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कर्म — karma by Darshankumar Joshi

⚡ कर्म

karma

Bhagavad Gita 3.5 — Karma Yoga

Sacred Action — the central law of Gita

Workflow orchestration for LLM agents. DAG-based execution, parallel steps, checkpointing.

Python Zero Dependencies Vedic Arsenal License

Formerly agent-workflow — Part of the Vedic Arsenal: 100 production-grade Python libraries for LLM agents, each named from the Vedas, Puranas, and Mahakavyas.


The Vedic Principle

"Karmanye vadhikaraste ma phaleshu kadachana" — Your right is to action alone, never to the fruits of action. — Bhagavad Gita 2.47

This is the central law of existence, and it is the central principle of karma — the workflow engine.

Each stage in the workflow has its dharma: its specific action, its specific responsibility. The pipeline does not concern itself with final outcomes — it executes each step with perfection and passes the result to the next stage. Budget enforcement, retry hooks, observability — all built into the sacred workflow of action, not outcome.


How It Works

flowchart LR
    A[Input] --> B[Stage 1]
    B --> C[Stage 2]
    C --> D[LLM Call]
    D --> E[Stage 4]
    E --> F[Output]
    B & C & D & E --> G[Budget Check]
    style D fill:#f59e0b,color:#000
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Installation

pip install karma

Or from source:

git clone https://github.com/darshjme/karma.git
cd karma && pip install -e .

Quick Start

from karma import *

# See examples/ for full usage

The Vedic Arsenal

karma is one of 100 libraries in darshjme/arsenal — each named from sacred Indian literature:

Sanskrit Name Source Technical Function
karma Bhagavad Gita 3.5 — Karma Yoga Sacred Action — the central law of Gita

Each library solves one problem. Zero external dependencies. Pure Python 3.8+.


Contributing

  1. Fork the repo
  2. Create feature branch (git checkout -b fix/your-fix)
  3. Add tests — zero dependencies only
  4. Open a PR

⚡ Built by Darshankumar Joshi · @thedarshanjoshi

"कर्मण्येवाधिकारस्ते मा फलेषु कदाचन" Your right is to action alone, never to its fruits. — Bhagavad Gita 2.47

Vedic Arsenal · GitHub · Twitter

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DAG-based workflow orchestration for LLM agents — topological sort, parallel execution, cycle detection, fault isolation. Zero dependencies.

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