Update app.py

app.py

@@ -1,9 +1,10 @@
 import gradio as gr
-import torch
-from transformers import AutoModelForCausalLM, AutoTokenizer
-from simple_salesforce import Salesforce
 import os
-from dotenv import load_dotenv
+from simple_salesforce import Salesforce
+import pandas as pd
+from reportlab.lib.pagesizes import letter
+from reportlab.pdfgen import canvas
+from io import BytesIO
 
 # Load environment variables
 load_dotenv()
@@ -14,187 +15,115 @@ 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}")
 
-# Defaults
-KPI_FLAG_DEFAULT = os.getenv('KPI_FLAG', 'True') == 'True'
-ENGAGEMENT_SCORE_DEFAULT = float(os.getenv('ENGAGEMENT_SCORE', '85.0'))
-
-# Load model and tokenizer (Updated to use distilgpt2)
-model_name = "distilgpt2"  # Using distilgpt2 for faster response
-tokenizer = AutoTokenizer.from_pretrained(model_name, use_fast=True)
-model = AutoModelForCausalLM.from_pretrained(model_name, low_cpu_mem_usage=True)
-
-if tokenizer.pad_token is None:
-    tokenizer.pad_token = tokenizer.eos_token
-    tokenizer.pad_token_id = tokenizer.convert_tokens_to_ids(tokenizer.pad_token)
-model.config.pad_token_id = tokenizer.pad_token_id
-
-# Refined Prompt to generate day-by-day tasks based on milestones
-PROMPT_TEMPLATE = """You are an AI assistant for construction supervisors. Given the role, project, milestones, and a reflection log, generate:
-
-1. A Daily Checklist with clear and concise tasks based on the role and milestones. 
-   Split the checklist into day-by-day tasks for a specified time period (e.g., one week).
-2. Focus Suggestions based on concerns or keywords in the reflection log. Provide at least 2 suggestions.
-
-Inputs:
-Role: {role}
-Project ID: {project_id}
-Milestones: {milestones}
-Reflection Log: {reflection}
-
-Output Format:
-Checklist (Day-by-Day):
-- Day 1: 
-   - Task 1
-   - Task 2
-- Day 2: 
-   - Task 1
-   - Task 2
-...
-Suggestions:
-- 
-"""
-
-# Salesforce Functions
-def get_roles_from_salesforce():
-    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("SELECT Role__c FROM Supervisor__c WHERE Role__c != NULL")
-        return list(set(record['Role__c'] for record in result['records']))
-    except Exception as e:
-        print(f"⚠️ Error fetching roles: {e}")
-        return ["Site Manager", "Safety Officer", "Project Lead"]
+# Salesforce credentials
+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')
 
-def get_supervisor_name_by_role(role):
+# Function to generate a PDF report for the supervisor
+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')
+            username=SF_USERNAME,
+            password=SF_PASSWORD,
+            security_token=SF_SECURITY_TOKEN,
+            domain=SF_DOMAIN
         )
-        role = role.replace("'", "\\'")
-        result = sf.query(f"SELECT Name FROM Supervisor__c WHERE Role__c = '{role}'")
-        return [record['Name'] for record in result['records']]
+        # Query for the supervisor record in the Supervisor_AI_Coaching__c object
+        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']
+
+        # Update the record with the download link in the Download_Link__c field
+        sf.Supervisor_AI_Coaching__c.update(supervisor_ai_coaching_id, {
+            'Download_Link__c': download_link  # Assuming 'Download_Link__c' is the custom field for storing the link
+        })
+        
+        return "Download link stored successfully."
+
     except Exception as e:
-        print(f"⚠️ Error fetching supervisor names: {e}")
-        return []
+        return f"Error storing download link: {e}"
+
+# Function to generate the report, provide the link, and store it in Salesforce
+def generate_and_store_report(role, supervisor_name, project_id, checklist, suggestions, report_type="PDF"):
+    # Generate the report
+    if report_type == "PDF":
+        report_path = generate_pdf_report(supervisor_name, project_id, checklist, suggestions)
+    else:
+        report_path = generate_csv_report(supervisor_name, project_id, checklist, suggestions)
 
