v0.1.7 — system-event laundering fix (security) + derived_from

• security (ingest/gate/compile): closed the system-event laundering
  bypass — third-party text embedded inside a SYSTEM/USER-authored event (a
  triage verdict quoting a received email's subject, a summary of a message
  body) previously acquired the event's full trust and could surface as
  assertable user facts. remember() gains derived_from: declare
  author=SYSTEM, derived_from=THIRD_PARTY and trust is capped at the minimum
  of the two — edges cap at use_only (claims still quarantine), and the
  episode routes to the unverified channel at the gate and is excluded from
  the compiled wiki (episodes now route by third-party influence, not
  authorship alone). Provenance records both fields; MCP remember exposes
  the parameter; documented in docs/concepts.md ("Mixed provenance") and
  SECURITY.md. Found by the first production consumer on a real-mailbox
  backfill (130 laundered assertable edges); reported in
  proposals/system-event-laundering.md with the attack fixture now locked as
  a regression test.

• ingest: an unparseable extraction no longer leaves a history gap — the
  turn records a content-free placeholder episode ("(unprocessed event —
  extraction returned no parseable JSON; content not retained)") with full
  provenance/evidence_ref. Deliberately not the raw event text: that would
  feed unmediated, possibly adversarial input straight into recall prompts.

• _json: among list fallbacks, extract_json now prefers a non-empty
  list of dicts (the shape of a bare triples array) over junk like [] or
  [1, 2] that happened to parse earlier in the prose.

• graph: his/her removed from the value-equivalence filler list — they
  can point at a third party ("his assistant" vs "her assistant") and so carry
  meaning; user-referential possessives (my/our/their) remain filler.

• examples: openai_provider.py — OpenAIComplete wraps any
  OpenAI-compatible chat-completions API (OpenAI, vLLM, Ollama's /v1), with
  per-role model mapping, honest structured-output fallback, and a memoized
  capability check. First outside contribution — thanks @vreddy-commits (#8).