DS4Server/PLAN.md

DS4Server implementation plan

Bundle/application identifier: DS4Server.rfc1437.de

The GUI is a Rust/Iced reimplementation of the user-facing model server and coding-agent workflows in ../ds4. The existing engine remains the behavioral reference: ds4.c/ds4.h define model and session behavior, ds4_server.c defines the compatible API, and ds4_agent.c defines agent sessions, tools, and turn orchestration.

Current status

Area	Status	Available now	Still open
App shell	Implemented	Native multi-window Iced app, Codex-inspired layout, native Application/Edit/Window menus, Preferences panel, Model Manager, and streaming composer	Native app release packaging
Projects and sessions	Implemented with transcripts and KV resume	Native folder picker, project-name dialog, create/select/delete projects and sessions, durable structured chat history, and per-session KV checkpoints	Rename/archive and model binding
Persistence	Implemented for local chat	SQLite in Application Support, Diesel ORM, embedded migrations, constrained defaults, streamed message updates, reopen tests, context/speed state, and local KV rehydration	Downloaded-artifact metadata and session-runtime migrations; HTTP chats deliberately never enter SQLite
Model runtime	DeepSeek Flash vertical implemented	Rust-owned mmap/model/session graph, local Metal kernels, full configured sparse context, DS4 sampling, one process-wide UI/HTTP owner, cancellation, idle unloading, prefix continuation, and KV checkpoint save/load	DSpark/SSD/steering and GLM/Pro execution
Local endpoint	Chat Completions vertical implemented	Automatic configurable localhost listener (port 4000 by default), verified-on-disk model discovery, transient requests, non-streaming and SSE Chat Completions, reasoning, usage, sampling, stops, cancellation, tools, and exact in-process tool replay	GUI status and enable/disable controls, Responses, legacy Completions, Anthropic Messages, full ds4_server.c fixture parity, and cross-restart exact tool replay
Agent	Solid local chat implemented	Multi-turn role rendering, structured reasoning disclosure, Markdown, automatic scrolling, context/speed display, durable transcript rehydration, and KV-backed resume	Tools, approvals, compaction, and richer statistics
A2UI	Future extension	bDS2 provides the reference structured render-tool contract	Native inline surfaces for local chat after core chat and tools are stable
Dev brain	Not started	No vault access	Obsidian vault selection, durable access, and agent knowledge/memory tools
Release	Not started	Development binary builds and tests	.app packaging, signing, entitlements, and notarization

The application manages durable project/session metadata and model preferences. Its Model Manager downloads, validates, and deletes managed GGUF artifacts without blocking the UI. Local chat now lazily acquires the Rust DeepSeek Flash executor, streams generated text, supports cancellation and multi-turn role replay, persists reasoning and answers while they stream, rehydrates selected sessions, and unloads model resources after the configured idle timeout. The current Rust graph supports the full configured context with ratio-4 sparse attention and durable local KV checkpoints. The shared HTTP Chat Completions service is available; the remaining protocol routes and agent tools remain open.

Phase 0 — project and session shell

Status: implemented.

• Show projects in a sidebar with their sessions nested underneath.
• Create projects with a native macOS folder picker and a project-name dialog.
• Create, select, and delete projects and sessions.
• Use a Codex-inspired two-pane layout with embedded, action-specific SVG icons.
• Persist projects and sessions in SQLite under ~/Library/Application Support/DS4Server.rfc1437.de/, using Diesel ORM queries and embedded Diesel migrations.
• Never delete workspace contents when removing app metadata.

Exit criterion: restart the app and see the same project/session tree.

Phase 1 — model library and on-demand loading

Status: partially implemented. The typed preference/download/intake path and a DeepSeek Flash Rust/Metal vertical are implemented, including full configured context, ratio-4 sparse indexed attention, prefix continuation, KV checkpoint save/load, DS4 sampling, cancellation, idle unload, and shared HTTP acquisition. Other model families and optional execution modes remain open.

