aish/docs/PHASE8.md

aish — Phase 8 Manifest

Project: aish — AI-augmented conversational shell Document: Phase 8 Requirements, Architecture & Design Decisions Status: Analyze (formulate complete; tree at 00869ba probed) Date: 2026-05-16

Analyze findings (2026-05-16):

A1. enforce_budget ONLY checks max_turns, not token_budget — major scope gap. Context:enforce_budget (context.lua:319) iterates while #self.turns > self.max_turns; self.token_budget = 4096 is set but NEVER consulted. So even with accurate tokenization, eviction decisions are unaffected — the new estimate_tokens() only feeds the prompt template's {ctx_used} display variable (repl.lua:630).

**Resolution**: extend Phase 8 with a NEW pillar 5: make
`enforce_budget` honor `token_budget` AS WELL AS max_turns —
evict the oldest pair when EITHER threshold is exceeded. This
is the real motivation for accurate tokenization; without it
Phase 8 is largely cosmetic. Folded into §1 (5 pillars now),
§3 (context.lua row), §9 (new risk row about under-eviction
becoming over-eviction if tokenize_fn returns a much higher
number than char/4).

A2. ffi.curl.M.post signature confirmed. (body, status) on success, (nil, err) on failure. Matches the formulate-time sketch. status is the integer HTTP code. The probe checks status == 200 and out correctly.

A3. Single caller of Context:estimate_tokens() in tree. Only repl.lua:630 (prompt template {ctx_used} substitution) calls it. No internal callers in context.lua. This means: - The wiring point is ONE line in repl.lua (the prompt template already runs ctx:estimate_tokens() on every prompt render). - With A1's extension, enforce_budget becomes a SECOND caller — and a more frequent one (per turn, not per prompt render). - Per-turn _tokens cache becomes important for the enforce_budget path (called from ask_ai after every turn).

A4. Q-T1 RESOLVED: per-turn _tokens cache lives on the turn dict. :reset clears ctx.turns so the cache dies with them. New turns get nil _tokens; lazy-set on first count. Trivial.

A5. Q-T2 RESOLVED: tokenize_fn closure captures active_cfg as an UPVALUE. Upvalues are resolved at closure call time, not at definition time. When the user :model cloud switches, active_cfg = config.models[name] reassigns the local; subsequent tokenize_fn calls see the new value. Natural; no explicit re-binding needed.

A6. Q-T3 RESOLVED: skip the probe entirely when cfg.tokenize.use_endpoint = false or unset. Don't even call broker.token_count — repl.lua won't wire tokenize_fn to Context.new in the first place. context.lua's tokenize_fn-nil branch handles it (char/4 fallback).

A7. Q-T6 RESOLVED (defer to follow-up): tools-schema tokens are a fixed cost per session (tools_schema doesn't change unless :mcp connect/disconnect lands a new session). The under-count is bounded and predictable. Defer to a future polish; v1 counts only messages. Document in §8 out-of-scope.

A8. Per-turn _tokens cache invalidation. Turn content is immutable after append (we don't mutate stored turns). Cache is safe to live forever on the turn. The only invalidation event is :reset (clears turns wholesale). No other invalidation needed.

A9. Probe latency baseline (Q-T4 deferred): probed manually during formulate — single tokenize call for ~50 char text ran in ~50ms locally. For 40 turns × 500 chars cached = 40 × 50ms = 2s ONLY on the first estimate after a fresh session. After caching, subsequent estimates are O(1) per turn (dict lookups).

A10. Streaming during chat_stream interleaves with tokenize? No — Context:estimate_tokens() is called OUTSIDE the streaming callback (in the main loop, before/after broker calls). No concurrent network competition.

A11. MCP tool turn content — role:"tool" turns have content strings too (the tool result). These get tokenized identically; no special-case needed. Cache key is the turn dict itself, so tool turns get their own _tokens slot.

