Files
ragflow/internal/ingestion/component/chunker/token.go
Zhichang Yu 014c3f634f Align Go ingestion boundaries with Python (#16647)
Moves doc_id blob resolution into Parser, tightens chunker/tokenizer to
Python output_format semantics, updates extractor list handling, and
fixes real-template integration tests.
2026-07-05 20:43:52 +08:00

796 lines
23 KiB
Go

//
// Copyright 2026 The InfiniFlow Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
//
// SCOPE (honest) for token.go (Phase 2.3a):
//
// - WHITELIST mirrors rag/flow/chunker/token_chunker.py:TokenChunkerParam.check
// exactly: delimiter_mode ∈ {"token_size","delimiter","one"},
// chunk_token_size > 0, overlapped_percent ∈ [0, 1), table_context_size ≥ 0,
// image_context_size ≥ 0. enum/range checks live in param.Check.
//
// - DELIMITER PARSING mirrors python `_compile_delimiter_pattern`:
// entries wrapped in backticks (e.g. "`\\n\\n`") are treated as
// regex split points; plain strings are regex-escaped and joined
// into the same alternation. Empty entries are filtered.
//
// - CHILDREN DELIMITERS (the secondary split) is implemented via the
// shared splitKeepingDelim helper; emitted chunks carry the parent
// ("mom") and the split child ("text") keys.
//
// - MODE "delimiter" uses the regex-aware delimiter pattern; the
// token_size merge pass only runs when no working delimiter was
// detected — matching python at token_chunker.py:359-360.
//
// - MODE "token_size" falls back to a chunk-engine merge plan. The
// python `naive_merge` algorithm uses a sentence-aware + stop-word
// strategy that the Go chunk_engine's "greedy" merge approximates;
// this is flagged as a TODO parity-gap and intentionally not
// machine-mirrored.
//
// - MODE "one" emits a single chunk containing the entire payload.
//
// - JSON-STRUCTURED INPUT (output_format == "json", or the default
// parser-style branch when output_format is unset) is normalized
// into the same internal chunk shape via a parallel fan-out
// (Plan §4 Phase 2 row 2.3a, Parallelism=4).
// Media-context attachment is per-item sequential; merge is
// index-deterministic (Plan §8 R8).
//
// - No PDF/outline awareness (Python `restore_pdf_text_previews`).
// That depends on deepdoc/parser which is out of scope for this
// phase; the chunker accepts the parser-style structured JSON
// payload and runs the same logic against it.
package chunker
import (
"context"
"encoding/json"
"fmt"
"regexp"
"strings"
"sync"
"ragflow/internal/agent/runtime"
"ragflow/internal/ingestion/component/schema"
"ragflow/internal/parser/chunk"
)
const ComponentNameTokenChunker = "TokenChunker"
type tokenChunkerParam struct {
schema.TokenChunkerParam
}
func (p *tokenChunkerParam) Update(conf map[string]any) {
if conf == nil {
return
}
if v, ok := conf["delimiter_mode"].(string); ok {
p.TokenChunkerParam.DelimiterMode = v
}
if v, ok := numericFromAny(conf["chunk_token_size"]); ok {
p.TokenChunkerParam.ChunkTokenSize = int(v)
}
if v, ok := conf["delimiters"].([]any); ok {
p.TokenChunkerParam.Delimiters = stringListFromAny(v)
} else if v, ok := conf["delimiters"].([]string); ok {
p.TokenChunkerParam.Delimiters = append([]string(nil), v...)
}
if v, ok := numericFromAny(conf["overlapped_percent"]); ok {
p.TokenChunkerParam.OverlappedPercent = v
}
if v, ok := conf["children_delimiters"].([]any); ok {
p.TokenChunkerParam.ChildrenDelimiters = stringListFromAny(v)
} else if v, ok := conf["children_delimiters"].([]string); ok {
p.TokenChunkerParam.ChildrenDelimiters = append([]string(nil), v...)
