Upload app.py

app.py

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+from openai import OpenAI
+import streamlit as st
+from langchain_openai import ChatOpenAI
+from langchain_openai.embeddings import OpenAIEmbeddings
+from langchain_text_splitters import RecursiveCharacterTextSplitter
+import markdown
+from operator import itemgetter
+from langchain.schema.runnable import RunnablePassthrough
+from langchain_core.prompts import ChatPromptTemplate
+from langchain.schema import Document
+from dotenv import load_dotenv
+from langchain_community.vectorstores import Qdrant
+#from langchain_qdrant import Qdrant
+import os
+import pandas as pd
+import numpy as np
+import datetime
+
+
+# Page config
+from PIL import Image, ImageEnhance
+
+st.set_page_config(
+    page_title="Narrativ 📰",
+    layout="wide",
+    initial_sidebar_state="expanded",
+    page_icon="🔍",
+)
+
+# Load environment variables
+load_dotenv()
+OPENAI_API_KEY = os.environ["OPENAI_API_KEY"]
+base_llm = ChatOpenAI(model="gpt-4o")
+embedding_model = OpenAIEmbeddings(model="text-embedding-3-small")
+
+prompt='I-495'
+date='2025-01-15'
+
+# Custom CSS for centered content
+st.markdown("""
+    <style>
+    .main-container {
+        max-width: 800px;
+        margin: 0 auto;
+        padding: 20px;
+    }
+    
+    .stSelectbox {
+        max-width: 400px;
+        margin: 0 auto;
+    }
+    
+    /* Center all text elements */
+    .centered-text {
+        text-align: center;
+    }
+    </style>
+""", unsafe_allow_html=True)
+
+# Header
+col1, col2, col3, col4,col5 = st.columns([1, 1, 2, 1, 1])
+
+
+with col3:
+    st.markdown("<h1 class='centered-text'>Search Narrativ</h1>", unsafe_allow_html=True)
+    
+with col4:
+    image = Image.open('./data/news_icon.png')
+    st.image(image, width=100, output_format="PNG", clamp=True)
+
+st.markdown("<p class='centered-text'>Enter a topic and optional date to analyze traffic.</p>", unsafe_allow_html=True)
+
+# Suggestions
+topic_suggestions = [
+    "I-495",
+    "I-95",
+    "accident"
+]
+
+data=pd.read_csv('./data/sentiment_index_traffic_index_final1.csv',
+                index_col='index',
+                parse_dates=True
+            )
+
+# Convert the index to datetime, if not already done
+data.index = pd.to_datetime(data.index)
+
+# Generate a sorted list of unique dates
+sorted_dates = sorted(pd.unique(data.index))
+
+# Format the sorted dates as string 'YYYY-MM-DD'
+date_suggestions = [pd.Timestamp(date).strftime('%Y-%m-%d') for date in sorted_dates]
+date_suggestions=np.append('',date_suggestions)
+# Create centered container for search
+# Define the allowed date range
+start_date = datetime.date(2025, 1, 15)
+end_date = datetime.date(2025, 1, 21)
+col1, col2= st.columns([1,1])
+with col1:
+    prompt = st.selectbox(
+        "Topic:",
+        options=[""] + topic_suggestions,
+        index=0,
+        key="topic_select",
+        placeholder="Select or type a topic..."
+    )
+with col2:    
+
+    # date = 
+    #st.date_input(
+    # "Choose a date:", 
+    # # min_value=start_date, 
+    # # max_value=end_date, 
+    # # value=start_date  # Default to start date
+    # )
+    date = st.selectbox(
+        "Date (optional):",
+        options=date_suggestions,
+        index=0,
+        key="date_select",
+        placeholder="Select or type a date..."
+    )
+    date=str(date)
+
+
+# st.write(f"You selected: {date} for the topic: {prompt}.")
+
+col1, col2, col3, col4 = st.columns([1,1,1,1])
+with col2:
+    chat = st.button("chat", key="chat_button", use_container_width=True)
+with col3:
+    tableau=st.button("tableau", key="tableau_button", use_container_width=True)
+
+# Handle search submission
+st.session_state.prompt = prompt
+st.session_state.date = date
+
+if chat:
+    
+    # You can add navigation to results page or display results here
+    st.success(f"Searching for: {prompt} {'on ' + date if date else ''}")
+    # Add your search processing logic here
+    st.switch_page("./pages/chat.py")
+
+if tableau:
+    st.switch_page("./pages/tableau.py")