toczix/sibo-research-db

Sibo Reddit Research Database

Chat with 7 million real patient experiences from 18 health subreddits — find what's actually working for symptoms like yours.

A SQLite database of public Reddit content from chronic-illness communities, designed to be queried conversationally by AI tools (Claude Desktop, Claude Code, Codex CLI, Cursor, Cline, VS Code Copilot Agent).

Not medical advice. Patient-reported data, not clinical. Use to find patterns and leads worth bringing to a doctor — never to diagnose or treat yourself.

Install in 3 steps

Step 1. Copy this into Claude Code or Codex CLI:

https://github.com/toczix/sibo-research-db
https://huggingface.co/datasets/toczix/sibo-research-db

I want to chat with this database for my SIBO-related symptoms. Please
install it for me — follow the README in the GitHub repo.

Step 2. Wait for the install (downloads a 5.4 GB database — go make coffee).

Step 3. Restart your AI tool. Start asking questions.

Full setup guide and a personal-timeline template you can copy at github.com/toczix/sibo-research-db.

For best results: pair this with your own timeline

The most valuable way to use this dataset is to feed the AI both this database and a personal medical timeline — a single file with your symptom history, what you've tried, what's worked, what hasn't, your lab results, and your working theory.

When the AI has both your data and 7 million patient reports to cross-reference, you get specific answers instead of generic ones. Instead of "here's what people say about rifaximin", you get "given your pattern of partial-response-then-relapse and your IMO diagnosis, here's what people with a similar profile reported trying next."

Don't have a timeline doc yet? A template — a randomized fictional version of the author's actual research document — is on the GitHub repo. Copy it, fill it in with your real data, point the AI at it via the SIBO_REPORT env var, and the file never leaves your machine.

Files

File	Size	What it is
reddit.db	5.4 GB	The database. SQLite with full-text-search indexes. Ready to use as-is.
reddit.db.zst	1.86 GB	Same database, compressed 66% smaller. Decompress with zstd -d reddit.db.zst.
checksums.txt	530 B	SHA-256 for both files

You only need ONE of reddit.db or reddit.db.zst. Pick the compressed one for faster download (you'll need zstd installed, which is one command on Mac/Linux/Windows).

What's in it

Subreddit	Topic	Comments
r/covidlonghaulers	Long COVID	1,883,928
r/Supplements	Supplement protocols	894,256
r/ibs	IBS	892,121
r/SIBO	SIBO	710,128
r/MCAS	Mast cell activation	558,683
r/dysautonomia	POTS / autonomic	433,599
r/Microbiome	Gut microbiome	313,367
r/LongCovid	Long COVID (alt community)	257,465
r/Candida	Candida overgrowth	251,539
r/FODMAPS	Low-FODMAP diet	249,222
r/HistamineIntolerance	Histamine reactions	227,376
r/FoodAllergies	Food sensitivities	203,735
r/ToxicMoldExposure	Mold illness	188,293
r/GutHealth	Gut health general	57,892
r/Longcovidgutdysbiosis	LC + gut overlap	36,437
r/FunctionalMedicine	Functional medicine	28,322
r/LeakyGutSyndrome	Intestinal permeability	11,890
r/SiboSuccessStories	Recovery stories	7,301

18 subreddits. 695,050 posts. 7,205,554 comments. Coverage roughly the start of each sub through May 2026 (r/ibs and r/Supplements are limited to 2021+ to keep the database manageable).

Using it without AI

The database is a regular SQLite file. You can query it directly:

import sqlite3

conn = sqlite3.connect("file:reddit.db?mode=ro", uri=True)
cur = conn.execute("""
    SELECT c.subreddit, c.body, c.score
    FROM comments_fts fts
    JOIN comments c ON c.rowid = fts.rowid
    WHERE comments_fts MATCH 'prucalopride AND tolerance'
    ORDER BY c.score DESC
    LIMIT 10
""")
for row in cur:
    print(row)

Schema:

posts(id, subreddit, author, title, selftext, score, num_comments,
      created_utc, permalink, link_flair_text, domain, is_self)

comments(id, subreddit, author, body, score, created_utc,
         link_id, parent_id, permalink)

Full-text search via FTS5 virtual tables posts_fts(title, selftext) and comments_fts(body).

Verify your download

sqlite3 reddit.db "PRAGMA integrity_check;"   # should print "ok"
sqlite3 reddit.db "SELECT COUNT(*) FROM posts; SELECT COUNT(*) FROM comments;"
shasum -a 256 reddit.db                       # compare against checksums.txt

Licensing

Code in the GitHub repo is MIT-licensed.

Reddit content is owned by its original authors and Reddit. It's being redistributed here from the public arctic-shift archive for research and educational use. This is not a claim of public-domain status.

Source

Scraped from arctic-shift, a public Reddit archive (no API key needed). The scrape and ingest scripts are in the GitHub repo if you want to rebuild from scratch or add other subreddits.