Update app.py

app.py

@@ -6,10 +6,10 @@ from keras.models import load_model
 from PIL import Image, ImageOps
 import numpy as np
 
-# Initialize Hugging Face Inference Client
+# Initialize Hugging Face Inference Client for climate change and design recommendations
 client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
 
-# Load the pre-trained Keras model for Mazingira 254
+# Load the pre-trained Keras model for Mazingira 254 (Environmental Theme Detection)
 model = load_model("keras_model.h5", compile=False)
 
 # Load class labels for environmental themes
@@ -20,7 +20,7 @@ with open("labels.txt", "r") as file:
 DEFAULT_MAX_TOKENS = 1000
 DEFAULT_TEMPERATURE = 0.7
 DEFAULT_TOP_P = 0.95
-DEFAULT_SYSTEM_MESSAGE = "You are an expert in environmental psychology. Provide expert recommendations addressing the user directly."
+DEFAULT_SYSTEM_MESSAGE = "You are an expert in environmental psychology and sustainable design. Provide innovative environmental design ideas to improve the climate and curb climate change, addressing the user directly."
 DEFAULT_ALIAS = "anon"  # Default alias
 
 def classify_image(img):
@@ -41,9 +41,7 @@ def classify_image(img):
         "Confidence Score": f"{confidence_score:.2f}"
     }
 
-def generate_recommendations(comfort, social_interaction, stressors, privacy, open_question, image_info, alias=DEFAULT_ALIAS, 
-                             max_tokens=DEFAULT_MAX_TOKENS, temperature=DEFAULT_TEMPERATURE, top_p=DEFAULT_TOP_P, 
-                             system_message=DEFAULT_SYSTEM_MESSAGE):
+def generate_design_ideas(comfort, social_interaction, stressors, privacy, open_question, image_info, alias=DEFAULT_ALIAS, max_tokens=DEFAULT_MAX_TOKENS, temperature=DEFAULT_TEMPERATURE, top_p=DEFAULT_TOP_P, system_message=DEFAULT_SYSTEM_MESSAGE):
     # Construct the input message for the model with context
     message = (
         f"{system_message}\n"
@@ -55,10 +53,10 @@ def generate_recommendations(comfort, social_interaction, stressors, privacy, op
         f"Open-ended Question: {open_question}\n"
         f"Detected Image Theme: {image_info['Detected Theme']}\n"
         f"Confidence Score: {image_info['Confidence Score']}\n"
-        f"Please provide personalized recommendations for {alias}, addressing them directly."
+        f"Please provide innovative environmental design ideas to improve climate and curb climate change, addressing {alias} directly."
     )
 
-    # Generate recommendations using the Hugging Face model
+    # Generate design ideas using the Hugging Face model
     response = client.chat_completion(
         [{"role": "user", "content": message}],
         max_tokens=max_tokens,
@@ -66,29 +64,28 @@ def generate_recommendations(comfort, social_interaction, stressors, privacy, op
         top_p=top_p
     )
 
-    recommendations = response.choices[0].message['content']
+    design_ideas = response.choices[0].message['content']
     # Convert the recommendations to address the user in first person
-    recommendations = recommendations.replace("You should", "I recommend that you")
-    
-    return recommendations
+    design_ideas = design_ideas.replace("You should", "I recommend that you")
+    return design_ideas
 
-def analyze_environmental_concerns(comfort, social_interaction, stressors, privacy, open_question, alias, img):
-    # Classify the image
+def analyze_environmental_design(comfort, social_interaction, stressors, privacy, open_question, alias, img):
+    # Classify the image for environmental themes
     image_info = classify_image(img)
     
     # Use default alias if none is provided
     alias = alias or DEFAULT_ALIAS
-    
-    # Generate a bar graph for the input scores with Ukiyo-e theme colors
+
+    # Generate a bar graph for the input scores with creative theme colors
     fig, ax = plt.subplots(figsize=(10, 6))  # Increased size for better visibility
     categories = ["Comfort and Well-being", "Social Interaction", "Environmental Stressors", "Privacy and Personal Space"]
     values = [comfort, social_interaction, stressors, privacy]
     
-    bars = ax.bar(categories, values, color=['#F08080', '#90EE90', '#000000', '#FFD700'])  # Light red, light green, black, gold
+    bars = ax.bar(categories, values, color=['#4CAF50', '#FFC107', '#2196F3', '#FF5722'])  # Green, Amber, Blue, Red
     
