DEV Community: Toprak

I built an encyclopedia of 376 psychoactive substances with Next.js and PostgreSQL

Toprak — Tue, 17 Mar 2026 00:39:21 +0000

Finding reliable information about psychoactive substances shouldn't require 15 open tabs. PsychonautWiki for pharmacology, TripSit for interactions, Erowid for trip reports, Reddit for community knowledge — I wanted one place where all of that connects.

So I built SubstanceWiki.

What it covers

376 substances with detailed profiles
15,015 interaction pairs with safety ratings
240 catalogued subjective effects across 7 categories
2,748 experience reports from real users
23,520 aggregated community posts from Reddit and forums
21 combo guides for common and high-risk combinations
10 side-by-side substance comparisons

Every substance page includes dosage tables by route of administration, duration timelines, subjective effect profiles, interaction safety data, and community context.

The tech stack

Next.js 16 with App Router and Turbopack
Prisma + PostgreSQL (hosted on Neon)
Tailwind CSS + shadcn/ui for the interface
Vercel for deployment
Dynamic sitemap generation, JSON-LD structured data on every page, and OG image support

The database schema has 11 models covering substances, effects, interactions, experience reports, articles, and community posts. Everything is cross-linked — substances link to their effects, effects link back to substances, interactions connect pairs with safety ratings.

Why harm reduction matters

People use substances whether we like it or not. Giving them accurate, complete information is how we keep them safer. Every substance page leads with safety information because that's what matters most.

The interaction checker alone covers 15,015 pairs — you can look up whether combining two substances is safe, risky, or dangerous in seconds.

Check it out

substancewiki.org

I'd love feedback on what's missing, what's confusing, or what could be structured better. This is safety-critical information, so clarity matters more than aesthetics.

I built an open-source encyclopedia of psychoactive substances with Next.js 16

Toprak — Mon, 09 Mar 2026 10:20:20 +0000

Substance information is fragmented. You need PsychonautWiki for pharmacology, TripSit for interaction charts, Erowid for experience reports, Reddit for community knowledge. I got tired of having 15 tabs open, so I built SubstanceWiki — a single, interconnected reference where everything links to everything.

Live site: substancewiki.org
Source: github.com/yagcioglutoprak/substance_wiki

The numbers

381 substance profiles with dosage guides and duration timelines
14,967 drug interaction safety ratings
240+ catalogued subjective effects
2,745 experience reports
11,698 effect-substance combination pages
~15,000 total pages generated

Tech stack

Next.js 16 with App Router and Turbopack
PostgreSQL via Prisma (11 models)
Tailwind CSS + shadcn/ui
Vercel for hosting
@vercel/og for dynamic OG images

Architectural decisions worth sharing

1. Pre-computed interactions, not runtime calculation

The interaction checker covers 14,967 substance combinations. Each pair has a safety rating (Safe, Low Risk, Caution, Unsafe, Dangerous) with detailed notes about mechanism of action.

These are pre-computed and stored in PostgreSQL — not calculated at runtime. A SubstanceInteraction model with foreign keys to both substances, indexed for fast lookup in both directions. Querying "what interacts dangerously with LSD?" is a single indexed query returning in <10ms.

2. Programmatic SEO at scale

From 381 substances and 240 effects, we generate:

381 main substance pages
762 dosage + effects sub-pages (/substances/[slug]/dosage, /substances/[slug]/effects)
11,698 effect-substance detail pages (/effects/[effect]/[substance])
28 comparison pages (/compare/lsd-vs-mdma)
11 combo safety guides
56 editorial articles

Each page has unique content, structured data (JSON-LD), dynamic OG images, and proper canonical URLs. The sitemap regenerates hourly with all 15,000+ URLs.

3. Community insights from Reddit

We process Reddit data via the Arctic Shift archive. Posts from relevant subreddits (r/drugs, r/psychonaut, r/nootropics, etc.) are classified, scored for quality, and linked to substance pages. This gives each substance a "community perspective" section with real discussions from people who've actually used it.

4. Dynamic OG images

Every page type gets a unique OG image generated via @vercel/og. This means every link shared on social media has a distinct, informative preview — not a generic site image.

5. Internal linking as an SEO strategy

Substance pages link to their effects. Effect pages link back to substances. Interactions connect pairs. Comparisons link both ways. This creates a dense web of internal links that helps both users and search engines understand the relationships between content.

6. FAQ schema for rich snippets

Each substance page dynamically generates FAQ content from the substance's data — "Is [substance] addictive?", "How long does [substance] last?", "What are the effects of [substance]?". This is wrapped in FAQPage JSON-LD schema, which can trigger FAQ rich snippets in Google search results.

