Nexus AI News

Nexus

A Jev-powered AI news feed.

Nexus ingests AI news from multiple sources, dedupes it, classifies each item with a single Jev (TypeSafe System One) call, and serves the result as a reverse-chronological feed with filters and a guarded, extractive chat search. No graph database, no generative LLM in the request path.

Sources (arxiv, hackernews, github, twitter, rss)
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dedup.ts (URL → title → arXiv-id → Jaccard + entity fingerprints)
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PostgreSQL raw_items
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Jev enrichment (TypeSafe System One, model jev-latest, 1 call/item)
   relevant? (Noul) · vertical (Choice) · event_type (Choice) · significance (Score)
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PostgreSQL feed_items (reverse-chron, indexed)
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Fastify API — GET /api/feed · GET /api/feed/meta · POST /api/chat
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React feed client — ActivityFeed, FilterBar, HotCards, guarded ChatBox

Quick Start

# 1. Start infrastructure (PostgreSQL)
docker compose up -d

# 2. Install dependencies
pnpm install

# 3. Build all packages
pnpm build

# 4. Start API and client dev servers (separate terminals)
pnpm dev:api
pnpm dev:client

# 5. Run the agent (source polling + Jev enrichment) separately
pnpm --filter @nexus/agent start

The client opens at http://localhost:5173 and the API serves at http://localhost:3001.

Monorepo Layout

Package	Path	Description
@nexus/shared	packages/shared	TypeScript interfaces, enums, constants, validation — imported by all packages
@nexus/agent	packages/agent	Source adapters + dedup + Jev enrichment
@nexus/api	packages/api	Fastify REST server for the feed and chat search
@nexus/client	packages/client	React feed UI (Vite)

Adding a Source Adapter

The primary contribution path is adding new data sources. Every adapter feeds raw items into the dedup + Jev enrichment pipeline, which classifies and inserts them into the feed automatically.

The RawItem Interface

// packages/agent/src/sources/types.ts
interface RawItem {
  source: string;        // adapter name, e.g. "arxiv"
  source_url: string;    // canonical URL for deduplication
  title: string;         // headline / paper title
  content: string;       // body text (Jev classifies, excerpt is sliced from here)
  published_at: string;  // ISO 8601 timestamp
  raw_metadata: Record<string, unknown>; // source-specific fields
}

Write Your Adapter

Extend BaseAdapter and implement fetchItems(). You get rate limiting, exponential retry with backoff, and URL-based deduplication for free.

// packages/agent/src/sources/my-source.ts
import type { RawItem } from "./types.js";
import { BaseAdapter } from "./base-adapter.js";

export class MySourceAdapter extends BaseAdapter {
  name = "my-source";
  priority = "P1" as const;

  constructor() {
    super({
      pollIntervalMs: 30 * 60 * 1000, // how often to poll
      rateLimitMs: 2000,               // min delay between requests
    });
  }

  protected async fetchItems(): Promise<RawItem[]> {
    const response = await fetch("https://api.example.com/items");
    if (!response.ok) throw new Error(`Fetch failed: ${response.status}`);

    const data = await response.json();
    return this.dedupeByUrl(
      data.map((item: any) => ({
        source: this.name,
        source_url: item.url,
        title: item.title,
        content: item.body,
        published_at: new Date(item.date).toISOString(),
        raw_metadata: { id: item.id },
      }))
    );
  }
}

Existing Adapters

Adapter	Source	Priority	Poll Interval	Auth
ArxivAdapter	arXiv RSS (cs.AI, cs.CL, cs.LG)	P0	30 min	None
HackerNewsAdapter	HN Algolia API	P0	15 min	None
GitHubTrendingAdapter	GitHub Search API	P0	60 min	Optional GITHUB_TOKEN
TwitterAdapter	X/Twitter API v2	P1	15 min	X_BEARER_TOKEN required
RssAdapter	Company blogs, TechCrunch AI, The Verge AI, Simon Willison	P1	2h (default)	None

Register Your Adapter

1. Add your adapter to the adapter list in packages/agent/src/start.ts:

import { MySourceAdapter } from "./sources/my-source.js";

const adapters: SourceAdapter[] = [
  new HackerNewsAdapter(),
  new ArxivAdapter(),
  new GitHubTrendingAdapter(),
  new MySourceAdapter(),          // add here
];

