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import streamlit as st | |
import os | |
import streamlit.components.v1 as components | |
from io import BytesIO | |
import requests | |
import ast | |
from langchain import PromptTemplate | |
from langchain.chains import RetrievalQA | |
from langchain.vectorstores import Chroma | |
from langchain.embeddings import SentenceTransformerEmbeddings | |
from bardapi import Bard | |
from typing import Any, List, Mapping, Optional | |
import yaml | |
with open("config.yml", "r") as ymlfile: | |
cfg = yaml.safe_load(ymlfile) | |
os.environ['_BARD_API_KEY'] = cfg["API_KEY"]["Bard"] | |
from langchain.llms.base import LLM | |
from langchain.callbacks.manager import CallbackManagerForLLMRun | |
class BardLLM(LLM): | |
def _llm_type(self) -> str: | |
return "custom" | |
def _call( | |
self, | |
prompt: str, | |
stop: Optional[List[str]] = None, | |
run_manager: Optional[CallbackManagerForLLMRun] = None, | |
) -> str: | |
response = Bard(token=os.environ['_BARD_API_KEY']).get_answer(prompt)['content'] | |
return response | |
def _identifying_params(self) -> Mapping[str, Any]: | |
"""Get the identifying parameters.""" | |
return {} | |
def get_image(url): | |
r = requests.get(url) | |
return BytesIO(r.content) | |
# Define global variables | |
embeddings = None | |
index = None | |
QUESTION_PROMPT = None | |
qa = None | |
result = [] | |
# Custom session state class for managing pagination | |
class SessionState: | |
def __init__(self): | |
self.page_index = 0 # Initialize page index | |
self.database_loaded = False # Initialize database loaded state | |
# Create a session state object | |
session_state = SessionState() | |
# Define the search function outside of Search_Property | |
def display_search_results(result, start_idx, end_idx): | |
if result: | |
st.subheader("Search Results:") | |
for idx in range(start_idx, end_idx): | |
if idx >= len(result): | |
break | |
property_info = result[idx] | |
st.markdown(f"**Result {idx + 1}**") | |
# Display property information | |
if 'Image URL' in property_info.metadata and property_info.metadata['Image URL'] is not None and not isinstance(property_info.metadata['Image URL'], float): | |
image_path_urls = property_info.metadata['Image URL'] | |
if image_path_urls is not None and not isinstance(image_path_urls, float): | |
# Convert the string to a Python list | |
imageUrls = ast.literal_eval(image_path_urls) | |
# Now, imageUrls is a list of strings | |
st.image(imageUrls[0],width=700) | |
st.markdown(f"🏡 {property_info.metadata['Title']}") | |
if 'Location' in property_info.metadata and property_info.metadata['Location'] is not None and not isinstance(property_info.metadata['Location'], float): | |
st.write(f"📍 Address: {property_info.metadata['Location']}") | |
if 'Area' in property_info.metadata and property_info.metadata['Area'] is not None and not isinstance(property_info.metadata['Area'], float): | |
st.markdown(f"📏 Size: {property_info.metadata['Area']}") | |
if 'Price' in property_info.metadata and property_info.metadata['Price'] is not None and not isinstance(property_info.metadata['Price'], float): | |
st.markdown(f"💰 Price: {property_info.metadata['Price']} ") | |
st.markdown(f"📅 Published Date: {property_info.metadata['Time stamp']}") | |
col3, col4 = st.columns([2, 1]) | |
with col3: | |
with st.expander("Full Property Information"): | |
st.write(f"🏡 Property Title: {property_info.metadata['Title']}") | |
if 'Area' in property_info.metadata and property_info.metadata['Area'] is not None and not isinstance(property_info.metadata['Area'], float): | |
st.write(f"📏 Size: {property_info.metadata['Area']}") | |
if 'Category' in property_info.metadata and property_info.metadata['Category'] is not None and not isinstance(property_info.metadata['Category'], float): | |
st.write(f"🏢 Category: {property_info.metadata['Category']}") | |
if 'Description' in property_info.metadata and property_info.metadata['Description'] is not None and not isinstance(property_info.metadata['Description'], float): | |
st.write(f"📝 Description: {property_info.metadata['Description']}") | |
if 'Price' in property_info.metadata and property_info.metadata['Price'] is not None and not isinstance(property_info.metadata['Price'], float): | |
st.write(f"💰 Price: {property_info.metadata['Price']}") | |
st.write(f"📅 Date: {property_info.metadata['Time stamp']}") | |
