# Release `1.0.19` Plan

## Purpose

This release starts the shift from `1.0.18` hardening to visible feature growth.

The goal is to keep compatibility work steady while shipping personality and capability slices that make OpenJibo feel less like a placeholder cloud and more like a real assistant platform.

## Snapshot

- Kickoff date: `2026-05-05`
- Cloud version source of truth: [OpenJiboCloudBuildInfo.cs](../src/Jibo.Cloud/dotnet/src/Jibo.Cloud.Application/Services/OpenJiboCloudBuildInfo.cs)
- Active release constant: `1.0.19`

## Scope

### 1. Persona And Identity Surface

- add natural voice responses for robot identity/personality prompts
- start building reusable content hooks for question-vs-command style responses
- keep first implementation rule-based and test-backed

### 1a. Original Personalized Function Inventory

Keep a running checklist of the legacy persona questions and identity surfaces we want to preserve or port:

- identity and origin: `what are you`, `who are you`, `what is Jibo`, `who made you`, `where are you from`
- persona and capability: `do you have a personality`, `what is your job`, `how much do you know`, `what do you want`
- self-description and social charm: `what's your name`, `do you have a nickname`, `do you like being Jibo`, `are there others like you`
- favorite-style prompts: `what is your favorite color`, `what is your favorite food`, `what is your favorite music`
- attraction and preference prompts: `what is your favorite flower`, `do you like R2D2`, `do you like the sun`, `do you like space`, `do you like kids`
- longer authored variants for the same prompt family when Pegasus shows richer phrasing, especially multi-clause and follow-up-heavy responses
- capability and charm prompts: `can you laugh`, `can you dance`
- affect and mood: `how are you`, `are you happy`, `are you sad`, `are you angry`
- memory and identity recall: `who am i`, `what is my name`, `when is my birthday`, `what is my favorite music`
- greeting and presence charm: `good morning`, `welcome back`, `who is this`, person-aware greeting follow-ups
- recognition follow-ups: `do you know me`, `do you remember me`, `can you recognize me`
- seasonal and contextual charm: holiday prompts, pizza day, surprise offers, personal report personality hooks
- conversational follow-ups that should stay local and warm instead of falling into generic chat

Current batch note:

- `favorite color`, `favorite food`, and `favorite music` are the first small favorites-family slice
- the latest pass adds longer authored variants for those favorites so the replies keep more of the original Pegasus cadence instead of collapsing to short placeholders
- the next source-backed batch now includes `favorite flower`, `R2D2`, `sun`, `space`, `kids`, plus a couple of charm prompts like `can you laugh` and `can you dance`
- the follow-up mood batch now includes `how are things`, `how is your day`, `are you sad`, and `are you angry`
- the personality follow-up batch now includes `what are you up to` and `what are you doing` so small talk stays warm and local instead of falling into generic chat
- the descriptor batch now includes `are you kind`, `are you funny`, `are you helpful`, `are you curious`, `are you loyal`, `are you mischievous`, and `are you likable`
- the seasonal batch now includes `what holidays do you celebrate`, New Year's resolution questions, `happy holidays`, `what halloween costume`, spring suggestions, and holiday gift prompts
- the latest social batch adds `welcome back`, `what are you thinking`, `what have you been doing`, and `what did you do` so presence and charm stay lively without distracting from the memory roadmap
- this pass keeps Build B moving while still favoring source-backed phrasing and preserving the command-vs-question boundary
- the next passes should keep the same pattern and prefer source-backed phrasing whenever the legacy MIM text is available
  - if a source-backed legacy line is missing, use a temporary direct reply only to keep the pass moving, then backfill source text later
  - after the favorites batch, the next doc pass should focus on richer persona follow-ups and the remaining memory/presence charm surfaces
- Build B is now reserved for the next source-backed scripted-response batch:
  - `how do you work`
  - `what do you eat`
  - `where do you live`
  - `where were you born`
  - `what languages do you speak`
  - `what do you like to do`
  - `what are you made of`
  - `what is your favorite flower`
  - `do you like R2D2`
  - `do you like the sun`
  - `do you like space`
  - `do you like kids`
  - `can you laugh`
  - `can you dance`

The goal is to port these in small batches, capture the source-backed phrasing where possible, and keep a test for each batch so the list never becomes a vague backlog graveyard.

