aiprims 0.1.0

Foundational execution primitives for AI, ML, and data systems

aiprims

Foundational execution primitives for AI, ML, and data systems.

aiprims is a lightweight, opinionated Python library that provides low-level primitives for execution identity, deterministic hashing, run reproducibility, and traceability across AI and ML systems.

It operates below orchestration tools, experiment trackers, and model frameworks. It does not replace them. It sits underneath all of them as a correctness foundation.

Differences between runs should never be mysterious.

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Install

pip install aiprims

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Modules

Module	Status	Purpose
aiprims.core.hash	v0.1.0	Deterministic content-derived identity for any object, file, or directory
aiprims.core.manifest	v0.1.0	Immutable execution manifest capturing all run inputs
aiprims.core.idempotency	v0.1.0	Idempotency keys for agent tool calls and pipeline steps
aiprims.core.config	v0.1.0	Canonical config normalisation before hashing
aiprims.core.env	v0.1.0	Environment fingerprinting — Python, OS, packages
aiprims.core.seed	v0.1.0	Explicit randomness control and seed isolation
aiprims.nlp	planned	NLP pipeline execution primitives
aiprims.llm	planned	LLM prompt fingerprinting and inference identity
aiprims.rag	planned	Chunk identity and corpus fingerprinting for RAG systems
aiprims.agents	planned	Execution envelopes and tool call wrapping for agentic systems

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Design Invariants

• Randomness is never implicit — all stochastic behavior must be explicitly seeded or flagged
• All inputs influencing execution must be visible — hidden dependencies are treated as failures
• Identity computation is always deterministic — same inputs, same identity, always
• Run identity is derivable locally — zero reliance on external systems
• Failures are explicit — no silent recovery from invalid states

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Part of the Garvaman OSS Stack

aiprims is the foundational layer of a composable AI infrastructure stack:

orion → application layer
agiorcx → agent coordination layer
ragaxis → RAG pipeline layer
aiprims → execution primitives (this library)

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License

MIT © 2026 Sai Harsha Kondaveeti