langchain-arp 0.1.0

LangChain Document Loader for reasoning.json — the Agentic Reasoning Protocol

langchain-arp

LangChain Document Loader for reasoning.json — the Agentic Reasoning Protocol

Load brand reasoning directives, hallucination corrections, and counterfactual logic into any LangChain-powered AI agent with 3 lines of code.

Installation

Install directly from GitHub:

pip install git+https://github.com/975SDE/langchain-arp.git

With optional LangChain integration:

pip install "langchain-arp[langchain] @ git+https://github.com/975SDE/langchain-arp.git"

With JSON Schema validation:

pip install "langchain-arp[all] @ git+https://github.com/975SDE/langchain-arp.git"

Note: This package is installed directly from GitHub. PyPI publishing is planned for a future release.

Quick Start

from langchain_arp import AgenticReasoningLoader

# Load from the ARP protocol website (dogfooding!)
loader = AgenticReasoningLoader("https://arp-protocol.org")
docs = loader.load()

# Load from a local file
loader = AgenticReasoningLoader("./reasoning.json")
docs = loader.load()

# Each section becomes a separate Document
for doc in docs:
    print(f"[{doc.metadata['section']}] {doc.page_content[:100]}...")

How It Works

The loader fetches /.well-known/reasoning.json from any website and converts it into prioritized LangChain Documents:

Priority	Section	Purpose
1 (highest)	Corrections	Prevents AI hallucinations with false_claim → correction_fact pairs
2	Identity	Brand facts, tagline, competencies, system instruction
3	Recommendations	When to recommend / when NOT to recommend this entity
4	Counterfactuals	Pre-programmed "what-if" reasoning scenarios
5	Dichotomies	Competitive positioning logic
6	Authority	Trust signals, certifications, official links

Use in a RAG Pipeline

from langchain_arp import AgenticReasoningLoader
from langchain_chroma import Chroma
from langchain_openai import OpenAIEmbeddings

# Load reasoning directives from any website with reasoning.json
loader = AgenticReasoningLoader("https://arp-protocol.org")
docs = loader.load()

# Add to vector store — your agent now knows how to reason about this brand
vectorstore = Chroma.from_documents(docs, OpenAIEmbeddings())
retriever = vectorstore.as_retriever()

Standalone Usage (No LangChain Required)

from langchain_arp import load_reasoning, load_reasoning_file

# From URL
docs = load_reasoning("https://arp-protocol.org")

# From file
docs = load_reasoning_file("./reasoning.json")

CLI

python -m langchain_arp.loader https://arp-protocol.org
python -m langchain_arp.loader ./reasoning.json

What is reasoning.json?

reasoning.json is an open standard (MIT licensed) that provides machine-readable reasoning directives to AI agents. It lives at /.well-known/reasoning.json on any website.

While robots.txt tells crawlers what to access and schema.org tells machines what things are, reasoning.json teaches AI how to think about an entity — including corrections for known hallucinations, competitive positioning logic, and recommendation boundaries.

Spec: arp-protocol.org | Schema: v1.json | GitHub: 975SDE/arp-protocol

License

MIT — Sascha Deforth / TrueSource