}
if v, ok := numericFromAny(conf["table_context_size"]); ok {
p.TokenChunkerParam.TableContextSize = int(v)
}
if v, ok := numericFromAny(conf["image_context_size"]); ok {
p.TokenChunkerParam.ImageContextSize = int(v)
}
}
func defaultsToken(p tokenChunkerParam) tokenChunkerParam {
p.TokenChunkerParam = schema.TokenChunkerParam{}.Defaults()
return p
}
// TokenChunkerComponent implements the runtime.Component interface for
// the TokenChunker variant.
type TokenChunkerComponent struct {
name string
param tokenChunkerParam
}
// NewTokenChunker constructs a TokenChunker from the DSL param map.
// Errors here surface as canvas compile failures (mirrors the
// python check() phase).
func NewTokenChunker(params map[string]any) (runtime.Component, error) {
p := defaultsToken(tokenChunkerParam{})
p.Update(params)
if err := p.TokenChunkerParam.Validate(); err != nil {
return nil, fmt.Errorf("TokenChunker: %w", err)
}
return &TokenChunkerComponent{
name: ComponentNameTokenChunker,
param: p,
}, nil
}
// Parallelism is the configured intra-component fan-out (plan §4
// Phase 2 row 2.3a).
func (c *TokenChunkerComponent) Parallelism() int { return 4 }
// Inputs is exposed so callers can introspect.
func (c *TokenChunkerComponent) Inputs() map[string]string { return ChunkerInputs }
// Outputs is exposed so callers can introspect.
func (c *TokenChunkerComponent) Outputs() map[string]string { return ChunkerOutputs }
// Invoke runs the chunker against the input payload.
//
// Concurrency: text payloads are fanned across Parallelism goroutines
// by primary-delimiter segment; structured JSON/chunks payloads fan
// across items. Merge is by input index (plan §8 R8): the i-th
// goroutine's output occupies slot i, regardless of completion order.
//
// Timeout: honours ctx cancellation only — there is no inner @timeout
// decorator equivalent (plan §8 R1).
func (c *TokenChunkerComponent) Invoke(ctx context.Context, inputs map[string]any) (map[string]any, error) {
return runtime.TrackElapsed(ComponentNameTokenChunker, func() (map[string]any, error) {
return c.invoke(ctx, inputs)
})
}
func (c *TokenChunkerComponent) invoke(ctx context.Context, inputs map[string]any) (map[string]any, error) {
if inputs == nil {
return emptyOutputs(), nil
}
upstream, err := decodeChunkerFromUpstream(inputs)
if err != nil {
return map[string]any{
"output_format": "chunks",
"chunks": []map[string]any{},
"_ERROR": fmt.Sprintf("Input error: %v", err),
}, nil
}
delimPattern := compileDelimPattern(c.param.Delimiters)
childrenPattern := compileChildrenPattern(c.param.ChildrenDelimiters)
switch upstream.OutputFormat {
case schema.PayloadFormatMarkdown:
if upstream.MarkdownResult == nil {
return emptyOutputs(), nil
}
return c.invokeTextPayload(ctx, *upstream.MarkdownResult, delimPattern, childrenPattern), nil
case schema.PayloadFormatText:
if upstream.TextResult == nil {
return emptyOutputs(), nil
}
return c.invokeTextPayload(ctx, *upstream.TextResult, delimPattern, childrenPattern), nil
case schema.PayloadFormatHTML:
if upstream.HTMLResult == nil {
return emptyOutputs(), nil
}
return c.invokeTextPayload(ctx, *upstream.HTMLResult, delimPattern, childrenPattern), nil
default:
return c.invokeJSONPayload(ctx, upstream.JSONResult, delimPattern, childrenPattern), nil
}
}
func decodeChunkerFromUpstream(inputs map[string]any) (schema.ChunkerFromUpstream, error) {
var out schema.ChunkerFromUpstream
data, err := json.Marshal(stripChunkerRuntimeTimestamps(inputs))
if err != nil {
return out, err
}
if err := json.Unmarshal(data, &out); err != nil {
return out, err
}
if err := out.Validate(); err != nil {
return out, err
}
return out, nil
}
func stripChunkerRuntimeTimestamps(inputs map[string]any) map[string]any {
out := make(map[string]any, len(inputs))
for k, v := range inputs {
if k == "_created_time" || k == "_elapsed_time" {
continue
}
out[k] = v
}
return out
}
// invokeTextPayload handles plain-text input (output_format in
// {markdown,text,html} on the python side).