### 2. Reliability And Device Proof

- complete update/backup/restore proof path with captures and operator docs
- the restore proof is the persisted-state rehydration path; do not scope it into a new hosted restore API until we have real device evidence
- continue alarm/gallery/yes-no cleanup from `1.0.18` evidence where regressions are still open
- improve short-turn STT reliability and low-signal screening

### 3. Pegasus-To-Cloud Platform Porting

- prioritize small source-backed slices from Pegasus/JiboOS that can be shipped safely
- keep Nimbus and stock payload compatibility as the release guardrail
- avoid broad subsystem rewrites without tests and live-capture evidence
- keep the legacy prompt inventory visible in the backlog so porting stays paced and traceable

### 4. Holidays And Seasonal Personality

- port holiday-aware personality responses as a visible extension of the new persona slice
- start with a small, source-backed set (for example birthdays/holidays already represented in legacy data paths)
- ensure holiday responses feel characterful while still routing through stock-compatible payloads

### 5. Multi-Tenant Memory Storage Foundation

- define tenant boundaries across account, loop, device, and person-memory records
- add storage abstractions that can move from in-memory/local JSON to hosted SQL/Blob without reworking behavior layers
- implement memory-ready schemas and repository contracts for user facts (names, birthdays, personal dates, preferences) with strict tenant scoping
- seed person-aware state keys now so future interactions can scope to account + loop + device + person without another shape change
- keep stateful interaction flows repository-backed instead of embedding more ad hoc metadata in the websocket layer
- the store seam now exposes revision metadata plus explicit load/save boundaries so durable adapters can drop in later without changing behavior code
- the backend seam is now selectable, with file-backed local persistence as the default and an Azure Blob Storage slot wired for future deployment wiring

### 6. Multi-Server Sync Path

- document the eventual sync boundary for stateful data that should move between servers
- treat the first pass as repository-local durability, then layer replication and conflict handling on top
- prefer explicit change records or versioned state snapshots over implicit last-writer wins when we outgrow a single node
- keep cross-server reconciliation out of the hot path until the single-server semantics are stable

Reference design:

- [persistence-architecture.md](persistence-architecture.md)

## First Implemented Slice In `1.0.19`

The first delivered slice in this release is persona expansion:

- `how old are you`
- `when's your birthday`
- `do you have a personality`
- `make a pizza`

`make a pizza` is now wired to the legacy scripted-response identity (`RA_JBO_MakePizza`) with pizza-making animation ESML, based on the original skill manifests.

This slice is intentionally small and user-visible. It creates immediate personality gains while we keep deeper platform work in parallel.

## Second Implemented Slice In `1.0.19`

The second delivered slice is first tenant-scoped personal memory:

- store birthday from phrases like `my birthday is April 12`
- recall birthday from phrases like `when is my birthday`
- store preferences from phrases like `my favorite music is jazz`
- recall preferences from phrases like `what is my favorite music`

Memory keys are scoped by account/loop/device tenant context so one tenant does not leak into another.

## Third Implemented Slice In `1.0.19`

The third delivered slice starts memory-triggered proactivity and broadens memory parsing:

- `surprise me` now runs a weighted proactivity selector
- selectors use tenant-scoped memory signals (favorites and likes/dislikes) plus date triggers
- February 9 (`National Pizza Day`) can proactively launch the pizza animation path
- proactive pizza fact offer flow now stores pending offer state and resolves direct `yes` / `no` follow-up answers
- memory parsing now covers:
  - names (`my name is ...`, `what is my name`)
  - important dates (`our anniversary is ...`, `when is our anniversary`)
  - likes/dislikes (`i like ...`, `i love ...`, `i dislike ...`, `i don't like ...`)
  - favorite phrase variants including reverse form (`pizza is my favorite food`)

## Fourth Implemented Slice In `1.0.19`

The fourth delivered slice starts weather compatibility using Pegasus-style report-skill routing:

- weather phrases now route to `report-skill` instead of generic placeholder chat
- outbound NLU launch uses legacy reactive intent `requestWeatherPR` (source-aligned with Pegasus manifests/tests)
- weather entity hints are added for:
  - `date = tomorrow` on tomorrow phrasing
  - `Weather = rain|snow|...` on condition questions (for example `will it rain tomorrow`)
- websocket output now emits local skill redirect + silent completion for weather launch, matching existing local-skill launch patterns

