Commit Graph
10 Commits
Author SHA1 Message Date
didarandClaude Sonnet 5 c5dd87ee32 feat: make ai_operator_settings config code the source of truth
Add sync_ai_operator_config_from_code() which overwrites the DB-cached
ai_operator_settings row from ai_operator_default_config() on startup
of ai_orchestrator_service and ai_voice_runtime_service. Greeting and
system prompt changes now go through git + deploy instead of manual
psql/API edits to prod. Also adds a root README pointing to existing docs.

Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
2026-08-21 21:00:34 +05:00
Didar KozhikovandClaude Sonnet 5 49489f89b5 Play a filler ack during slow voice decisions and cache KB search rows
Two independent latency fixes for the voice-assistant reply pipeline,
both scoped to the parts of the flow that run regardless of whether
voice_v2 is enabled for a queue:

1. media_runtime._process_utterance: the v1/fallback turn path (used by
   any queue not covered by AI_VOICE_V2_QUEUE_CODES) silently awaited the
   full LLM decision with no audio playing at all, unlike the v2 path
   which already has a decision-timeout ack. Give v1 the same behavior:
   wait up to 600ms (_v1_ack_wait_seconds) for the decision, and if it's
   still not ready, play a short "Секунду." filler via the existing
   _emit_early_ack before the real reply, instead of leaving the caller
   in silence for the full LLM+TTS round trip. Reuses the same ack
   selection/playback code path v2 already exercises, so no new failure
   modes - just an added timeout branch mirroring the existing v2 one.

2. ai_orchestrator_service._kb_search: every voice/chat turn re-ran a
   full-table scan of kb_articles (all columns, including body text) and
   rescored every row in Python, even though the KB rarely changes
   mid-conversation. Added an in-process cache keyed by language, gated
   on a cheap content fingerprint (row count + max id + max updated_at +
   summed title/body/tags length, all computed server-side without
   transferring the text columns). A fingerprint mismatch always
   triggers a fresh fetch, so this can never serve stale results after
   an insert/update/delete - unlike a naive TTL cache, which would have
   been be wrong the moment a test (or a real KB edit) changed the table
   within the cache window.

   Note the first fingerprint design (count + max id + max updated_at
   only) was insufficient: utc_now_iso() truncates to whole seconds and
   SQLite reuses primary keys after a full-table delete, so two
   different row sets written in the same wall-clock second could share
   a fingerprint. Caught this via a real test failure
   (test_ai_whatsapp_relaxed_kb_search_answers_phrase_query breaking
   only when run after test_ai_orchestrator_service.py in the same
   process) before it could reach production; the summed content-length
   term closes the gap.

Added test_media_runtime_plays_filler_ack_when_v1_decision_is_slow
(asserts greeting -> ack -> reply delivery order when process_turn is
slow) and verified the KB cache against the full
test_ai_orchestrator_service.py + test_ai_whatsapp_orchestrator_service.py
suite plus a wider kb/orchestrator/whatsapp/telegram/voice-filtered run:
only the same pre-existing, already-documented failures remain (unrelated
sales_service test-isolation ordering, one known persona-prompt
assertion) - no new failures from either change.

Streaming the LLM decision itself (start speaking reply_text before the
full structured JSON response finishes generating) was scoped but
deliberately deferred: it needs incremental JSON parsing on top of SSE
streaming to detect when just the reply_text field is complete, shared
across both voice and text-channel decision paths - a separate,
higher-risk change that deserves its own PR and testing pass rather than
being bundled here.

Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
2026-08-19 21:54:02 +05:00
Magzhan Zhumabayev ce3ba270aa Add configurable AI operator persona 2026-05-11 17:37:26 +05:00
Yera AllandClaude Opus 4.6 6798320209 fix: remove dead code duplicates, add SQL LIMIT across all services
- Remove duplicate function definitions with hardcoded "AI-оператор" strings
  (ai_voice_runtime, ai_orchestrator, voice_name_config, voice.py)
- Remove unreachable dead code after return in ai_voice_runtime
- Add SQL LIMIT to 17 unbounded queries across 12 services to prevent OOM
- Move Python-side filtering to SQL WHERE in reporting_service
- Downgrade 19 logger.warning to logger.info for normal-flow events in media_runtime

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-04-13 12:04:26 +05:00
Yera All 6b8f5d069b feat(ai): add rolling conversation summary memory 2026-04-13 11:59:43 +05:00
Yera All fc976804e4 feat(voice): add admin-configurable elevenlabs tts 2026-04-11 16:46:43 +05:00
Yera All 6035c5d4d0 feat(ai): shift name extraction to LLM payload piggybacking to improve contextual accuracy 2026-04-07 11:01:17 +05:00
Yera All 1497bb0feb feat(ai): Finalize voice operator persona and voice name flow 2026-04-06 23:19:24 +05:00
Yera All d959c2b2f0 Add voice name flow controls and analytics 2026-04-05 03:26:18 +05:00
Yera All 5374c202d9 Initial import with GitLab CI/CD and registry deploy flow 2026-04-02 17:05:45 +05:00