Create app.py

app.py

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+# app.py
+
+import streamlit as st
+import random
+import pandas as pd
+import time
+import speech_recognition as sr
+from openai import OpenAI
+from PyPDF2 import PdfReader
+import langchain
+from langchain.text_splitter import RecursiveCharacterTextSplitter
+from langchain.vectorstores import FAISS
+from langchain.embeddings.openai import OpenAIEmbeddings
+from langchain.chains import RetrievalQA
+from langchain.chat_models import ChatOpenAI
+from langchain.embeddings import HuggingFaceEmbeddings
+
+
+# Set DeepSeek API Key
+api_key = "0f33d8a8b7714460bc4b8335b66d217a"
+base_url = "https://api.aimlapi.com/v1"
+
+# Initialize OpenAI client
+api = OpenAI(api_key=api_key, base_url=base_url)
+
+# Generate 300 Dummy Messages with Severity Levels
+severities = ["High", "Medium", "Low"]
+messages = [
+    {"message": f"Disaster Alert {i}", "severity": random.choice(severities)}
+    for i in range(300)
+]
+df = pd.DataFrame(messages)
+
+# Streamlit UI
+st.set_page_config(page_title="BDRS", layout="wide")
+
+st.title("🌍 BeaconAi Disaster Response System")
+st.write("Real-time disaster response with DeepSeek AI-powered chatbot & voice recognition.")
+
+# Live-updating Disaster Message Dashboard
+st.subheader("📊 Social Media Monitoring")
+chart_placeholder = st.empty()
+
+# Function to Randomly Pick 5 Messages
+def get_random_messages():
+    return df.sample(5)
+
+
+# Placeholder for chart
+chart_placeholder = st.empty()
+
+# Define severity categories
+severities = ["Low", "Medium", "High"]
+
+# Function to update chart
+def update_chart():
+    selected_messages = get_random_messages()
+    severity_counts = selected_messages["severity"].value_counts().reindex(severities, fill_value=0)
+
+    # Create DataFrame
+    chart_data = pd.DataFrame({"Severity": severities, "Count": severity_counts.values})
+
+    # Update the chart
+    chart_placeholder.bar_chart(chart_data, x="Severity", y="Count", use_container_width=True)
+
+# Auto-refresh every second
+st.button("Refresh Data", on_click=st.rerun)
+
+update_chart()
+
+
+
+# PDF Processing for Chatbot Context (Pre-Provided PDF)
+pdf_path = "/content/Natural Disaster Safety Manual.pdf"  # Ensure this file is in the same directory as app.py
+
+pdf_reader = PdfReader(pdf_path)
+raw_text = ""
+for page in pdf_reader.pages:
+    raw_text += page.extract_text() + "\n"
+
+# Convert to Embeddings for Retrieval
+text_splitter = RecursiveCharacterTextSplitter(chunk_size=500, chunk_overlap=50)
+texts = text_splitter.split_text(raw_text)
+embeddings = HuggingFaceEmbeddings(model_name="sentence-transformers/all-MiniLM-L6-v2")
+vector_db = FAISS.from_texts(texts, embeddings)
+retriever = vector_db.as_retriever()
+
+# LangGraph-Powered Q&A System
+chat_model = ChatOpenAI(model="deepseek-chat", api_key=api_key, base_url=base_url)
+qa = RetrievalQA.from_chain_type(llm=chat_model, chain_type="stuff", retriever=retriever)
+
+# Chatbot UI
+st.subheader("🤖 AI-Powered Disaster Chatbot")
+user_query = st.text_input("Ask the chatbot:")
+
+if user_query:
+    response = qa.run(user_query)
+    st.write("**Chatbot Response:**", response)
+
+
+# Voice Recognition for Non-English Users
+st.subheader("🎙️ Voice Recognition (Speech-to-Text)")
+
+if st.button("Start Recording"):
+    recognizer = sr.Recognizer()
+    with sr.Microphone() as source:
+        st.write("Listening...")
+        audio = recognizer.listen(source)
+
+    try:
+        recognized_text = recognizer.recognize_google(audio)
+        st.write("**Recognized Text:**", recognized_text)
+    except sr.UnknownValueError:
+        st.write("Sorry, could not understand.")
+    except sr.RequestError:
+        st.write("Could not request results. Check your internet connection.")
+
+# Disaster Guide Dropdown
+st.subheader("🌪️ Disaster Preparedness Guide")
+
+disaster_options = {
+    "Wildfire": {
+        "steps": [
+            "Evacuate if ordered.",
+            "Keep emergency supplies ready.",
+            "Close all doors and windows."
+        ],
+        "video": "https://www.youtube.com/watch?v=OCjl6tp8dnw"
+    },
+    "Earthquake": {
+        "steps": [
+            "Drop, Cover, and Hold On.",
+            "Stay indoors until shaking stops.",
+            "Move away from windows."
+        ],
+        "video": "https://www.youtube.com/watch?v=BLEPakj1YTY"
+    },
+    "Flood": {
+        "steps": [
+            "Move to higher ground.",
+            "Avoid walking or driving through floodwaters.",
+            "Stay tuned to emergency alerts."
+        ],
+        "video": "https://www.youtube.com/watch?v=43M5mZuzHF8"
+    }
+}
+
+selected_disaster = st.selectbox("Select a disaster type:", list(disaster_options.keys()))
+
+if selected_disaster:
+    st.write("### 🛠 Steps to Follow:")
+    for step in disaster_options[selected_disaster]["steps"]:
+        st.write(f"- {step}")
+
+    st.write("📺 [Watch Video Guide]({})".format(disaster_options[selected_disaster]["video"]))
+
+st.write("🚀 Stay prepared and stay safe!")