Update app.py

app.py

@@ -7,21 +7,21 @@ from huggingface_hub import InferenceClient
 client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
 
 # Set default values for model parameters and system message
-DEFAULT_MAX_TOKENS = 1000
-DEFAULT_TEMPERATURE = 0.8
+DEFAULT_MAX_TOKENS = 512
+DEFAULT_TEMPERATURE = 0.7
 DEFAULT_TOP_P = 0.95
-DEFAULT_SYSTEM_MESSAGE = "You are an expert in environmental psychology. Provide expert recommendations addressing the client directly. Not like a letter though but like a professional report."
+DEFAULT_SYSTEM_MESSAGE = "You are an expert in environmental psychology. Provide expert recommendations addressing the user directly."
 
-def generate_recommendations(comfort, social_interaction, stressors, privacy, open_question, max_tokens=DEFAULT_MAX_TOKENS, temperature=DEFAULT_TEMPERATURE, top_p=DEFAULT_TOP_P, system_message=DEFAULT_SYSTEM_MESSAGE):
+def generate_recommendations(comfort, social_interaction, stressors, privacy, open_question, 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"
-               f"On a scale of 1-5, with 5 being the highest and 1 being the least ideal, the user rated the following:\n"
+               f"On a scale of 1-5, with 5 being the highest and 1 being the least ideal, {alias} rated the following:\n"
                f"Comfort and Well-being: {comfort}\n"
                f"Social Interaction: {social_interaction}\n"
                f"Environmental Stressors: {stressors}\n"
                f"Privacy and Personal Space: {privacy}\n"
                f"Open-ended Question: {open_question}\n"
-               f"Please provide personalized recommendations addressing the user directly.")
+               f"Please provide personalized recommendations for {alias}, addressing them directly.")
 
     # Generate recommendations using the Hugging Face model
     response = client.chat_completion(
@@ -36,7 +36,7 @@ def generate_recommendations(comfort, social_interaction, stressors, privacy, op
     recommendations = recommendations.replace("You should", "I recommend that you")
     return recommendations
 
-def analyze_environmental_concerns(comfort, social_interaction, stressors, privacy, open_question):
+def analyze_environmental_concerns(comfort, social_interaction, stressors, privacy, open_question, alias):
     # Generate a bar graph for the input scores with Ukiyo-e 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"]
@@ -46,7 +46,7 @@ def analyze_environmental_concerns(comfort, social_interaction, stressors, priva
     
     # Improve graph display
     ax.set_ylabel('Score', fontsize=14, color='#333333')
-    ax.set_title('Environmental Psychology Concerns', fontsize=16, color='#333333')
+    ax.set_title(f'Environmental Psychology Concerns 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')
@@ -57,7 +57,7 @@ def analyze_environmental_concerns(comfort, social_interaction, stressors, priva
         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
-    recommendations = generate_recommendations(comfort, social_interaction, stressors, privacy, open_question)
+    recommendations = generate_recommendations(comfort, social_interaction, stressors, privacy, open_question, alias)
     
     return fig, recommendations
 
@@ -100,7 +100,8 @@ 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="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
 ]
 
 outputs = [