     # Improve graph display
     ax.set_ylabel('Score', fontsize=14, color='#333333')
-    ax.set_title(f'Environmental Psychology Concerns for {alias}', fontsize=16, color='#333333')
+    ax.set_title(f'Environmental Design Assessment for {alias}', fontsize=16, color='#333333')
     ax.yaxis.set_major_locator(MaxNLocator(integer=True))
     ax.tick_params(axis='y', colors='#333333')
     ax.tick_params(axis='x', colors='#333333')
@@ -98,41 +95,45 @@ def analyze_environmental_concerns(comfort, social_interaction, stressors, priva
         yval = bar.get_height()
         ax.text(bar.get_x() + bar.get_width()/2, yval, int(yval), va='bottom', ha='center', color='black', fontsize=12)
 
-    # Generate recommendations using the model, passing the image analysis results
-    recommendations = generate_recommendations(comfort, social_interaction, stressors, privacy, open_question, image_info, alias)
-    
-    return fig, recommendations
+    # Generate design ideas using the model, passing the image analysis results
+    design_ideas = generate_design_ideas(comfort, social_interaction, stressors, privacy, open_question, image_info, alias)
 
-# Custom CSS for Ukiyo-e theme
+    return fig, design_ideas
+
+# Custom CSS for modern design
 custom_css = """
 body {
-    font-family: 'Garamond', serif;
-    background-color: #FAF3F3; /* Light background color */
+    font-family: 'Arial', sans-serif;
+    background-color: #e0f7fa;
+    color: #00695c;
 }
-.container {
-    border: 2px solid #F08080; /* Light red border */
+
+.gradio-container {
     border-radius: 10px;
     padding: 20px;
-    background-color: #FFFFFF; /* White background for content */
-}
-h1 {
-    color: #F08080; /* Light red */
+    background: linear-gradient(135deg, #a5d6a7, #1b5e20);
+    box-shadow: 0px 4px 15px rgba(0, 0, 0, 0.2);
 }
-h2, h3, h4 {
-    color: #333333; /* Dark grey for headings */
-}
-.gradio-slider .slider .slider-handle {
-    background-color: #90EE90; /* Light green slider handle */
-}
-.gradio-slider .slider .slider-track {
-    background-color: #F08080; /* Light red track */
-}
-.gradio-textbox input, .gradio-textbox textarea {
-    border: 2px solid #000000; /* Black border for inputs */
+
+.gradio-container h1 {
+    font-family: 'Arial', sans-serif;
+    font-size: 2.5em;
+    text-align: center;
+    color: #ffffff;
 }
+
 .gradio-button {
-    background-color: #FFD700; /* Gold background for buttons */
-    color: #000000; /* Black text for buttons */
+    background-color: #00796b;
+    border: none;
+    color: white;
+    padding: 10px 20px;
+    font-size: 1em;
+    cursor: pointer;
+    border-radius: 5px;
+}
+
+.gradio-button:hover {
+    background-color: #004d40;
 }
 """
 
@@ -142,21 +143,21 @@ inputs = [
     gr.Slider(minimum=1, maximum=5, step=1, label="How would you rate Social Interaction?"),
     gr.Slider(minimum=1, maximum=5, step=1, label="How would you rate Environmental Stressors?"),
     gr.Slider(minimum=1, maximum=5, step=1, label="How would you rate Privacy and Personal Space?"),
-    gr.Textbox(placeholder="Describe any additional concerns or suggestions you have.", label="Open-ended Question", lines=3),
-    gr.Textbox(placeholder="Enter a single-word alias (e.g., anon).", label="Client Alias", lines=1),  # New input for alias
-    gr.Image(type="pil", label="Upload an Image for Theme Detection")  # New input for image
+    gr.Textbox(placeholder="Describe any environmental challenges or ideas you have.", label="Open-ended Question", lines=3),
+    gr.Textbox(placeholder="Enter your alias (e.g., anon).", label="Client Alias", lines=1),  # New input for alias
+    gr.Image(type="pil", label="Upload an Image for Environmental Theme Detection")  # New input for image
 ]
 
 outputs = [
-    gr.Plot(label="Concerns Graph"),
-    gr.Textbox(label="Recommendations", lines=5)
+    gr.Plot(label="Environmental Design Assessment"),
+    gr.Textbox(label="Creative Design Ideas", lines=5)
 ]
 
 gr.Interface(
-    fn=analyze_environmental_concerns,
+    fn=analyze_environmental_design,
     inputs=inputs,
     outputs=outputs,
-    title="Mazingira: Environmental Psychology Concerns Analyzer",
-    description="Input your environmental psychology concerns to receive personalized recommendations and a visual graph, along with image-based analysis.",
+    title="MAZINGIRA 254: Climate-Smart Environmental Design Ideas",
+    description="Input your environmental concerns and ideas to receive creative design recommendations and a visual assessment of climate change impact.",
     css=custom_css  # Apply custom CSS
 ).launch()