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Wontopos — long-term memory for AI agents. Pure semantic retrieval, identical recall in every language, ~100× lower LLM bill.

Project description

Wontopos — long-term memory for AI agents

pip install wontopos
from wontopos import Client

mem = Client(api_key="wos-...")
mem.add("she prefers tea over coffee", user_id="alice")

# one call → short-term + long-term + context, ready for your LLM prompt
ctx = mem.recall("what does alice drink?", user_id="alice")

Why

  • Pure semantic retrieval — no keyword/BM25. Identical recall in every language (한국어 · 日本語 · 中文 · English).
  • No LLM in the loopstore / search / recall never call a language model. You pay embeddings, not generation.
  • Bounded retrievalrecall() returns a small, fixed-size slice (~1,200 tokens) regardless of how much you've stored. Your LLM bill stops growing with history.

Methods

Method Purpose
add(content, user_id, **metadata) Store one memory
add_turn(user_msg, assistant_msg, user_id?) Store a conversation exchange
add_bulk(content, user_id, category=, timestamp=) Backfill a long history
update(old_memory_id, new_content, user_id?) Supersede an old fact
search(query, user_id, limit=10, **opts) Semantic search
recall(query, user_id) One-call context (short + long + surrounding)
history(user_id) Recent turns (short-term)
stats(user_id) Counts
delete(user_id, memory_id) Delete one memory
delete_all(user_id) GDPR erase (delete every memory for the user)
add_speaker(speaker, user_id?) Register a person (explicit, up to 50 to start)
list_speakers(user_id?) Registered people + per-person memory counts
remove_speaker(speaker, user_id?) Unregister; memories stay, the tag goes

All methods take a user_id — it names the store: one isolated memory space per end-user, agent, or topic, then per account (your API key). WHO said each memory inside a store is the speaker tag below — storing the assistant's own words never needs a separate id.

Who said it (speakers)

Every memory can carry a speaker: "me" for the assistant's own words, or a person's name. Speakers are explicit, like stores: register a person once, then store under their name — a typo can never silently become a new person. Search accepts a speaker too, so you can recall one person's words only.

mem.add_speaker("Bob", user_id="alice")      # once per person
mem.add("I promised to send the report on Friday", user_id="alice", speaker="me")
mem.add("Bob said the deadline moved to Tuesday", user_id="alice", speaker="Bob")
mem.search("what did Bob say about deadlines?", user_id="alice", speaker="Bob")

A store registers up to 50 people to start (a limit we plan to raise); "me" never needs registration and never counts against it.

Recall caching

Opt in per search and repeated or extended queries reuse the previous result at 10% of the normal rate (Tablet and Scroll models):

hits = mem.search("...the conversation so far...", user_id="alice",
                  cache_control={"ttl": "5m"})   # or "1h"

Reliability

Built in, no configuration needed:

  • Automatic retries — 429 / 502 / 503 and connection errors retry twice with exponential backoff + jitter, honoring the server's Retry-After. Tune with Client(retries=...); retries=0 disables.
  • Redirects refused — the API key never follows a 3xx to another host.
  • Timeouts — 30s per attempt by default (Client(timeout=...)).
  • Key never in logsrepr(client) masks the API key.
  • Wipe guarddelete() without a memory_id raises instead of silently meaning "delete everything"; wiping a store is only ever the explicit delete_all(user_id) / delete_store(user_id).

Errors

Any non-2xx response raises WosError(status, message). When the server sent a request id it's on e.request_id — include it when contacting support.

from wontopos import Client, WosError

try:
    mem.search("...", user_id="alice")
except WosError as e:
    if e.status == 401:
        print("API key invalid or revoked")
    elif e.status == 429:
        print("Rate limited — back off")   # already retried twice by then
    else:
        print(e.status, e.message, e.request_id)

Self-host

Point at your own engine:

mem = Client(api_key="...", base_url="https://wos.your-host.com")

Links

Changelog

  • 2.2.8 — reliability + hardening: automatic retries (429/502/503 + connection errors, backoff + jitter, honors Retry-After), redirects refused, key masked in repr, WosError.request_id, guard against delete() without memory_id, plain-HTTP warning, User-Agent, with_model().
  • 2.2.7 — speakers: add_speaker / list_speakers / remove_speaker.
  • 2.2.6 — docs: user_id = store, clarified everywhere.
  • 2.2.5 — docs: speakers + recall caching sections.
  • 2.2.4 — Python/TypeScript/Rust converge on one version; all three now release in lockstep (same version, same surface). Patch releases are additive.

License: MIT.

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