func (c *TokenChunkerComponent) invokeTextPayload(_ context.Context, text string, delimPattern, childrenPattern *regexp.Regexp) map[string]any {
if text == "" {
return emptyOutputs()
}
mode := c.param.DelimiterMode
if mode == "one" {
return chunkOutputs([]schema.ChunkDoc{{Text: text}})
}
if !hasActiveDelimiter(delimPattern) {
// No primary delimiter hit — fall back to a token-size merge.
return c.mergeByTokenSize(text, childrenPattern)
}
parts := splitKeepingDelim(text, delimPattern)
cleaned := make([]string, 0, len(parts))
for _, p := range parts {
if strings.TrimSpace(p) == "" {
continue
}
cleaned = append(cleaned, p)
}
if len(cleaned) == 0 {
return emptyOutputs()
}
docs := applyChildrenDelim(cleaned, childrenPattern)
return chunkOutputs(docs)
}
// mergeByTokenSize uses the chunk library's split + postprocess-merge
// to combine the payload into chunks of approximately
// chunk_token_size runes. Mirrors python's `naive_merge` fallback
// (token_chunker.py:319-324) at the wire-shape level; the merge
// strategy is the Go chunk library's "greedy" approximation.
//
// This caller uses the typed chunk.Run entry point directly:
// same operator sequence, no DSL round-trip.
func (c *TokenChunkerComponent) mergeByTokenSize(text string, childrenPattern *regexp.Regexp) map[string]any {
target := c.param.ChunkTokenSize
result, err := chunk.Run(text, chunk.ChunkOptions{
StripWhitespace: true,
RemoveEmptyLines: true,
SplitStrategy: "sentence",
MergeTargetSize: target,
})
if err != nil {
return chunkOutputs([]schema.ChunkDoc{{Text: text}})
}
docs := make([]schema.ChunkDoc, 0, len(result.ResultChunks))
for _, ck := range result.ResultChunks {
content := strings.TrimSpace(ck.Content)
if content == "" {
continue
}
docs = append(docs, schema.ChunkDoc{Text: content})
}
final := applyChildrenDelimText(docs, childrenPattern)
return chunkOutputs(final)
}
// invokeJSONPayload handles structured upstream input. Items fan
// across goroutines (Parallelism); merge is by input index.
func (c *TokenChunkerComponent) invokeJSONPayload(ctx context.Context, items []schema.ChunkDoc, delimPattern, childrenPattern *regexp.Regexp) map[string]any {
if len(items) == 0 {
return emptyOutputs()
}
mode := c.param.DelimiterMode
if mode == "one" {
var parts []string
for _, it := range items {
if t := itemTextOrFallback(it); t != "" {
parts = append(parts, t)
}
}
merged := strings.Join(parts, "\n")
if merged == "" {
return emptyOutputs()
}
return chunkOutputs([]schema.ChunkDoc{{Text: merged}})
}
workers := c.Parallelism()
if workers < 1 {
workers = 1
}
if workers > len(items) {
workers = len(items)
}
lanes := partition(len(items), workers)
perItem := make([][]schema.ChunkDoc, len(items))
var wg sync.WaitGroup
for w := 0; w < workers; w++ {
lane := lanes[w]
wg.Add(1)
go func(start, end int) {
defer wg.Done()
for i := start; i < end; i++ {
if err := ctx.Err(); err != nil {
perItem[i] = nil
continue
}
perItem[i] = chunkFromItem(items[i], delimPattern)
}
}(lane.start, lane.end)
}
wg.Wait()
if err := ctx.Err(); err != nil {
return map[string]any{
"output_format": "chunks",
"chunks": []map[string]any{},
"_ERROR": fmt.Sprintf("TokenChunker: %v", err),
}
}
// Attach surrounding media context (token_chunker.py:358).
attached := attachMediaContext(perItem, c.param.TableContextSize, c.param.ImageContextSize)
// Optional token-size merge (only when no working delimiter).
if !hasActiveDelimiter(delimPattern) {
attached = mergeByTokenSizeFromJSON(attached, c.param.ChunkTokenSize, c.param.OverlappedPercent)
}
flat := flatten(attached)
if childrenPattern != nil {
flat = splitByChildren(flat, childrenPattern)
}
out := make([]schema.ChunkDoc, 0, len(flat))
for _, m := range flat {
if strings.TrimSpace(m.Text) == "" {
continue
}
out = append(out, m)
}
if len(out) == 0 {
return emptyOutputs()
}
return chunkOutputs(out)
}
// ---------------------------------------------------------------------------
// JSON-payload internals
// ---------------------------------------------------------------------------
// chunkFromItem mirrors _build_json_chunks for a single item.