Harm reduction first

Every substance page leads with safety information. The interaction checker exists because combining substances is one of the most dangerous things people do, and having that information one click away can save lives.

This isn't a project that glorifies substance use. It's a project that acknowledges people use substances and tries to give them the best information possible to stay safe.

What's next

Multilingual support (Spanish, Portuguese, German)
User-contributed experience reports
Mobile app
API for third-party integrations

Check it out at substancewiki.org and the source at GitHub. Feedback welcome — especially on accuracy of substance data, since getting this right is literally a matter of safety.

I built an open-source encyclopedia of psychoactive substances with Next.js 16 — here's what I learned

Toprak — Sun, 08 Mar 2026 09:35:35 +0000

Live site: substancewiki.org
Source: github.com/yagcioglutoprak/substance_wiki

The numbers

381 substance profiles with dosage guides and duration timelines
14,967 drug interaction safety ratings
240+ catalogued subjective effects
2,745 experience reports
11,698 effect-substance combination pages
~15,000 total pages generated

Tech stack

Next.js 16 with App Router and Turbopack
PostgreSQL via Prisma (11 models)
Tailwind CSS + shadcn/ui
Vercel for hosting
@vercel/og for dynamic OG images

Architectural decisions worth sharing

1. Pre-computed interactions, not runtime calculation

The interaction checker covers 14,967 substance combinations. Each pair has a safety rating (Safe, Low Risk, Caution, Unsafe, Dangerous) with detailed notes about mechanism of action.

These are pre-computed and stored in PostgreSQL — not calculated at runtime. A SubstanceInteraction model with foreign keys to both substances, indexed for fast lookup in both directions. Querying "what interacts dangerously with LSD?" is a single indexed query returning in <10ms.

2. Programmatic SEO at scale

From 381 substances and 240 effects, we generate:

381 main substance pages
762 dosage + effects sub-pages
11,698 effect-substance detail pages
28 comparison pages
11 combo safety guides
56 editorial articles

Each page has unique content, structured data (JSON-LD), dynamic OG images, and proper canonical URLs. The sitemap regenerates hourly with all 15,000+ URLs.

3. Community insights from Reddit

4. Dynamic OG images

Every page type gets a unique OG image generated via @vercel/og. This means every link shared on social media has a distinct, informative preview — not a generic site image.

5. Internal linking as an SEO strategy

6. FAQ schema for rich snippets

Each substance page dynamically generates FAQ content from the substance's data. This is wrapped in FAQPage JSON-LD schema, which can trigger FAQ rich snippets in Google search results.

Harm reduction first

This isn't a project that glorifies substance use. It's a project that acknowledges people use substances and tries to give them the best information possible to stay safe.

What's next

Multilingual support (Spanish, Portuguese, German)
User-contributed experience reports
Mobile app
API for third-party integrations

Check it out at substancewiki.org and the source at GitHub. Feedback welcome — especially on accuracy of substance data, since getting this right is literally a matter of safety.

I built a macOS menu bar app in ~900 lines of Python that tracks Claude + ChatGPT limits — here's how

Toprak — Thu, 26 Feb 2026 10:18:40 +0000

I got tired of getting blindsided by Claude Pro rate limits mid-session. The solution: a menu bar app that reads the same private API that claude.ai/settings/usage calls.

Here's what made it interesting to build:

The Cloudflare problem

Claude's API is behind Cloudflare. Regular requests or httpx get 403'd immediately. The fix: curl_cffi with impersonate="chrome131" to spoof the TLS fingerprint. This was the single biggest hurdle.

Browser cookie detection

Rather than making users copy-paste cookies, I used browser-cookie3 to read them directly from Chrome, Arc, Firefox, Safari, or Brave. Key insight: try Firefox first — it uses a plain SQLite database with no Keychain prompt. Chromium browsers need a one-time "Always Allow" dialog.

AppKit threading rule

rumps runs on the main thread. All UI updates (menu rebuilds) must happen there. My background fetch thread puts results in a queue.Queue, and a 0.25-second timer on the main thread drains it. Violate this and you get intermittent crashes.

Inconsistent API scale

The API returns five_hour (session) as a 0–1 fraction, but seven_day (weekly) as a 0–100 percentage. The fix: if raw > 1.0: already_pct else multiply_by_100. Spent embarrassing time debugging this.

One-line install

curl -fsSL https://raw.githubusercontent.com/yagcioglutoprak/AIQuotaBar/main/install.sh | bash

It also tracks ChatGPT usage in the same menu bar indicator.

MIT licensed, ~900 lines Python: https://github.com/yagcioglutoprak/AIQuotaBar

Happy to go deep on any of these implementation details in the comments.