Update app.py

app.py

@@ -19,15 +19,31 @@ IMAGEGEN_API_URL = "https://api-inference.huggingface.co/models/Artples/LAI-Imag
 # Headers for Hugging Face API requests
 headers = {"Authorization": f"Bearer {HUGGINGFACE_API_KEY}"}
 
-# CSS
+# Inject custom CSS for green theme
 st.markdown("""
     <style>
-    body {background-color: #ffffff;}
-    .stApp {color: #2e7d32; font-family: 'Arial', sans-serif;}
-    .stButton>button {background-color: #66bb6a; color: #fff; font-weight: bold;}
-    .stTextInput>div>input {background-color: #e8f5e9; color: #2e7d32;}
-    .stMarkdown h1, .stMarkdown h2, .stMarkdown h3, .stMarkdown p {color: #388e3c;}
-    .stMarkdown h2 {font-weight: bold;}
+    body {
+        background-color: #ffffff;
+    }
+    .stApp {
+        color: #2e7d32;
+        font-family: 'Arial', sans-serif;
+    }
+    .stButton>button {
+        background-color: #66bb6a;
+        color: #fff;
+        font-weight: bold;
+    }
+    .stTextInput>div>input {
+        background-color: #e8f5e9;
+        color: #2e7d32;
+    }
+    .stMarkdown h1, .stMarkdown h2, .stMarkdown h3, .stMarkdown p {
+        color: #388e3c;
+    }
+    .stMarkdown h2 {
+        font-weight: bold;
+    }
     </style>
 """, unsafe_allow_html=True)
 
@@ -57,7 +73,7 @@ def fetch_real_data(city: str) -> dict:
         "weather_condition": weather_data['weather'][0].get('main', 'Data not available')
     }
 
-# Function to determine mood
+# Function to determine mood based on weather data
 def determine_mood(data: dict) -> str:
     weather_condition = data["weather_condition"].lower()
     temperature = data["temperature"]
@@ -90,11 +106,48 @@ def generate_story_with_ai(narrative: str, mood: str) -> str:
     )
     return response.choices[0].message['content'].strip()
 
+# Function to generate simulated environmental data
+def generate_simulated_data(city: str) -> dict:
+    prompt = (
+        f"Generate simulated environmental data for {city} in JSON format with fields:\n"
+        f"1. AQI\n2. Deforestation Rate\n3. Water Quality\n4. Biodiversity Impact"
+    )
+    response = openai.ChatCompletion.create(
+        model="gpt-3.5-turbo",
+        messages=[{"role": "user", "content": prompt}],
+        max_tokens=100,
+        temperature=0.8
+    )
+    response_content = response.choices[0].message['content'].strip()
+    try:
+        return eval(response_content)
+    except Exception as e:
+        st.error(f"Error parsing simulated data: {e}")
+        return {}
+
+# Function to generate music from Hugging Face API
+def generate_music(description: str) -> bytes:
+    payload = {"inputs": description}
+    response = requests.post(MUSICGEN_API_URL, headers=headers, json=payload)
+    if response.status_code != 200:
+        st.error(f"Error generating music: {response.status_code} {response.text}")
+        return None
+    return response.content
+
+# Function to generate an image based on the story
+def generate_image(description: str) -> bytes:
+    payload = {"inputs": description}
+    response = requests.post(IMAGEGEN_API_URL, headers=headers, json=payload)
+    if response.status_code != 200:
+        st.error(f"Error generating image: {response.status_code} {response.text}")
+        return None
+    return response.content
+
 # Function to fetch NGOs using OpenAI
 def fetch_nearby_ngos_with_openai(city: str, interests: list) -> list:
     prompt = (
         f"List NGOs near {city} that focus on {', '.join(interests)}. "
-        "Provide the names, locations, and focus areas in JSON format."
+        "Provide the names, locations, and focus areas in JSON format as a list of dictionaries."
     )
     response = openai.ChatCompletion.create(
         model="gpt-3.5-turbo",
@@ -103,8 +156,14 @@ def fetch_nearby_ngos_with_openai(city: str, interests: list) -> list:
         temperature=0.7
     )
     response_content = response.choices[0].message['content'].strip()
+    
     try:
-        return eval(response_content)
+        ngo_list = eval(response_content)
+        if isinstance(ngo_list, list) and all(isinstance(ngo, dict) for ngo in ngo_list):
+            return ngo_list
+        else:
+            st.error("Unexpected response format. Could not parse NGO data.")
+            return []
     except Exception as e:
         st.error(f"Error fetching NGO data: {e}")
         return []
@@ -151,7 +210,7 @@ if st.button("Find Nearby NGOs"):
 if st.session_state.ngos:
     st.subheader("🌟 NGOs Near You")
     for ngo in st.session_state.ngos:
-        st.write(f"**{ngo['name']}**")
-        st.write(f"📍 Location: {ngo['location']}")
-        st.write(f"🌱 Focus Area: {ngo['focus']}")
+        st.write(f"**{ngo.get('name', 'Unknown NGO')}**")
+        st.write(f"📍 Location: {ngo.get('location', 'Unknown Location')}")
+        st.write(f"🌱 Focus Area: {ngo.get('focus', 'Unknown Focus Area')}")
         st.write("---")