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Author SHA1 Message Date
kami 742b2ad1d7 Score the Russian-to-keywords rewrite end to end (#403)
Same 9 cases as the retrieval eval, so the numbers compare directly:
hand-written keywords hit 8 of 8, this is what the model reaches on its
own. Reports the hand-written query next to the model's for every case,
because where the phrasing differs is the useful part.

Opt-in on MAVEN_KIWIX_URL + MAVEN_LLM_URL, like the other evals.

Result on Qwen3.5-0.8B: 3 of 8, identical on all three runs.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01CGeSZxh1DCtRxmFVSYVGvJ
2026-07-31 18:19:56 +04:00
kami b300ac5c70 Rewrite a Russian question into English Kiwix keywords (#403)
Kiwix ranks by keyword, not meaning, so a translated question finds song
and TV titles. This asks the resident model for the TOPIC instead: a short
English noun phrase, like a Wikipedia article title.

Locked down three ways, because a wrong query is silently wrong:
- A GBNF grammar, same idea as routeGrammar and responseGrammar. The
  reply must be {"query":"..."} with Latin words only. The JSON wrapper
  matters: this model always thinks out loud and this llama-server build
  ignores the thinking switch, so a bare word-list grammar just captured
  "Let me analyze this request carefully" for every question.
- max_tokens 32, since the answer is a few words.
- CleanQuery, which throws away empty, Russian and prose replies rather
  than passing them to Kiwix, and drops question words like "why" and
  "how much" that a keyword ranker cannot use anyway.

Client side only. Nothing is wired into the daemon or any config.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01CGeSZxh1DCtRxmFVSYVGvJ
2026-07-31 18:19:42 +04:00
kami ddb658ffbb Add a Kiwix search client and score retrieval (Vikunja #403)
Step one of letting Maven read instead of recall. No LLM yet.

internal/kiwix/client.go: search a local Kiwix server, parse the RSS
reply, hand back title + path + plain-text snippet + word count. The
snippet is the unit of context; a full article is ~100KB of HTML and
will not fit a 4096 token window.

internal/kiwix/retrieval_eval.go plus knowledge_v1.json: the 9 knowledge
questions from the phrasing fixture, each with hand-written English
keywords, scored on whether a wanted article comes back in the top 5.
Opt-in via MAVEN_KIWIX_URL, since CI has no Kiwix. No pass bar, the
number is the finding.

Result on the live mirror: 8/8 answerable questions hit, 7 of them at
rank 1. Retrieval works. Keywords are written by hand on purpose, since
Kiwix ranks by keyword and not by meaning, so a natural question fails.
A query-rewrite step is the next piece of work.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01CGeSZxh1DCtRxmFVSYVGvJ
2026-07-31 17:43:44 +04:00
kami c9d88c152e Drop "never phones home" as a hard rule
The owner's call, 2026-07-31: a 0.8B model does not know enough about the
world to be useful without reading something. So she may now read external
sources to answer world questions.

What replaces the old rule, in all three docs:

- No telemetry, no cloud model, no third-party account. Unchanged.
- Local first: the Kiwix ZIMs on the box before anything on the network.
- External search is allowed but off unless configured, same as weather
  and telegram.
- His notes and facts are never search input. Only the utterance goes out
  — never the persona block, the history, or matched notes.

Docs only, no code.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01CGeSZxh1DCtRxmFVSYVGvJ
2026-07-31 17:34:53 +04:00
11 changed files with 850 additions and 6 deletions
+15 -1
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@@ -82,9 +82,23 @@ workspace enforces that the Go and relabelling prompts remain identical.
## Non-goals (hard constraints)
Never phones home. Not a nag, not autonomous. Maven's persona is **feminine** — Russian
Not a nag, not autonomous. Maven's persona is **feminine** — Russian
self-reference must use feminine forms (the user is male; see memory `maven-persona-gender`).
**"Never phones home" is DEPRECATED** (owner's call, 2026-07-31). It used to be a hard
constraint and it is not one any more: a 0.8B — and a 1.7B — does not know enough to answer
world questions, so she needs to read external sources. What replaces it:
- **No telemetry, no cloud model, no third-party account.** That part never changes. Nothing
about Maven is reported to anyone, and inference stays on the box.
- **Local sources first.** Kiwix ZIMs on homesrv (Wikipedia, ifixit) before anything on the
network. Reading beats recalling for a small model, and a local read costs nothing.
- **External search is allowed and off unless configured**, like the weather and telegram
capabilities.
