ワンクリックで
test
// Run TTS round-trip tests — pure-logic unit tests and optional integration tests against live TTS/STT services.
// Run TTS round-trip tests — pure-logic unit tests and optional integration tests against live TTS/STT services.
| name | test |
| description | Run TTS round-trip tests — pure-logic unit tests and optional integration tests against live TTS/STT services. |
| triggers | ["test","run tests","test tts","verify","check"] |
Run unit tests and integration tests for the TTS pipeline.
cd /home/spark/git/autonomous-intelligence/realtime-api && bash scripts/test_tts.sh --logic-only
cd /home/spark/git/autonomous-intelligence/realtime-api && bash scripts/test_tts.sh
Speak the result:
/home/spark/git/autonomous-intelligence/realtime-api/scripts/speak.sh "All tests passed."
Build and deploy the realtime-api Docker container with full verification that deployed code matches local source.
Speak text aloud using the Magpie TTS container in the realtime-api Docker stack. Zero external dependencies — just curl + aplay.
Unified memory management for notes, knowledge graph, RAG search, and file analysis. Use when working with: (1) Core memory — protected identity, projects, relationships, and system facts that should never be forgotten, (2) Working notes — per-session ephemeral notes organized by section, (3) MongoDB RAG — vector-search-enabled notes with importance scoring, decay, deduplication, and archival, (4) Neo4j knowledge graph — entities, relationships, merge duplicates, reinforce mentions, Cypher queries, (5) File analysis — deep file reading that extracts knowledge into all memory layers, (6) Service initialization — health-check, start/stop MongoDB, Neo4j, TEI embeddings via docker-compose with partial setup support.
Query MongoDB notes store for memory analysis and statistics.
Query Neo4j knowledge graph for entities, relationships, and graph analysis.
Calls qq agent from cli.