Update app.py

app.py

@@ -11,18 +11,23 @@ logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(
 logger = logging.getLogger(__name__)
 
 # Salesforce credentials (use environment variables for security)
-SF_USERNAME = os.getenv('SF_USERNAME','[email protected]')
-SF_PASSWORD = os.getenv('SF_PASSWORD','Teja90325@')
-SF_SECURITY_TOKEN = os.getenv('SF_SECURITY_TOKEN','clceSdBgQ30Rx9BSC66gAcRx')
-SF_DOMAIN = os.getenv('SF_DOMAIN','login')
-HUGGINGFACE_API_KEY = os.getenv('HUGGINGFACE_API_KEY', '')
+SF_USERNAME = os.getenv('SF_USERNAME')
+SF_PASSWORD = os.getenv('SF_PASSWORD')
+SF_SECURITY_TOKEN = os.getenv('SF_SECURITY_TOKEN')
+SF_DOMAIN = os.getenv('SF_DOMAIN', 'login')  # Default to 'login' if not set
+HUGGINGFACE_API_KEY = os.getenv('HUGGINGFACE_API_KEY')
+
+# Validate that environment variables are set
+if not all([SF_USERNAME, SF_PASSWORD, SF_SECURITY_TOKEN, HUGGINGFACE_API_KEY]):
+    logger.error("Missing required environment variables (SF_USERNAME, SF_PASSWORD, SF_SECURITY_TOKEN, or HUGGINGFACE_API_KEY)")
+    raise ValueError("Missing required environment variables. Please set SF_USERNAME, SF_PASSWORD, SF_SECURITY_TOKEN, and HUGGINGFACE_API_KEY.")
 
 # Initialize Salesforce connection
 try:
     sf = Salesforce(
-        username=[email protected],
-        password='Teja90325@',
-        security_token=clceSdBgQ30Rx9BSC66gAcRx,
+        username=SF_USERNAME,
+        password=SF_PASSWORD,
+        security_token=SF_SECURITY_TOKEN,
         domain=SF_DOMAIN
     )
     logger.info("Successfully connected to Salesforce")
@@ -59,6 +64,36 @@ Suggestions:
 Quote:
 {your_motivational_quote}"""
 
+def fetch_salesforce_data_for_role(role):
+    """Fetch Project__c records from Salesforce based on the selected role."""
+    if sf is None:
+        logger.error("Salesforce connection not initialized")
+        return None, None, None, "Error: Salesforce connection not initialized"
+
+    try:
+        # Query Project__c records where the Supervisor's role matches the selected role
+        query = f"""
+            SELECT Id, Name, Project_Name__c, Milestones__c, Weather_Log__c, 
+                   Supervisor__r.Role__c, Supervisor__r.Name, Supervisor__c
+            FROM Project__c
+            WHERE Supervisor__r.Role__c = '{role}' AND Milestones__c != null
+            LIMIT 1
+        """
+        projects = sf.query(query)['records']
+        if not projects:
+            logger.info(f"No projects found for role: {role}")
+            return None, None, None, f"No projects found for role: {role}"
+
+        project = projects[0]  # Take the first project
+        project_id = project['Name']
+        milestones = project['Milestones__c'] or 'No milestones'
+        reflection = f"Weather: {project['Weather_Log__c'] or 'Sunny, 25°C'}"
+        logger.info(f"Fetched project {project_id} for role {role}")
+        return project, project_id, milestones, reflection
+    except Exception as e:
+        logger.error(f"Error fetching Salesforce data: {e}")
+        return None, None, None, f"Error fetching Salesforce data: {e}"
+
 def generate_outputs(role, project_id, milestones, reflection):
     """Generate checklist, suggestions, and quote using distilgpt2."""
     # Input validation
@@ -149,69 +184,63 @@ def generate_outputs(role, project_id, milestones, reflection):
             quote = generated_text[quote_start:].strip()
     except Exception as e:
         logger.error(f"Error parsing output: {e}")
-        return f"Error parsing output: {e}", "", ""
+       -return f"Error parsing output: {e}", "", ""
 
