geethaAICoach3 / app.py
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import gradio as gr
import torch
from transformers import AutoModelForCausalLM, AutoTokenizer
from simple_salesforce import Salesforce
import os
from dotenv import load_dotenv
# Load environment variables
load_dotenv()
# Check if required environment variables are set
required_env_vars = ['SF_USERNAME', 'SF_PASSWORD', 'SF_SECURITY_TOKEN']
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}")
# Get configurable values for KPI_Flag__c and Engagement_Score__c
KPI_FLAG_DEFAULT = os.getenv('KPI_FLAG', 'True') == 'True' # Default to True if not set
ENGAGEMENT_SCORE_DEFAULT = float(os.getenv('ENGAGEMENT_SCORE', '85.0')) # Default to 85.0
# Initialize model and tokenizer
model_name = "distilgpt2"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name)
# Avoid warnings by setting pad token
if tokenizer.pad_token is None:
tokenizer.pad_token = tokenizer.eos_token if tokenizer.eos_token else "[PAD]"
tokenizer.pad_token_id = tokenizer.convert_tokens_to_ids(tokenizer.pad_token)
model.config.pad_token_id = tokenizer.pad_token_id
# Prompt template for generating structured output
PROMPT_TEMPLATE = """You are an AI coach for construction supervisors. Based on the following inputs, generate a daily checklist, focus suggestions, and a motivational quote.
Inputs:
Role: {role}
Project: {project_id}
Milestones: {milestones}
Reflection: {reflection}
Format your response clearly like this:
Checklist:
- {milestones_list}
Suggestions:
- {suggestions_list}
Quote:
- Your motivational quote here
"""
# Function to get all 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')
)
# Query distinct Role__c values
result = sf.query("SELECT Role__c FROM Supervisor__c WHERE Role__c != NULL")
# Extract roles and remove duplicates
roles = list(set(record['Role__c'] for record in result.get('records', [])))
print(f"βœ… Fetched {len(roles)} unique roles from Salesforce")
return roles
except Exception as e:
print(f"⚠️ Error fetching roles from Salesforce: {e}")
print("Using fallback roles...")
return ["Site Manager", "Safety Officer", "Project Lead"] # Match actual active roles
# Function to get supervisor's Name (Auto Number) by role
def get_supervisor_name_by_role(role):
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')
)
# Escape single quotes in the role to prevent SOQL injection
role = role.replace("'", "\\'")
# Query all supervisors for the selected role
result = sf.query(f"SELECT Name FROM Supervisor__c WHERE Role__c = '{role}'")
if result['totalSize'] == 0:
print("❌ No matching supervisors found.")
return []
# Extract all supervisor names
supervisor_names = [record['Name'] for record in result['records']]
print(f"βœ… Found supervisors: {supervisor_names} for role: {role}")
return supervisor_names
except Exception as e:
print(f"⚠️ Error fetching supervisor names: {e}")
return []
# Function to get project IDs and names assigned to selected supervisor
def get_projects_for_supervisor(supervisor_name):
try:
# Use the selected supervisor name to fetch the associated project
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')
)
# Escape single quotes in the supervisor_name
supervisor_name = supervisor_name.replace("'", "\\'")
# Step 1: Get the Salesforce record ID of the supervisor based on the Name
supervisor_result = sf.query(f"SELECT Id FROM Supervisor__c WHERE Name = '{supervisor_name}' LIMIT 1")
if supervisor_result['totalSize'] == 0:
print("❌ No supervisor found with the given name.")
return ""
supervisor_id = supervisor_result['records'][0]['Id']
# Step 2: Query Project__c records where Supervisor_ID__c matches the supervisor's record ID
project_result = sf.query(f"SELECT Name FROM Project__c WHERE Supervisor_ID__c = '{supervisor_id}' LIMIT 1")
if project_result['totalSize'] == 0:
print("❌ No project found for supervisor.")
return ""
project_name = project_result['records'][0]['Name']
print(f"βœ… Found project: {project_name} for supervisor: {supervisor_name}")
return project_name
except Exception as e:
print(f"⚠️ Error fetching project for supervisor: {e}")
return ""
# Function to generate AI-based coaching output
def generate_outputs(role, supervisor_name, project_id, milestones, reflection):
if not all([role, supervisor_name, project_id, milestones, reflection]):
return "Error: All fields are required.", "", ""
# Format the prompt
milestones_list = "\n- ".join([m.strip() for m in milestones.split(",")])
suggestions_list = ""
if "delays" in reflection.lower():
suggestions_list = "- Consider adjusting timelines to accommodate delays.\n- Communicate delays to all relevant stakeholders."
elif "weather" in reflection.lower():
suggestions_list = "- Ensure team has rain gear.\n- Monitor weather updates for possible further delays."
elif "equipment" in reflection.lower():
suggestions_list = "- Inspect all equipment to ensure no malfunctions.\n- Schedule maintenance if necessary."
