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import streamlit as st
import os
from typing import List, Tuple, Optional
from pinecone import Pinecone
from langchain_pinecone import PineconeVectorStore
from langchain_huggingface import HuggingFaceEmbeddings
from langchain_openai import ChatOpenAI
from langchain_core.prompts import PromptTemplate
from dotenv import load_dotenv
from RAG import RAG
import logging
from image_scraper import DigitalCommonwealthScraper
import shutil
# Configure logging
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)
# Page configuration
st.set_page_config(
page_title="Boston Public Library Chatbot",
page_icon="π€",
layout="wide"
)
def initialize_models() -> Tuple[Optional[ChatOpenAI], HuggingFaceEmbeddings]:
"""Initialize the language model and embeddings."""
try:
load_dotenv()
if "llm" not in st.session_state:
# Initialize OpenAI model
st.session_state.llm = ChatOpenAI(
model="gpt-3.5-turbo",
temperature=0,
timeout=60, # Added reasonable timeout
max_retries=2
)
if "embeddings" not in st.session_state:
# Initialize embeddings
st.session_state.embeddings = HuggingFaceEmbeddings(
model_name="sentence-transformers/all-mpnet-base-v2"
#model_name="sentence-transformers/all-MiniLM-L6-v2"
)
if "pinecone" not in st.session_state:
pinecone_api_key = os.getenv("PINECONE_API_KEY")
INDEX_NAME = 'bpl-test'
#initialize vectorstore
pc = Pinecone(api_key=pinecone_api_key)
index = pc.Index(INDEX_NAME)
st.session_state.pinecone = PineconeVectorStore(index=index, embedding=st.session_state.embeddings)
if "vectorstore" not in st.session_state:
#st.session_state.vectorstore = CloudSQLVectorStore(embedding=st.session_state.embeddings)
st.session_state.vectorstore = st.session_state.pinecone
except Exception as e:
logger.error(f"Error initializing models: {str(e)}")
st.error(f"Failed to initialize models: {str(e)}")
return None, None
def process_message(
query: str,
llm: ChatOpenAI,
vectorstore: PineconeVectorStore,
) -> Tuple[str, List]:
"""Process the user message using the RAG system."""
try:
response, sources = RAG(
query=query,
llm=llm,
vectorstore=vectorstore,
)
return response, sources
except Exception as e:
logger.error(f"Error in process_message: {str(e)}")
return f"Error processing message: {str(e)}", []
def display_sources(sources: List) -> None:
"""Display sources with minimal output: content preview, source, URL, and image/audio if available."""
if not sources:
st.info("No sources available for this response.")
return
st.subheader("Sources")
for doc in sources:
try:
metadata = doc.metadata
source = metadata.get("source", "Unknown Source")
title = metadata.get("title_info_primary_tsi", "Unknown Title")
format_type = metadata.get("format", "").lower()
is_audio = "audio" in format_type
expander_title = f"π {title}" if is_audio else title
with st.expander(expander_title):
# Content preview
if hasattr(doc, 'page_content'):
st.markdown(f"**Content:** {doc.page_content[:300]} ...")
# URL building
doc_url = metadata.get("URL", "").strip()
if not doc_url and source:
doc_url = f"https://www.digitalcommonwealth.org/search/{source}"
st.markdown(f"**Source ID:** {source}")
st.markdown(f"**Format:** {format_type if format_type else 'Not specified'}")
st.markdown(f"**URL:** {doc_url}")
# π Try to show audio if it's an audio entry and there's a media file
if is_audio:
# Try to find a playable media file β if metadata has audio URLs
# For now, just embed a dummy player or placeholder
st.info("This is an audio entry.")
# Optionally:
# st.audio("https://example.com/audio-file.mp3") # replace with real audio URL
else:
# πΌοΈ Show image if it's not audio
scraper = DigitalCommonwealthScraper()
images = scraper.extract_images(doc_url)
images = images[:1]
if images:
output_dir = 'downloaded_images'
if os.path.exists(output_dir):
shutil.rmtree(output_dir)
downloaded_files = scraper.download_images(images)
st.image(downloaded_files, width=400, caption=[
img.get('alt', f'Image') for img in images
])
except Exception as e:
logger.warning(f"[display_sources] Error displaying document: {e}")
st.error("Error displaying one of the sources.")
def main():
st.title("Digital Commonwealth RAG π€")
INDEX_NAME = 'bpl-rag'
# Initialize session state
if "messages" not in st.session_state:
st.session_state.messages = []
if "show_settings" not in st.session_state:
st.session_state.show_settings = False
if "num_sources" not in st.session_state:
st.session_state.num_sources = 10
initialize_models()
# π΅ Settings button
open_settings = st.button("βοΈ Settings")
if open_settings:
st.session_state.show_settings = True
if st.session_state.show_settings:
with st.container():
st.markdown("---")
st.markdown("### βοΈ Settings")
num_sources = st.number_input(
"Number of Sources to Display",
min_value=1,
max_value=100,
value=st.session_state.num_sources,
step=1,
)
st.session_state.num_sources = num_sources
close_settings = st.button("β Close Settings")
if close_settings:
st.session_state.show_settings = False
st.markdown("---")
# Show chat history
for message in st.session_state.messages:
with st.chat_message(message["role"]):
st.markdown(message["content"])
# β¬οΈ CHAT INPUT BOX always stuck to bottom
user_input = st.chat_input("Type your question here...")
if user_input:
with st.chat_message("user"):
st.markdown(user_input)
st.session_state.messages.append({"role": "user", "content": user_input})
with st.chat_message("assistant"):
with st.spinner("Thinking... Please be patient..."):
response, sources = process_message(
query=user_input,
llm=st.session_state.llm,
vectorstore=st.session_state.vectorstore
)
if isinstance(response, str):
st.markdown(response)
st.session_state.messages.append({
"role": "assistant",
"content": response
})
display_sources(sources[:int(st.session_state.num_sources)])
else:
st.error("Received an invalid response format")
# Footer (optional, will be above chat input)
st.markdown("---")
st.markdown(
"Built with Langchain + Streamlit + Pinecone",
help="Natural Language Querying for Digital Commonwealth"
)
st.markdown(
"The Digital Commonwealth site provides access to photographs, manuscripts, books, "
"audio recordings, and other materials of historical interest that have been digitized "
"and made available by members of Digital Commonwealth."
)
if __name__ == "__main__":
main() |