Update app.py

app.py

@@ -1,76 +1,94 @@
+# app.py
+
 import streamlit as st
 from transformers import pipeline
 import requests
 
-# --- Must Be First: Set Page Config ---
-st.set_page_config(page_title="ClimateGPT 🌱", layout="centered")
+# 🟢 Streamlit Page Configuration (must be first Streamlit command)
+st.set_page_config(page_title="ClimateGPT", layout="centered")
 
-# --- Streamlit App UI ---
+# 🌍 App Title and Intro
 st.title("🌍 ClimateGPT: Your Eco-Education Buddy")
-st.markdown("Learn about recycling, eco habits, carbon emissions and how to help the planet.")
-st.markdown("---")
+st.markdown("""
+Welcome to **ClimateGPT**, your personal assistant for learning about climate change, sustainability, and carbon footprint.
+Ask a question in any supported language, and get informative answers with optional translation!
+""")
 
-# --- Set API Key from Streamlit Secrets ---
-CLIMATIQ_API_KEY = st.secrets["climate_api"]
+# 🌐 Climate Topics for Filtering
+CLIMATE_TOPICS = [
+    "climate", "carbon", "recycle", "emission", "eco", "green",
+    "pollution", "environment", "sustainability", "energy", "co2"
+]
 
-# --- Load Lightweight, Fast Model ---
-@st.cache_resource
-def load_model():
-    return pipeline("text2text-generation", model="google/flan-t5-small")
+# ✅ Relevance Check
+def is_relevant_query(query):
+    return any(word in query.lower() for word in CLIMATE_TOPICS)
 
-llm = load_model()
+# 🧠 Load the lightweight model for faster response
+llm = pipeline("text2text-generation", model="google/flan-t5-small")
 
-# --- Emission Calculator ---
-def get_emissions(distance_km=100):
-    url = "https://beta3.api.climatiq.io/estimate"
-    headers = {"Authorization": f"Bearer {CLIMATIQ_API_KEY}"}
-    payload = {
-        "emission_factor": {
-            "activity_id": "passenger_vehicle-vehicle_type_car-fuel_source_na-engine_size_na-vehicle_age_na-vehicle_weight_na"
-        },
-        "parameters": {
-            "distance": distance_km,
-            "distance_unit": "km"
-        }
-    }
-    try:
-        response = requests.post(url, json=payload, headers=headers, timeout=10)
-        data = response.json()
-        co2 = data.get('co2e', 0)
-        return f"{co2:.2f} kg CO₂ for {distance_km} km"
-    except requests.exceptions.RequestException:
-        return "Emission data not available."
+# 🌍 Language Mapping for LibreTranslate
+LANGUAGES = {
+    "English": "en",
+    "Urdu": "ur",
+    "Spanish": "es",
+    "French": "fr",
+    "German": "de",
+    "Chinese": "zh"
+}
+
+# 📌 LibreTranslate API Endpoint
+TRANSLATE_API = "https://libretranslate.de/translate"
 
-# --- Optional: Translation using LibreTranslate ---
-def translate_text(text, target_lang="es"):
-    if target_lang == "en":
-        return text
+# 🚀 Translation function
+def translate_text(text, target_lang):
     try:
-        response = requests.post("https://libretranslate.de/translate", json={
+        if target_lang == "en":
+            return text
+        payload = {
             "q": text,
             "source": "en",
             "target": target_lang,
             "format": "text"
-        }, timeout=8)
-        return response.json().get('translatedText', text)
-    except requests.exceptions.RequestException:
-        return "Translation service is currently unavailable."
+        }
+        response = requests.post(TRANSLATE_API, json=payload, timeout=10)
+        return response.json().get("translatedText", text)
+    except Exception as e:
+        return f"Translation failed: {e}"
+
+# 🚗 Carbon Emission Estimation via Climatiq API
+def get_carbon_estimate(distance_km):
+    headers = {
+        "Authorization": f"Bearer {st.secrets['climate_api']}"
+    }
+    payload = {
+        "emission_factor": {"activity_id": "passenger_vehicle-vehicle_type_car-fuel_source_na-engine_size_na-vehicle_age_na"},
+        "parameters": {"distance": distance_km, "distance_unit": "km"}
+    }
+    try:
+        response = requests.post("https://beta3.api.climatiq.io/estimate", headers=headers, json=payload)
+        emissions = response.json()["co2e"]
+        return f"Estimated CO₂ Emission: {emissions:.2f} kg for {distance_km} km"
+    except:
+        return "Failed to fetch emission estimate."
 
-# --- Chatbot Logic ---
-st.markdown("### 💬 Ask a climate-related question:")
-user_query = st.text_input("For example: How can I reduce plastic use? Or: How much CO₂ is emitted in a 100km car trip?")
-target_language = st.selectbox("🌐 Translate the response to:", ["None", "en", "es", "fr", "de", "ur", "zh"], index=0)
+# 🧾 User Inputs
+user_query = st.text_input("Ask your climate-related question:")
+language = st.selectbox("Choose output language:", list(LANGUAGES.keys()))
 
-if st.button("🌿 Get Response") and user_query:
-    with st.spinner("Generating eco-friendly answer..."):
-        response = llm(user_query, max_length=200)[0]['generated_text']
+# ✈️ Optional Carbon Estimate
+with st.expander("Optional: Estimate CO₂ emissions for travel"):
+    distance = st.number_input("Enter travel distance in kilometers:", min_value=0.0, step=1.0)
+    if distance:
+        st.info(get_carbon_estimate(distance))
 
-        if target_language != "None":
-            translated = translate_text(response, target_lang=target_language)
-            st.success(translated)
-        else:
-            st.success(response)
+# 📤 Process Query
+if user_query:
+    if is_relevant_query(user_query):
+        response = llm(user_query, max_length=200, do_sample=False)[0]['generated_text']
+    else:
+        response = "❗ This chatbot only answers questions related to climate, sustainability, and eco-friendly habits."
 
-        if any(word in user_query.lower() for word in ["carbon", "co2", "emission"]):
-            emission = get_emissions()
-            st.info(f"🚗 Estimated Emissions: {emission}")
+    translated_response = translate_text(response, LANGUAGES[language])
+    st.markdown("---")
+    st.markdown(f"**Response:** {translated_response}")