Update utils.py

utils.py

@@ -1,6 +1,4 @@
 import matplotlib.pyplot as plt
-from simple_salesforce import Salesforce
-import os
 
 def validate_inputs(input_data):
     """
@@ -35,48 +33,4 @@ def generate_heatmap(delay_probability, label):
     ax.set_xlabel("Delay Probability (%)")
     ax.set_title("Delay Risk Heatmap")
     plt.tight_layout()
-    return fig
-
-def send_to_salesforce(input_data, prediction):
-    """
-    Send prediction data to Salesforce as a Prediction__c custom object record.
-    """
-    # Salesforce credentials (set these in Hugging Face Space environment variables)
-    sf_username = os.getenv("SF_USERNAME")
-    sf_password = os.getenv("SF_PASSWORD")
-    sf_security_token = os.getenv("SF_SECURITY_TOKEN")
-    sf_client_id = os.getenv("SF_CLIENT_ID")
-    sf_client_secret = os.getenv("SF_CLIENT_SECRET")
-    sf_domain = os.getenv("SF_DOMAIN", "login")  # Use 'test' for sandbox, 'login' for production
-
-    if not all([sf_username, sf_password, sf_security_token, sf_client_id, sf_client_secret]):
-        raise ValueError("Missing Salesforce credentials. Set SF_USERNAME, SF_PASSWORD, SF_SECURITY_TOKEN, SF_CLIENT_ID, and SF_CLIENT_SECRET in environment variables.")
-
-    # Authenticate with Salesforce
-    sf = Salesforce(
-        username=sf_username,
-        password=sf_password,
-        security_token=sf_security_token,
-        client_id=sf_client_id,
-        client_secret=sf_client_secret,
-        domain=sf_domain
-    )
-
-    # Prepare data for Salesforce
-    high_risk_phases_text = "; ".join([f"{p['phase']}: {p['task']} ({p['risk']:.1f}%)" for p in prediction['high_risk_phases']])
-    data = {
-        "Project_Name__c": input_data["project_name"],
-        "Phase__c": input_data["phase"],
-        "Task__c": input_data["task"],
-        "Delay_Probability__c": prediction["delay_probability"],
-        "AI_Insights__c": prediction["ai_insights"],
-        "Weather_Condition__c": prediction["weather_condition"],
-        "High_Risk_Phases__c": high_risk_phases_text
-    }
-
-    # Create a new record in Prediction__c
-    try:
-        result = sf.Prediction__c.create(data)
-        return f"Successfully created Salesforce record with ID: {result['id']}"
-    except Exception as e:
-        raise Exception(f"Failed to create Salesforce record: {str(e)}")
+    return fig