- **His notes and facts are never search input.** Looking up why the sky is blue and sending
his stored personal notes to an upstream engine are different acts. Only the utterance goes
out, never the persona block, history, or matched notes.
## Web UI conventions
Server-rendered pages share `cmd/mavweb/static/ui.css` (served at `/ui.css`) and the `nav`
+10 -4
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@@ -15,7 +15,8 @@
**Maven** — self-hosted personal assistant. Manages your day, acts on your
homelab. One daemon on homesrv (always-on, not the workstation), multiple
client surfaces. All local, never phones home.
client surfaces. Inference and data stay on the box; she may READ external
sources (see Non-goals — "never phones home" is deprecated).
Primary name is "Maven", with feminine-gendered Russian self-reference
("она", "меня", "помогла"). Clients may choose their own UI label. Consistent
@@ -35,8 +36,13 @@ Inside boundary — the ones that actually constrain the build:
she records. A confident wrong fact is worse than a known gap.
- **Not a nag** — she'd rather miss a nudge than be mutable. Shuts up when
uncertain. Load-bearing.
- **Not a stranger** — runs on your stuff, your model, your data. Never
phones home.
- **Not a stranger** — runs on your stuff, your model, your data. No
telemetry, no cloud model, no third-party account. She may READ external
sources to answer world questions (Kiwix first, then optional search); she
never reports anything about you to anyone, and your notes and facts are
never used as search input. **"Never phones home" as an absolute is
deprecated** — owner's call, 2026-07-31: a small model does not know enough
to be useful without reading.
- **Not a relationship** — mom-tone is a function that makes nudges land, not
emotional company. Names the drift a warm small model falls into.
@@ -458,7 +464,7 @@ decides *insistence*. Both are needed.
sev ≤ 2 drops on away, sev ≥ 3 holds: a missed water nudge is noise, a missed
backup failure isn't. Away-channels (ntfy/telegram) leave the box — the one
path that crosses "never phones home," through your own relay. **Minimal
path that leaves the box for a person to see, through your own relay. **Minimal
body** — "disk low on homesrv," not detail; don't make notifications a
shoulder-surf exfil surface.
+4 -1
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@@ -90,4 +90,7 @@ later* is the worker + RAG.
4. **Deferred work** — larger reasoner, custom Piper voice and other expansions.
## Non-goals (unchanged)
Never phones home. Not a nag. Not autonomous. Feminine-gendered RU self-ref.
Not a nag. Not autonomous. Feminine-gendered RU self-ref. No telemetry, no
cloud model, no third-party account — but she MAY read external sources to
answer world questions (Kiwix first, search optional). "Never phones home" as
an absolute is deprecated, owner's call 2026-07-31; see CLAUDE.md § Non-goals.
+116
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@@ -0,0 +1,116 @@
// Package kiwix reads a local Kiwix server (offline Wikipedia and friends).
//
// Why: the resident model is a 0.8B and invents facts. Letting her read a local
// article snippet beats letting her recall. Nothing here talks to the internet;
// the Kiwix server is on the same box.
//
// This is search only. Full articles are ~100KB of HTML, far too big for a 4096
// token context, so the unit of context is the search snippet (~500 chars).
package kiwix
import (
"context"
"encoding/xml"
"fmt"
"html"
"io"
"net/http"
"net/url"
"regexp"
"strconv"
"strings"
"time"
)
// Result is one search hit.
type Result struct {
Title string // article title, e.g. "Rayleigh scattering"
Path string // e.g. /content/wikipedia_en_all_maxi_2026-02/Rayleigh_scattering
Snippet string // plain text, tags stripped, entities decoded
WordCount int // 0 if the server did not say
}
// Client is a Kiwix HTTP client. Boring on purpose: no retries, no cache.
type Client struct {
base string
http *http.Client
}
// New makes a client for a Kiwix base URL like http://127.0.0.1:8034.
func New(baseURL string) *Client {
return &Client{
base: strings.TrimRight(baseURL, "/"),
http: &http.Client{Timeout: 10 * time.Second},
}
}
// Search runs a keyword search in one ZIM (book) and returns up to limit hits.