A12. include_usage interaction with tokenize: orthogonal. The tokenize probe uses a separate (non-streaming) /tokenize endpoint; never sees the chat completion's stream_options.

PHASE0 is the locked substrate; PHASE1-7 are layered on top. This manifest specifies what Phase 8 adds — accurate tokenization: replace the char/4 heuristic on Context:estimate_tokens() with a per-broker /tokenize round-trip where supported, char/4 fallback otherwise.

Resolves Q1 (PHASE0.md §13, originally targeted at Phase 3 — deferred forward across each phase). PHASE0 §11 amendment to add Phase 8 row lands in the same commit as this formulate doc.

---

1. Scope of Phase 8

Five pillars (A1 added pillar 5):

1. Per-endpoint tokenize probe (cached) — at first use, send a probe to the broker's tokenize endpoint with a tiny payload; if it returns {tokens: [...]} we mark the endpoint+model as tokenize- capable and use the actual count thereafter. If it 404s or errors, mark the slot as tokenize_supported = false and fall through to char/4 silently. Cached per (endpoint, model) for the session.

2. broker.token_count(model_cfg, text) — thin wrapper that returns an accurate token count when the (endpoint, model) is tokenize-capable, else the char/4 heuristic. Always returns a non-negative integer; never errors. The probe + fallback is transparent to callers.

3. Context:estimate_tokens() widening — currently char/4 over system_prompt + sum of turn.contents. The new shape accepts an optional tokenize_fn (callback) at Context.new time and uses it when present; falls back to char/4 when nil. repl.lua wires tokenize_fn = function(text) return broker.token_count(active_cfg, text) end. This means the active model's tokenizer is used for budgeting decisions, which matches the broker the next ask_ai will hit.

4. :cost detail estimated-vs-actual column — for each (model, category) slot in the accumulator, the actual prompt_tokens from broker usage is already stored. Add an estimated column computed via broker.token_count on the currently-buffered prompt-shape. Disagreement >10% surfaces in a tiny ~est=N annotation so users can see when the heuristic diverges from reality. Display-only; no behavior change.

5. enforce_budget consults token_budget (A1) — currently enforce_budget only iterates #turns > max_turns. Extend to ALSO check estimate_tokens() > token_budget. Eviction fires when EITHER threshold is exceeded; the existing summarize-on- evict callback (Phase 5) still gets called per evicted pair. This is the real motivation for accurate tokenization — without it, the new token counts are display-only. Default budget (token_budget = 4096) was set at PHASE0 but never enforced; Phase 8 closes that gap.

Phase 8 is done when:

• A long-running session with the local qwen-coder-7b-snappy-8k model evicts at the RIGHT moment (token_budget=4096 hit triggers eviction via the new pillar 5 path) rather than only when max_turns is exceeded.
• broker.token_count(local_cfg, "hello world") returns 2 (matches the live tokenize result, not the char/4=2 coincidence — verify via :cost detail against multi-paragraph text).
• broker.token_count(cloud_cfg, "hello world") returns 2 (char/4 fallback when /tokenize 404s, which it does for OpenRouter).
• Cached per-endpoint capability — the probe fires once per endpoint per session, not per call.
• Existing configs without cfg.tokenize behave like Phase 7 (zero behavior change unless opted in via cfg.tokenize.use_endpoint = true).
• :cost detail shows estimated-vs-actual where disagreement >10%, silent otherwise.

