sf-code-gen README

Salesforce code generation utils using Local LLMs. Uses the Local LLMs running with ollama. Default LLM is llama3.2:latest.

Features

SCG:codegen

• Generates Apex Code for the given requirements using LLM

SCG:summarize

• Summarizes the Opportunities owned by the given user email-id

• Make sure you have logged in the Salesforce org using:

    # for dev / production orgs
	sf force auth web login -s               

    # for sandboxes
	sf force auth web login -s    -r https://test.salesforce.com           

SCG:salescloud objects record counts

• Generate KPI insights for Salesforce Sales Cloud object record counts

• Make sure you have logged in the Salesforce org using:

    # for dev / production orgs
	sf force auth web login -s               

    # for sandboxes
	sf force auth web login -s    -r https://test.salesforce.com           

SCG:salescloud objects field population summary

• Analyze and summarize the field population percentages for the Salesforce Sales Cloud objects

• Make sure you have logged in the Salesforce org using:

    # for dev / production orgs
	sf force auth web login -s               

    # for sandboxes
	sf force auth web login -s    -r https://test.salesforce.com           

SCG:salescloud opportunity chart

• Generate Python code to create a bar chart using matplotlib for StageName vs Opportunity Count

• Make sure you have logged in the Salesforce org using:

    # for dev / production orgs
	sf force auth web login -s               

    # for sandboxes
	sf force auth web login -s    -r https://test.salesforce.com           

SCG:translate

• Takes in xlf file in TSV (tab separated values)

  • Use this tool to convert xlf to TSV

• Translates the lines in this TSV file for the given language

SCG:image read

• Takes in an image file and describes about the image in English, uses llava model as LLM

SCG:Run Python code in the editor (markdown)"

• Takes in markdown file with a python code segment and runs it

Release Notes

0.0.1

• Initial release

0.0.2

• Image read added

0.0.3

• Run Python code in the markdown doc added

Enjoy!