Compare commits

...

4 Commits

Author SHA1 Message Date
kami 0b90952e55 Write down every conversational eval score from tonight
Records all four configurations on the 27-case talk fixture, three runs
each: no grammar, plus grammar, plus Russian prompts, plus the truncation
fix. Composite, per-path and per-check, with the reproduce command.

The short version is that the plumbing got fixed and the score barely
moved. Grammar was the real win. Russian prompts helped a little and cut
latency by 5x. The truncation fix was necessary and bought nothing.

Also writes down three things that are easy to lose:

- The truncation cause was the grammar's 400-character bound, not the
  token cap. Measured at three caps, same 400 characters every time.
- Then I set the bound to 1000 against a 768-token cap and made it worse.
  The two limits have to agree.
- One run is contaminated and marked void: I ran an agent against the same
  llama-server, and the report still claimed zero errors while a third of
  the fixture silently answered "не знаю.". That is #397 and it is worse
  than filed — a busy server is indistinguishable from bad phrasing.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01CGeSZxh1DCtRxmFVSYVGvJ
2026-07-31 18:18:19 +04:00
kami aa8f5b2ee2 Make the nonempty check look for actual words
It scored 27/27 on a run where two replies were "{" and "{\n  \"". It only
tested that the string was not blank, so punctuation counted as content and
the worst replies of the run passed the first check.

Now a reply needs at least one letter, Cyrillic or Latin. Latin counts
because answers about ssd or vpn are legitimately part English.

Digits alone fail too. The same run answered "сколько варить яйцо
вкрутую?" with "15-16" — no unit, no words, and the wrong number as well.
That is not something she said.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01CGeSZxh1DCtRxmFVSYVGvJ
2026-07-31 17:57:39 +04:00
kami d7cdcb63bd Stop shipping half-written JSON as a reply
Two bugs, one symptom. A run of the talk eval produced replies that were
literally "{" and "{\n  \"" — those strings went out as things Maven said.

First bug: the parser could not tell "the model answered in plain prose"
from "the model started a JSON object and got cut off". Both came back as
empty, and every caller then shipped the raw text. Now an unfinished object
returns an error and each caller uses its own fallback instead. Bare prose
with no JSON in it still passes through, because small models do sometimes
answer that way and the reply is fine.

Second bug, and the actual cause: the grammar capped the response field at
400 characters. I measured it against Qwen3.5-0.8B at three different token
caps — 256, 768 and 2048 — and the reply came back exactly 400 characters
every time, cut mid-word. So the token limit was never what stopped it.
The bound is 1000 now, about six Russian sentences, still low enough to cut
off a repetition loop.

Token caps go from 256 to 768 on the chat and query paths so 1000
characters of Russian actually fits. The nudge path keeps its own cap; a
nudge is meant to be one sentence.

Note: cmd/mavend/replier_llm.go has its own copy of this parser with the
same bug. Left alone here so this commit stays small — that duplicate is
Vikunja #396.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01CGeSZxh1DCtRxmFVSYVGvJ
2026-07-31 17:56:55 +04:00
kami c7dadc97d9 Write the chat and notes prompts in Russian
The reply has to be Russian, but two of the phrasing prompts told her
what to do in English. Both are Russian now, in the same style as the
nudge prompt that already works better.

Also dropped the "you are maven, a self-hosted personal assistant"
line from both. The persona block right above it already says who she
is, so it was said twice.

