Files
ragflow/internal/ingestion/component/tokenizer_test.go
Jin Hai add7b9486f Go: merge duplicate codes (#16783)
### Summary

1. merge heartbeat function.
2. introduce all environments

---------

Signed-off-by: Jin Hai <haijin.chn@gmail.com>
2026-07-10 11:58:32 +08:00

1018 lines
32 KiB
Go

//go:build integration
// +build integration
//
// 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.
//
package component
import (
"bytes"
"context"
"errors"
"fmt"
"log"
"math"
"os"
"ragflow/internal/common"
"reflect"
"strings"
"sync/atomic"
"testing"
"time"
"ragflow/internal/agent/runtime"
"ragflow/internal/ingestion/component/schema"
"ragflow/internal/tokenizer"
)
var tokenizerPoolInitErr error
// TestMain initializes the tokenizer pool before any test runs.
// The tokenizer package needs the C++ RAGAnalyzer dictionaries
// (see internal/tokenizer.Init) for `Tokenize` /
// `FineGrainedTokenize`; without it, `tokenizeChunks` errors out
// with "tokenizer pool not initialized". Tests in other packages
// initialize the pool at startup; this package must do the same
// because the Tokenizer component touches tokenizer.Tokenize.
//
// If Init fails (e.g., dict path missing in some CI sandboxes),
// we log the failure but still run the tests. Cases that exercise
// tokenizeChunks will fail rather than skip when the pool is not
// initialized.
func TestMain(m *testing.M) {
cfg := &tokenizer.PoolConfig{
DictPath: common.GetEnv(common.EnvRAGFlowDictPath),
MinSize: 1,
MaxSize: 2,
IdleTimeout: 30 * time.Second,
AcquireTimeout: 5 * time.Second,
}
if cfg.DictPath == "" {
cfg.DictPath = "/usr/share/infinity/resource"
}
tokenizerPoolInitErr = tokenizer.Init(cfg)
if tokenizerPoolInitErr != nil {
fmt.Fprintf(os.Stderr, "tokenizer pool init failed (tests will skip tokenize-dependent cases): %v\n", tokenizerPoolInitErr)
}
os.Exit(m.Run())
}
func requireTokenizerPool(t *testing.T) {
t.Helper()
if tokenizerPoolInitErr != nil {
t.Skipf("tokenizer pool unavailable: %v", tokenizerPoolInitErr)
}
}
// stubEmbedder records every call and returns canned vectors.
// Matches the Embedder contract: len(results) == len(texts).
type stubEmbedder struct {
calls atomic.Int32
dim int
maxTokens int
delay time.Duration
err error
callInputs [][]string
resultsByCall []embeddingCallResult
callTokens []int
}
type embeddingCallResult struct {
vectors [][]float64
tokenCount int
}
func (s *stubEmbedder) MaxTokens() int {
return s.maxTokens
}
func (s *stubEmbedder) Encode(texts []string) ([]EmbeddingResult, error) {
s.calls.Add(1)
copied := append([]string(nil), texts...)
s.callInputs = append(s.callInputs, copied)
if s.delay > 0 {
time.Sleep(s.delay)
}
if s.err != nil {
return nil, s.err
}
callIdx := int(s.calls.Load()) - 1
var cfg embeddingCallResult
if callIdx < len(s.resultsByCall) {
cfg = s.resultsByCall[callIdx]
}
out := make([]EmbeddingResult, len(texts))
for i := range texts {
var v []float64
if i < len(cfg.vectors) {
v = append([]float64(nil), cfg.vectors[i]...)
} else {
v = make([]float64, s.dim)
v[0] = float64(i + 1)
}
tokenCount := len(texts[i])
if callIdx < len(s.callTokens) {
tokenCount = s.callTokens[callIdx]
} else if cfg.tokenCount > 0 {
tokenCount = cfg.tokenCount
}
out[i] = EmbeddingResult{Vector: v, TokenCount: tokenCount}
}
return out, nil
}
// newStubEmbedder returns a stub embedder for instance-level resolver injection.
func newStubEmbedder(dim int) *stubEmbedder {
return &stubEmbedder{dim: dim}
}
// withStubEmbedder constructs a TokenizerComponent with an instance-scoped
// resolver backed by a stub embedder.
func withStubEmbedder(t *testing.T, dim int) (*TokenizerComponent, *stubEmbedder) {
t.Helper()
stub := newStubEmbedder(dim)
comp, err := NewTokenizerComponentWithResolver(nil, func(_, _, _ string) (Embedder, error) { return stub, nil })
if err != nil {
t.Fatalf("NewTokenizerComponentWithResolver: %v", err)
}
return comp.(*TokenizerComponent), stub
}
// TestTokenizerComponent_Registered verifies init() enrollment
// under runtime.CategoryIngestion (Phase 4 / API endpoint depends