1. Implemented: the typed model/runtime preference contract described below is complete before chat, the HTTP endpoint, or the engine lifecycle.
2. Implemented for DeepSeek Flash: mmap-backed loading, tokenizer/prompt rendering, Rust-owned session creation/evaluation/sampling, prefix sync, and KV save/load are complete.
3. Implemented: retain the tested model restrictions from DwarfStar. Main and DSpark artifacts reject invalid GGUF versions, catalog mismatches, and incompatible metadata, tensor shapes, offsets, or quantization before promotion and again before model use.
4. Partially implemented: reuse the existing .metal kernels and preserve mmap-backed resident loading plus the explicit SSD-streaming path. Keep Objective-C only at the Metal interop boundary.
5. Keep exactly one model resident process-wide. Local chat and every endpoint request must use the same owner and queue; model selection may replace the resident model only after active work reaches a safe boundary. Multiple simultaneously loaded models are out of scope because DS4Server targets models large enough to consume most available memory.
6. Implemented for local chat: move engine work off the UI thread and support cooperative cancellation at the safe session boundaries already defined by ds4_session_sync.

DS4 KV-cache port and shared session core

KV-cache behavior is part of the DS4 engine contract, not a new application cache to redesign. Port the existing ds4_session and ds4_kvstore behavior to Rust while preserving its semantics and on-disk compatibility:

• A live engine session owns one mutable inference timeline: exact rendered tokens, logits, and the DS4-specific KV graph state. Callers provide the full token prefix and the Rust port of ds4_session_sync must retain the longest compatible prefix, evaluate only its suffix, or safely rewind, invalidate, and rebuild exactly when DS4 does.
• Carry over DS4's safe cancellation/checkpoint boundaries, common-prefix matching, canonical rewrite and replay, snapshots, payload staging, save/load, strip-to-transcript behavior, and atomic replacement. The engine continues to own the opaque KV payload format; UI, HTTP, and persistence code must not reinterpret tensor state.
• Port ds4_kvstore policy rather than replacing it with a generic cache: exact token and rendered-text prefix lookup, cold and continued aligned checkpoints, model/quantization/context/payload-ABI compatibility checks, tool-call replay metadata, disk-budget enforcement, hit tracking, and eviction behavior.
• Use one process-wide Rust model owner and KV checkpoint implementation for local chat and the HTTP server. Model access is serialized so two callers never mutate the single resident inference graph concurrently.
• Application projects and sessions belong exclusively to local chat. HTTP requests are transient and must never create projects, sessions, messages, transcript rows, request-identity mappings, or any other durable chat record. The outside client owns conversation identity and resends the history needed for each request, exactly as ds4_server.c expects.
• Transient HTTP requests may read and write engine-owned KV cache files for compatible-prefix reuse. Those opaque cache files are the only server-side persistence permitted for external conversations and do not establish an application session or recoverable transcript.
• Store engine-owned checkpoints under Application Support in kv-cache/. Local chats use their application session ID; HTTP uses content-addressed entries under kv-cache/http/. The large opaque payload is never stored in SQLite, and HTTP cache entries do not create application sessions.
• Cache sharing does not merge conversations or expose transcript text. It shares only the DS4 implementation and compatible opaque prefix checkpoints; the request body remains the source of truth for external conversation state.
• Engine unload must first leave every reusable live timeline in a valid persisted checkpoint. Reload restores a compatible checkpoint immediately; if model identity, quantization, context size, payload ABI, or rendered history is incompatible, rebuild from the transcript and replace the stale checkpoint only after the new state is valid.

Lazy lifecycle

• Start the application and the local HTTP endpoint with no model loaded.
• Acquire the configured model only when generation starts, whether initiated by a local chat or an OpenAI-compatible endpoint request. Concurrent first requests share the same load instead of opening the model more than once.
• Expose Unloaded → Downloading → Loading → Ready → Unloading plus failure states and progress in the GUI. A request that triggered loading waits for the shared load and receives a clear error if download or initialization fails.
• Treat active local generations, endpoint requests, prefills, and tool turns as model activity. Start the idle timer only when all activity has stopped.
• Unload the engine after the configured idle timeout. New work cancels a pending unload; work arriving after unload transparently loads the model again. Persisted transcripts and KV files remain available when model memory is released.
• Changing the selected model prevents new work from using the old model and unloads it as soon as current work reaches a safe boundary.

Preferences foundation (implemented)

• Provide a Preferences panel from the sidebar and the standard macOS Command-, shortcut.
• Let the user choose the active model. Default to deepseek-v4-flash.
• Let the user enable or disable DSpark for the selected model. Disable the control for models that do not support DSpark.
• Let the user configure the inactivity timeout; default to 10 minutes.
• Let the user configure the localhost endpoint port; default to 4000 and apply a changed port when preferences are saved.
• Persist preferences in the application SQLite database. Changing preferences never loads a model by itself.