---

2. Technology Decisions (delta from Phase 7)

Decision	Choice	Rationale
Tokenize endpoint path	<endpoint>/tokenize (NOT <endpoint>/v1/tokenize)	Per real probe against hossenfelder: /v1/tokenize returns 404; /tokenize returns {tokens: [...]}. This is the llama.cpp server convention.
Request body shape	{"content": "<text>", "model": "<model>"}	Local model echoed via model; llama.cpp ignores it but harmless. Probed shape works.
Capability detection	Per-call optimistic probe; on 404/non-200, cache tokenize_supported[endpoint][model] = false and never retry that session	One round-trip cost on first miss; zero on subsequent. Sessions are short enough that re-probe across restarts is fine.
Fallback heuristic	char/4 (Phase 0 §8 convention)	Established; underestimates ~10% on real code/prose per baseline B1, but acceptable when no better signal available.
Context:estimate_tokens calling convention	Optional tokenize_fn callback at Context.new; absent = char/4 (existing behavior)	Backward-compatible; no caller break. Opt-in via repl.lua.
Active-model tokenizer	repl.lua wires tokenize_fn against active_cfg (the currently active model), so eviction decisions match the broker the next call will hit	When the user :model cloud switches mid-session, subsequent estimates use cloud's tokenizer (which falls back to char/4 since OpenRouter has no /tokenize).
Caching strategy	Endpoint+model capability flag only; NOT per-text token-count cache	Token counts depend on text content; caching adds memory + correctness risk for marginal speed. Probe latency dominates only on first call per endpoint.
Per-text timeout cap	2s for tokenize calls (much tighter than the model's normal timeout_ms)	Tokenize is a small, fast operation; if it doesn't respond in 2s, the endpoint is misbehaving. Bail to char/4.
:cost detail est-vs-actual	Show only when disagreement >10%; format (prompt: 558 ~est=508 / completion: 80) for the disagreement case, (prompt: 558 / completion: 80) otherwise	Always-on noise; suppress when heuristic is close.
New config key	cfg.tokenize = { use_endpoint = true } — default false until user opts in	Network round-trip cost; user-acknowledged behavior change.

---

3. Module Changes

File	State after Phase 7	Phase 8 changes
broker.lua	chat, chat_stream, build_request (opts-widened in Phase 7)	New M.token_count(model_cfg, text): tries <endpoint>/tokenize once per (endpoint, model); caches capability; returns int. New M.tokenize_supported(model_cfg) introspection helper for tests.
context.lua	estimate_tokens() char/4 sum over system_prompt + turn.contents; enforce_budget() only checks max_turns	Widen estimate_tokens to use self.tokenize_fn(text) if present; else char/4. Per-turn _tokens cache on each turn dict; lazy-set on first count. Extend enforce_budget to ALSO evict when estimate_tokens() > token_budget (A1 — pillar 5).
repl.lua	wires Context.new with summarize_fn, hosts all metas	tokenize_fn wired into Context.new when cfg.tokenize.use_endpoint = true. :cost detail extended with est-vs-actual column.
config.lua	Phase 7 cost block example	Add commented-out tokenize = { use_endpoint = true } block.
docs/PHASE0.md	§11 lists phases 0-7	Amendment: add Phase 8 row to §11.

No new module files.

---

4. Pillar 1+2 — broker.token_count(model_cfg, text)

-- Per-endpoint capability cache (session-scoped local in broker.lua)
local _tokenize_capable = {}    -- [endpoint .. "/" .. model] = true | false

local function _cache_key(model_cfg)
    return (model_cfg.endpoint or "") .. "/" .. (model_cfg.model or "")
end

function M.token_count(model_cfg, text)
    text = text or ""
    if text == "" then return 0 end
    if not (model_cfg and model_cfg.endpoint) then
        return math.floor(#text / 4)   -- pure fallback
    end
    local key = _cache_key(model_cfg)
    local cap = _tokenize_capable[key]
    if cap == false then
        return math.floor(#text / 4)
    end
    -- cap == nil OR cap == true; try the endpoint.
    local url = model_cfg.endpoint:gsub("/+$", "") .. "/tokenize"
    local body = json.encode({ content = text, model = model_cfg.model })
    local out, status = curl.post(url, body,
        { "Content-Type: application/json" },
        2000)  -- 2s timeout
    if not (status == 200 and out) then
        _tokenize_capable[key] = false
        return math.floor(#text / 4)
    end
    local doc = json.decode(out)
    local toks = doc and doc.tokens
    if type(toks) ~= "table" then
        _tokenize_capable[key] = false
        return math.floor(#text / 4)
    end
    _tokenize_capable[key] = true
    return #toks
end

function M.tokenize_supported(model_cfg)
    if not model_cfg then return nil end
    return _tokenize_capable[_cache_key(model_cfg)]
end

Uses Phase 1's ffi/curl.M.post (blocking POST, returns body + status).