     return checklist, suggestions, quote
 
-def fetch_and_process_salesforce_data():
-    """Fetch Project__c records from Salesforce and generate AI outputs."""
+def store_in_salesforce(project, role, project_id, milestones, reflection, checklist, suggestions, quote):
+    """Store the generated outputs in Salesforce Supervisor_AI_Coaching__c."""
     if sf is None:
         logger.error("Salesforce connection not initialized")
         return "Error: Salesforce connection not initialized"
 
     try:
-        # Query Project__c records
-        query = """
-            SELECT Id, Name, Project_Name__c, Milestones__c, Weather_Log__c, 
-                   Supervisor__r.Role__c, Supervisor__r.Name__c
-            FROM Project__c
-            WHERE Milestones__c != null
-            LIMIT 10
+        # Update or create Supervisor_AI_Coaching__c record
+        coaching_query = f"""
+            SELECT Id
+            FROM Supervisor_AI_Coaching__c
+            WHERE Project_ID__c = '{project['Id']}'
+            LIMIT 1
         """
-        projects = sf.query(query)['records']
-        logger.info(f"Fetched {len(projects)} Project__c records")
+        coaching_records = sf.query(coaching_query)['records']
+
+        coaching_data = {
+            'Project_ID__c': project['Id'],
+            'Supervisor_ID__c': project['Supervisor__c'],
+            'Daily_Checklist__c': checklist,
+            'Suggested_Tips__c': suggestions,
+            'Reflection_Log__c': reflection,
+            'Last_Refresh_Date__c': datetime.utcnow().isoformat(),
+            'Engagement_Score__c': 50 if checklist != 'Not generated.' else 0,
+            'KPI_Flag__c': 'delay' in suggestions.lower() or 'issue' in suggestions.lower()
+        }
 
-        for project in projects:
-            role = project['Supervisor__r']['Role__c'] if project['Supervisor__r'] != null else 'Supervisor'
-            project_id = project['Name']
-            milestones = project['Milestones__c'] or 'No milestones'
-            reflection = f"Weather: {project['Weather_Log__c'] or 'Sunny, 25°C'}"
+        if coaching_records:
+            sf.Supervisor_AI_Coaching__c.update(coaching_records[0]['Id'], coaching_data)
+            logger.info(f"Updated Supervisor_AI_Coaching__c for Project {project_id}")
+        else:
+            sf.Supervisor_AI_Coaching__c.create(coaching_data)
+            logger.info(f"Created Supervisor_AI_Coaching__c for Project {project_id}")
 
-            # Generate AI outputs
-            checklist, suggestions, quote = generate_outputs(role, project_id, milestones, reflection)
-            logger.info(f"Generated outputs for Project {project_id}")
+        return f"Successfully stored data for Project {project_id} in Salesforce"
+    except Exception as e:
+        logger.error(f"Error storing data in Salesforce: {e}")
+        return f"Error storing data in Salesforce: {e}"
 
-            # Update or create Supervisor_AI_Coaching__c record
-            coaching_query = f"""
-                SELECT Id
-                FROM Supervisor_AI_Coaching__c
-                WHERE Project_ID__c = '{project['Id']}'
-                LIMIT 1
-            """
-            coaching_records = sf.query(coaching_query)['records']
+def on_role_change(role):
+    """Handle role selection change, fetch Salesforce data, generate outputs, and store in Salesforce."""
+    # Fetch data from Salesforce based on the selected role
+    project, project_id, milestones, reflection = fetch_salesforce_data_for_role(role)
+    if project is None:
+        return "", "", "", "", project_id, milestones, reflection
 