DS4 model and generation preferences (implemented)

The Preferences panel must expose every persistent model, runtime, and generation parameter accepted by the ds4 command line. ../ds4/ds4_cli.c, ds4.h, and the shared GPU/distributed parsers are the source of truth; use the same defaults, ranges, units, dependencies, and model-family overrides rather than inventing application-specific behavior.

• Model and capacity: selected main GGUF (--model), optional MTP/DSpark support GGUF (--mtp), context tokens (--ctx), maximum generated tokens (--tokens), and system prompt (--system). Managed catalog selections map to their installed files instead of requiring users to type paths.
• Sampling and reasoning: temperature (--temp), top-p, min-p, optional seed, and one reasoning mode representing --think, --think-max, or --nothink. Preserve DS4's explicit-vs-default distinction because GLM applies model-family sampling defaults only when the user has not overridden them.
• Execution: the macOS app uses Metal exclusively; omit the unnecessary CPU backend and backend selector. Persist CPU helper threads for host-side work, GPU power percentage, prefill chunk, exact/quality kernels, and warm weights.
• Speculative decoding: MTP draft-token count and margin, GLM MTP, GLM MTP timing, DSpark enablement, DSpark confidence threshold, and DSpark strict target-only decode. Enabling a dependent control must enable or require its support artifact exactly as the CLI does.
• SSD streaming: enablement, cold start, expert count or GiB cache budget, fully resident GLM layers, and explicit expert preload count. Retain the distinction between unset/automatic and an explicit zero where DS4 does.
• GPU placement: per-device VRAM budgets, device indices, and CUDA tensor parallelism when available. Hide or disable these controls in a Metal-only or CPU-only build rather than accepting values the engine cannot honor.
• Directional steering: direction-vector file, FFN scale, and attention scale, including the CLI rule that a file with no explicit scale defaults the FFN scale to 1.
• Advanced diagnostics that change model execution: simulated used memory and routed expert profile output. Keep these in an Advanced section with clear diagnostic labels, but persist and pass them through like their CLI equivalents.

Prompt sources, raw one-shot mode, inspect/dump/perplexity/imatrix/self-test actions, and distributed coordinator/worker network topology are CLI workflows, not persistent model parameters; they belong to their corresponding chat, diagnostic, or deployment surfaces rather than Preferences. Any future DS4 CLI option must be classified explicitly as either a preference or one of these non-preference actions.

Implement this before chat as one typed settings path shared by the local GUI, the lazy engine lifecycle, and HTTP defaults:

• Persist unset/automatic values separately from explicit values and provide a Reset to DS4 defaults action. Validate before saving with the same accepted ranges and cross-field rules as the CLI.
• Mark settings as load-time or turn-time. A load-time change unloads/reloads at the next safe boundary; sampling, seed, token budget, and reasoning changes apply to the next turn without duplicating the engine.
• Local chat uses these values directly. HTTP requests use them as defaults and may override only request-scoped generation fields supported by the API; both paths still resolve through the same effective-settings builder.
• Add a focused parity test that inventories every option branch in the DS4 CLI model/runtime, sampling, and steering groups and fails until each option is mapped to a typed preference or explicitly classified as a non-preference action.

Exit criterion: save, restart, and recover every supported DS4 model/runtime and generation value; show the same effective defaults and validation as the CLI; and construct one engine configuration plus one turn configuration without chat or HTTP code re-parsing preference fields.

Targeted downloads and storage

• Preferences only selects the model/runtime configuration. A separate Model Manager window, reachable from the native Window menu, lists every managed main and DSpark artifact with its on-disk size and state, and provides Download/Resume, Validate, Stop, and confirmed Delete actions.
• A dedicated worker thread performs HTTP and verification work so the Model Manager and the rest of the application stay interactive.
• Use an in-process Rust HTTP client with Rustls rather than invoking a system downloader. Stream response chunks directly into a .part file and use a Rust SHA-256 implementation for verification.
• Report aggregate bytes present, total bytes, bytes missing, percentage, smoothed transfer rate, current artifact/verification phase, and estimated time remaining. Keep the detailed display in Model Manager and a persistent status bar with a Stop action while the transfer runs.
• During SHA-256 verification, show a dedicated progress bar based on bytes read and hashed rather than the already-complete file size. Update the bytes verified, verification throughput, percentage, and estimated time remaining throughout the pass so large models never appear stalled at 100%.
• Stop is non-destructive: close the active transfer and retain its .part file. Starting the download again in the same process or after quitting and relaunching must derive progress from that file and issue an HTTP range request from its exact byte length. If the server ignores the range request, safely restart that artifact from byte zero rather than appending corrupt data.
• Promote a .part file only after its exact size and SHA-256 are verified. A stopped verification keeps the complete partial file so the next run can verify and promote it without downloading it again.
• Store managed model artifacts under ~/Library/Application Support/DS4Server.rfc1437.de/models/<model-id>/ and mmap/load them from there. Do not place managed models in the app bundle or a project directory.
• Download only the artifact explicitly requested in Model Manager; never prefetch other catalog models or optional artifacts.
• Remove checksum-invalid partial files without touching a valid model. Keep partial files after cancellation, application exit, network failure, or an interrupted verification so they remain restart-resumable.
• Delete model artifacts only through an explicit, confirmed Model Manager action; changing Preferences must never remove files.

