Code & Development · PyPI

langchain-ejentum

LangChain integration for the Ejentum Reasoning Harness. Eight BaseTool subclasses: four dynamic (reasoning, code, anti-deception, memory) and four adaptive (adaptive-reasoning, adaptive-code, adaptive-anti-deception, adaptive-memory) that pre-fit the operation to the task via an adapter LLM. Each call returns a structured cognitive injection: a natural-language procedure plus an executable reasoning topology.

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Details

Author
Ejentum
GitHub profile
@ejentum
Category
Code & Development
Platform
PyPI
GitHub
https://github.com/ejentum/langchain-ejentum
Framework
langchain
Language
python
Stars
0
First indexed
2026-06-01
Last active
—
Directory sync
2026-06-01
@ejentum

Overview

LangChain integration for the Ejentum Reasoning Harness. Eight BaseTool subclasses: four dynamic (reasoning, code, anti-deception, memory) and four adaptive (adaptive-reasoning, adaptive-code, adaptive-anti-deception, adaptive-memory) that pre-fit the operation to the task via an adapter LLM. Each call returns a structured cognitive injection: a natural-language procedure plus an executable reasoning topology.

Quick start

pip

pip install langchain-ejentum

Snippet generated from the published metadata; check the source page for full setup, configuration, and prerequisites.

What langchain-ejentum can do

agentllmaireasoningagentic-ai
  • Agent — Plans, decides, and executes multi-step tasks autonomously.
  • Llm — llm task automation.
  • Ai — ai task automation.
  • Reasoning — Works through multi-step problems with explicit logic.
  • Agentic Ai — agentic-ai task automation.

Frequently asked questions

What is langchain-ejentum?
LangChain integration for the Ejentum Reasoning Harness. Eight BaseTool subclasses: four dynamic (reasoning, code, anti-deception, memory) and four adaptive (adaptive-reasoning, adaptive-code, adaptive-anti-deception, adaptive-memory) that pre-fit the operation to the task via an adapter LLM. Each call returns a structured cognitive injection: a natural-language procedure plus an executable reasoning topology.
How do I install langchain-ejentum?
Use pip: `pip install langchain-ejentum`. Full setup details on the source page linked above.
Is langchain-ejentum open source?
langchain-ejentum is published on PyPI.
What are alternatives to langchain-ejentum?
Comparable agents include ECC, system-prompts-and-models-of-ai-tools, claude-code. Browse the full MeshKore directory to find more by category, framework, or language.

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Profile data for langchain-ejentum is sourced from PyPI, published by Ejentum.

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