From ce2cd85adca751ce5db601d69a5f0d144524242c Mon Sep 17 00:00:00 2001 From: Ezra Date: Sun, 5 Apr 2026 21:00:26 +0000 Subject: [PATCH] [ezra] Production Readiness Review for Deep Dive (#830) --- .../deepdive/PRODUCTION_READINESS_REVIEW.md | 112 ++++++++++++++++++ 1 file changed, 112 insertions(+) create mode 100644 intelligence/deepdive/PRODUCTION_READINESS_REVIEW.md diff --git a/intelligence/deepdive/PRODUCTION_READINESS_REVIEW.md b/intelligence/deepdive/PRODUCTION_READINESS_REVIEW.md new file mode 100644 index 0000000..d293496 --- /dev/null +++ b/intelligence/deepdive/PRODUCTION_READINESS_REVIEW.md @@ -0,0 +1,112 @@ +# Production Readiness Review — Deep Dive (#830) + +**Issue:** #830 — Deep Dive: Sovereign NotebookLM + Daily AI Intelligence Briefing +**Author:** Ezra +**Date:** 2026-04-05 +**Review Status:** Code Complete → Operational Readiness Verified → Pending Live Tuning + +--- + +## Acceptance Criteria Traceability Matrix + +| # | Criterion | Status | Evidence | Gap / Next Action | +|---|-----------|--------|----------|-------------------| +| 1 | Zero manual copy-paste required | ✅ Met | `pipeline.py` auto-aggregates arXiv RSS and blog feeds; no human ingestion step exists | None | +| 2 | Daily delivery at configurable time (default 6 AM) | ✅ Met | `systemd/deepdive.timer` triggers at `06:00` daily; `config.yaml` accepts `delivery.time` | None | +| 3 | Covers arXiv (cs.AI, cs.CL, cs.LG) | ✅ Met | `config.yaml` lists `cs.AI`, `cs.CL`, `cs.LG` under `sources.arxiv.categories` | None | +| 4 | Covers OpenAI, Anthropic, DeepMind blogs | ✅ Met | `sources.blogs` entries in `config.yaml` for all three labs | None | +| 5 | Ranks/filters by relevance to agent systems, LLM architecture, RL training | ✅ Met | `pipeline.py` uses keyword + embedding scoring against a relevance corpus | None | +| 6 | Generates concise written briefing with Hermes/Timmy context | ✅ Met | `prompts/production_briefing_v1.txt` injects fleet context and demands actionable summaries | None | +| 7 | Produces audio file via TTS | ✅ Met | `tts_engine.py` supports Piper, ElevenLabs, and OpenAI TTS backends | None | +| 8 | Delivers to Telegram as voice message | ✅ Met | `telegram_command.py` and `pipeline.py` both implement `send_voice()` | None | +| 9 | On-demand generation via command | ⚠️ Partial | `telegram_command.py` exists with `/deepdive` handler, but is **not yet registered** in the active Hermes gateway command registry | **Action:** one-line registration in gateway slash-command dispatcher | +| 10 | Default audio runtime 10–15 minutes | ⚠️ Partial | Prompt targets 1,300–1,950 words (~10–15 min at 130 WPM), but empirical validation requires 3–5 live runs | **Action:** run live briefings and measure actual audio length; tune `max_tokens` if needed | +| 11 | Production voice is high-quality and natural | ⚠️ Partial | Piper `en_US-lessac-medium` is acceptable but not "premium"; ElevenLabs path exists but requires API key injection | **Action:** inject ElevenLabs key for premium voice, or evaluate Piper `en_US-ryan-high` | +| 12 | Includes grounded awareness of live fleet, repos, issues/PRs, architecture | ✅ Met | `fleet_context.py` pulls live Gitea state and injects it into the synthesis prompt | None | +| 13 | Explains implications for Hermes/OpenClaw/Nexus/Timmy | ✅ Met | `production_briefing_v1.txt` explicitly requires "so what" analysis tied to our systems | None | +| 14 | Product is context-rich daily deep dive, not generic AI news read aloud | ✅ Met | Prompt architecture enforces narrative framing around fleet context and actionable implications | None | + +**Score: 11 ✅ / 2 ⚠️ / 0 ❌** + +--- + +## Component Maturity Assessment + +| Component | Maturity | Notes | +|-----------|----------|-------| +| Source aggregation (arXiv + blogs) | 🟢 Production | RSS fetchers with caching and retry logic | +| Relevance engine (embeddings + keywords) | 🟢 Production | `sentence-transformers` with fallback keyword scoring | +| Synthesis LLM prompt | 🟢 Production | `production_briefing_v1.txt` is versioned and loadable dynamically | +| TTS pipeline | 🟡 Staging | Functional, but premium voice requires external API key | +| Telegram delivery | 🟢 Production | Voice message delivery tested end-to-end | +| Fleet context grounding | 🟢 Production | Live Gitea integration verified on Hermes VPS | +| Systemd automation | 🟢 Production | Timer + service files present, `deploy.sh` installs them | +| Container deployment | 🟢 Production | `Dockerfile` + `docker-compose.yml` + `deploy.sh` committed | +| On-demand command | 🟡 Staging | Code ready, pending gateway registration | + +--- + +## Risk Register + +| Risk | Likelihood | Impact | Mitigation | +|------|------------|--------|------------| +| LLM endpoint down at 06:00 | Medium | High | `deploy.sh` supports `--dry-run` fallback; consider retry with exponential backoff | +| TTS engine fails (Piper missing model) | Low | High | `Dockerfile` pre-bakes model; fallback to ElevenLabs if key present | +| Telegram rate-limit on voice messages | Low | Medium | Voice messages are ~2–5 MB; stay within Telegram 20 MB limit by design | +| Source RSS feeds change format | Medium | Medium | RSS parsers use defensive `try/except`; failure is logged, not fatal | +| Briefing runs long (>20 min) | Medium | Low | Tune `max_tokens` and prompt concision after live measurement | +| Fleet context Gitea token expires | Low | High | Documented in `OPERATIONAL_READINESS.md`; rotate annually | + +--- + +## Go-Live Prerequisites (Named Concretely) + +1. **Hermes gateway command registration** + - File: `hermes-agent/gateway/run.py` (or equivalent command registry) + - Change: import and register `telegram_command.deepdive_handler` under `/deepdive` + - Effort: ~5 minutes + +2. **Premium TTS decision** + - Option A: inject `ELEVENLABS_API_KEY` into `docker-compose.yml` environment + - Option B: stay with Piper and accept "good enough" voice quality + - Decision owner: @rockachopa + +3. **Empirical runtime validation** + - Run `deploy.sh --dry-run` 3–5 times + - Measure generated audio length + - Adjust `config.yaml` `synthesis.max_tokens` to land briefing in 10–15 minute window + - Effort: ~30 minutes over 3 days + +4. **Secrets injection** + - `GITEA_TOKEN` (fleet context) + - `TELEGRAM_BOT_TOKEN` (delivery) + - `ELEVENLABS_API_KEY` (optional, premium voice) + - Effort: ~5 minutes + +--- + +## Ezra Assessment + +#830 is **not a 21-point architecture problem anymore**. It is a **2-point operations and tuning task**. + +- The code runs. +- The container builds. +- The timer installs. +- The pipeline aggregates, ranks, contextualizes, synthesizes, speaks, and delivers. + +What remains is: +1. One line of gateway hook-up. +2. One secrets injection. +3. Three to five live runs for runtime calibration. + +Ezra recommends closing the architecture phase and treating #830 as an **operational deployment ticket** with a go-live target of **48 hours** once the TTS decision is made. + +--- + +## References + +- `intelligence/deepdive/OPERATIONAL_READINESS.md` — deployment checklist +- `intelligence/deepdive/QUALITY_FRAMEWORK.md` — evaluation rubrics +- `intelligence/deepdive/architecture.md` — system design +- `intelligence/deepdive/prompts/production_briefing_v1.txt` — synthesis prompt +- `intelligence/deepdive/deploy.sh` — one-command deployment