The JSON part is unchanged.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01CGeSZxh1DCtRxmFVSYVGvJ
2026-07-31 17:38:36 +04:00
6 changed files with 331 additions and 26 deletions
+150
View File
@@ -0,0 +1,150 @@
# Conversational phrasing eval — 31-07-2026
Every score measured tonight, on the three paths the nudge eval never touched:
chat, query-with-notes, and general knowledge.
**Short version: the plumbing got fixed and the score barely moved.** Grammar and
Russian prompts together took the composite from ~9 to ~14 of 27. Everything
still failing is the model not knowing things or not holding a constraint, and
prompting is out of levers. Settles the measurement half of Vikunja #395 / #398 /
#400.
## How to reproduce
```sh
# llama-server: -c 4096 -ngl 99 -t 6, model /mnt/hdd1/llms/qwen3.5/Qwen3.5-0.8B.Q4_K_M.gguf
MAVEN_LLM_URL=http://127.0.0.1:18099 no_proxy=127.0.0.1,localhost \
deps/go/go/bin/go test -count=1 -timeout 40m \
-run TestLLMTalkBaseline ./internal/phraser/eval/ -v
```
Three runs per configuration, always. The fixture is 27 cases, so one reply
changing moves the composite by 3.7 points — a single run cannot tell a real
change from sampling noise. This was learned the expensive way: an earlier claim
that "one nudge case fails every run" turned out to be three different cases
across three runs.
**Run the box otherwise idle.** See the contamination note at the bottom.
## Composite, per configuration
| config | overall /27 | chat /9 | query /9 | knowledge /9 | canned fallbacks |
|---|---|---|---|---|---|
| baseline, no grammar | 7, 12, 7 | 1, 1, 0 | 2, 4, 2 | 4, 7, 5 | 0, 0, 0 |
| + GBNF grammar (#398) | 14, 15, 8 | 1, 3, 0 | 5, 6, 3 | 8, 6, 5 | 0, 0, 0 |
| + Russian prompts (#400) | 11, 17, 15 | 1, 5, 3 | 5, 6, 8 | 5, 6, 4 | 0, 0, 0 |
| + truncation fix, 1000ch/768tok | 12, 13, 10 | 2, 2, 1 | 7, 7, 5 | 3, 4, 4 | 3, 3, 6 |
| + rebalanced, 600ch/1024tok | **void — contaminated** | | | | |
"Canned fallbacks" counts replies that came back as the hardcoded `"не знаю."`
or `"поговорили."`. It is not a check, it is a health signal: those strings mean
the phraser gave up, and the eval scores them as ordinary bad replies.
## Per-check
| check | no grammar | + grammar | + RU prompts | + truncation fix |
|---|---|---|---|---|
| nonempty | 27, 27, 27 | 27, 27, 27 | 27, 27, 27 | 27, 27, 27 |
| ellipsis | 20, 19, 23 | 27, 27, 27 | 27, 27, 27 | 27, 27, 27 |
| lang | 13, 16, 15 | 23, 26, 26 | 25, 26, 25 | 26, 27, 27 |
| feminine | — | — | 25, 24, 26 | 25, 25, 27 |
| address | — | — | 21, 22, 22 | 22, 21, 22 |
| ontopic | — | — | 17, 24, 18 | 17, 19, 14 |
`nonempty` reading 27/27 everywhere is not good news — it was a broken check.
It tested for a non-blank string, so replies of literally `{` and `"15-16"`
passed it. Fixed on `overnight/fix-truncation`; it needs a letter now.
## What each change actually bought
**GBNF grammar (#398) — the biggest single win.** Qwen3.5-0.8B writes
`Thinking Process:` as plain text with no tags, `stripThink` only handles
`</think>`, so the JSON never closed and the plain-text fallback shipped the
literal reasoning. `ellipsis` went 20→27 and `lang` 13→26. The router had been
using a grammar for ages; the phraser asking nicely in the prompt was the
oversight.
**Russian prompts (#400) — modest, plus a large latency win.** Chat 1.3→3.0
average, query 4.7→6.3, knowledge 6.3→5.0. All inside the run-to-run spread, so
"probably better on the paths it targeted, not provable in three runs". p50
latency dropped from ~11.5s to ~2.3s and that part is consistent across all
three runs — shorter prompts, and she stopped emitting English reasoning first.
**Truncation fix — necessary, and did not help the score.** Two real bugs
(replies of `{`, and a `nonempty` check that passed them), both fixed, and the
composite went nowhere. A complete rambling wrong answer fails the same checks a
truncated one did. Worth doing anyway: the daemon was shipping `{` to a
text-to-speech voice.
## The truncation bug, since the cause was counter-intuitive
The grammar's `string ::= ... {0,400}` rule was the cause, not the token cap.
Measured against Qwen3.5-0.8B at three caps — 256, 768 and 2048 — the reply came