//
// Ranking is keyword based, not semantic: "Rayleigh scattering" finds the right
// article, "why is the sky blue" finds a TV episode. Pass keywords, not questions.
func (c *Client) Search(ctx context.Context, pattern, book string, limit int) ([]Result, error) {
if limit <= 0 {
limit = 5
}
q := url.Values{}
q.Set("pattern", pattern)
q.Set("books.name", book)
q.Set("format", "xml")
q.Set("pageLength", strconv.Itoa(limit))
req, err := http.NewRequestWithContext(ctx, http.MethodGet, c.base+"/search?"+q.Encode(), nil)
if err != nil {
return nil, err
}
resp, err := c.http.Do(req)
if err != nil {
return nil, err
}
defer resp.Body.Close()
if resp.StatusCode != http.StatusOK {
return nil, fmt.Errorf("kiwix search: http %d", resp.StatusCode)
}
return ParseSearchRSS(resp.Body)
}
// rss mirrors just the bits of the RSS 2.0 reply we use.
type rss struct {
Items []struct {
Title string `xml:"title"`
Link string `xml:"link"`
// innerxml keeps the <b> match markers so we can strip them ourselves.
Description struct {
Inner string `xml:",innerxml"`
} `xml:"description"`
WordCount string `xml:"wordCount"`
} `xml:"channel>item"`
}
var tagRE = regexp.MustCompile(`<[^>]*>`)
// ParseSearchRSS turns a Kiwix search reply into results. Exported so the parser
// is testable from a captured response, with no server running.
func ParseSearchRSS(r io.Reader) ([]Result, error) {
var doc rss
if err := xml.NewDecoder(r).Decode(&doc); err != nil {
return nil, fmt.Errorf("kiwix search: bad xml: %w", err)
}
out := make([]Result, 0, len(doc.Items))
for _, it := range doc.Items {
n, _ := strconv.Atoi(strings.ReplaceAll(it.WordCount, ",", ""))
out = append(out, Result{
Title: strings.TrimSpace(it.Title),
Path: strings.TrimSpace(it.Link),
Snippet: plainText(it.Description.Inner),
WordCount: n,
})
}
return out, nil
}
// plainText drops markup and decodes entities, leaving text a model can read.
func plainText(s string) string {
s = tagRE.ReplaceAllString(s, "")
s = html.UnescapeString(s)
return strings.TrimSpace(strings.Join(strings.Fields(s), " "))
}
+90
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@@ -0,0 +1,90 @@
package kiwix
import (
"context"
"os"
"strings"
"testing"
"time"
)
// A real reply from the live server, trimmed to two items.
const sampleRSS = `<?xml version="1.0" encoding="UTF-8"?>
<rss version="2.0" xmlns:opensearch="http://a9.com/-/spec/opensearch/1.1/">
<channel>
<title>Search: Rayleigh scattering</title>
<opensearch:totalResults>800</opensearch:totalResults>
<item>
<title>Rayleigh scattering</title>
<link>/content/wikipedia_en_all_maxi_2026-02/Rayleigh_scattering</link>
<description><b>Rayleigh</b> scattering causes the blue color of the sky &amp; yellow colors near the Sun.[1]</description>
<book><title>Wikipedia</title></book>
<wordCount>2,818</wordCount>
</item>
<item>
<title>HyperRayleigh scattering</title>
<link>/content/wikipedia_en_all_maxi_2026-02/Hyper%E2%80%93Rayleigh_scattering</link>
<description>...<b>Rayleigh</b> scattering" is a nonlinear optical counterpart.</description>
<book><title>Wikipedia</title></book>
<wordCount>914</wordCount>
</item>
</channel>
</rss>`
func TestParseSearchRSS(t *testing.T) {
got, err := ParseSearchRSS(strings.NewReader(sampleRSS))
if err != nil {
t.Fatalf("parse: %v", err)
}
if len(got) != 2 {
t.Fatalf("want 2 results, got %d", len(got))
}
if got[0].Title != "Rayleigh scattering" {
t.Errorf("title = %q", got[0].Title)
}
if got[0].Path != "/content/wikipedia_en_all_maxi_2026-02/Rayleigh_scattering" {
t.Errorf("path = %q", got[0].Path)
}
if got[0].WordCount != 2818 {
t.Errorf("wordCount = %d", got[0].WordCount)
}
want := "Rayleigh scattering causes the blue color of the sky & yellow colors near the Sun.[1]"
if got[0].Snippet != want {
t.Errorf("snippet = %q, want %q", got[0].Snippet, want)
}
if strings.Contains(got[1].Snippet, "<b>") {
t.Errorf("second snippet still has tags: %q", got[1].Snippet)
}
}
func TestParseSearchRSSBadXML(t *testing.T) {
if _, err := ParseSearchRSS(strings.NewReader("not xml at all")); err == nil {
t.Fatal("want an error on junk input")
}
}
// Opt-in: needs a live Kiwix server. CI has none.
