ConceptNet (api.conceptnet.io) was returning sustained 502s, breaking
every guess with an "Upstream hiccup" reply. Replace with env.AI.run
on @cf/baai/bge-small-en-v1.5 and score guesses by computing cosine
similarity locally against the target vector.
The local google-10k wordlist doubles as the in/out-of-vocabulary set,
so OOV detection is an O(1) Set.has() with no upstream call. The
similarity() response shape is unchanged, so handlers/render/state
stay as-is.
Free on the Workers Free plan: 10k Neurons/day cap, ~0.0037 Neurons
per 2-word guess → ~2.7M guesses/day headroom for this bot.
ConceptNet provides a free public /relatedness endpoint (returns cosine-like
[-1, 1]) and /c/en/{term} for vocabulary check. No random-word endpoint, so
we ship a curated local target pool in wordlist.js (~250 words) and verify
each pick via the concept endpoint with a fallback to an unverified pick.
Each guess now makes two parallel ConceptNet calls (concept + relatedness)
instead of a single word2sim call. Slightly higher latency but zero hosting
cost and no dependency on the self-hosted word2sim instance.
- api-client.js rewritten; UpstreamError replaces Word2SimError (aliased
for backwards compat with older imports).
- wordlist.js added (curated target pool + pickFromPool).
- handlers.js: drops RANDOM_FILTERS (no filtering needed; pool is curated).
- index.js: drops WORD2SIM_API_URL env var; ConceptNet base hardcoded.
- wrangler.toml + .dev.vars.example: drop WORD2SIM_API_URL.
- api-client tests rewritten for ConceptNet shape; total tests 336 → 341.
Telegram commands /semantle, /semantle_new, /semantle_giveup, /semantle_stats.
Round starts with /random pick from hosted word2sim; each guess scored via
/similarity. Unlimited guesses; solve on case-insensitive exact match.
New env var WORD2SIM_API_URL (wrangler.toml, .env.deploy). Includes
module README and 90 unit tests covering api-client, state, format,
render, and handlers.
tiennm99