Exit criterion: select a supported DeepSeek V4 or GLM 5.2 GGUF, load it without blocking the UI only when a chat begins, run a deterministic prompt, unload it after the configured idle timeout, and pass the matching ../ds4 token-output fixture. Repeat through the local endpoint and verify both paths share the same engine lifecycle.

Phase 2 — OpenAI-compatible local endpoint

Status: partially implemented. The shared single-model runtime, verified-model discovery, configurable localhost port, and the first ds4_server.c-compatible Chat Completions vertical are implemented. The remaining protocol routes plus GUI status and enable/disable controls remain open.

1. Partially implemented: add a localhost-only HTTP service whose lifecycle is independent of the engine. It can listen while the model is unloaded and acquires the configured model only for inference. It listens on configurable port 4000 by default; start/stop controls remain open. Never expose a LAN listener without an explicit setting.
2. Implement the DwarfStar compatibility surface from ds4_server.c in this order, preserving its request parsing, prompt formatting, reasoning fields, streaming events, errors, usage accounting, stop behavior, tool replay, and cancellation semantics rather than inventing an app-specific protocol:
   • GET /v1/models
   • POST /v1/chat/completions
   • POST /v1/responses
   • POST /v1/completions GET /v1/models scans managed artifacts without forcing a model to load and reports only main model files that are fully downloaded and have a matching on-disk verification marker. Missing, partial, unverified, or checksum-invalid artifacts are never advertised.
3. Support streaming SSE, reasoning output, usage accounting, cancellation, sampling parameters, tool schemas, and tool choice.
4. Port exact sampled tool-call replay and deterministic canonicalization from ds4_server.c so a client's normalized JSON does not destroy KV-prefix reuse.
5. Route API work through the single process-wide model owner and engine-owned KV store defined in Phase 1. External requests are always stateless at the application layer: never write their messages to SQLite and never bind a Responses conversation, request identifier, or client-supplied session key to a local project/session. The client must replay its protocol history; DS4-compatible prefix lookup may accelerate that replay using opaque KV cache files. Add resident batching only if one-model serialized execution is later proven insufficient.
6. Display endpoint address, model, active requests, token rates, and errors in the GUI.

Exit criterion: the upstream DwarfStar server tests pass against the app for non-streaming and streaming Chat Completions and Responses calls, including a multi-turn tool call. Verified installed models are listed without loading one; missing/unverified models are absent; local and HTTP generations cannot load two models concurrently; external calls leave no project, session, message, or transcript rows behind; and compatible KV cache files remain reusable.

Phase 3 — durable agent sessions

Status: partially implemented for local chat only. Project/session metadata, structured transcripts, context statistics, and per-session KV checkpoints are durable. Model binding and archive behavior remain open. This phase never applies to external endpoint conversations.

Extend each metadata-only session with transcript and shared-checkpoint metadata:

Application Support/DS4Server.rfc1437.de/
  data.sqlite3
  models/<model-id>/
    main.gguf
    dspark.gguf       # only when enabled
  kv-cache/
    <local-session-id>.bin
    http/<conversation-tag>.bin

• Implemented: migrated message tables persist local user text, reasoning state, assistant output, context usage, and generation speed while generation streams. Local session KV payloads remain engine-owned files written with atomic replacement; SQLite never stores opaque tensor data.
• Record model identity, context size, rendered token history, title, timestamps, and working directory.
• Restore compatible KV immediately. If KV is absent or incompatible, rebuild from the transcript and show prefill progress.
• Add strip/archive behavior equivalent to the native agent: retain the transcript and clear its checkpoint reference. Remove the cache file only when it is not reusable by another live/session prefix; otherwise normal DS4 disk-budget eviction reclaims it.
• Version formats before the first release and add migrations only when a real format change exists.