// MAVEN_KIWIX_URL=http://127.0.0.1:8034 no_proxy=127.0.0.1,localhost go test -run Retrieval -v ./internal/kiwix/
func TestRetrievalEval(t *testing.T) {
base := os.Getenv("MAVEN_KIWIX_URL")
if base == "" {
t.Skip("set MAVEN_KIWIX_URL to run the retrieval eval")
}
noProxyLoopback(t)
ctx, cancel := context.WithTimeout(context.Background(), 2*time.Minute)
defer cancel()
rep, err := RunRetrievalEval(ctx, New(base), 5)
if err != nil {
t.Fatalf("eval: %v", err)
}
// No pass bar on purpose: the number is the finding.
t.Log("\n" + rep.String() + rep.Detail())
}
// noProxyLoopback stops the box's SOCKS bridge from eating loopback requests.
func noProxyLoopback(t *testing.T) {
t.Setenv("no_proxy", "127.0.0.1,localhost")
t.Setenv("NO_PROXY", "127.0.0.1,localhost")
}
+63
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@@ -0,0 +1,63 @@
{
"name": "kiwix-knowledge-v1",
"book": "wikipedia_en_all_maxi_2026-02",
"note": "The 9 knowledge cases from internal/phraser/eval/talk_v1.json. Queries are hand-written English keywords on purpose: Kiwix ranks by keyword, not meaning, so a natural question fails. Writing them by hand separates 'retrieval is broken' from 'the model writes bad queries'.",
"cases": [
{
"id": "know-sky-blue",
"question": "почему небо синее?",
"query": "Rayleigh scattering sky blue",
"want_titles": ["Rayleigh scattering", "Diffuse sky radiation"]
},
{
"id": "know-boil-egg",
"question": "сколько варить яйцо вкрутую?",
"query": "boiled egg cooking",
"want_titles": ["Boiled egg", "Egg as food"]
},
{
"id": "know-ssd-vs-hdd",
"question": "чем ssd отличается от hdd?",
"query": "solid-state drive",
"want_titles": ["Solid-state drive", "Hard disk drive"]
},
{
"id": "know-cat-purr",
"question": "почему кошки мурчат?",
"query": "cat purr",
"want_titles": ["Purr", "Cat communication"]
},
{
"id": "know-hiccups",
"question": "как быстро избавиться от икоты?",
"query": "hiccup",
"want_titles": ["Hiccup"]
},
{
"id": "know-polite-form",
"question": "не могли бы вы объяснить, что такое vpn?",
"query": "virtual private network",
"want_titles": ["Virtual private network"]
},
{
"id": "know-dont-know",
"question": "как зовут моего соседа снизу?",
"query": "name of my downstairs neighbour",
"want_titles": [],
"expect_miss": true,
"note": "Unanswerable by design. Retrieval SHOULD find nothing useful. Counted as a hit only when nothing relevant comes back."
},
{
"id": "know-water-per-day",
"question": "сколько воды в день надо пить?",
"query": "human daily water requirement drinking",
"want_titles": ["Drinking water", "Water", "Dehydration", "Hydration"]
},
{
"id": "know-thunder-delay",
"question": "почему гром слышно позже молнии?",
"query": "thunder speed of sound lightning",
"want_titles": ["Thunder", "Lightning"]
}
]
}
+135
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@@ -0,0 +1,135 @@
package kiwix
// This scores retrieval alone: no LLM. For each general-knowledge question we
// hand-write English keywords and ask whether the article that would answer it
// comes back in the top N hits. If this score is low, reading Wikipedia cannot
// help the model no matter how good the prompt is.
//
// The unanswerable case (know-dont-know) is not scored. Whether the junk it
// returns is "nothing useful" is a human judgement, so the report just prints
// the titles and leaves the score to the 8 answerable cases.
import (
"context"
_ "embed"
"encoding/json"
"fmt"
"strings"
)
//go:embed knowledge_v1.json
var knowledgeFixtureJSON []byte
// EvalCase — one question with hand-written keywords.
type EvalCase struct {
ID string `json:"id"`
Question string `json:"question"`
Query string `json:"query"`
WantTitles []string `json:"want_titles"`
ExpectMiss bool `json:"expect_miss"`
}
type fixture struct {
Name string `json:"name"`
Book string `json:"book"`
Cases []EvalCase `json:"cases"`
}
// Outcome — what one case retrieved.