-            coaching_data = {
-                'Project_ID__c': project['Id'],
-                'Supervisor_ID__c': project['Supervisor__c'],
-                'Daily_Checklist__c': checklist,
-                'Suggested_Tips__c': suggestions,
-                'Reflection_Log__c': reflection,
-                'Last_Refresh_Date__c': datetime.utcnow().isoformat(),
-                'Engagement_Score__c': 50 if checklist != 'Not generated.' else 0,
-                'KPI_Flag__c': 'delay' in suggestions.lower() or 'issue' in suggestions.lower()
-            }
+    # Generate outputs
+    checklist, suggestions, quote = generate_outputs(role, project_id, milestones, reflection)
 
-            if coaching_records:
-                sf.Supervisor_AI_Coaching__c.update(coaching_records[0]['Id'], coaching_data)
-                logger.info(f"Updated Supervisor_AI_Coaching__c for Project {project_id}")
-            else:
-                sf.Supervisor_AI_Coaching__c.create(coaching_data)
-                logger.info(f"Created Supervisor_AI_Coaching__c for Project {project_id}")
+    # Store the generated outputs in Salesforce
+    store_result = store_in_salesforce(project, role, project_id, milestones, reflection, checklist, suggestions, quote)
 
-        return f"Processed {len(projects)} projects successfully"
-    except Exception as e:
-        logger.error(f"Error processing Salesforce data: {e}")
-        return f"Error processing Salesforce data: {e}"
+    return checklist, suggestions, quote, store_result, project_id, milestones, reflection
 
 def create_interface():
     """Create Gradio interface for manual testing."""
@@ -219,7 +248,7 @@ def create_interface():
         gr.Markdown("### Construction Supervisor AI Coach")
         with gr.Row():
             role = gr.Dropdown(choices=["Supervisor", "Foreman", "Project Manager"], label="Role", value="Supervisor")
-            project_id = gr.Textbox(label="Project ID", placeholder="e.g., PROJ-123")
+        project_id = gr.Textbox(label="Project ID", placeholder="e.g., PROJ-123")
         milestones = gr.Textbox(
             label="Milestones (comma-separated)",
             placeholder="e.g., Foundation complete, Framing started, Roof installed"
@@ -229,31 +258,18 @@ def create_interface():
             lines=3,
             placeholder="e.g., Facing delays due to weather and equipment issues."
         )
-        with gr.Row():
-            submit = gr.Button("Generate")
-            clear = gr.Button("Clear")
-            sf_button = gr.Button("Process Salesforce Data")
         checklist_output = gr.Textbox(label="Checklist", lines=4)
         suggestions_output = gr.Textbox(label="Suggestions", lines=4)
         quote_output = gr.Textbox(label="Quote", lines=2)
         sf_output = gr.Textbox(label="Salesforce Processing Result", lines=2)
-        
-        submit.click(
-            fn=generate_outputs,
-            inputs=[role, project_id, milestones, reflection],
-            outputs=[checklist_output, suggestions_output, quote_output]
-        )
-        clear.click(
-            fn=lambda: ("Supervisor", "", "", ""),
-            inputs=None,
-            outputs=[role, project_id, milestones, reflection]
-        )
-        sf_button.click(
-            fn=fetch_and_process_salesforce_data,
-            inputs=None,
-            outputs=sf_output
+
+        # Fetch data, generate outputs, and store in Salesforce when role changes
+        role.change(
+            fn=on_role_change,
+            inputs=role,
+            outputs=[checklist_output, suggestions_output, quote_output, sf_output, project_id, milestones, reflection]
         )
-    
+
     return demo
 
 if __name__ == "__main__":
@@ -261,6 +277,4 @@ if __name__ == "__main__":
         demo = create_interface()
         demo.launch(server_name="0.0.0.0", server_port=7860, share=False)
     except Exception as e:
-        logger.error(f"Error launching Gradio interface: {e}")
-
-
+        logger.error(f"Error launching Gradio interface: {e}")