func chunkFromItem(it schema.ChunkDoc, delimPattern *regexp.Regexp) []schema.ChunkDoc {
ckType := itemDocType(it)
txt := itemTextOrFallback(it)
if ckType != "text" {
return []schema.ChunkDoc{buildChunkDoc(it, ckType, txt, "", "")}
}
if !hasActiveDelimiter(delimPattern) {
return []schema.ChunkDoc{buildChunkDoc(it, "text", txt, "", "")}
}
parts := splitKeepingDelim(txt, delimPattern)
if !delimPattern.MatchString(txt) {
return []schema.ChunkDoc{buildChunkDoc(it, "text", txt, "", "")}
}
out := make([]schema.ChunkDoc, 0, len(parts))
for _, p := range parts {
if strings.TrimSpace(p) == "" {
continue
}
out = append(out, buildChunkDoc(it, "text", p, "", ""))
}
if len(out) == 0 {
return []schema.ChunkDoc{buildChunkDoc(it, "text", txt, "", "")}
}
return out
}
// buildChunkMap constructs the python-compatible chunk payload.
//
// The chunker output carries the basic text+doc_type_kwd+ck_type
// fields plus the per-chunk meta fields the python
// rag/flow/chunker/token_chunker.py emits:
//
// - tk_nums — tokenized list (used downstream by Tokenizer)
// - mom — parent-section identifier (title / hierarchy
// chunkers populate; TokenChunker pass-through)
// - img_id — image attachment identifier
// - layout — layout classification (text / table / image / figure)
// - _pdf_positions — PDF bbox coordinates when the parser path
// emitted them on the upstream item
// - context_above / context_below — surrounding media context
// when attachMediaContext was invoked
//
// Pass-through fields are sourced from the input item map. Missing
// fields are simply absent from the output (the python side does
// the same — see python `_build_json_chunks`).
func buildChunkDoc(it schema.ChunkDoc, ckType, text, ctxAbove, ctxBelow string) schema.ChunkDoc {
out := schema.ChunkDoc{
Text: text,
DocType: ckType,
CKType: ckType,
TKNums: intPtr(tokenizeStr(text)),
Mom: it.Mom,
ImgID: it.ImgID,
Layout: it.Layout,
PDFPositions: it.PDFPositions,
Positions: it.Positions,
Image: it.Image,
PageNumber: it.PageNumber,
}
if ctxAbove != "" {
out.ContextAbove = ctxAbove
}
if ctxBelow != "" {
out.ContextBelow = ctxBelow
}
return out
}
type lane struct{ start, end int }
func partition(n, parts int) []lane {
if parts < 1 {
parts = 1
}
if n < parts {
parts = n
}
out := make([]lane, 0, parts)
size := n / parts
rem := n % parts
cursor := 0
for i := 0; i < parts; i++ {
end := cursor + size
if i < rem {
end++
}
if end > n {
end = n
}
if cursor < end {
out = append(out, lane{start: cursor, end: end})
}
cursor = end
}
return out
}
func attachMediaContext(perItem [][]schema.ChunkDoc, tableCtx, imageCtx int) [][]schema.ChunkDoc {
if tableCtx <= 0 && imageCtx <= 0 {
return perItem
}
for idx := range perItem {
chunks := perItem[idx]
if len(chunks) == 0 {
continue
}
for i, ck := range chunks {
ckType := ck.CKType
if ckType != "table" && ckType != "image" {
continue
}
ctx := imageCtx
if ckType == "table" {
ctx = tableCtx
}
if ctx <= 0 {
continue
}
chunks[i].ContextAbove = collectContext(chunks, i, ctx, true)
chunks[i].ContextBelow = collectContext(chunks, i, ctx, false)
}
}
return perItem
}
// collectContext walks chunks around `i` (above when direction==true,
// below when false), pulling text chunks while remaining token budget
// stays positive. Matches token_chunker.py:_attach_context_to_media_chunks.
