Skip to main content
Logo

AmritaSense

PyPI Version Python Version License Discord QQ Group

"Sense is all you need."

AmritaSense is a general-purpose workflow orchestration engine that replaces traditional graph-based models with an instruction set architecture—treating workflows not as nodes-and-edges diagrams, but as programmable execution streams driven by a lightweight virtual machine.

Why AmritaSense?

Most workflow engines force you into a graph mindset: define nodes, connect edges, manage state objects. AmritaSense takes a different path. You compose nodes and control flow just like writing ordinary code—the engine compiles them into a linear instruction sequence, then executes them step by step. The result: zero scheduling overhead, native interrupt support, and the expressive power of assembly-level control flow.

Core Features

  • Complete Instruction SetIF/ELIF/ELSE, WHILE/DO-WHILE, GOTO/CALL, TRY/CATCH/THEN/FIN, NOP, INTERRUPT. All control flow is first-class, not simulated through graph routing.
  • VM-Style Execution—A program counter (PointerVector) and call stack drive execution. Jumps are integer operations, not graph traversals.
  • Native REPL Debuggerfrom amrita_sense.debugger import * gives you breakpoints, stepping, and state inspection. Sync API for interactive REPL use (step, cont); async API (step_async, cont_async) for scripted debugging. Built atop the engine's Panic/Recover mechanism and composite middleware injection.
  • Async-Native Suspend/Resume—Two Future callbacks enable full workflow interruption at any node boundary. Built for debuggers and human-in-the-loop systems.
  • Declarative Dependency Injection—Nodes declare dependencies via function signatures. The engine resolves them at runtime with type matching and concurrent resolution.
  • Ultra Lightweight— Compiles 100,000 nodes in ~200ms. Runs anywhere from Raspberry Pi to cloud.
  • Self-Compile Instructions—Extend the instruction set with SelfCompileInstruction. Compile-time expansion, zero runtime overhead.

Installation

pip install amrita-sense

Quick Look

import asyncio
from amrita_sense import Node, WorkflowInterpreter as WorkflowPC, IF

@Node()
def condition() -> bool: return True

@Node()
def action(): print("Done")

@Node()
def end(): print("End of workflow")

flow = IF(condition, action) >> end
pc = WorkflowPC(flow.render())

if __name__ == "__main__":
  asyncio.run(pc.run())

See more demos in demos/

Documentation

Full guides, concept explanations, and API reference at sense.amritabot.com.

Contributing

Contributions are welcome. See CONTRIBUTING.md and our Code of Conduct.

License

Apache V2. See LICENSE.

AIGC Content Licensing Policy

AACLP V1. See POLICY_OF_AIGC (Official Link) for details.

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

amrita_sense-0.5.1.tar.gz (93.7 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

amrita_sense-0.5.1-py3-none-any.whl (86.6 kB view details)

Uploaded Python 3

File details

Details for the file amrita_sense-0.5.1.tar.gz.

File metadata

  • Download URL: amrita_sense-0.5.1.tar.gz
  • Upload date:
  • Size: 93.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: uv/0.11.33 {"installer":{"name":"uv","version":"0.11.33","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"Ubuntu","version":"24.04","id":"noble","libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":true}

File hashes

Hashes for amrita_sense-0.5.1.tar.gz
Algorithm Hash digest
SHA256 0e289824fdeeb114111866282a3e5bca2c3d9a45503745cb136ea9320f8c064c
MD5 410fe0baa4e0f4052f784e760b0ec9b4
BLAKE2b-256 7aba90b336dbed2bfbb889e46633368b1064dca1351e8e20783b1e236b207ebb

See more details on using hashes here.

File details

Details for the file amrita_sense-0.5.1-py3-none-any.whl.

File metadata

  • Download URL: amrita_sense-0.5.1-py3-none-any.whl
  • Upload date:
  • Size: 86.6 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: uv/0.11.33 {"installer":{"name":"uv","version":"0.11.33","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"Ubuntu","version":"24.04","id":"noble","libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":true}

File hashes

Hashes for amrita_sense-0.5.1-py3-none-any.whl
Algorithm Hash digest
SHA256 1bd400432d3c2532b0ad0de29c9fa356fef0a2b54044cd1fd5f78ba8fc86de7e
MD5 d0d70f94a836ab1a00447803beaed818
BLAKE2b-256 6184eea1e78ccfc90fd40f74a010080b200662eefc097f2465be28eb1f44c629

See more details on using hashes here.

Release history Release notifications | RSS feed

0.7.0

2 files

0.6.2

2 files

0.6.1

2 files

0.6.0

2 files

This release

0.5.1 This release

2 files

0.5.0

2 files

0.4.6

2 files

0.4.5.1

2 files

0.4.5

2 files

0.4.4

2 files

0.4.3

2 files

0.4.2

2 files

0.4.1

2 files

0.4.0

2 files

0.3.3.1

2 files

0.3.3

2 files

0.3.2

2 files

0.3.1.post1

2 files

0.3.1

2 files

0.3.0

2 files

0.2.4

2 files

0.2.3

2 files

0.2.2

2 files

0.2.1

2 files

0.2.0

2 files

0.1.0

2 files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page