Update app.py

app.py

@@ -4,10 +4,6 @@ from transformers import AutoModelForCausalLM, AutoTokenizer
 from simple_salesforce import Salesforce
 import os
 from dotenv import load_dotenv
-import pandas as pd
-from reportlab.lib.pagesizes import letter
-from reportlab.pdfgen import canvas
-from io import BytesIO
 
 # Load environment variables
 load_dotenv()
@@ -18,7 +14,7 @@ missing_vars = [var for var in required_env_vars if not os.getenv(var)]
 if missing_vars:
     raise EnvironmentError(f"Missing required environment variables: {missing_vars}")
 
-# Default settings
+# Defaults
 KPI_FLAG_DEFAULT = os.getenv('KPI_FLAG', 'True') == 'True'
 ENGAGEMENT_SCORE_DEFAULT = float(os.getenv('ENGAGEMENT_SCORE', '85.0'))
 
@@ -107,16 +103,26 @@ def get_projects_for_supervisor(supervisor_name):
         print(f"⚠️ Error fetching project: {e}")
         return ""
 
+def field_exists(sf, object_name, field_name):
+    try:
+        obj_desc = getattr(sf, object_name).describe()
+        return field_name in [field['name'] for field in obj_desc['fields']]
+    except Exception as e:
+        print(f"⚠️ Error checking field {field_name}: {e}")
+        return False
+
 # New function to generate Salesforce dashboard URL (Visualforce Page)
 def generate_salesforce_dashboard_url(supervisor_name, project_id):
+    # Use the provided Salesforce Visualforce URL with supervisorName and projectId as parameters
     return f"https://aicoachforsitesupervisors-dev-ed--c.develop.vf.force.com/apex/DashboardPage?supervisorName={supervisor_name}&projectId={project_id}"
 
 # Dashboard button function
 def open_dashboard(role, supervisor_name, project_id):
+    # Generate dynamic URL based on supervisor and project
     dashboard_url = generate_salesforce_dashboard_url(supervisor_name, project_id)
     return f'<a href="{dashboard_url}" target="_blank" rel="noopener noreferrer" style="font-size:16px;">Open Salesforce Dashboard</a>'
 
-# Function to generate day-by-day tasks
+# Generate function
 def generate_outputs(role, supervisor_name, project_id, milestones, reflection):
     if not all([role, supervisor_name, project_id, milestones, reflection]):
         return "❗ Please fill all fields.", ""
@@ -133,7 +139,7 @@ def generate_outputs(role, supervisor_name, project_id, milestones, reflection):
         with torch.no_grad():
             outputs = model.generate(
                 inputs['input_ids'],
-                max_new_tokens=150,
+                max_new_tokens=150,  # Increased max tokens to capture more content
                 no_repeat_ngram_size=2,
                 do_sample=True,
                 top_p=0.9,
@@ -150,9 +156,11 @@ def generate_outputs(role, supervisor_name, project_id, milestones, reflection):
         e = text.find(end, s) if end else len(text)
         return text[s + len(start):e].strip() if s != -1 else ""
 
+    # Extract the checklist and suggestions
     checklist = extract_between(result, "Checklist:\n", "Suggestions:")
     suggestions = extract_between(result, "Suggestions:\n", None)
 
+    # If checklist or suggestions are empty, generate fallback content
     if not checklist.strip():
         checklist = generate_fallback_checklist(role, milestones)
     if not suggestions.strip():
@@ -160,110 +168,77 @@ def generate_outputs(role, supervisor_name, project_id, milestones, reflection):
 
     return checklist, suggestions
 
-# Fallback checklist and suggestions generation
+# Fallback generation for checklist and suggestions
 def generate_fallback_checklist(role, milestones):
     checklist_items = []
-    if milestones:
+
+    # If milestones are provided, add them to the checklist directly
+    if milestones and milestones.strip():
         kpis = [kpi.strip() for kpi in milestones.split(",")]
         for kpi in kpis:
             checklist_items.append(f"- Ensure progress on {kpi}")
     else:
         checklist_items.append("- Perform daily safety inspection")
+    
     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.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.append("- Monitor team coordination")
+        suggestions_items.append("- Review safety protocols with the team")
+    
     return "\n".join(suggestions_items)
 