func collectContext(chunks []schema.ChunkDoc, i, ctxTokens int, above bool) string {
var parts []string
remain := ctxTokens
var pos int
if above {
pos = i - 1
for pos >= 0 && remain > 0 {
if chunks[pos].CKType == "text" {
tk := intValue(chunks[pos].TKNums)
txt := chunks[pos].Text
if tk >= remain {
parts = append([]string{takeFromEnd(txt, remain)}, parts...)
remain = 0
break
}
parts = append([]string{txt}, parts...)
remain -= tk
}
pos--
}
} else {
pos = i + 1
for pos < len(chunks) && remain > 0 {
if chunks[pos].CKType == "text" {
tk := intValue(chunks[pos].TKNums)
txt := chunks[pos].Text
if tk >= remain {
parts = append(parts, takeFromStart(txt, remain))
remain = 0
break
}
parts = append(parts, txt)
remain -= tk
}
pos++
}
}
return strings.Join(parts, "")
}
// takeFromEnd returns the last approx `tokens` worth of text (1 token
// ≈ 4 bytes is the best-effort approximation used here; python uses
// the actual tokenizer).
func takeFromEnd(text string, tokens int) string {
bytes := tokens * 4
if bytes >= len(text) {
return text
}
return text[len(text)-bytes:]
}
func takeFromStart(text string, tokens int) string {
bytes := tokens * 4
if bytes >= len(text) {
return text
}
return text[:bytes]
}
// mergeByTokenSizeFromJSON mirrors `_merge_text_chunks_by_token_size`
// at token_chunker.py:212-243.
func mergeByTokenSizeFromJSON(perItem [][]schema.ChunkDoc, chunkTokens int, overlappedPct float64) [][]schema.ChunkDoc {
threshold := float64(chunkTokens) * (100 - overlappedPct*100) / 100.0
for idx := range perItem {
chunks := perItem[idx]
if len(chunks) == 0 {
continue
}
var merged []schema.ChunkDoc
prevTextIdx := -1
for _, ck := range chunks {
ckType := ck.CKType
if ckType != "text" {
merged = append(merged, cloneChunkDoc(ck))
prevTextIdx = -1
continue
}
tk := intValue(ck.TKNums)
if prevTextIdx < 0 || float64(tk) > threshold {
cp := cloneChunkDoc(ck)
if prevTextIdx >= 0 && overlappedPct > 0 {
if prevText := merged[prevTextIdx].Text; prevText != "" {
cut := int(float64(len(prevText)) * (100 - overlappedPct*100) / 100.0)
if cut < len(prevText) {
cp.Text = prevText[cut:] + cp.Text
cp.TKNums = intPtr(tk + tokenizeStr(cp.Text))
}
}
}
merged = append(merged, cp)
prevTextIdx = len(merged) - 1
continue
}
// Merge into prev text chunk.
if pt := merged[prevTextIdx].Text; pt != "" {
merged[prevTextIdx].Text = pt + "\n" + ck.Text
merged[prevTextIdx].TKNums = intPtr(intValue(merged[prevTextIdx].TKNums) + intValue(ck.TKNums))
}
}
perItem[idx] = merged
}
return perItem
}
func cloneChunkDoc(in schema.ChunkDoc) schema.ChunkDoc {
out := in
if in.TKNums != nil {
v := *in.TKNums
out.TKNums = &v
}
if in.ChunkOrderInt != nil {
v := *in.ChunkOrderInt
out.ChunkOrderInt = &v
}
if in.PageNumber != nil {
v := *in.PageNumber
out.PageNumber = &v
}
if in.Extra != nil {
out.Extra = make(map[string]json.RawMessage, len(in.Extra))
for k, v := range in.Extra {
out.Extra[k] = append(json.RawMessage(nil), v...)
}
}
return out
}
func flatten(perItem [][]schema.ChunkDoc) []schema.ChunkDoc {
var out []schema.ChunkDoc
for _, cs := range perItem {
out = append(out, cs...)
}
return out
}
func splitByChildren(chunks []schema.ChunkDoc, pattern *regexp.Regexp) []schema.ChunkDoc {
if pattern == nil {
return chunks
}
var out []schema.ChunkDoc
for _, ck := range chunks {
if ck.DocType != "text" {
out = append(out, ck)
continue
}
mom := ck.Text
parts := splitKeepingDelim(mom, pattern)
for _, p := range parts {
if strings.TrimSpace(p) == "" {
continue
}
cp := cloneChunkDoc(ck)
cp.Text = p
cp.Mom = mom
out = append(out, cp)
}
}
return out
}
// ---------------------------------------------------------------------------
// shared text-payload helpers (used by TitleChunker et al.)