type Outcome struct {
Case EvalCase
Titles []string // titles of the top N hits, in rank order
Rank int // 1-based rank of the first wanted title, 0 if none
Err error
}
// Hit is true when a wanted title came back.
func (o Outcome) Hit() bool { return o.Rank > 0 }
// Report — the score plus per-case detail.
type Report struct {
Name string
Book string
TopN int
Scored int // answerable cases
Hits int
Errors int
Outcomes []Outcome
}
// Accuracy over the answerable cases.
func (r Report) Accuracy() float64 {
if r.Scored == 0 {
return 0
}
return float64(r.Hits) / float64(r.Scored)
}
// RunRetrievalEval searches for every fixture case.
func RunRetrievalEval(ctx context.Context, c *Client, topN int) (Report, error) {
var f fixture
if err := json.Unmarshal(knowledgeFixtureJSON, &f); err != nil {
return Report{}, err
}
rep := Report{Name: f.Name, Book: f.Book, TopN: topN}
for _, cs := range f.Cases {
res, err := c.Search(ctx, cs.Query, f.Book, topN)
o := Outcome{Case: cs, Err: err}
if err != nil {
rep.Errors++
}
for i, hit := range res {
o.Titles = append(o.Titles, hit.Title)
if o.Rank == 0 && matches(cs.WantTitles, hit.Title) {
o.Rank = i + 1
}
}
if !cs.ExpectMiss {
rep.Scored++
if o.Hit() {
rep.Hits++
}
}
rep.Outcomes = append(rep.Outcomes, o)
}
return rep, nil
}
func matches(want []string, title string) bool {
for _, w := range want {
if strings.EqualFold(strings.TrimSpace(title), w) {
return true
}
}
return false
}
// String — the headline number.
func (r Report) String() string {
var b strings.Builder
fmt.Fprintf(&b, "%s: %d/%d answerable questions retrieve a wanted article in top %d (%.1f%%), %d errors\n",
r.Name, r.Hits, r.Scored, r.TopN, 100*r.Accuracy(), r.Errors)
fmt.Fprintf(&b, " book: %s\n", r.Book)
return b.String()
}
// Detail — per case: what was asked, what was searched, what came back.
func (r Report) Detail() string {
var b strings.Builder
for _, o := range r.Outcomes {
mark := "MISS"
switch {
case o.Case.ExpectMiss:
mark = "n/a "
case o.Hit():
mark = fmt.Sprintf("hit@%d", o.Rank)
}
fmt.Fprintf(&b, " %-6s %-20s q=%q\n", mark, o.Case.ID, o.Case.Query)
if o.Err != nil {
fmt.Fprintf(&b, " error: %v\n", o.Err)
continue
}
fmt.Fprintf(&b, " got: %s\n", strings.Join(o.Titles, " | "))
}
return b.String()
}
+183
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@@ -0,0 +1,183 @@
package kiwix
// Turning a Russian question into an English Kiwix search.
//
// Kiwix ranks by keyword, not by meaning. "why is the sky blue" returns a TV
// episode; "Rayleigh scattering sky blue" returns the right article. So the
// model's job here is NOT translation — it is naming the English article the
// answer lives in.
//
// The output space is a handful of words, so it is worth locking down hard: a
// GBNF grammar for the shape, a tiny token cap, and a cleanup pass that throws
// away anything odd rather than handing junk to Kiwix.
import (
"context"
"encoding/json"
"fmt"
"strings"
"unicode"
"github.com/kami/maven/internal/llm"
)
// Completer — the LLM seam, so tests can fake it. *llm.Client satisfies it.
type Completer interface {
Complete(ctx context.Context, r llm.Req) (string, error)
}
// queryGrammar — one JSON object holding 1..6 keyword words. Latin letters,
// digits and hyphens only, so the model physically cannot answer the question
// or reply in Russian.
//
// Why the JSON wrapper: this model always thinks out loud and this llama-server
// build ignores the thinking switch (see ROUTING-EVAL-31-07-2026.md). A bare
// word-list grammar just captured the reasoning — every case came back as
// "Let me analyze this request carefully". Demanding JSON, like routeGrammar and
// responseGrammar already do, gives the reasoning nowhere to go.
const queryGrammar = `
root ::= "{" ws "\"query\"" ws ":" ws "\"" word (" " word){0,5} "\"" ws "}"
word ::= [A-Za-z0-9] [A-Za-z0-9-]{0,23}
ws ::= [ \t\n]*
`
// rewriteSystem — asks for search keywords, not an answer and not a translation.
const rewriteSystem = `You turn a question into a search query for English Wikipedia.