## Fifth Implemented Slice In `1.0.19`

The fifth delivered slice adds provider-backed weather content while preserving Pegasus launch compatibility:

- OpenWeather provider abstraction and infrastructure wiring are added to the hosted cloud
- weather requests still launch `report-skill` with `requestWeatherPR` and legacy weather/date entities
- weather replies now include cloud-generated spoken summaries from provider data:
  - current conditions (`Right now in ...`)
  - tomorrow forecast shape (`Tomorrow in ...`) with high/low temperatures when available
- simple location extraction is supported for phrasing like `what's the weather in Chicago tomorrow`
- provider config supports appsettings and `OPENWEATHER_API_KEY` environment fallback for deployment

## Personality Import Ladder

This is the practical plan for importing legacy Jibo `mims` into OpenJibo without pretending we already have a full Pegasus runtime.

### What Is Possible Today

OpenJibo can already host a meaningful subset of legacy personality content because it has:

- a shared catalog for content-driven replies
- chitchat state-machine routing with route metadata
- outbound payload support for `skillId`, `mim_id`, `mim_type`, `prompt_id`, `prompt_sub_category`, and ESML
- existing examples that already behave like legacy MIMs for pizza, dance, news, weather, and generic chat

### What We Need To Build

To move from hand-wired examples to broader imports, we need three small platform pieces:

1. a MIM inventory importer that can scan the legacy tree and produce a normalized catalog
2. a prompt-selection layer that can choose by `skill_id`, `mim_id`, prompt category, and condition metadata
3. a safe ESML/prompt renderer that preserves existing stock-compatible payload shapes

### What Can Be Ported With Each Build

#### Build A: Declarative Prompt Packs

Port immediately:

- `core-responses`
- `deflector`
- the simplest `emotion-responses`
- any `scripted-responses` that are just direct prompt lists with no special state machine

Why these first:

- they are already close to the current `JiboExperienceCatalog` model
- they give us user-visible personality quickly
- they are the best fit for low-risk testing tomorrow

#### Build B: Conditioned Prompt Packs

Port after the importer and renderer are in place:

- `gqa-responses`
- structured emotion responses with `condition` gates
- prompt sets that select different replies by user state or Jibo state

Why these next:

- they are still mostly declarative
- they need a small amount of condition evaluation, but not a new conversation engine

#### Build C: Conversation Families

Port after Build B:

- richer `scripted-responses` families that depend on follow-up state
- special-date / holiday personality sets
- more nuanced chitchat branches that need context-aware routing
- longer authored variants for existing prompts when the source text contains them, so the robot keeps the familiar Pegasus cadence without inventing new dialog composition yet
- dialog joining / composition as a post-release feature, kept out of the 1.0.19 ladder so we do not blur authored phrasing with a runtime joiner

Why these later:

- they need state and follow-up behavior, not just prompt selection
- they are where personality feels most alive, but they are also where bugs will be easiest to introduce

#### Build D: Full Parity Cleanup

Port after the core ladder is stable:

- large cross-skill collections
- any MIMs that depend on Pegasus-only parser assumptions
- any files that need a dedicated runtime abstraction instead of catalog lookup

## System Diagram Alignment Snapshot (`2026-05-06`)

Legacy architecture (`system_diagram.png`) has been mapped to current OpenJibo cloud services so release execution stays anchored to:

- where we were (Pegasus/Jibo cloud design intent)
- where we are (current hosted `.NET` modular monolith)
- where we are headed (durable memory, proactivity catalogs, parser depth, provider aggregation)

Reference:

- [system-diagram-alignment.md](system-diagram-alignment.md)

## Greetings And Presence Planning Snapshot (`2026-05-07`)

Pegasus greeting and presence behavior has now been captured into a source-anchored OpenJibo implementation plan.

Reference:

- [greetings-presence-plan.md](greetings-presence-plan.md)

## Live Validation Snapshot (`2026-05-07`)

User-confirmed end-to-end behavior now includes:

- `Hey Jibo -> What's your cloud version?` (working)
- `Hey Jibo -> What's the time?` (working)
- `Hey Jibo -> Surprise me -> pizza fact -> $YESNO (Yes) -> fact` (working)
- `Hey Jibo -> Surprise me -> pizza fact -> $YESNO (No) -> decline reply` (working)

This confirms the pizza-fact offer state now keeps the yes/no branch open through completion and does not require a second wake-word reset for the follow-up answer.

