE)")
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 ######################
# Uncomment these lines to process and embed your data only once.
# chunks = process_giz_worldwide()
# temp_doc = create_documents(chunks, 'chunks')
collection_name = "giz_worldwide"
# hybrid_embed_chunks(docs=temp_doc, collection_name=collection_name, del_if_exists=True)

################### Hybrid Search ######################################################
client = get_client()
print(client.get_collections())

# Get the maximum end_year across the entire collection
max_end_year = get_max_end_year(client, collection_name)

# Get all unique sub-regions
_, unique_sub_regions = get_regions(region_df)

# Fetch unique country codes and map to country names
@st.cache_data
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))

# Dynamically filter countries based on selected region
if region_filter == "All/Not allocated":
    filtered_country_names = unique_country_names
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)

# ToDo: Add year filter later if needed (currently commented out)
# with col3:
#     current_year = datetime.now().year
#     default_start_year = current_year - 5
#     end_year_range = st.slider(
#         "Project End Year",
#         min_value=2010,
#         max_value=max_end_year,
#         value=(default_start_year, max_end_year),
#     )

# Checkbox to control whether to show only exact matches
show_exact_matches = st.checkbox("Show only exact matches", value=False)

def filter_results(results, country_filter, region_filter):
    filtered = []
    for r in results:
        metadata = r.payload.get('metadata', {})
        countries = metadata.get('countries', "[]")
        year_str = metadata.get('end_year')
        if year_str:
            extracted = extract_year(year_str)
            try:
                end_year_val = int(extracted) if extracted != "Unknown" else 0
            except ValueError:
                end_year_val = 0
        else:
            end_year_val = 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

        if (
            (country_filter == "All/Not allocated" or selected_iso_code in c_list)
            and (region_filter == "All/Not allocated" or countries_in_region)
        ):
            filtered.append(r)
    return filtered

# Run the search 
results = hybrid_search(client, var, collection_name, limit=500)
semantic_all = results[0]
lexical_all = results[1]

# Filter out very short content
semantic_all = [r for r in semantic_all if len(r.payload["page_content"]) >= 5]
lexical_all = [r for r in lexical_all if len(r.payload["page_content"]) >= 5]

# Apply a threshold to SEMANTIC results (score >= 0.0)
semantic_thresholded = [r for r in semantic_all if r.score >= 0.0]

filtered_semantic = filter_results(semantic_thresholded, country_filter, region_filter)
filtered_lexical = filter_results(lexical_all, country_filter, region_filter)

filtered_semantic_no_dupe = remove_duplicates(filtered_semantic)
filtered_lexical_no_dupe = remove_duplicates(filtered_lexical)

# Define a helper function to format currency values
def format_currency(value):
    try:
        # Convert to float then int for formatting (assumes whole numbers)
        return f"€{int(float(value)):,}"
    except (ValueError, TypeError):
        return value

#  Display Results
if show_exact_matches:
    st.write(f"Showing **Top 15 Lexical Search results** for query: {var}")

    query_substring = var.strip().lower()
    lexical_substring_filtered = []
    for r in lexical_all:
        if query_substring in r.payload["page_content"].lower():
            lexical_substring_filtered.append(r)

    filtered_lexical = filter_results(lexical_substring_filtered, country_filter, region_filter)
    filtered_lexical_no_dupe = remove_duplicates(filtered_lexical)

    if not filtered_lexical_no_dupe:
        st.write('No exact matches, consider unchecking "Show only exact matches"')
    else:
        for res in filtered_lexical_no_dupe[:15]:
            metadata = res.payload.get('metadata', {})
            # Get title and id; do not format as a link.
            project_name = metadata.get('project_name', 'Project Link')
            proj_id = metadata.get('id', 'Unknown')
            st.markdown(f"#### {project_name} [{proj_id}]")

            # Build snippet from objectives and descriptions.
            objectives = metadata.get("objectives", "")
            desc_de = metadata.get("description.de", "")
            desc_en = metadata.get("description.en", "")
            description = desc_de if desc_de else desc_en
            full_snippet = f"Objective: {objectives} Description: {description}"
            preview_limit = 400  # preview limit in characters
            preview_snippet = full_snippet if len(full_snippet) <= preview_limit else full_snippet[:preview_limit] + "..."
            # Using HTML to add a tooltip with the full snippet text.
            st.markdown(f'<span title="{full_snippet}">{preview_snippet}</span>', unsafe_allow_html=True)

            # Keywords remain the same.
            full_text = res.payload['page_content']
            top_keywords = extract_top_keywords(full_text, top_n=5)
            if top_keywords:
                st.markdown(f"_{' · '.join(top_keywords)}_")

            # Metadata: get client, duration and budget details.
            client_name = metadata.get('client', 'Unknown Client')
            start_year = metadata.get('start_year', None)
            end_year = metadata.get('end_year', None)
            total_volume = metadata.get('total_volume', "Unknown")
            total_project = metadata.get('total_project', "Unknown")

            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"

            formatted_project_budget = format_currency(total_project)
            formatted_total_volume = format_currency(total_volume)

            additional_text = (
                f"Commissioned by **{client_name}**\n"
                f"Projekt duration **{start_year_str}-{end_year_str}**\n"
                f"Budget: Project: **{formatted_project_budget}**, total volume: **{formatted_total_volume}**"
            )
            st.markdown(additional_text)
            st.divider()

else:
    st.write(f"Showing **Top 15 Semantic Search results** for query: {var}")
    
    if not filtered_semantic_no_dupe:
        st.write("No relevant results found.")
    else:
        for res in filtered_semantic_no_dupe[:15]:
            metadata = res.payload.get('metadata', {})
            project_name = metadata.get('project_name', 'Project Link')
            proj_id = metadata.get('id', 'Unknown')
            st.markdown(f"#### {project_name} [{proj_id}]")

            # Build snippet from objectives and descriptions.
            objectives = metadata.get("objectives", "")
            desc_de = metadata.get("description.de", "")
            desc_en = metadata.get("description.en", "")
            description = desc_de if desc_de else desc_en
            full_snippet = f"Objective: {objectives} Description: {description}"
            preview_limit = 400
            preview_snippet = full_snippet if len(full_snippet) <= preview_limit else full_snippet[:preview_limit] + "..."
            st.markdown(f'<span title="{full_snippet}">{preview_snippet}</span>', unsafe_allow_html=True)

            # Keywords
            full_text = res.payload['page_content']
            top_keywords = extract_top_keywords(full_text, top_n=5)
            if top_keywords:
                st.markdown(f"_{' · '.join(top_keywords)}_")

            client_name = metadata.get('client', 'Unknown Client')
            start_year = metadata.get('start_year', None)
            end_year = metadata.get('end_year', None)
            total_volume = metadata.get('total_volume', "Unknown")
            total_project = metadata.get('total_project', "Unknown")

            start_year_str = extract_year(start_year) if start_year else "Unknown"
            end_year_str = extract_year(end_year) if end_year else "Unknown"

            formatted_project_budget = format_currency(total_project)
            formatted_total_volume = format_currency(total_volume)

            additional_text = (
                f"Commissioned by **{client_name}**\n"
                f"Projekt duration **{start_year_str}-{end_year_str}**\n"
                f"Budget: Project: **{formatted_project_budget}**, total volume: **{formatted_total_volume}**"
            )
            st.markdown(additional_text)
            st.divider()

# Uncomment the following lines if you need to debug by listing raw results.
# 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()