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| import os | |
| import requests | |
| from io import BytesIO | |
| from PyPDF2 import PdfReader | |
| import streamlit as st | |
| import folium | |
| from streamlit_folium import st_folium | |
| from langchain.text_splitter import RecursiveCharacterTextSplitter | |
| from langchain_community.embeddings import HuggingFaceEmbeddings | |
| from langchain_community.vectorstores import FAISS | |
| from groq import Groq | |
| from dotenv import load_dotenv | |
| load_dotenv() | |
| # ------------------------------ | |
| # 🔐 API Keys | |
| # ------------------------------ | |
| OPENWEATHER_API_KEY = os.environ.get("OPENWEATHER_API_KEY") | |
| AQICN_TOKEN = os.environ.get("AQICN_TOKEN") | |
| GROQ_API_KEY = os.environ.get("GROQ_API_KEY") | |
| # ------------------------------ | |
| # ⚙️ Groq Client | |
| # ------------------------------ | |
| def get_groq_client(): | |
| return Groq(api_key=GROQ_API_KEY) | |
| client = get_groq_client() | |
| # ------------------------------ | |
| # 📚 RAG Functions | |
| # ------------------------------ | |
| def get_drive_links(): | |
| return [ | |
| "https://drive.google.com/file/d/1zEM3MxxpWcK9oaWc1GcmhamrGqgPjGig/view?usp=sharing", | |
| "https://drive.google.com/file/d/1Km2a_JzOPLQAyPvpkF3NjuXVU5RXwuZg/view?usp=sharing", | |
| "https://drive.google.com/file/d/1aj6QUMOy-6-idm3242yqxrgnt_7zjgjo/view?usp=sharing", | |
| "https://drive.google.com/file/d/1fmyAoEh_qRiHYvT78cmj4jWLcOcV4Y3K/view?usp=sharing", | |
| "https://drive.google.com/file/d/17-ZSypeJlhIc6B2hsJ_qm5xMMZP2xEWL/view?usp=sharing" | |
| ] | |
| def download_pdf_from_drive(link): | |
| file_id = link.split("/d/")[1].split("/")[0] | |
| url = f"https://drive.google.com/uc?id={file_id}&export=download" | |
| response = requests.get(url) | |
| if response.status_code == 200: | |
| return BytesIO(response.content) | |
| raise Exception("Failed to download PDF.") | |
| def extract_text_from_pdf(pdf_stream): | |
| reader = PdfReader(pdf_stream) | |
| text = "" | |
| for page in reader.pages: | |
| extracted = page.extract_text() | |
| if extracted: | |
| text += extracted | |
| return text | |
| def chunk_text(text, chunk_size=500, chunk_overlap=50): | |
| splitter = RecursiveCharacterTextSplitter( | |
| chunk_size=chunk_size, chunk_overlap=chunk_overlap | |
| ) | |
| return splitter.split_text(text) | |
| def process_all_documents(): | |
| links = get_drive_links() | |
| all_chunks = [] | |
| for link in links: | |
| pdf = download_pdf_from_drive(link) | |
| text = extract_text_from_pdf(pdf) | |
| chunks = chunk_text(text) | |
| all_chunks.extend(chunks) | |
| return all_chunks | |
| def build_vector_db(chunks): | |
| embeddings = HuggingFaceEmbeddings(model_name="sentence-transformers/all-MiniLM-L6-v2") | |
| return FAISS.from_texts(chunks, embedding=embeddings) | |
| def query_vector_db(query, vector_db): | |
| docs = vector_db.similarity_search(query, k=3) | |
| context = "\n".join([doc.page_content for doc in docs]) | |
| completion = client.chat.completions.create( | |
| model="llama3-8b-8192", | |
| messages=[ | |
| {"role": "system", "content": f"Use the following context:\n{context}"}, | |
| {"role": "user", "content": query}, | |
| ] | |
| ) | |
| return completion.choices[0].message.content | |
| # ------------------------------ | |
| # 🛰 Weather & Risk Functions | |
| # ------------------------------ | |
| def get_coordinates(city): | |
| url = f"http://api.openweathermap.org/geo/1.0/direct?q={city}&limit=1&appid={OPENWEATHER_API_KEY}" | |
| res = requests.get(url).json() | |
| if res: | |
| return res[0]['lat'], res[0]['lon'] | |
| return None, None | |
| def get_weather(lat, lon): | |
| url = f"https://api.openweathermap.org/data/2.5/weather?lat={lat}&lon={lon}&appid={OPENWEATHER_API_KEY}&units=metric" | |
| res = requests.get(url).json() | |
| return res['main']['temp'], res['weather'][0]['description'] | |
| def get_aqi(lat, lon): | |
| url = f"https://api.waqi.info/feed/geo:{lat};{lon}/?token={AQICN_TOKEN}" | |
| res = requests.get(url).json() | |
| if res["status"] == "ok": | |
| return res["data"]["aqi"] | |