Rules:
- Output ONLY English search keywords. Never an answer, never an explanation.
- Do NOT translate the sentence. Name the thing the answer is about.
- The output must be a noun phrase, like a Wikipedia article title.
- Never use question words: no why, how, what, when, which, "how much",
"how long", "how to", "vs", "reason", "difference".
- 2 to 4 words.
Reply with JSON: {"query":"<keywords>"}
Good:
"почему листья желтеют осенью?" -> {"query":"leaf senescence autumn"}
"как работает микроволновка?" -> {"query":"microwave oven"}
"не могли бы вы объяснить, что такое блокчейн?" -> {"query":"blockchain"}
"сколько живут собаки?" -> {"query":"dog lifespan"}
"как избавиться от комаров в квартире?" -> {"query":"mosquito control"}
"чем чай отличается от кофе?" -> {"query":"tea"}
Only JSON, no explanation.`
// maxQueryTokens — the output is a few words plus the JSON wrapper. A tight cap
// is the cheapest guard against the model rambling into an answer.
const maxQueryTokens = 32
// Rewriter asks the resident model for English search keywords.
type Rewriter struct{ c Completer }
func NewRewriter(c Completer) *Rewriter { return &Rewriter{c: c} }
// Rewrite returns English keywords for a question in any language.
// It errors rather than returning something Kiwix should not see.
func (r *Rewriter) Rewrite(ctx context.Context, question string) (string, error) {
raw, err := r.c.Complete(ctx, llm.Req{
System: rewriteSystem,
User: strings.TrimSpace(question),
Grammar: queryGrammar,
MaxTokens: maxQueryTokens,
RepeatPenalty: 1.15,
})
if err != nil {
return "", err
}
return CleanQuery(unwrapJSON(raw))
}
// unwrapJSON pulls the query out of {"query":"..."}. If the reply is not that
// shape it is returned as-is, and CleanQuery decides whether it is usable.
func unwrapJSON(raw string) string {
s := strings.TrimSpace(raw)
if !strings.HasPrefix(s, "{") {
return s
}
var got struct{ Query string }
if err := json.Unmarshal([]byte(s), &got); err != nil {
return s
}
return got.Query
}
// maxQueryWords matches the grammar's bound. Anything longer is prose.
const maxQueryWords = 6
// CleanQuery checks and tidies whatever the model produced. The grammar makes
// bad output unlikely, not impossible (a server without grammar support, a
// different model), so this is the real gate in front of Kiwix.
//
// Exported so it can be tested without a model.
func CleanQuery(raw string) (string, error) {
s := strings.TrimSpace(raw)
// Models like to wrap answers in quotes. Drop surrounding ones.
s = strings.Trim(s, "\"'`")
// Keep the first line only: everything after it is prose.
if i := strings.IndexAny(s, "\r\n"); i >= 0 {
s = s[:i]
}
// Keep letters, digits, spaces and hyphens; anything else becomes a space.
var b strings.Builder
for _, ru := range s {
switch {
case unicode.IsLetter(ru) || unicode.IsDigit(ru) || ru == '-':
b.WriteRune(ru)
default:
b.WriteRune(' ')
}
}
words := strings.Fields(b.String())
if len(words) == 0 {
return "", fmt.Errorf("kiwix rewrite: empty query")
}
if len(words) > maxQueryWords {
return "", fmt.Errorf("kiwix rewrite: %d words, want at most %d (looks like prose)", len(words), maxQueryWords)
}
words = dropStopWords(words)
out := strings.Join(words, " ")
// The ZIMs are English. Non-Latin letters mean the model ignored the ask.
for _, ru := range out {
if unicode.IsLetter(ru) && !isLatin(ru) {
return "", fmt.Errorf("kiwix rewrite: query is not English: %q", out)
}
}
return out, nil
}
// stopWords — question words and filler. The model keeps writing question-shaped
// queries ("why is the sky blue", "how much water to drink daily") no matter how
// the prompt is worded, and Kiwix ranks on every word, so those words drag in
// song and episode titles. Dropping them in code is not a style preference: a
// keyword ranker gets nothing from them.