if 'Location' in property_info.metadata and property_info.metadata['Location'] is not None and not isinstance(property_info.metadata['Location'], float): | |
st.write(f"📍 Address: {property_info.metadata['Location']}") | |
st.write(f"🆔 ID: {property_info.metadata['ID']}") | |
if 'Estate type' in property_info.metadata and property_info.metadata['Estate type'] is not None and not isinstance(property_info.metadata['Estate type'], float): | |
st.write(f"🏠 Housing Type: {property_info.metadata['Estate type']}") | |
if 'Email' in property_info.metadata and property_info.metadata['Email'] is not None and not isinstance(property_info.metadata['Email'], float): | |
st.write(f"✉️ Email: {property_info.metadata['Email']}") | |
if 'Mobile Phone' in property_info.metadata and property_info.metadata['Mobile Phone'] is not None and not isinstance(property_info.metadata['Mobile Phone'], float): | |
st.write(f"📞 Phone: {property_info.metadata['Mobile Phone']}") | |
if 'Certification status' in property_info.metadata and property_info.metadata['Certification status'] is not None and not isinstance(property_info.metadata['Certification status'], float): | |
st.write(f"🏆 Certification status: {property_info.metadata['Certification status']}") | |
if 'Direction' in property_info.metadata and property_info.metadata['Direction'] is not None and not isinstance(property_info.metadata['Direction'], float): | |
st.write(f"🧭 Direction: {property_info.metadata['Direction']}") | |
if 'Rooms' in property_info.metadata and property_info.metadata['Rooms'] is not None and not isinstance(property_info.metadata['Rooms'], float): | |
st.write(f"🚪 Rooms: {property_info.metadata['Rooms']}") | |
if 'Bedrooms' in property_info.metadata and property_info.metadata['Bedrooms'] is not None and not isinstance(property_info.metadata['Bedrooms'], float): | |
st.write(f"🛏️ Bedrooms: {property_info.metadata['Bedrooms']}") | |
if 'Kitchen' in property_info.metadata and property_info.metadata['Kitchen'] is not None and not isinstance(property_info.metadata['Kitchen'], float): | |
st.write(f"🍽️ Kitchen: {property_info.metadata['Kitchen']}") | |
if 'Living room' in property_info.metadata and property_info.metadata['Living room'] is not None and not isinstance(property_info.metadata['Living room'], float): | |
st.write(f"🛋️ Living room: {property_info.metadata['Living room']}") | |
if 'Bathrooms' in property_info.metadata and property_info.metadata['Bathrooms'] is not None and not isinstance(property_info.metadata['Bathrooms'], float): | |
st.write(f"🚽 Bathrooms: {property_info.metadata['Bathrooms']}") | |
if 'Front width' in property_info.metadata and property_info.metadata['Front width'] is not None and not isinstance(property_info.metadata['Front width'], float): | |
st.write(f"📐 Front width: {property_info.metadata['Front width']}") | |
if 'Floor' in property_info.metadata and property_info.metadata['Floor'] is not None and not isinstance(property_info.metadata['Floor'], float): | |
st.write(f"🧱 Floor: {property_info.metadata['Floor']}") | |
if 'Parking Slot' in property_info.metadata and property_info.metadata['Parking Slot'] is not None and not isinstance(property_info.metadata['Parking Slot'], float): | |
st.write(f"🚗 Parking Slot: {property_info.metadata['Parking Slot']}") | |
if 'Seller name' in property_info.metadata and property_info.metadata['Seller name'] is not None and not isinstance(property_info.metadata['Seller name'], float): | |
st.write(f"👤 Seller Name: {property_info.metadata['Seller name']}") | |
if 'Seller type' in property_info.metadata and property_info.metadata['Seller type'] is not None and not isinstance(property_info.metadata['Seller type'], float): | |
st.write(f"👨💼 Seller type: {property_info.metadata['Seller type']}") | |
if 'Seller Address' in property_info.metadata and property_info.metadata['Seller Address'] is not None and not isinstance(property_info.metadata['Seller Address'], float): | |
st.write(f"📌 Seller Address: {property_info.metadata['Seller Address']}") | |
if 'Balcony Direction' in property_info.metadata and property_info.metadata['Balcony Direction'] is not None and not isinstance(property_info.metadata['Balcony Direction'], float): | |
st.write(f"🌄 Balcony Direction: {property_info.metadata['Balcony Direction']}") | |