| return "Unavailable" | |
| def get_glacier_risk(city): | |
| data = { | |
| "Skardu": ("High glacier melt risk", "July–August"), | |
| "Hunza": ("Moderate glacier melt risk", "June–August"), | |
| "Chitral": ("GLOF potential during peak summer", "July"), | |
| } | |
| return data.get(city.title(), ("No glacier melt alert", "N/A")) | |
| def get_flood_risk(city): | |
| data = { | |
| "Karachi": ("Urban flood risk (monsoon)", "July–September"), | |
| "Lahore": ("Localized flooding in low-lying areas", "July–August"), | |
| "Sukkur": ("Flood risk due to Indus overflow", "August–September"), | |
| } | |
| return data.get(city.title(), ("No flood alert", "N/A")) | |
| def get_climate_advice(city, season, age, interest): | |
| prompt = f"""As a climate adaptation advisor, suggest realistic, long-term actions someone can take in {city} during the {season} season to reduce their climate vulnerability. | |
| The person is {age} years old and interested in {interest}. Consider water scarcity, heat, flooding, and energy challenges in {city}. | |
| Make the advice practical, location-aware, and future-focused.""" | |
| chat = client.chat.completions.create( | |
| model="llama3-8b-8192", | |
| messages=[{"role": "user", "content": prompt}] | |
| ) | |
| return chat.choices[0].message.content | |
| st.title("🌿 PakClimate (Climate Change Awareness App)") | |
| # ------------------------------ | |
| # 🧭 Tabs | |
| # ------------------------------ | |
| tabs = st.tabs(["🏠 Home", "🤖 RAG Chatbot", "🌍 Climate Intelligence Map", "🧠 Climate Adaptation Advisor"]) | |
| # ------------------------------ | |
| # 🏠 Home Tab | |
| # ------------------------------ | |
| with tabs[0]: | |
| st.markdown(""" | |
| ### 🧠 A platform to raise awareness about climate change in Pakistan 🇵🇰 | |
| Pakistan is facing serious climate challenges: | |
| - 🌡️ Rising temperatures & heatwaves | |
| - 🌊 Urban flooding & glacier melt | |
| - 🚱 Water stress | |
| - 💨 Poor air quality | |
| These climate threats are: | |
| - 🧒 Endangering public health, especially for children and the elderly | |
| - 🌾 Disrupting agriculture and food security, reducing crop yields and threatening livelihoods | |
| - 🏙️ Overwhelming urban infrastructure, damaging homes, roads, and drainage systems | |
| - 💧 Depleting freshwater resources, making clean water scarce for millions | |
| - ⚡ Straining energy systems, increasing demand while reducing hydropower capacity | |
| - 🏞️ Threatening biodiversity and ecosystems, from mountains to coastlines | |
| - 🏠 Displacing communities, especially in flood-prone and drought-hit regions | |
| This app informs and empowers citizens to understand and act on climate risks using real-time data and long-term guidance. | |
| Let's make a difference! | |
| """) | |
| st.markdown("### The impact is powerfull...") | |
| image_files = ["img1.png", "img2.png", "img3.png", "img4.png", "img5.png"] | |
| cols = st.columns(5) | |
| for col, img in zip(cols, image_files): | |
| if os.path.exists(img): | |
| col.image(img, use_container_width=True) | |
| else: | |
| col.warning(f"Missing: {img}") | |
| # ------------------------------ | |
| # 🤖 RAG Chatbot Tab | |
| # ------------------------------ | |
| with tabs[1]: | |
| st.title("📄 Let's Learn about Climate Change") | |
| VECTOR_DB_PATH = "vector_store" | |
| def get_or_load_vector_db(): | |
| embeddings = HuggingFaceEmbeddings(model_name="sentence-transformers/all-MiniLM-L6-v2") | |
| if os.path.exists(VECTOR_DB_PATH): | |
| return FAISS.load_local(VECTOR_DB_PATH, embeddings, allow_dangerous_deserialization=True) | |
| chunks = process_all_documents() | |
| db = FAISS.from_texts(chunks, embedding=embeddings) | |
| db.save_local(VECTOR_DB_PATH) | |
| return db | |
| if "vector_db" not in st.session_state: | |
| st.session_state.vector_db = get_or_load_vector_db() | |
| if "chat_history" not in st.session_state: | |
| st.session_state.chat_history = [] | |
| st.markdown("#### 💡 Try asking one of these FAQs:") | |
| faqs = [ | |
| "What is climate change?", | |
| "What are the recent disasters caused by climate change in Pakistan?", | |