## Personal Report Planning Snapshot (`2026-05-07`)

Personal report parity planning is now captured with Pegasus source anchors for weather visuals/animations, live news, commute, and calendar gap coverage.

Reference:

- [personal-report-parity-plan.md](personal-report-parity-plan.md)

## Next Queued Task (`2026-05-06`)

Queued next `1.0.19` implementation task (now started):

- dialog parsing expansion and ambiguity guardrails

Execution focus:

- import additional Pegasus parser phrases/entities into intent handling where safe
- reduce trigger-only captures that drop the rest of the utterance
- preserve command-vs-question personality split and local skill payload compatibility
- add focused tests for new phrase families and ambiguity boundaries
- keep listener-state observability aligned with the legacy GLSM flow while phrase guardrails are added

First completed guardrail slice under this queue:

- GLSM listener flow capture + telemetry mapping
- stale pending-listen recovery path for long-open no-context/no-audio listens

Second completed guardrail slice under this queue:

- tightened date/time ambiguity handling (`what's your birthday`/`what's your bday` no longer falls into date intent)
- expanded Pegasus-inspired memory/weather phrase coverage:
  - birthday alias parsing (`my bday is ...`, `when is my bday`)
  - shorthand preference sets (`my favorite sport football`)
  - weather variants (`what's today's weather look like`, `will it be sunny tomorrow`)
- listener continuation guardrail now differentiates incomplete preference fragments from complete shorthand preference sets

Third completed guardrail slice under this queue:

- expanded Pegasus `userLikesThing` / `userDislikesThing` / `doesUserLikeThing` / `doesUserDislikeThing` phrase-family coverage
  - includes additional dislike/negation variants (`loathe`, `did not like`, `didn't enjoy`, `don't really like`)
  - includes group-preference variants (`we like`, `we love`, `we dislike`, `we can't stand`)
  - includes lookup variants (`do you think i like ...`, `do you believe i don't like ...`)
- added affinity set/lookup attempt guardrails so partial captures route to affinity prompts instead of generic chat
- extended auto-finalize continuation deferral for the new Pegasus affinity stems (`we like`, `i loathe`, and related variants)
- added focused interaction + websocket tests for the new parser/guardrail behavior

Next queued implementation track after parser guardrails:

- personal report parity slices (weather visual parity, live news path, commute/calendar gap closure)

First completed slice in this personal-report parity track:

- added provider-ready news briefing path with Nimbus-compatible `news` payload continuity
- preserved fallback behavior when no live provider is configured
- added memory/transcript category hinting for provider requests (`sports`, `technology`, `business`, etc.)
- added provider-side request caching for both news and weather to reduce integration churn and repeated lookups
- added focused interaction + websocket tests for provider-backed news speech output and request-hint plumbing

## Next Slices

1. MIM import foundation for personality expansion
2. Dialog parsing expansion
3. Presence-aware greetings and identity-triggered proactivity
4. Personal report parity slices
5. Holidays and seasonal personality slice beyond pizza day
6. Durable memory persistence path
7. Update/backup/restore end-to-end proof - implemented
8. STT noise-screening and short-utterance reliability pass
9. Provider-backed news expansion and deeper weather parity
10. Capture indexing and retention boundary for group testing, including a lightweight manifest beside raw capture files
11. Binary-safe media storage seam with file and Azure Blob adapters, ready for original/thumbnails follow-up

For slice 1, use the new import ladder above to keep the work grounded in what OpenJibo can already render today versus what needs new scaffolding.
For slices 2-5, use Pegasus phrase lists, MIM IDs, and behavior patterns as the source anchor before broadening into OpenJibo-native improvements.

## Definition Of Done

Release `1.0.19` is complete when:

- planned slices have focused tests and updated docs
- regression checklist passes for the existing stock-OS compatibility paths
- live runs confirm no critical regressions in alarms, gallery, yes/no, and cloud-version diagnostics
- memory/personality storage proves tenant isolation by account/loop/device boundaries and is compatible with the target hosted cloud footprint