2. Write a test in packages/agent/src/sources/__tests__/ following existing patterns.

3. Run tests: pnpm --filter @nexus/agent test

Jev Enrichment

Every deduped RawItem gets exactly one call to TypeSafe's System One API (POST https://api.typesafe.ai/v1/systemone, model jev-latest, Bearer TYPESAFE_API_KEY). Jev is a decision model — it answers typed questions (Noul, Choice, Score) against structured JSON, it does not generate text. One call answers all four questions for an item:

• is_ai_relevant (Noul) — dropped if confidence < 0.6
• vertical (Choice) — one of the 21 Vertical values, or none
• event_type (Choice) — launch | funding | release | acquisition | paper | update | shutdown | other
• significance (Score) — a 5-point rubric mapped to 0.2–1.0

The excerpt shown in the feed is the first 280 characters of the source content — never an LLM summary, so it can't hallucinate.

Chat Search

POST /api/chat is a guarded, extractive search box, not a chatbot. It classifies the query with one Jev call (on-topic check, vertical/event-type/timeframe extraction), then returns real rows from feed_items via Postgres trigram search. There is no generative model anywhere in the chat path — there's nothing for a prompt injection to talk to.

MCP Server

The feed is exposed to agents as a public, read-only Model Context Protocol server over Streamable HTTP:

https://nexus.carapace.bot/mcp

Tool	What it does
search_news	Full-text search (phrases, OR, -exclude), filterable by vertical / event_type / source / since
get_latest_news	Newest items first, same filters, cursor-paginated via next_cursor
get_feed_stats	Total count plus counts per vertical and event_type

Add it to Claude Code with claude mcp add --transport http nexus https://nexus.carapace.bot/mcp. Stateless (no sessions), extractive only — same validation as GET /api/feed, no model calls. Registry manifest: server.json.

Data Model

feed_items

id (uuid) · title · url (unique) · source · published_at · excerpt · vertical · event_type · significance (0.0–1.0) · created_at

Verticals

21 spatial-cluster categories, defined in packages/shared/src/types.ts (e.g. foundation_models, agents, safety_alignment, consumer_products, ...).

Event Types

launch | funding | release | acquisition | paper | update | shutdown | other

Contributing

1. Fork the repo and create a branch: feat/my-feature, fix/some-bug, or chore/cleanup
2. Write conventional commit messages: feat: add devto adapter, fix: handle empty RSS feed
3. Run checks before opening a PR:

pnpm test          # run all tests
pnpm lint          # eslint
pnpm typecheck     # tsc --noEmit

4. Keep PRs focused — one adapter or feature per PR.

Environment Variables

Variable	Required	Default	Description
TYPESAFE_API_KEY	Yes	—	TypeSafe API key for Jev (System One) enrichment and chat classification
POSTGRES_HOST	No	localhost	PostgreSQL host
POSTGRES_PORT	No	5432	PostgreSQL port
POSTGRES_DB	No	nexus	PostgreSQL database name
POSTGRES_USER	No	nexus	PostgreSQL user
POSTGRES_PASSWORD	Yes	—	PostgreSQL password
X_BEARER_TOKEN	No	—	X/Twitter API bearer token (enables Twitter adapter)
GITHUB_TOKEN	No	—	GitHub PAT (raises rate limits for GitHub adapter)
API_KEY	No	—	API key for write/admin endpoints
API_PORT	No	3001	API server port
API_HOST	No	0.0.0.0	API server bind address
CLIENT_PORT	No	5173	Client dev server port

Tech Stack

• Database — PostgreSQL 16 (raw_items, feed_items, pg_trgm search)
• API — Fastify
• Client — Vite + React
• Search — Fuse.js (client-side, loaded items), pg_trgm (server, chat + feed search)
• Agent — TypeSafe Jev (System One) for enrichment and chat classification
• Deploy — Railway (Postgres + API) + Vercel (client)

Cost

Enrichment is roughly 1 Jev call per new deduped item, at ~50–100 items/day across all sources, plus 1 Jev call per chat query. There is no Neo4j, no Redis, and no generative LLM anywhere in the pipeline — that's the entire compute bill.

License

MIT