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Salesforce

Tools for interacting with Salesforce.

Overviewโ€‹

This notebook provides examples of interacting with Salesforce using LangChain.

Setupโ€‹

  1. Install the required dependencies:
   pip install langchain-salesforce
  1. Set up your Salesforce credentials as environment variables:
   export SALESFORCE_USERNAME="your-username"
export SALESFORCE_PASSWORD="your-password"
export SALESFORCE_SECURITY_TOKEN="your-security-token"
export SALESFORCE_DOMAIN="test" # Use 'test' for sandbox, remove for production

These environment variables will be automatically picked up by the integration.

Getting Your Security Tokenโ€‹

If you need a security token:

  1. Log into Salesforce
  2. Go to Settings
  3. Click on "Reset My Security Token" under "My Personal Information"
  4. Check your email for the new token

Instantiationโ€‹

import os

from langchain_salesforce import SalesforceTool

username = os.getenv("SALESFORCE_USERNAME", "your-username")
password = os.getenv("SALESFORCE_PASSWORD", "your-password")
security_token = os.getenv("SALESFORCE_SECURITY_TOKEN", "your-security-token")
domain = os.getenv("SALESFORCE_DOMAIN", "login")

tool = SalesforceTool(
username=username, password=password, security_token=security_token, domain=domain
)

Invocationโ€‹

def execute_salesforce_operation(
operation, object_name=None, query=None, record_data=None, record_id=None
):
"""Executes a given Salesforce operation."""
request = {"operation": operation}
if object_name:
request["object_name"] = object_name
if query:
request["query"] = query
if record_data:
request["record_data"] = record_data
if record_id:
request["record_id"] = record_id
result = tool.run(request)
return result

Queryโ€‹

This example queries Salesforce for 5 contacts.

query_result = execute_salesforce_operation(
"query", query="SELECT Id, Name, Email FROM Contact LIMIT 5"
)

Describe an Objectโ€‹

Fetches metadata for a specific Salesforce object.

describe_result = execute_salesforce_operation("describe", object_name="Account")

List Available Objectsโ€‹

Retrieves all objects available in the Salesforce instance.

list_objects_result = execute_salesforce_operation("list_objects")

Create a New Contactโ€‹

Creates a new contact record in Salesforce.

create_result = execute_salesforce_operation(
"create",
object_name="Contact",
record_data={"LastName": "Doe", "Email": "doe@example.com"},
)

Update a Contactโ€‹

Updates an existing contact record.

update_result = execute_salesforce_operation(
"update",
object_name="Contact",
record_id="003XXXXXXXXXXXXXXX",
record_data={"Email": "updated@example.com"},
)

Delete a Contactโ€‹

Deletes a contact record from Salesforce.

delete_result = execute_salesforce_operation(
"delete", object_name="Contact", record_id="003XXXXXXXXXXXXXXX"
)

Chainingโ€‹

from langchain.prompts import PromptTemplate
from langchain_openai import ChatOpenAI
from langchain_salesforce import SalesforceTool

tool = SalesforceTool(
username=username, password=password, security_token=security_token, domain=domain
)

llm = ChatOpenAI(model="gpt-4o-mini")

prompt = PromptTemplate.from_template(
"What is the name of the contact with the id {contact_id}?"
)

chain = prompt | tool.invoke | llm

result = chain.invoke({"contact_id": "003XXXXXXXXXXXXXXX"})
API Reference:PromptTemplate | ChatOpenAI

API referenceโ€‹

langchain-salesforce README


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