from pulp import radiance

rw = radiance.rootwords
rw.sentences.ingest(source="sample.txt")

print(rw.sentences.count())   # 4
hits = rw.sentences.identify(query="*")

Introduction

Getting started

$pip install pulp-sdk

From draft to decision

Score a Reddit thread

Ground a claim in evidence

sample.txt2 paras · 160 chars

Sections

§1 Introduction

Paras

¶1: first paragraph block

¶2: second paragraph block

Sentences

S1S2S3S4

Clauses

C1C2C3C4C5C6

Claims

Claim 1Claim 2Claim 3

Phrases

NPVPNPVPPPNP

Named Entities

Pulp [ORG]

Words

ifwewaitforcertaintywewillbe+20 more

Characters

0 → 159

Special Characters

spaces × 27punct × 8nbsp × 0

Special Patterns

0 patterns detected

RootCause

Ethos

—

Pathos

—

Logos

—

Kairos

—

Style

—

Clarity

—

Focus

—

Awareness

—

Persuasive Velocity—

StemReferences

CensusFECCongressFed. Reg.RegulationsLegiScanGovInfoGDELTCivicWikimediaData.govPodcast Idx

rank

life_stageyoung_adult

education_levelbachelors

locationurban

occupationtech

Psychographics

Impelling

Compelling

Repelling

Mindstate

alpha 10 Hzcalm

Environment

vision onhearing onsmell offtouch offtaste off

Memory

purchases 12content 48brands 5

motivationdesirefear

define

apply

post

heatmap

price

trace

uptimeresize

q3-report.pdf

chart.png

keynote.mp4

WeftConversations

ThreadsChatInlineSide panels

DyeMedia

TextToday

ImageToday

SoundSoon

VideoSoon

BightInteractions

MouseKeyboardVoice · soonCombos · soon

Device & browser frames

Structured Discussion Bracket

Perspective scroll showcase

Scroll Scrubber

Production

Coming soon

Conventions

Sentences

Complete grammatical units. The default grain for scoring handoffs to RootCause.

ingestcountidentify

Verb	Description
`ingest`	Load sentences from a para
`count`	Return the number of sentences
`identify`	Locate specific sentences matching a query

from pulp import radiance

rw = radiance.rootwords
rw.sentences.ingest(source="sample.txt")

print(rw.sentences.count())   # 4
hits = rw.sentences.identify(query="*")