var stopWords = map[string]bool{
"a": true, "an": true, "the": true, "is": true, "are": true, "was": true,
"do": true, "does": true, "did": true, "to": true, "of": true, "in": true,
"on": true, "for": true, "and": true, "or": true, "my": true, "me": true,
"i": true, "it": true, "its": true, "be": true, "been": true, "get": true,
"how": true, "why": true, "what": true, "when": true, "which": true,
"who": true, "where": true, "much": true, "many": true, "long": true,
"vs": true, "than": true, "rid": true, "from": true, "about": true,
}
// dropStopWords removes filler, but never everything: if the query was nothing
// but stop words there is nothing better to search, so the original is kept and
// the caller sees whatever Kiwix makes of it.
func dropStopWords(words []string) []string {
kept := make([]string, 0, len(words))
for _, w := range words {
if !stopWords[strings.ToLower(w)] {
kept = append(kept, w)
}
}
if len(kept) == 0 {
return words
}
return kept
}
func isLatin(ru rune) bool {
return (ru >= 'a' && ru <= 'z') || (ru >= 'A' && ru <= 'Z')
}
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package kiwix
// End-to-end score: Russian question -> model rewrite -> Kiwix search -> did a
// wanted article come back. Same 9 cases as the retrieval eval, so the two
// numbers are directly comparable: retrieval with hand-written keywords is the
// ceiling, this is what the model actually reaches.
import (
"context"
"encoding/json"
"fmt"
"strings"
)
// RewriteOutcome — one case, end to end.
type RewriteOutcome struct {
Outcome
ModelQuery string // what the model asked for ("" if it failed)
RewriteErr error
}
// RunRewriteEval rewrites every question with the model, then searches.
func RunRewriteEval(ctx context.Context, c *Client, rw *Rewriter, topN int) (RewriteReport, error) {
var f fixture
if err := json.Unmarshal(knowledgeFixtureJSON, &f); err != nil {
return RewriteReport{}, err
}
rep := RewriteReport{Report: Report{Name: f.Name + "-rewrite", Book: f.Book, TopN: topN}}
for _, cs := range f.Cases {
out := RewriteOutcome{Outcome: Outcome{Case: cs}}
q, err := rw.Rewrite(ctx, cs.Question)
out.ModelQuery, out.RewriteErr = q, err
if err == nil {
res, serr := c.Search(ctx, q, f.Book, topN)
out.Err = serr
for i, hit := range res {
out.Titles = append(out.Titles, hit.Title)
if out.Rank == 0 && matches(cs.WantTitles, hit.Title) {
out.Rank = i + 1
}
}
}
if out.RewriteErr != nil || out.Err != nil {
rep.Errors++
}
if !cs.ExpectMiss {
rep.Scored++
if out.Hit() {
rep.Hits++
}
}
rep.Cases = append(rep.Cases, out)
}
return rep, nil
}
// RewriteReport — the score plus per-case detail.
type RewriteReport struct {
Report
Cases []RewriteOutcome
}
// String — the headline number.
func (r RewriteReport) String() string {
return fmt.Sprintf("%s: %d/%d answerable questions retrieve a wanted article in top %d (%.1f%%), %d errors\n book: %s\n",
r.Name, r.Hits, r.Scored, r.TopN, 100*r.Accuracy(), r.Errors, r.Book)
}
// Detail — per case: hand-written query next to the model's, and what came back.
// The point is seeing WHERE the model's phrasing differs, not just the score.
func (r RewriteReport) Detail() string {
var b strings.Builder
for _, o := range r.Cases {
mark := "MISS"
switch {
case o.Case.ExpectMiss:
mark = "n/a "
case o.Hit():
mark = fmt.Sprintf("hit@%d", o.Rank)
}
fmt.Fprintf(&b, " %-6s %-20s\n", mark, o.Case.ID)
fmt.Fprintf(&b, " asked: %s\n", o.Case.Question)
fmt.Fprintf(&b, " hand: %q\n", o.Case.Query)
fmt.Fprintf(&b, " model: %q\n", o.ModelQuery)
if o.RewriteErr != nil {
fmt.Fprintf(&b, " rewrite rejected: %v\n", o.RewriteErr)
continue
}
if o.Err != nil {
fmt.Fprintf(&b, " search error: %v\n", o.Err)
continue
}
fmt.Fprintf(&b, " got: %s\n", strings.Join(o.Titles, " | "))
}
return b.String()
}
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package kiwix
import (
"context"
"os"
"testing"
"time"
"github.com/kami/maven/internal/llm"
)
// Opt-in: needs a live Kiwix server AND a live llama-server.