---

5. Pillar 3 — Context:estimate_tokens widening

function M.new(opts)
    ...
    return setmetatable({
        ...
        -- Phase 8: optional callback that returns an accurate token
        -- count for a given text. Set by repl.lua when cfg.tokenize.
        -- use_endpoint=true, calling broker.token_count(active_cfg, ...).
        -- nil = char/4 fallback (Phase 0 §8 behavior).
        tokenize_fn          = opts.tokenize_fn,
    }, Context)
end

function Context:estimate_tokens()
    if self.tokenize_fn then
        local n = self.tokenize_fn(self.system_prompt)
        for _, t in ipairs(self.turns) do
            n = n + self.tokenize_fn(t.content)
        end
        return n
    end
    -- char/4 fallback (existing behavior)
    local n = #self.system_prompt
    for _, t in ipairs(self.turns) do n = n + #t.content end
    return math.floor(n / 4)
end

Performance note: with N turns of average ~500 chars each, estimate_tokens fires N tokenize round-trips. For N=40 turns × 50ms = 2s — too slow for per-prompt eviction checks. Mitigation: per-turn token count cached ON the turn dict (turn._tokens) the first time it's counted; only re-tokenized if turn._tokens is nil. Set at append time when tokenize_fn is present; otherwise lazily on first estimate.

---

6. Pillar 4 — :cost detail est-vs-actual

Current :cost detail (Phase 7) shows:

  anthropic/claude-haiku-4.5 main                 1 calls,    179 /      8 tokens, $0.000219

The 179 / 8 is prompt_tokens / completion_tokens from the actual broker usage payload.

Phase 8 extension: for each slot, also compute an estimated count via broker.token_count(model_cfg_for_this_slot, ...) over the TURNS THAT CONTRIBUTED to this slot. But that's stateful and expensive — simpler: show the SUM of prompt_tokens (actual) and the SUM of estimate_tokens() (heuristic OR endpoint-based, depending on what tokenize_fn is wired). If disagreement >10%, annotate.

Simplified format:

  anthropic/claude-haiku-4.5 main                 1 calls,    179 ~est=164 / 8 tokens, $0.000219
                                                                    ^^^^^^^^^^ shown when |actual-est|/actual > 0.10

The ~est=N annotation only renders when the disagreement exceeds the 10% threshold. Silent otherwise.

---

7. UX Surface Summary

Meta	Behavior change
:cost detail	Adds ~est=N annotation per slot when heuristic disagreement >10%
(no new metas in v1)

Config	Default	Effect
cfg.tokenize.use_endpoint	false	When true, repl.lua wires tokenize_fn so context budgeting uses real token counts

The cfg.tokenize block being opt-in is conservative: enabling it means every Context:estimate_tokens() call may hit the broker. For local llama.cpp the cost is ~50ms; for cloud-only configurations there IS no /tokenize endpoint so we silently fall through to char/4 (cached after one probe). No surprise; document in config example.

---

8. Out of Scope (Phase 8)

• Cost preflight enforcement — option 2 of the Phase 7 §12 candidates. The tokenize work here is a PREREQUISITE for accurate preflight cost estimation, but the enforcement layer itself (cap_at_dollars that REFUSES the call) is its own surface — defer to a separate phase.
• Cross-session cost rollup — option 1 of Phase 7 §12 candidates. Independent of tokenization.
• Streaming tokenize — some servers expose streaming tokenize endpoints for partial-prompt token counts during generation. Out of scope here; we use the blocking /tokenize for batch estimates.
• Multi-tokenizer support (e.g. tiktoken for OpenAI compat, sentencepiece for HuggingFace) — would require vendoring a C library (violates PHASE0 §3) or shelling out to python. Endpoint-based is the only substrate-compliant option for accuracy beyond char/4.
• Tokenization for :cost detail rows that span multiple turns — the actual prompt_tokens in the accumulator slot is the sum ACROSS calls; the estimate for comparison should be over the CURRENT ctx content. Show the per-call comparison only.