Exit criterion: quit during normal use, relaunch, select a session, and resume the same conversation without prefill when its KV payload is compatible.

Phase 4 — agent chat and tools

Status: basic local chat implemented. The conversation area streams multi-turn DeepSeek Flash output, persists and rehydrates structured reasoning and answers, and supports Stop; tool turns and the coding-agent runtime remain open.

Every chat feature must persist its semantic state and rehydrate it when a session is reopened in the same implementation slice. In-memory-only chat features are incomplete by definition; disclosure state and other purely ephemeral presentation preferences are the only exception.

1. Partially implemented: build the classic chat surface. Transcript, structured reasoning disclosure, composer, streamed output, and Stop are complete; tool-call cards, queued input, prefill progress, and generation statistics remain. Local turns must call the same session registry and KV path used by the HTTP endpoint.
2. Port the native agent turn loop from ds4_agent.c, including model-specific system prompts and DeepSeek DSML/GLM tool-call parsing.
3. Implement the local tool set with the project directory as its boundary:
   • shell command execution
   • file read and continuation
   • file write
   • anchored edit
   • text/file search
   • opt-in Dev Brain knowledge lookup and memory storage
4. Stream assistant tokens and partial tool calls into Iced while inference and tools run on workers. Preserve cooperative interruption and a valid KV prefix at every stop point.
5. Require confirmation for commands or writes outside the project boundary, destructive actions, and network tools. Add web search/page visiting only after the local tool loop is stable.
6. Port context compaction and system-prompt reinjection after ordinary multi-turn operation is correct.

Native macOS menus (required with chat)

Status: partially implemented. Application, Edit, and Window menus are installed; Cut, Copy, Paste, and Select All now bridge into the focused Iced text field. File/View/Help menus, dynamic enabled state, the remaining Edit actions, and selectable transcript text remain open.

The application must install and maintain a complete native macOS menu bar; the application-name menu alone is not sufficient. Use platform menu roles, ordering, selectors, and standard key equivalents rather than drawing menus inside the Iced window.

• Provide the standard Application, File, Edit, View, Window, and Help menus. Include the normal macOS Application actions (About, Settings, Services, Hide, Hide Others, Show All, and Quit) and Window actions (Minimize, Zoom, Bring All to Front) with native behavior.
• Make File actions operate on real application concepts: New Session, Add/Open Project, and Close Window. Make View actions cover actual available views, including sidebar visibility and Enter Full Screen. Help opens the local help or documentation surface. Do not add permanently inert placeholder items.
• The Edit menu is part of the chat acceptance criteria. Undo, Redo, Cut, Copy, Paste, Paste and Match Style where supported, Delete, and Select All must act on the current first responder. They must work in the chat composer and every other editable text field; Copy and Select All must also work for selectable transcript text.
• Prefer native first-responder selectors for native controls. Where an Iced widget owns focus, bridge the same menu command into that focused widget so menu clicks and Command-Z, Shift-Command-Z, Command-X, Command-C, Command-V, and Command-A behave identically.
• Validate menu enabled state whenever focus or application state changes: editing commands reflect the focused selection/clipboard and session/project commands reflect whether their action is currently possible. Menu actions must use the same application messages as toolbar/sidebar actions instead of duplicating business logic.
• Preserve conventional macOS labels, grouping, keyboard shortcuts, and accessibility metadata. Keep platform-specific menu integration behind the macOS application shell so the chat and session core remain platform-neutral.

Exit criterion: with the composer focused, every standard Edit command works from both the menu and its keyboard shortcut, including undo/redo across multiple edits; transcript text can be copied; and Application, File, View, Window, and Help expose functional, correctly enabled native actions.