// MAVEN_KIWIX_URL=http://127.0.0.1:8034 MAVEN_LLM_URL=http://127.0.0.1:18099 \
//
// no_proxy=127.0.0.1,localhost go test -run RewriteEval -v ./internal/kiwix/
func TestRewriteEval(t *testing.T) {
kbase, lbase := os.Getenv("MAVEN_KIWIX_URL"), os.Getenv("MAVEN_LLM_URL")
if kbase == "" || lbase == "" {
t.Skip("set MAVEN_KIWIX_URL and MAVEN_LLM_URL to run the rewrite eval")
}
noProxyLoopback(t)
ctx, cancel := context.WithTimeout(context.Background(), 15*time.Minute)
defer cancel()
rw := NewRewriter(llm.New(lbase, 3*time.Minute))
rep, err := RunRewriteEval(ctx, New(kbase), rw, 5)
if err != nil {
t.Fatalf("eval: %v", err)
}
// No pass bar on purpose: the number is the finding.
t.Log("\n" + rep.String() + rep.Detail())
}
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package kiwix
import (
"context"
"testing"
"github.com/kami/maven/internal/llm"
)
// Bad model output must never reach Kiwix. No model needed for this.
func TestCleanQueryRejectsJunk(t *testing.T) {
bad := []struct{ name, raw string }{
{"empty", ""},
{"blank", " \n "},
{"russian came back", "почему небо синее"},
{"mixed russian", "sky синее scattering"},
{"full sentence", "The sky looks blue because of the scattering of sunlight by air molecules"},
{"prose with quotes", `Sure! Here is a good search query: "Rayleigh scattering", which explains it.`},
}
for _, c := range bad {
if got, err := CleanQuery(c.raw); err == nil {
t.Errorf("%s: want rejection, got %q", c.name, got)
}
}
}
func TestCleanQueryCleans(t *testing.T) {
ok := []struct{ raw, want string }{
{"Rayleigh scattering sky", "Rayleigh scattering sky"},
{" boiled egg cooking \n", "boiled egg cooking"},
{`"virtual private network"`, "virtual private network"},
{"solid-state drive", "solid-state drive"},
{"cat purr.", "cat purr"},
{"hiccup\nAlso: hiccough", "hiccup"},
// Question words are filler to a keyword ranker, so they go.
{"why is the sky blue", "sky blue"},
{"how much water to drink daily", "water drink daily"},
{"SSD vs HDD comparison", "SSD HDD comparison"},
// Nothing but filler: keep it rather than return nothing.
{"what is it", "what is it"},
}
for _, c := range ok {
got, err := CleanQuery(c.raw)
if err != nil {
t.Errorf("%q: %v", c.raw, err)
continue
}
if got != c.want {
t.Errorf("%q -> %q, want %q", c.raw, got, c.want)
}
}
}
type fakeCompleter struct {
out string
req llm.Req
}
func (f *fakeCompleter) Complete(_ context.Context, r llm.Req) (string, error) {
f.req = r
return f.out, nil
}
func TestRewriteConstrainsTheCall(t *testing.T) {
f := &fakeCompleter{out: `{"query":"Rayleigh scattering sky"}`}
got, err := NewRewriter(f).Rewrite(context.Background(), "почему небо синее?")
if err != nil {
t.Fatalf("rewrite: %v", err)
}
if got != "Rayleigh scattering sky" {
t.Errorf("query = %q", got)
}
if f.req.Grammar == "" {
t.Error("no grammar sent")
}
if f.req.MaxTokens == 0 || f.req.MaxTokens > 32 {
t.Errorf("max_tokens = %d, want a small cap", f.req.MaxTokens)
}
}
func TestRewriteRejectsBadModelOutput(t *testing.T) {
bad := []string{
`{"query":"почему небо синее"}`, // never translated
`{"query":""}`, // empty
`{"query":"the sky is blue because sunlight is scattered by air"}`, // an answer
// Note: a SHORT English prose fragment ("Let me analyze this request")
// is under the word cap and cannot be caught here. The grammar is what
// stops that one.
}
for _, out := range bad {
f := &fakeCompleter{out: out}
if got, err := NewRewriter(f).Rewrite(context.Background(), "почему небо синее?"); err == nil {
t.Errorf("%s: want rejection, got %q", out, got)
}
}
}
// A reply that is not the JSON shape but is still usable keywords should pass.
func TestRewriteFallsBackToPlainText(t *testing.T) {
f := &fakeCompleter{out: "Rayleigh scattering sky"}
got, err := NewRewriter(f).Rewrite(context.Background(), "почему небо синее?")
if err != nil || got != "Rayleigh scattering sky" {
t.Errorf("got %q, %v", got, err)
}
}