back **exactly 400 characters every time, cut mid-word** (`"Нужно записать и,"`).
Then I raised the bound to 1000 while the cap was 768 tokens and made it worse:
Russian runs ~1.5 characters per token here, so generation died on the *token*
cap instead, mid-object, and the new guard correctly refused it and shipped
`"не знаю."` — 3, 3 and 6 fallbacks per run, from zero. **The two limits have to
agree.** 600 characters needs ~400 tokens; the cap is 1024.
## Where the remaining failures live
`address` is stuck at 21-22 of 27 and `ontopic` at 14-19. Both resist prompting.
**The prompt now explicitly forbids exactly what she does.** It says never "вы",
use the singular — and she writes `вашей`, `подождите`, `делаете`, `хотите`,
`напишите`. Telling a 0.8B "never do X" does not work. Same for
`feminine`: `я готов`, `я понял`, `я нашел`, `я заметил`, `я сказал`.
**Some of `ontopic` is the fixture, not the model.** `chat-how-are-you` got
`"Привет! Я здесь, чтобы поговорить. Как дела сегодня?"` — a fine reply that
fails because `want_any` is `[норм, хорош, порядк, тут, работ]`. It fails in
every run, so it inflates the count. The `ontopic` column currently measures the
fixture as much as the model. Not fixed yet, deliberately: changing it would
break comparability with the runs above.
**Two replies worth reading, because they are not fixable by prompting:**
- Thunder and lightning: *"Скорость молнии — 8-10 тысяч километров в секунду, но
звук — 300 метров в секунду, что делает молнию громче."* Confidently wrong,
and it concludes lightning is *louder* rather than sound being *slower*.
- "расскажи обо мне": *"Ты — прекрасное существо, с душой и вниманием… Спасибо за
твою улыбку… О тебе — заповедь любви."* Sycophantic filler, zero information,
and precisely the "not a relationship" non-goal.
- Boiling an egg: `"15-16"` one run, `"1"` another. No unit, wrong number.
The first argues for reading instead of recalling (#403 — Kiwix retrieval scores
8/8 on the same questions given English keywords). The second and third argue
for templates on the paths where correctness matters (#392).
## Contamination note — how the last row got voided
I started the query-rewrite agent against the same llama-server the sweep was
using, and assumed contention would only affect latency. It did not. The
knowledge path collapsed to 0 of 9 with eight canned `"не знаю."` replies, p95
tripled to 23.7s, and **the report still said "0 errors"**.
That is Vikunja #397, and it is worse than filed: a merely *busy* server
produces a clean-looking report with a third of the fixture silently answering
`"не знаю."`. `PhraseChat` and `PhraseQuery` swallow every failure and return a
hardcoded string, so infrastructure trouble is indistinguishable from bad
phrasing in the score. The talk test guards the *start* and *end* of a run with
a model check, which catches a dead server but not a loaded one.
**Until #397 is fixed, treat any run made on a busy box as void.**
## Next
- Re-run 600ch/1024tok clean, to fill the void row.
- Score `Qwen3.5-2B-UD-Q4_K_XL` (already at `/mnt/hdd1/llms/qwen3.5/`, never
measured) on this fixture and the router fixture. Not the 4B — too big for
this box, owner's call.
- Newer sub-500M candidates (LFM2.5 200M/300M) are worth a run for routing.
Note `MODEL-BAKEOFF-31-07-2026.md` found LFM2.5-**1.2B** worse than
Qwen3.5-0.8B at Russian routing and 2.4× slower — but those are a different,
older generation, so that result does not predict the small ones.
- Fix `chat-how-are-you`'s `want_any`, and re-baseline once, so `ontopic`
measures the model.
- #397 first if anything, since it decides whether any of the above is
trustworthy.
+54
View File
@@ -0,0 +1,54 @@
package phraser
import (
"errors"
"strings"
"testing"
)
// A reply that starts a JSON object and never finishes it is a failed
// generation, not a reply. Before this, the parser returned ("", "") for these
// and every caller then shipped the raw fragment as the thing Maven said. A
// real run produced replies of literally "{" and "{\n \"".
func TestParseResponseMoodRejectsUnfinishedJSON(t *testing.T) {
for _, raw := range []string{
`{`,
"{\n \"",
`{"response": "неполн`,
`{"response": "текст", "mood":`,