-def get_projects_for_supervisor(supervisor_name):
+    # Create a download link
+    download_link = f"/static/{report_path}"  # Assuming the app is set up to serve static files from the 'static' directory
+    
+    # Store the download link in Salesforce
+    result = store_download_link_in_salesforce(supervisor_name, download_link)
+    
+    return download_link, result
+
+# Function to get roles from Salesforce
+def get_roles_from_salesforce():
     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')
+            username=SF_USERNAME,
+            password=SF_PASSWORD,
+            security_token=SF_SECURITY_TOKEN,
+            domain=SF_DOMAIN
         )
-        supervisor_name = supervisor_name.replace("'", "\\'")
-        supervisor_result = sf.query(f"SELECT Id FROM Supervisor__c WHERE Name = '{supervisor_name}' LIMIT 1")
-        if supervisor_result['totalSize'] == 0:
-            return ""
-        supervisor_id = supervisor_result['records'][0]['Id']
-        project_result = sf.query(f"SELECT Name FROM Project__c WHERE Supervisor_ID__c = '{supervisor_id}' LIMIT 1")
-        return project_result['records'][0]['Name'] if project_result['totalSize'] > 0 else ""
-    except Exception as e:
-        print(f"⚠️ Error fetching project: {e}")
-        return ""
-
-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}"
-
-def generate_salesforce_report_url(supervisor_name, project_id):
-    # Similar function to generate a report URL for supervisor and project
-    return f"https://aicoachforsitesupervisors-dev-ed--c.develop.vf.force.com/apex/ReportPage?supervisorName={supervisor_name}&projectId={project_id}"
-
-# Function to open the dashboard page
-def open_dashboard(role, supervisor_name, project_id):
-    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 open the report page
-def open_report_page(role, supervisor_name, project_id):
-    report_url = generate_salesforce_report_url(supervisor_name, project_id)
-    return f'<a href="{report_url}" target="_blank" rel="noopener noreferrer" style="font-size:16px;">Open Supervisor Report</a>'
-
-# 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.", ""
-
-    prompt = PROMPT_TEMPLATE.format(
-        role=role,
-        project_id=project_id,
-        milestones=milestones,
-        reflection=reflection
-    )
-
-    inputs = tokenizer(prompt, return_tensors="pt", padding=True, truncation=True, max_length=512)
-    try:
-        with torch.no_grad():
-            outputs = model.generate(
-                inputs['input_ids'],
-                max_new_tokens=150,  # Increased max tokens to capture more content
-                no_repeat_ngram_size=2,
-                do_sample=True,
-                top_p=0.9,
-                temperature=0.7,
-                pad_token_id=tokenizer.pad_token_id
-            )
-        result = tokenizer.decode(outputs[0], skip_special_tokens=True)
+        result = sf.query("SELECT Role__c FROM Supervisor__c WHERE Role__c != NULL")
+        return list(set(record['Role__c'] for record in result['records']))
     except Exception as e:
-        print(f"⚠️ Generation error: {e}")
-        return "", ""
-
-    def extract_between(text, start, end):
-        s = text.find(start)
-        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():
-        suggestions = generate_fallback_suggestions(reflection)
-
-    return checklist, suggestions
-
-# Fallback generation for checklist and suggestions
-def generate_fallback_checklist(role, milestones):
-    checklist_items = []
-
-    # 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)
+        print(f"⚠️ Error fetching roles: {e}")
+        return ["Site Manager", "Safety Officer", "Project Lead"]
 
 # Interface
 def create_interface():
@@ -215,7 +144,7 @@ def create_interface():
             clear = gr.Button("Clear")
             refresh = gr.Button("🔄 Refresh Roles")
             dashboard_btn = gr.Button("Dashboard")
-            report_btn = gr.Button("Report")
+            report_btn = gr.Button("Download Report")
 
         checklist_output = gr.Textbox(label="✅ Daily Checklist")
         suggestions_output = gr.Textbox(label="💡 Focus Suggestions")
@@ -235,7 +164,10 @@ def create_interface():
         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)
-        report_btn.click(fn=open_report_page, inputs=[role, supervisor_name, project_id], outputs=report_link)
+        
+        report_btn.click(fn=generate_and_store_report, 
+                         inputs=[role, supervisor_name, project_id, checklist_output, suggestions_output], 
+                         outputs=[report_link, gr.HTML("")])
 
     return demo