Dev Brain — Obsidian knowledge and memory

• Add an optional Dev Brain setting in Preferences. Use the native macOS folder picker to select an existing Obsidian vault, allow the vault to be changed or disconnected, and persist its canonical path plus a security-scoped bookmark in SQLite so sandboxed builds can regain access after restart.
• Keep the vault global to the application rather than tied to one project or session. The selected vault remains in its original location; never copy it into Application Support or a project directory.
• Add one local dev_brain agent tool with the minimum useful operations: search Markdown notes, read a selected note, and create or append a memory note. Return vault-relative paths with results so the agent can cite where knowledge came from.
• Restrict every operation to the explicitly selected vault. Resolve and check paths before access, ignore .obsidian and hidden files, and do not provide deletion or arbitrary overwrite operations initially.
• Let the agent retrieve relevant global knowledge during a turn and record durable conclusions after a turn. Vault access is opt-in, does not preload the model, and must not block sessions when no vault is configured or available.
• Reuse the existing local file/search implementation underneath the new vault boundary instead of building a second filesystem stack.

Exit criterion: create a project session, ask the model to inspect and edit a small fixture repository, review each tool result in the GUI, restart, and continue from the persisted session. With Dev Brain enabled, store a memory in one session and retrieve it with a cited vault-relative note path from a session in another project after restarting the app.

Phase 5 — A2UI rich local-chat surfaces

Status: future extension; not part of the core milestone. Start only after ordinary local chat, structured tool calls, transcript persistence, and cancellation are stable. Use the A2UI implementation in ../bDS2 as the behavioral reference, especially its render-tool schemas, typed surface normalization, inline message placement, chart geometry, and interaction state.

• Expose typed render_card, render_chart, render_form, render_list, render_metric, render_mindmap, render_table, and render_tabs tools to the local agent. Keep these tools presentation-only; they return structured data and do not perform project mutations themselves.
• Support the bDS2 chart set initially: bar, stacked bar, line, area, pie, donut, and heatmap. Render charts and mind maps with native Iced primitives and SVG geometry inside the assistant message rather than adding a web view.
• Treat tool arguments as untrusted data. Validate type, nesting depth, row and series counts, numeric values, labels, action names, and payload size before rendering. Never accept model-authored HTML, JavaScript, styles, file URLs, or arbitrary commands.
• Attach each validated surface to the assistant message/tool call that created it and persist the versioned structured payload with the transcript. A restarted session must reconstruct the same surface without asking the model to emit it again.
• Build a surface only after its tool arguments are complete and valid while allowing ordinary assistant text to continue streaming. Malformed or unknown render payloads fall back to a bounded JSON/text representation and must not fail the surrounding chat turn.
• Preserve local interaction state for forms and tabs. Dispatch form submits and card actions through a small allowlist of application actions; any action that mutates files, settings, or external state still follows the normal approval path.
• Provide keyboard navigation, readable labels, theme-aware colors, and a text or tabular fallback for chart data so the information remains accessible and copyable.
• Keep A2UI local-chat-only initially. Do not extend the OpenAI-compatible HTTP surface or invent a general plugin/component protocol until a real client requires it.

Exit criterion: ask the local agent to present fixture data as each supported surface type; verify a chart and nested tab surface render correctly, an interactive form returns validated values, malformed payloads degrade safely, and all surfaces survive application restart with their message history.

Verification and packaging

Status: partially implemented. Formatting, Clippy, build, and unit-test commit gates are documented in AGENTS.md; database migration/CRUD constraints and the preferences shortcut have unit coverage. Model fixtures, integration tests, and release packaging remain open.

• Keep unit coverage narrow: persistence round trips, format compatibility, DS4 KV prefix/rewrite/store/load parity, cross-surface session binding, request parsing, and tool-boundary checks.
• Reuse ../ds4 fixtures for prompt rendering, sampling, server streaming, and KV correctness; run live Metal tests only when a supported GGUF is available.
• Preserve the DwarfStar/llama.cpp notices required by ../ds4/LICENSE for reused or adapted source and kernels.
• Produce a signed .app with the exact identifier above, then add hardened runtime, entitlements, notarization, and update delivery as release work.

Recommended next milestones

1. Finish the Flash session core as one larger slice: port the ratio-4 indexer and indexed attention for full configured context, then add prefix sync and compatible KV checkpoint save/load. Implemented.
2. Put the OpenAI-compatible endpoint on the same engine lifecycle so local chats and HTTP requests cannot load duplicate models. Keep HTTP conversation state transient except for opaque KV cache files. Chat Completions vertical implemented; remaining reference routes are open.
3. Local transcript/KV persistence and the conversation UI are implemented; port the agent tools after the shared endpoint lifecycle is stable.
4. Add the opt-in Dev Brain tool after local file/search boundaries and agent approvals are stable.
5. Add bDS2-style A2UI render tools and native inline surfaces after the core local chat/tool loop is complete.