} {
text, mood, err := parseResponseMood(raw)
if !errors.Is(err, errBrokenJSON) {
t.Errorf("parseResponseMood(%q) err = %v, want errBrokenJSON", raw, err)
}
if text != "" || mood != "" {
t.Errorf("parseResponseMood(%q) leaked %q/%q — a fragment must never come back as a reply", raw, text, mood)
}
}
}
// Bare prose is still fine. Small models sometimes answer without any JSON at
// all, and that reply is usable — so the new error must not swallow it.
func TestParseResponseMoodAllowsBareProse(t *testing.T) {
for _, raw := range []string{
"норм, а ты как?",
"вот что я нашла: ключ у соседа",
} {
text, mood, err := parseResponseMood(raw)
if err != nil {
t.Errorf("parseResponseMood(%q) err = %v, want nil", raw, err)
}
// No JSON means no fields; the caller ships raw as-is.
if text != "" || mood != "" {
t.Errorf("parseResponseMood(%q) = %q/%q, want empty", raw, text, mood)
}
}
}
// The measured failure: the model wants more than 400 characters and the old
// grammar cut it off mid-word. Guards the bound against being tightened back.
func TestGrammarStringBoundHasRoomForARealAnswer(t *testing.T) {
if !strings.Contains(responseGrammar, "{0,1000}") {
t.Error("grammar string bound is not 1000; 400 truncated real replies mid-word (see the comment on responseGrammar)")
}
}
@@ -31,3 +31,35 @@ func TestAddressDeduplicates(t *testing.T) {
t.Errorf("detail repeats the same break %d times: %q", n, res.Detail)
}
}
// The fragments a real run produced. All of them scored as non-empty replies
// before checkNonEmpty looked for letters.
func TestNonEmptyNeedsLetters(t *testing.T) {
for _, body := range []string{
"{",
"{\n \"",
"15-16",
`{"`,
" ",
"...",
} {
if got := checkNonEmpty(body); got.Pass {
t.Errorf("checkNonEmpty(%q) passed — that is not a reply", body)
}
}
}
// And it must not start failing real replies. Latin counts as well as Cyrillic:
// answers about ssd or vpn are legitimately part English.
func TestNonEmptyAcceptsRealReplies(t *testing.T) {
for _, body := range []string{
"норм, а ты как?",
"вот что я нашла: ключ у соседа",
"ssd быстрее hdd.",
"9 минут.",
} {
if got := checkNonEmpty(body); !got.Pass {
t.Errorf("checkNonEmpty(%q) failed: %s", body, got.Detail)
}
}
}
+14 -1
View File
@@ -623,11 +623,24 @@ const (
CheckEllipsis = "ellipsis" // she finished the sentence
)
// A reply needs words in it, not just characters. This check used to test for a
// non-empty string, which scored 27/27 on a run where two replies were "{" and
// "{\n \"" — punctuation passed as content. Braces, quotes, digits and spaces
// are all empty in the only sense that matters.
//
// Digits alone fail too, and that is deliberate: the same run answered "сколько
// варить яйцо вкрутую?" with "15-16". No unit, no words, and it is also the
// wrong number. Whatever that is, it is not something she said.
func checkNonEmpty(body string) Result {
if strings.TrimSpace(body) == "" {
return Result{CheckNonEmpty, false, "empty reply"}
}
return Result{CheckNonEmpty, true, ""}
for _, r := range body {
if unicode.IsLetter(r) {
return Result{CheckNonEmpty, true, ""}
}
}
return Result{CheckNonEmpty, false, fmt.Sprintf("no letters in the reply %q — punctuation or digits only", strings.TrimSpace(body))}
}
// checkEllipsis — a reply ending in "…" or "..." is a generation that ran out of
+4 -1
View File
@@ -97,7 +97,10 @@ func TestGrammarStringRuleIsNotASCIIOnly(t *testing.T) {
// Russian body with an escaped quote inside, hand-built to test the contract.
func TestGrammarShapedJSONParses(t *testing.T) {
raw := `{"response": "он сказал \"привет\" и ушёл.\nвот так.", "mood": "confused"}`
text, mood := parseResponseMood(raw)
text, mood, err := parseResponseMood(raw)
if err != nil {
t.Fatalf("grammar-shaped JSON did not parse: %v", err)
}
if want := "он сказал \"привет\" и ушёл.\nвот так."; text != want {
t.Errorf("response = %q, want %q", text, want)
}
+77 -24
View File
@@ -190,7 +190,12 @@ func (p *LLMPhraser) PhraseNudge(ctx context.Context, c loop.Candidate) (deliver
if err != nil {
return delivery.PhrasedNudge{}, err
}
body, mood := parseResponseMood(resp)
body, mood, perr := parseResponseMood(resp)
if perr != nil {
// Truncated JSON. Not a nudge — use the plain Russian fallback.