# Fill in the prompt template
prompt = PROMPT_TEMPLATE.format(
role=role,
project_id=project_id,
milestones=milestones,
reflection=reflection,
milestones_list=milestones_list,
suggestions_list=suggestions_list
)
# Tokenize input
inputs = tokenizer(prompt, return_tensors="pt", max_length=512, truncation=True, padding=True)
# Generate response
try:
with torch.no_grad():
outputs = model.generate(
inputs['input_ids'],
max_length=1024, # Increased to allow for longer outputs
num_return_sequences=1,
no_repeat_ngram_size=2,
do_sample=True,
top_p=0.9,
temperature=0.8,
pad_token_id=tokenizer.pad_token_id
)
generated_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
except Exception as e:
print(f"⚠️ Error during model generation: {e}")
return "Error: Failed to generate outputs.", "", ""
# Parse sections
def extract_section(text, start_marker, end_marker):
start = text.find(start_marker)
if start == -1:
return "Not found"
start += len(start_marker)
end = text.find(end_marker, start) if end_marker else len(text)
return text[start:end].strip()
checklist = extract_section(generated_text, "Checklist:\n", "Suggestions:")
suggestions = extract_section(generated_text, "Suggestions:\n", "Quote:")
quote = extract_section(generated_text, "Quote:\n", None)
# Save to Salesforce
save_to_salesforce(role, project_id, milestones, reflection, checklist, suggestions, quote, supervisor_name)
return checklist, suggestions, quote
# Function to check if a field exists in a Salesforce object
def field_exists(sf, object_name, field_name):
try:
# Describe the object to get its fields
obj_desc = getattr(sf, object_name).describe()
fields = [field['name'] for field in obj_desc['fields']]
return field_name in fields
except Exception as e:
print(f"⚠️ Error checking if field {field_name} exists in {object_name}: {e}")
return False
# Function to create a record in Salesforce
def save_to_salesforce(role, project_id, milestones, reflection, checklist, suggestions, quote, supervisor_name):
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')
)
# Escape single quotes in supervisor_name and project_id
supervisor_name = supervisor_name.replace("'", "\\'")
project_id = project_id.replace("'", "\\'")
# Step 1: Get the Salesforce record ID for the supervisor
supervisor_result = sf.query(f"SELECT Id FROM Supervisor__c WHERE Name = '{supervisor_name}' LIMIT 1")
if supervisor_result['totalSize'] == 0:
print(f"❌ No supervisor found with Name: {supervisor_name}")
return
supervisor_id = supervisor_result['records'][0]['Id']
# Step 2: Get the Salesforce record ID for the project
project_result = sf.query(f"SELECT Id FROM Project__c WHERE Name = '{project_id}' LIMIT 1")
if project_result['totalSize'] == 0:
print(f"❌ No project found with Name: {project_id}")
return
project_record_id = project_result['records'][0]['Id']
# Truncate text fields to avoid exceeding Salesforce field length limits (assuming 255 characters for simplicity)
MAX_TEXT_LENGTH = 255
checklist = checklist[:MAX_TEXT_LENGTH] if checklist else ""
suggestions = suggestions[:MAX_TEXT_LENGTH] if suggestions else ""
reflection = reflection[:MAX_TEXT_LENGTH] if reflection else ""
# Prepare data for Salesforce with explicit mapping
data = {
'Supervisor_ID__c': supervisor_id, # Lookup field expects the record ID of Supervisor__c
'Project_ID__c': project_record_id, # Lookup field expects the record ID of Project__c
'Daily_Checklist__c': checklist, # Maps to the generated Daily Checklist
'Suggested_Tips__c': suggestions, # Maps to the generated Focus Suggestions
'Reflection_Log__c': reflection, # Maps to the Reflection Log input
'KPI_Flag__c': KPI_FLAG_DEFAULT, # Configurable via .env
'Engagement_Score__c': ENGAGEMENT_SCORE_DEFAULT # Configurable via .env
}
# Check if Milestones_KPIs__c field exists before mapping
if field_exists(sf, 'Supervisor_AI_Coaching__c', 'Milestones_KPIs__c'):
# Truncate milestones as well if the field exists
milestones = milestones[:MAX_TEXT_LENGTH] if milestones else ""
data['Milestones_KPIs__c'] = milestones
else:
print("⚠️ Milestones_KPIs__c field does not exist in Supervisor_AI_Coaching__c. Skipping mapping.")
# Create record
response = sf.Supervisor_AI_Coaching__c.create(data)
print("βœ… Record created successfully in Salesforce.")
print("Record ID:", response['id'])
except Exception as e:
print(f"❌ Error saving to Salesforce: {e}")
print("Data being sent:", data)
if hasattr(e, 'content'):
print("Salesforce API response:", e.content)
# Gradio Interface
def create_interface():
# Fetch roles from Salesforce
roles = get_roles_from_salesforce()
print(f"Fetched Roles: {roles}")
with gr.Blocks(theme="soft") as demo:
gr.Markdown("# πŸ—οΈ Construction Supervisor AI Coach")
gr.Markdown("Enter details to generate a daily checklist, focus suggestions, and a motivational quote.")
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)")
reflection = gr.Textbox(label="Reflection Log", lines=4)
with gr.Row():
submit = gr.Button("Generate", variant="primary")
clear = gr.Button("Clear")
refresh_btn = gr.Button("πŸ”„ Refresh Roles")
checklist_output = gr.Textbox(label="βœ… Daily Checklist")
suggestions_output = gr.Textbox(label="πŸ’‘ Focus Suggestions")
quote_output = gr.Textbox(label="✨ Motivational Quote")
# Event: When role changes, update supervisor name dropdown
role.change(
fn=lambda r: gr.update(choices=get_supervisor_name_by_role(r)),
inputs=[role],
outputs=[supervisor_name]
)
# Event: When supervisor name changes, update project ID
supervisor_name.change(
fn=get_projects_for_supervisor,
inputs=[supervisor_name],
outputs=[project_id]
)
submit.click(
fn=generate_outputs,
inputs=[role, supervisor_name, project_id, milestones, reflection],
outputs=[checklist_output, suggestions_output, quote_output]
)
clear.click(
fn=lambda: ("", "", "", "", ""),
inputs=None,
outputs=[role, supervisor_name, project_id, milestones, reflection]
)
refresh_btn.click(
fn=lambda: gr.update(choices=get_roles_from_salesforce()),
outputs=role
)
return demo
if __name__ == "__main__":
app = create_interface()
app.launch()