Salesforce

The Salesforce Node allows you to connect directly to your Salesforce CRM account and query structured sales and customer data. It supports SQL queries to retrieve contact, lead, opportunity, and account information, making it easier to automate workflows, analyze performance, or power downstream nodes like LLMs or VectorDBs.

Once connected, Stack AI can use this data to enhance sales processes, generate insights, and improve decision-making.

Step-by-step guide for Salesforce connection credentials:

1. Obtain your login credentials:

   • Username: your Salesforce login name.

   • Password: your Salesforce account password.

1. After logging in, click on your profile picture on the upper right.

1. A dropdown menu will appear, click on Settings.

1. On the Settings page, on the left navigation, select Reset My Security Token.

1. Click on Reset Security Token.

1. On click, the new Security token will be sent to the email associated to your Salesforce account.

1. Finally, in the email, this will be the Security token that will be used for the connection.

How to connect it?

Steps to connect:

1. Add the Salesforce node from the Apps section into your Stack AI project.

1. Select "Query Salesforce" as the Action.

1. Click on "Select a connection" or create a new connection with your credentials.

1. Choose the appropriate domain for your Salesforce environment:

   Domain

   Use When

   "login" or left blank

   Connecting to production or developer orgs

   "test"

   Connecting to a sandbox instance

   mycustomdomain

   Using a custom domain (recommended for SSO or OAuth setups)

1. Add your Salesforce Schema in the configurations of the node to define which table you want to extract.

   • For example: TABLE Contact (Id TEXT, Name TEXT, Industry TEXT);

     
   • To list tables from your Salesforce account, you can run the included Python script below on your local machine.

from simple_salesforce import Salesforce

# Salesforce credentials (replace with environment variables in production)
username = ""
password = ""
security_token = ""

# 🔍 Specify object names to include (DANGER leaving the list empty will include ALL)
included_objects = ["Contact", "Account", "Opportunity"]  # Case-sensitive

# Connect to Salesforce
sf = Salesforce(username=username, password=password, security_token=security_token)

# Mapping Salesforce field types to SQL types
def map_salesforce_type(sf_type):
    mapping = {
        "string": "TEXT",
        "textarea": "TEXT",
        "picklist": "TEXT",
        "id": "VARCHAR(18)",
        "boolean": "BOOLEAN",
        "int": "INTEGER",
        "double": "FLOAT",
        "currency": "DECIMAL(18,2)",
        "percent": "DECIMAL(5,2)",
        "date": "DATE",
        "datetime": "TIMESTAMP",
        "email": "TEXT",
        "phone": "TEXT",
        "url": "TEXT",
        "reference": "VARCHAR(18)",
        "base64": "BYTEA",
        "location": "TEXT",
    }
    return mapping.get(sf_type, "TEXT")


# Get all object descriptions
objects = sf.describe()["sobjects"]

# Open file for writing schema output
with open("salesforce_schema.txt", "w") as file:
    for obj in objects:
        obj_name = obj["name"]
        
        # Apply filter if specified
        if included_objects and obj_name not in included_objects:
            continue
        
        try:
            obj_details = sf.__getattr__(obj_name).describe()
            field_defs = []

            for field in obj_details["fields"]:
                field_name = field["name"]
                field_type = map_salesforce_type(field["type"])
                field_defs.append(f"{field_name} {field_type}")

            field_list = ", ".join(field_defs)
            table_def = f"TABLE {obj_name} ({field_list});"
            print(table_def)
            file.write(table_def + "\n")

        except Exception as e:
            error_msg = f"-- Could not process {obj_name}: {e}"
            print(error_msg)
            file.write(error_msg + "\n")

print("\nFiltered schema has been saved to 'salesforce_schema.txt'")

1. Connect the input, it can be in natural language or SOQL query from an Input node or LLM.

2. Connect the output to a downstream node like an Output node or directly to an LLM.

Visual overview

Below are some examples of valid SQL queries for your Salesforce database, provided that it has been included in the Schema:

SELECT Name, Email FROM Contact

SELECT Id, Email FROM Contact WHERE Income > USD10000

SELECT Id, Email FROM Contact WHERE LastName = 'Aceituno'

SELECT Id, Email, Name, ParentAccount.Name FROM Contact

Available Actions

1. Salesforce Query

• Purpose: Query Salesforce using plain English or SOQL.

• Inputs:

  • sql_schema (required): The database schema (tables, columns, types, etc.).

  • query (required): Your question in plain English or a SOQL query.

2. Create Case

• Purpose: Create a new case in Salesforce.

• Inputs:

  • subject (required): The subject/title of the case.

  • status (optional): Status of the case (e.g., New, Working, Closed).

  • priority (optional): Priority level (e.g., High, Medium, Low).

  • origin (optional): Source of the case (e.g., Web, Phone, Email).

  • description (optional): Detailed description.

  • account_id (optional): Salesforce Account ID to associate.

  • contact_id (optional): Salesforce Contact ID to associate.

3. Update Case

• Purpose: Update an existing case.

• Inputs:

  • case_id (required): Salesforce Case ID to update.

  • subject (optional): New subject/title.

  • status (optional): New status.

  • priority (optional): New priority.

  • origin (optional): New origin/source.

  • description (optional): New description.

  • account_id (optional): New Account ID.

  • contact_id (optional): New Contact ID.

4. Delete Case

• Purpose: Delete a case.

• Inputs:

  • case_id (required): Salesforce Case ID to delete.

5. Create Opportunity

• Purpose: Create a new opportunity.

• Inputs:

  • name (required): Name of the opportunity.

  • stage_name (required): Sales stage (e.g., Prospecting, Closed Won).

  • close_date (required): Expected close date (YYYY-MM-DD).

  • amount (optional): Opportunity amount.

  • account_id (optional): Account ID to associate.

  • description (optional): Description.

6. Update Opportunity

• Purpose: Update an existing opportunity.

• Inputs:

  • opportunity_id (required): Salesforce Opportunity ID to update.

  • name (optional): New name.

  • stage_name (optional): New stage.

  • close_date (optional): New close date.

  • amount (optional): New amount.

  • description (optional): New description.

7. Delete Opportunity

• Purpose: Delete an opportunity.

• Inputs:

  • opportunity_id (required): Salesforce Opportunity ID to delete.

8. Create Contact

• Purpose: Create a new contact.

• Inputs:

  • last_name (required): Last name of the contact.

  • first_name (optional): First name.

  • email (optional): Email address.

  • phone (optional): Phone number.

  • account_id (optional): Account ID to associate.

  • title (optional): Job title.

9. Update Contact

• Purpose: Update an existing contact.

• Inputs:

  • contact_id (required): Salesforce Contact ID to update.

  • last_name (optional): New last name.

  • first_name (optional): New first name.

  • email (optional): New email.

  • phone (optional): New phone.

  • title (optional): New job title.

10. Delete Contact

• Purpose: Delete a contact.

• Inputs:

  • contact_id (required): Salesforce Contact ID to delete.

If you need details on the outputs or want to see the full schema for any specific action, let me know!