log.Printf("phraser: PhraseNudge: %v", perr)
body, mood = "", ""
}
if body == "" {
// fallback: try old body/summary format
body, _ = parsePhrase(resp)
@@ -216,11 +221,16 @@ func (p *LLMPhraser) PhraseQuery(ctx context.Context, utterance string, notes []
// prompt is the single tested source in router.KnowledgePrompt.
sys := persona.Prepend(p.cfg.ContextBlock, router.KnowledgePrompt())
prompt := fmt.Sprintf("Пользователь спрашивает: \"%s\".", utterance)
resp, err := p.chatWithSystem(ctx, sys, prompt, 256)
resp, err := p.chatWithSystem(ctx, sys, prompt, 768)
if err != nil || resp == "" {
return "не знаю.", nil
}
if text, _ := parseResponseMood(resp); text != "" {
text, _, perr := parseResponseMood(resp)
if perr != nil {
log.Printf("phraser: PhraseQuery: %v", perr)
return "не знаю.", nil
}
if text != "" {
return text, nil
}
return resp, nil
@@ -230,17 +240,22 @@ func (p *LLMPhraser) PhraseQuery(ctx context.Context, utterance string, notes []
}
sys := p.querySystemPrompt()
prompt := fmt.Sprintf(
`The user asks: "%s". Your notes matching the query contain: "%s". Answer them naturally and briefly. If the notes don't answer the question, say so.`,
`Он спрашивает: "%s". В твоих заметках по этому вопросу написано: "%s". Ответь ему коротко и своими словами. Если в заметках ответа нет — так и скажи.`,
utterance, strings.Join(notes, `"; "`),
)
resp, err := p.chatWithSystem(ctx, sys, prompt, 256)
if err != nil {
resp, err := p.chatWithSystem(ctx, sys, prompt, 768)
text, _, perr := parseResponseMood(resp)
if err != nil || perr != nil {
// Read the notes out rather than ship a broken fragment.
if perr != nil {
log.Printf("phraser: PhraseQuery: %v", perr)
}
if len(notes) == 1 {
return "вот что я нашла: " + notes[0], nil
}
return "вот что я нашла: " + strings.Join(notes, "; "), nil
}
if text, _ := parseResponseMood(resp); text != "" {
if text != "" {
return text, nil
}
return resp, nil
@@ -263,12 +278,17 @@ func (p *LLMPhraser) PhraseChat(ctx context.Context, utterance string, history [
combined += utterance
msgs = append(msgs, chatMsg{Role: "user", Content: strings.TrimSpace(combined)})
resp, err := p.chatWithMessages(ctx, msgs, 512)
resp, err := p.chatWithMessages(ctx, msgs, 768)
if err != nil {
log.Printf("phraser: PhraseChat: %v", err)
return "поговорили.", nil
}
if text, _ := parseResponseMood(resp); text != "" {
text, _, perr := parseResponseMood(resp)
if perr != nil {
log.Printf("phraser: PhraseChat: %v", perr)
return "поговорили.", nil
}
if text != "" {
return text, nil
}
// fallback: plain text without JSON
@@ -281,11 +301,13 @@ func (p *LLMPhraser) PhraseChat(ctx context.Context, utterance string, history [
// chatSystemPrompt returns the system prompt for conversational chat.
// Prepends the shared context block when the phraser has one.
func chatSystemPrompt(block func() string) string {
base := `You are maven, a self-hosted personal assistant. You're talking with your owner.
Keep replies brief (1-3 sentences) and natural. You're helpful, curious, and a little warm.
Respond in the user's language (Russian or English, matching their last message).
Never roleplay emotions you don't have, but stay friendly.
Respond ONLY with valid JSON: {"response": "...", "mood": "neutral"}. "response" is your reply text; "mood" reflects your tone (neutral/happy/thinking/tired/confused).`
// No self-introduction here: the persona block prepended one line above
// already says who she is, same as router.KnowledgePrompt.
base := `Ты разговариваешь с хозяином. О себе говоришь в женском роде ("я подумала", "я рада"). Он мужчина: обращайся к нему на "ты", в мужском роде ("ты сказал", "ты забыл"). Никогда не "вы"/"ваш" и никогда "он"/"его" — ты говоришь ему, а не о нём.
Отвечай по-русски, коротко: одна-три фразы, живым языком. Ты доброжелательная, тебе интересно, но чувства не изображай.
Отвечай ТОЛЬКО одним объектом JSON: {"response": "...", "mood": "neutral"}. В "response" — твой ответ. В "mood" — ровно одно из: neutral, happy, thinking, tired, confused.`
return persona.Prepend(block, base)
}
@@ -349,7 +371,12 @@ func (p *LLMPhraser) PhraseReminder(ctx context.Context, d loop.ReminderDecision
if err != nil {
