Update app.py

app.py

@@ -4,7 +4,6 @@ from transformers import AutoModelForCausalLM, AutoTokenizer
 from simple_salesforce import Salesforce
 import os
 from dotenv import load_dotenv
-import uuid
 
 # Load environment variables
 load_dotenv()
@@ -32,8 +31,8 @@ model.config.pad_token_id = tokenizer.pad_token_id
 # Better Prompt
 PROMPT_TEMPLATE = """You are an AI coach for construction supervisors. Given the role, project, milestones, and a reflection log, generate:
 
-1. A Daily Checklist based on the milestones and role.
-2. Focus Suggestions based on concerns or keywords in the reflection log.
+1. A Daily Checklist based on the milestones and role. Ensure to include at least 4 items.
+2. Focus Suggestions based on concerns or keywords in the reflection log. Provide at least 2 suggestions.
 
 Inputs:
 Role: {role}
@@ -49,17 +48,6 @@ Suggestions:
 - 
 """
 
-# Sample data for Daily Checklist and Focus Suggestions
-SAMPLE_CHECKLIST = """- Conduct morning safety briefing
-- Review incident reports from previous day
-- Ensure progress on safety training
-- Perform daily site inspection"""
-
-SAMPLE_SUGGESTIONS = """- Monitor team coordination
-- Review safety protocols with the team
-- Follow up on reported incidents
-- Provide guidance on timely incident recording"""
-
 # Salesforce Functions
 def get_roles_from_salesforce():
     try:
@@ -158,10 +146,8 @@ def save_to_salesforce(role, project_id, milestones, reflection, checklist, sugg
 def generate_fallback_checklist(role, milestones):
     checklist_items = []
     if role.lower() == "safety officer":
-        checklist_items.extend([
-            "- Conduct morning safety briefing",
-            "- Review incident reports from previous day"
-        ])
+        checklist_items.append("- Conduct morning safety briefing")
+        checklist_items.append("- Review incident reports from previous day")
     
     if milestones and milestones.strip():
         kpis = [kpi.strip() for kpi in milestones.split(",")]
@@ -170,31 +156,27 @@ def generate_fallback_checklist(role, milestones):
     else:
         checklist_items.append("- Perform daily safety inspection")
     
-    return "\n".join(checklist_items) or SAMPLE_CHECKLIST
+    return "\n".join(checklist_items)
 
 def generate_fallback_suggestions(reflection):
     suggestions_items = []
     reflection_lower = reflection.lower()
     if "student" in reflection_lower or "learning" in reflection_lower:
-        suggestions_items.extend([
-            "- Ensure students are logging incidents consistently",
-            "- Provide guidance on timely incident recording"
-        ])
+        suggestions_items.append("- Ensure students are logging incidents consistently")
+        suggestions_items.append("- Provide guidance on timely incident recording")
     if "incident" in reflection_lower:
         suggestions_items.append("- Follow up on reported incidents with corrective actions")
     
     if not suggestions_items:
-        suggestions_items.extend([
-            "- Monitor team coordination",
-            "- Review safety protocols with the team"
-        ])
+        suggestions_items.append("- Monitor team coordination")
+        suggestions_items.append("- Review safety protocols with the team")
     
-    return "\n".join(suggestions_items) or SAMPLE_SUGGESTIONS
+    return "\n".join(suggestions_items)
 
 # Generate Function
 def generate_outputs(role, supervisor_name, project_id, milestones, reflection):
     if not all([role, supervisor_name, project_id, milestones, reflection]):
-        return SAMPLE_CHECKLIST, SAMPLE_SUGGESTIONS
+        return "❗ Please fill all fields.", ""
 
     prompt = PROMPT_TEMPLATE.format(
         role=role,
@@ -208,7 +190,7 @@ def generate_outputs(role, supervisor_name, project_id, milestones, reflection):
         with torch.no_grad():
             outputs = model.generate(
                 inputs['input_ids'],
-                max_new_tokens=100,
+                max_new_tokens=100,  # Limit output length to avoid delays
                 no_repeat_ngram_size=2,
                 do_sample=True,
                 top_p=0.9,
@@ -251,12 +233,12 @@ def create_interface():
         gr.Markdown("## 🧠 AI-Powered Supervisor Assistant")
 
         with gr.Row():
-            role = gr.Dropdown(choices=roles, label="Role", value="Safety Officer")
-            supervisor_name = gr.Dropdown(choices=[], label="Supervisor Name", value="John Doe")
-            project_id = gr.Textbox(label="Project ID", value="PROJ-001", interactive=False)
+            role = gr.Dropdown(choices=roles, label="Role")
+            supervisor_name = gr.Dropdown(choices=[], label="Supervisor Name")
+            project_id = gr.Textbox(label="Project ID", interactive=False)
 
-        milestones = gr.Textbox(label="Milestones (comma-separated KPIs)", value="Safety training, daily inspection", placeholder="E.g. Safety training, daily inspection")
-        reflection = gr.Textbox(label="Reflection Log", lines=4, value="Team is learning to log incidents, but some delays occurred.", placeholder="Any concerns, delays, updates...")
+        milestones = gr.Textbox(label="Milestones (comma-separated KPIs)", placeholder="E.g. Safety training, daily inspection")
+        reflection = gr.Textbox(label="Reflection Log", lines=4, placeholder="Any concerns, delays, updates...")
 
         with gr.Row():
             generate = gr.Button("Generate")
@@ -264,8 +246,8 @@ def create_interface():
             refresh = gr.Button("🔄 Refresh Roles")
             dashboard_btn = gr.Button("Dashboard")
 
-        checklist_output = gr.Textbox(label="✅ Daily Checklist", value=SAMPLE_CHECKLIST)
-        suggestions_output = gr.Textbox(label="💡 Focus Suggestions", value=SAMPLE_SUGGESTIONS)
+        checklist_output = gr.Textbox(label="✅ Daily Checklist")
+        suggestions_output = gr.Textbox(label="💡 Focus Suggestions")
         dashboard_link = gr.HTML("")
 
         role.change(fn=lambda r: gr.update(choices=get_supervisor_name_by_role(r)), inputs=role, outputs=supervisor_name)
@@ -286,4 +268,4 @@ def create_interface():
 
 if __name__ == "__main__":
     app = create_interface()
-    app.launch()
+    app.launch()