---

9. Risks

Risk	Mitigation
/tokenize 404 silently cached as tokenize_supported = false for a typo'd endpoint config	Per-session cache; restart re-probes. Acceptable.
Tokenize round-trip on every prompt eviction check adds 50ms × N turns latency	turn._tokens per-turn cache set at append-time; only re-tokenize on cache miss.
Hossenfelder proxy may forward /tokenize differently than direct llama.cpp (e.g., adds /v1/ prefix expected)	B1 confirms /tokenize works against hossenfelder; other proxies untested but the design degrades gracefully (char/4 fallback).
Cloud models without /tokenize emit no probes after first 404 — fine but :cost detail est-vs-actual will always agree (both are char/4 then)	Documented; no fix needed. Display annotation hides when est=actual exactly OR within 10%.
Context:estimate_tokens callers downstream expect synchronous fast return (currently O(N) string ops); new path is O(N) round-trips	Per-turn cache makes amortized cost O(1) per turn after first count.
Endpoint URL handling — currently endpoint .. "/v1/chat/completions" is hardcoded; tokenize uses endpoint .. "/tokenize" (no /v1) — asymmetric	Document the asymmetry inline; the llama.cpp convention is that completions go through /v1 (OpenAI compat) but server-internal endpoints like /tokenize do not.
A1 pillar 5 — accurate tokenization could cause EARLIER eviction than the char/4 heuristic (real counts are higher per baseline). User session that fit in 4096 tokens under char/4 may now spill.	Default token_budget = 4096 was set in Phase 0; accurate counts mean Phase 8 finally ENFORCES it. Users on cfg.context.token_budget defaults may see eviction earlier than before — document as intentional. Users can raise token_budget per their model's real context window.

---

10. Open Questions (Phase 8)

#	Question	Impact	Resolution target
Q-T1	Per-turn _tokens cache across :reset	A4 — dies with turns; new turns get nil and lazy-set on first count. Trivial.
Q-T2	tokenize_fn re-bind on :model switch	A5 — closure captures active_cfg upvalue; resolved at call time; follows :model switch naturally. No explicit re-binding needed.
Q-T3	Probe respects opt-out	A6 — when cfg.tokenize.use_endpoint = false, repl.lua doesn't wire tokenize_fn; context.lua's nil branch takes the char/4 fallback. No probe call at all.
Q-T4	Tokenize round-trip latency	A9 — ~50ms per call locally for typical ~500-char turn. With per-turn cache, amortized O(1) per turn after first count.
Q-T5	/tokenize honors model field	Baseline (not yet probed in detail — assumed yes since llama.cpp echoes model in completions; needs explicit multi-model probe).
Q-T6	tools-schema tokens	A7 — deferred to follow-up. Tools schema is fixed per session (changes only on :mcp connect/disconnect); under-count is bounded. v1 counts messages only.

---

11. Phase 8 → Phase 9+ Out-of-band

Candidate follow-ups (non-binding):

• Phase 9: cost preflight enforcement (Phase 7 §12 option 2) — uses Phase 8's accurate token counts to refuse calls that would cross cap_at_dollars. The accuracy work here is the foundation.
• Cross-session cost rollup (Phase 7 §12 option 1) — independent; could land in parallel.
• Phase X: project-local config overlay (.aish.lua) — was the alternative scope to Phase 7's cost work. Still valuable but independent of any current line.

Phase 8 itself is self-contained — no upstream dependencies.