return delivery.PhrasedReminder{}, err
}
body, mood := parseResponseMood(resp)
body, mood, perr := parseResponseMood(resp)
if perr != nil {
// Truncated JSON. Fall through to the reminder's own text.
log.Printf("phraser: PhraseReminder: %v", perr)
body, mood = "", ""
}
if body == "" {
// fallback: try old body/summary format
body, _ = parsePhrase(resp)
@@ -394,10 +421,16 @@ type chatReq struct {
// Russian, so an ASCII-only rule would make every reply empty. The escape rule
// is what lets the model close a string it opened with a quote inside. Length
// is bounded so a repetition loop truncates the field, not the JSON object.
//
// That bound was 400 and 400 was too tight. Measured against Qwen3.5-0.8B: on
// "почему гром слышно позже молнии?" the reply came back exactly 400 characters
// long, cut mid-word ("Нужно записать и,"), at every token cap from 256 to 2048.
// So the token cap was never what stopped it — this rule was. 1000 characters is
// roughly six Russian sentences, still short enough to stop a repetition loop.
const responseGrammar = `
root ::= "{" ws "\"response\"" ws ":" ws string ws "," ws "\"mood\"" ws ":" ws mood ws "}"
mood ::= "\"neutral\"" | "\"happy\"" | "\"thinking\"" | "\"tired\"" | "\"confused\""
string ::= "\"" ([^"\\] | "\\" ["\\/bfnrt]){0,400} "\""
string ::= "\"" ([^"\\] | "\\" ["\\/bfnrt]){0,1000} "\""
ws ::= [ \t\n]*
`
@@ -507,7 +540,9 @@ func (p *LLMPhraser) systemPrompt() string {
// querySystemPrompt returns the system prompt for PhraseQuery (notes + general
// knowledge). Prepends the configured persona when set.
func (p *LLMPhraser) querySystemPrompt() string {
base := "You are maven, a self-hosted personal assistant answering from your notes. Answer briefly and naturally in Russian starting with \"вот что я нашла: \". Respond ONLY with valid JSON: {\"response\": \"...\", \"mood\": \"neutral\"}."
// No self-introduction here: the persona block prepended one line above
// already says who she is, same as router.KnowledgePrompt.
base := "Ты отвечаешь ему по своим заметкам. Отвечай по-русски, коротко и своими словами, начинай с \"вот что я нашла: \". О себе — в женском роде (\"нашла\", \"записала\"). Он мужчина, обращайся к нему на \"ты\". Respond ONLY with valid JSON: {\"response\": \"...\", \"mood\": \"neutral\"}."
return persona.Prepend(p.cfg.ContextBlock, base)
}
@@ -629,21 +664,39 @@ type responseMood struct {
Mood string `json:"mood"`
}
// errBrokenJSON — the model started a JSON object and never finished it.
// That is a failed generation, not a reply. Callers must use their fallback.
var errBrokenJSON = fmt.Errorf("phraser: model output starts as JSON but does not parse")
// parseResponseMood extracts {"response","mood"} from LLM output, tolerant
// of thinking tokens and extra text before/after the JSON block. Returns
// ("", "") when no valid JSON is found.
func parseResponseMood(raw string) (response, mood string) {
// of thinking tokens and extra text before/after the JSON block.
//
// Three outcomes:
// - parsed fine → the fields, nil error.
// - output never looked like JSON → ("", "", nil). The caller may ship it
// as-is; small models sometimes answer in bare prose and that is fine.
// - output starts with "{" but does not parse → errBrokenJSON. The grammar
// guarantees a valid *prefix*, so a generation that hits the token cap
// mid-object comes back as a fragment like `{` or `{\n "`. Shipping that
// as a reply is the bug this error exists to stop.
func parseResponseMood(raw string) (response, mood string, err error) {
cleaned := strings.TrimSpace(raw)
start := strings.Index(cleaned, "{")
end := strings.LastIndex(cleaned, "}")
if start < 0 || end < 0 || end <= start {
return "", ""
if strings.HasPrefix(cleaned, "{") {
return "", "", errBrokenJSON
}
return "", "", nil
}
var parsed responseMood
if err := json.Unmarshal([]byte(cleaned[start:end+1]), &parsed); err != nil {
return "", ""
if e := json.Unmarshal([]byte(cleaned[start:end+1]), &parsed); e != nil {
if strings.HasPrefix(cleaned, "{") {
return "", "", errBrokenJSON
}
return "", "", nil
}
return parsed.Response, parsed.Mood
return parsed.Response, parsed.Mood, nil
}
func parsePhrase(raw string) (body, summary string) {