-# Function to generate the PDF report
-def generate_pdf_report(supervisor_name, project_id, checklist, suggestions):
-    file_path = f"reports/{supervisor_name}_{project_id}_report.pdf"
-    buffer = BytesIO()
-    c = canvas.Canvas(buffer, pagesize=letter)
-    c.drawString(100, 750, f"Supervisor: {supervisor_name}")
-    c.drawString(100, 735, f"Project ID: {project_id}")
-    c.drawString(100, 700, "Daily Checklist:")
-    y_position = 685
-    for task in checklist.splitlines():
-        c.drawString(100, y_position, f"- {task}")
-        y_position -= 15
-    c.drawString(100, y_position - 20, "Focus Suggestions:")
-    y_position -= 40
-    for suggestion in suggestions.splitlines():
-        c.drawString(100, y_position, f"- {suggestion}")
-        y_position -= 15
-    c.showPage()
-    c.save()
-    buffer.seek(0)
-    with open(file_path, 'wb') as f:
-        f.write(buffer.read())
-    return file_path
-
-# Function to generate CSV report
-def generate_csv_report(supervisor_name, project_id, checklist, suggestions):
-    file_path = f"reports/{supervisor_name}_{project_id}_report.csv"
-    data = {
-        "Supervisor": [supervisor_name],
-        "Project ID": [project_id],
-        "Checklist": [checklist],
-        "Suggestions": [suggestions]
-    }
-    df = pd.DataFrame(data)
-    df.to_csv(file_path, index=False)
-    return file_path
-
-# Function to store the download link in Salesforce
-def store_download_link_in_salesforce(supervisor_name, download_link):
-    try:
-        sf = Salesforce(
-            username=os.getenv('SF_USERNAME'),
-            password=os.getenv('SF_PASSWORD'),
-            security_token=os.getenv('SF_SECURITY_TOKEN'),
-            domain=os.getenv('SF_DOMAIN', 'login')
-        )
-        result = sf.query(f"SELECT Id FROM Supervisor_AI_Coaching__c WHERE Supervisor_Name__c = '{supervisor_name}' LIMIT 1")
-        if result['totalSize'] == 0:
-            return "Supervisor not found."
-        supervisor_ai_coaching_id = result['records'][0]['Id']
-        sf.Supervisor_AI_Coaching__c.update(supervisor_ai_coaching_id, {
-            'Download_Link__c': download_link
-        })
-        return "Download link stored successfully."
-    except Exception as e:
-        return f"Error storing download link: {e}"
-
-# Interface function
+# Interface
 def create_interface():
     roles = get_roles_from_salesforce()
     with gr.Blocks(theme="soft") as demo:
         gr.Markdown("## 🧠 AI-Powered Supervisor Assistant")
+
         with gr.Row():
             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)", 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")
             clear = gr.Button("Clear")
             refresh = gr.Button("🔄 Refresh Roles")
             dashboard_btn = gr.Button("Dashboard")
+
         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)
         supervisor_name.change(fn=get_projects_for_supervisor, inputs=supervisor_name, outputs=project_id)
-        generate.click(fn=generate_outputs, inputs=[role, supervisor_name, project_id, milestones, reflection], outputs=[checklist_output, suggestions_output])
-        clear.click(fn=lambda: ("", "", "", "", ""), inputs=None, outputs=[role, supervisor_name, project_id, milestones, reflection])
+
+        generate.click(fn=generate_outputs,
+                       inputs=[role, supervisor_name, project_id, milestones, reflection],
+                       outputs=[checklist_output, suggestions_output])
+
+        clear.click(fn=lambda: ("", "", "", "", ""), inputs=None,
+                    outputs=[role, supervisor_name, project_id, milestones, reflection])
+
         refresh.click(fn=lambda: gr.update(choices=get_roles_from_salesforce()), outputs=role)
+
         dashboard_btn.click(fn=open_dashboard, inputs=[role, supervisor_name, project_id], outputs=dashboard_link)
+
     return demo
 
 if __name__ == "__main__":
     app = create_interface()
     app.launch()
+    
+