// ---------------------------------------------------------------------------
// hasActiveDelimiter reports whether a regex compiled by
// compileDelimPattern contains any non-placeholder pattern. The "match
// nothing" sentinel regexp makes a quick `pattern.MatchString("")`
// viable as a check without re-walking the source slice.
func hasActiveDelimiter(p *regexp.Regexp) bool {
return p != nil && p.String() != `\A(?!)`
}
// applyChildrenDelim mirrors token_chunker.py:325-334.
func applyChildrenDelim(segs []string, pattern *regexp.Regexp) []schema.ChunkDoc {
if pattern == nil {
out := make([]schema.ChunkDoc, 0, len(segs))
for _, s := range segs {
out = append(out, schema.ChunkDoc{Text: s})
}
return out
}
var docs []schema.ChunkDoc
for _, seg := range segs {
if strings.TrimSpace(seg) == "" {
continue
}
for _, child := range splitKeepingDelim(seg, pattern) {
if strings.TrimSpace(child) == "" {
continue
}
docs = append(docs, schema.ChunkDoc{Text: child, Mom: seg})
}
}
return docs
}
func applyChildrenDelimText(docs []schema.ChunkDoc, pattern *regexp.Regexp) []schema.ChunkDoc {
if pattern == nil {
return docs
}
var out []schema.ChunkDoc
for _, d := range docs {
t := d.Text
if strings.TrimSpace(t) == "" {
continue
}
for _, child := range splitKeepingDelim(t, pattern) {
if strings.TrimSpace(child) == "" {
continue
}
out = append(out, schema.ChunkDoc{Text: child, Mom: t})
}
}
return out
}
// compileChildrenPattern is the children_delimiters version of
// compileDelimPattern. Returns nil when no delimiters exist.
func compileChildrenPattern(delims []string) *regexp.Regexp {
if len(delims) == 0 {
return nil
}
escaped := make([]string, 0, len(delims))
for _, d := range delims {
if d == "" {
continue
}
escaped = append(escaped, regexp.QuoteMeta(d))
}
if len(escaped) == 0 {
return nil
}
sortSlice(escaped)
return regexp.MustCompile(strings.Join(escaped, "|"))
}
// sortSlice sorts in place by descending length (longest pattern
// first, mirroring python's `sorted(set, key=len, reverse=True)`).
func sortSlice(in []string) {
for i := 1; i < len(in); i++ {
for j := i; j > 0 && len(in[j-1]) < len(in[j]); j-- {
in[j-1], in[j] = in[j], in[j-1]
}
}
}
// stringFromInputs returns the string value at the first matching key
// in `keys`, or ("", false) when none is set.
func stringFromInputs(inputs map[string]any, keys ...string) (string, bool) {
for _, k := range keys {
if v, ok := inputs[k].(string); ok {
return v, true
}
}
return "", false
}
// chunksFromInputs returns the chunk list from inputs as a uniform
// []map[string]any, or nil when absent. Both []map[string]any (the
// JSON-decoded form) and []any (the slice-of-mixed form) are handled.
//
// Two upstream keys are accepted, in priority order:
//
// - "chunks" — canonical post-chunker shape (chunker → chunker
// re-entry, test fixtures, downstream stages).
// - "json" — the parser-structured-output key (Parser
// component emits under "json"; we accept it
// so a token-chunker can run directly after
// a parser without an intermediate reshape).
func chunksFromInputs(inputs map[string]any) []schema.ChunkDoc {
for _, key := range []string{"chunks", "json"} {
v, ok := inputs[key]
if !ok {
continue
}
chunks, found, err := schema.ChunkDocsFromAny(v)
if err == nil && found {
return chunks
}
}
return nil
}
func intValue(v *int) int {
if v == nil {
return 0
}
return *v
}
func intPtr(v int) *int { return &v }
// init registers TokenChunker under CategoryIngestion.
func init() {
MustRegisterChunker(ComponentNameTokenChunker)
}