| "What are the effects of climate change on natural resources of Pakistan?", | |
| "How does Government of Pakistan see the issue of climate change?" | |
| ] | |
| faq_cols = st.columns(2) | |
| for i, faq in enumerate(faqs): | |
| if faq_cols[i % 2].button(faq): | |
| st.session_state.faq_query = faq | |
| query = st.text_input("💬 Any other...", value=st.session_state.get("faq_query", "")) | |
| col1, col2 = st.columns([1, 4]) | |
| with col1: | |
| if st.button("🧹 Clear Chat"): | |
| st.session_state.chat_history = [] | |
| st.session_state.faq_query = "" | |
| query = "" | |
| if query: | |
| response = query_vector_db(query, st.session_state.vector_db) | |
| st.session_state.chat_history.append(("You", query)) | |
| st.session_state.chat_history.append(("AI", response)) | |
| st.session_state.faq_query = "" | |
| if st.session_state.chat_history: | |
| st.subheader("💬 Chat Conversation") | |
| for role, msg in st.session_state.chat_history: | |
| if role == "You": | |
| st.markdown(f"**🧑 {role}:** {msg}") | |
| else: | |
| st.markdown(f"**🤖 {role}:** {msg}") | |
| # ------------------------------ | |
| # 🌍 Climate Map Tab | |
| # ------------------------------ | |
| with tabs[2]: | |
| st.subheader("📍 Real-time Climate Risk & Weather Map") | |
| city = st.text_input("🏙️ Enter a city in Pakistan (e.g., Lahore, Skardu, Karachi):") | |
| if city: | |
| lat, lon = get_coordinates(city) | |
| if lat is not None: | |
| temp, weather = get_weather(lat, lon) | |
| aqi = get_aqi(lat, lon) | |
| flood_alert, flood_period = get_flood_risk(city) | |
| glacier_alert, glacier_period = get_glacier_risk(city) | |
| st.markdown(f""" | |
| **📍 City:** {city.title()} | |
| **🌡️ Temperature:** {temp}°C | |
| **🌤️ Weather:** {weather} | |
| **🌫️ AQI:** {aqi} | |
| **🌊 Flood Risk:** {flood_alert} | |
| ⏰ *Active during:* {flood_period} | |
| **🧊 Glacier Melt Risk:** {glacier_alert} | |
| ⏰ *Active during:* {glacier_period} | |
| """) | |
| m = folium.Map(location=[lat, lon], zoom_start=6, tiles="cartodbpositron") | |
| folium.raster_layers.WmsTileLayer( | |
| url='https://firms.modaps.eosdis.nasa.gov/wms/', | |
| name='FIRMS - Active Fires (MODIS)', | |
| layers='fires_modis', | |
| fmt='image/png', | |
| transparent=True, | |
| attr="NASA FIRMS" | |
| ).add_to(m) | |
| folium.raster_layers.WmsTileLayer( | |
| url='https://gibs.earthdata.nasa.gov/wms/epsg4326/best/wms.cgi?', | |
| name='MODIS Snow/Ice Daily', | |
| layers='MODIS_Terra_Snow_Cover_Daily', | |
| fmt='image/png', | |
| transparent=True, | |
| attr="NASA GIBS" | |
| ).add_to(m) | |
| folium.raster_layers.WmsTileLayer( | |
| url='https://sedac.ciesin.columbia.edu/geoserver/wms', | |
| name='Flood Hazard Frequency', | |
| layers='ndh:flood-hazard-frequency-distribution', | |
| fmt='image/png', | |
| transparent=True, | |
| attr="SEDAC" | |
| ).add_to(m) | |
| folium.Marker([lat, lon], tooltip=f"{city.title()} | Temp: {temp}°C | AQI: {aqi}", | |
| icon=folium.Icon(color="blue")).add_to(m) | |
| for z in ["Skardu", "Hunza", "Chitral"]: | |
| z_lat, z_lon = get_coordinates(z) | |
| folium.Marker([z_lat, z_lon], tooltip=z, icon=folium.Icon(color="red")).add_to(m) | |
| for z in ["Karachi", "Lahore", "Sukkur"]: | |
| z_lat, z_lon = get_coordinates(z) | |
| folium.Marker([z_lat, z_lon], tooltip=z, icon=folium.Icon(color="orange")).add_to(m) | |
| folium.LayerControl().add_to(m) | |
| st_folium(m, width=700, height=500) | |
| else: | |
| st.error("❌ City not found. Please check the spelling.") | |
| # ------------------------------ | |
| # 🧠 Climate Advisor Tab | |
| # ------------------------------ | |
| with tabs[3]: | |
| st.markdown("### 🧠 Climate Adaptation Advisor") | |
| col1, col2 = st.columns(2) | |
| with col1: | |
| city = st.text_input("City", "Lahore") | |
| season = st.selectbox("Season", ["Summer", "Winter", "Monsoon", "Spring", "Autumn"]) | |
| with col2: | |
| age = st.slider("Your Age", 10, 80, 25) | |
| interest = st.text_input("Your Interest", "Health") | |
| if st.button("Generate Advice"): | |
| advice = get_climate_advice(city, season, age, interest) | |
| st.success("✅ Climate Advice Generated:") | |
| st.write(advice) | |