if 'Furniture' in property_info.metadata and property_info.metadata['Furniture'] is not None and not isinstance(property_info.metadata['Furniture'], float): | |
st.write(f"🛋️ Furniture: {property_info.metadata['Furniture']}") | |
if 'Toilet' in property_info.metadata and property_info.metadata['Toilet'] is not None and not isinstance(property_info.metadata['Toilet'], float): | |
st.write(f"🚽 Toilet: {property_info.metadata['Toilet']}") | |
with col4: | |
st.empty() | |
if 'Image URL' in property_info.metadata and property_info.metadata['Image URL'] is not None and not isinstance(property_info.metadata['Image URL'], float): | |
imageCarouselComponent = components.declare_component("image-carousel-component", path="./frontend/public") | |
image_path_urls = property_info.metadata['Image URL'] | |
if image_path_urls is not None and not isinstance(image_path_urls, float): | |
# Convert the string to a Python list | |
imageUrls = ast.literal_eval(image_path_urls) | |
if len(imageUrls) > 1: | |
selectedImageUrl = imageCarouselComponent(imageUrls=imageUrls, height=200) | |
if selectedImageUrl is not None: | |
st.image(selectedImageUrl) | |
# Add a divider after displaying property info | |
st.markdown("<hr style='border: 2px solid white'>", unsafe_allow_html=True) # Horizontal rule as a divider | |
def Search_Property(): | |
global embeddings, index, result, QUESTION_PROMPT, qa | |
st.title("🏘️ Property Search ") | |
# Load data and create the search | |
if not session_state.database_loaded: | |
st.info("Loading database... This may take a moment.") | |
embeddings = SentenceTransformerEmbeddings(model_name="keepitreal/vietnamese-sbert") | |
# Create a Chroma object with persistence | |
db = Chroma(persist_directory="./chroma_index_1", embedding_function=embeddings) | |
# Get documents from the database | |
db.get() | |
llm=BardLLM() | |
qa = RetrievalQA.from_chain_type( | |
llm=llm, | |
chain_type="stuff", | |
retriever=db.as_retriever(search_type="similarity", search_kwargs={"k":4}), | |
return_source_documents=True) | |
question_template = """ | |
Context: You are a helpful and informative bot that answers questions posed below using provided context.\ | |
You have to be truthful. Do not recommend or propose any infomation of the properties.\ | |
Be sure to respond in a complete sentence, being comprehensive, including all information in the provided context.\ | |
Imagine you're talking to a friend and use natural language and phrasing.\ | |
You can only use Vietnamese do not use other languages. | |
QUESTION: '{question}' | |
ANSWER: | |
""" | |
QUESTION_PROMPT = PromptTemplate( | |
template=question_template, input_variables=["question"] | |
) | |
session_state.database_loaded = True | |
if session_state.database_loaded: | |
col1, col2 = st.columns([2, 1]) # Create a two-column layout | |
with col1: | |
query = st.text_input("Enter your property search query:") | |
search_button = st.button("Search", help="Click to start the search") | |
if search_button: | |
if not query: | |
st.warning("Please input your query") | |
else: | |
with st.spinner("Searching..."): | |
if query is not None: # Check if model_embedding is not None | |
qa.combine_documents_chain.llm_chain.prompt = QUESTION_PROMPT | |
qa.combine_documents_chain.verbose = True | |
qa.return_source_documents = True | |
results = qa({"query":query,}) | |
result = results["source_documents"] | |
session_state.page_index = 0 # Reset page index when a new search is performed | |
with col2: | |
if len(result) > 0: | |
st.info(f'Total Results: {len(result)} properties found.') # Display "Total Results" in the second column | |
if result: | |
N = 5 | |
prev_button, next_button = st.columns([4,1]) | |
last_page = len(result) // N | |
# Update page index based on button clicks | |
if prev_button.button("Previous", key="prev_button"): | |
if session_state.page_index - 1 < 0: | |
session_state.page_index = last_page | |
else: | |
session_state.page_index -= 1 | |
if next_button.button("Next", key="next_button"): | |
if session_state.page_index > last_page: | |
st.warning("Displayed all results") | |
session_state.page_index = 0 | |
else: | |
session_state.page_index += 1 | |
# Calculate the range of results to display (5 properties at a time) | |
start_idx = session_state.page_index * N | |
end_idx = (1 + session_state.page_index) * N | |
# Display results for the current page | |
display_search_results(result, start_idx, end_idx) | |