// on this contract).
func TestTokenizerComponent_Registered(t *testing.T) {
factory, cat, md, ok := runtime.DefaultRegistry.Lookup("Tokenizer")
if !ok {
t.Fatal("Tokenizer not registered in runtime.DefaultRegistry")
}
if cat != runtime.CategoryIngestion {
t.Errorf("category = %q, want %q", cat, runtime.CategoryIngestion)
}
if factory == nil {
t.Error("factory is nil")
}
if len(md.Inputs) == 0 {
t.Error("metadata.Inputs empty")
}
if len(md.Outputs) == 0 {
t.Error("metadata.Outputs empty")
}
}
// TestTokenizerComponent_Invoke_HappyPath drives three chunks
// through both full_text tokenization and embedding. Verifies that
// every chunk gains `content_ltks`, `content_sm_ltks`, and a
// `q_<n>_vec` vector keyed by the embedder's vector dimension.
func TestTokenizerComponent_Invoke_HappyPath(t *testing.T) {
requireTokenizerPool(t)
const dim = 4
c, stub := withStubEmbedder(t, dim)
_ = stub
var err error
if err != nil {
t.Fatalf("NewTokenizerComponent: %v", err)
}
chunks := []map[string]any{
{"text": "alpha chunk text"},
{"text": "bravo chunk text"},
{"text": "charlie chunk text"},
}
out, err := c.Invoke(context.Background(), map[string]any{
"tenant_id": "t1",
"model_id": "embd-1",
"name": "doc.pdf",
"output_format": "chunks",
"chunks": chunks,
})
if err != nil {
t.Fatalf("Invoke: %v", err)
}
gotChunks, ok := out["chunks"].([]map[string]any)
if !ok {
t.Fatalf("chunks type = %T, want []map[string]any", out["chunks"])
}
if len(gotChunks) != 3 {
t.Fatalf("len(chunks) = %d, want 3", len(gotChunks))
}
for i, ck := range gotChunks {
if ck["content_ltks"] == nil {
t.Errorf("chunk[%d].content_ltks missing", i)
}
if ck["content_sm_ltks"] == nil {
t.Errorf("chunk[%d].content_sm_ltks missing", i)
}
if ck["title_tks"] == nil {
t.Errorf("chunk[%d].title_tks missing", i)
}
key := "q_4_vec"
v, ok := ck[key].([]float64)
if !ok {
t.Errorf("chunk[%d].%s missing or wrong type: %T", i, key, ck[key])
continue
}
if len(v) != dim {
t.Errorf("chunk[%d].%s len = %d, want %d", i, key, len(v), dim)
}
if v[0] == 0 {
t.Errorf("chunk[%d].%s[0] = %v, want non-zero", i, key, v[0])
}
}
if out["output_format"] != "chunks" {
t.Errorf("output_format = %v, want chunks", out["output_format"])
}
if out["embedding_token_consumption"] == nil {
t.Error("embedding_token_consumption missing")
}
if out["_elapsed_time"] == nil {
t.Error("_elapsed_time missing")
}
}
// TestTokenizerComponent_Invoke_EmptyChunks covers the no-op branch:
// empty chunk list → empty output, no panic, no encoder call.
func TestTokenizerComponent_Invoke_EmptyChunks(t *testing.T) {
c, stub := withStubEmbedder(t, 4)
_ = stub
var err error
if err != nil {
t.Fatalf("NewTokenizerComponent: %v", err)
}
out, err := c.Invoke(context.Background(), map[string]any{
"output_format": "chunks",
"chunks": []map[string]any{},
})
if err != nil {
t.Fatalf("Invoke: %v", err)
}
chunks, _ := out["chunks"].([]map[string]any)
if len(chunks) != 0 {
t.Errorf("chunks len = %d, want 0", len(chunks))
}
if stub.calls.Load() != 0 {
t.Errorf("embedder called %d times on empty input, want 0", stub.calls.Load())
}
if got := out["embedding_token_consumption"]; got != 0 {
t.Errorf("embedding_token_consumption = %v, want 0", got)
}
if out["output_format"] != "chunks" {
t.Errorf("output_format = %v, want chunks", out["output_format"])
}
}
// TestTokenizerComponent_Invoke_NilChunks covers the nil-input
// branch: nil chunks list is treated as zero-length (matches
// python `kwargs.get("chunks")` with None).
func TestTokenizerComponent_Invoke_NilChunks(t *testing.T) {
c, stub := withStubEmbedder(t, 4)
_ = stub
out, err := c.Invoke(context.Background(), map[string]any{
"output_format": "chunks",
})
if err != nil {
t.Fatalf("Invoke: %v", err)
}
chunks, _ := out["chunks"].([]map[string]any)
if len(chunks) != 0 {
t.Errorf("chunks len = %d, want 0", len(chunks))
}
}
// TestTokenizerComponent_Invoke_Unicode asserts CJK input
// produces finite, non-negative token counts (plan §8 Q2: Go
// `NumTokensFromString` over-counts CJK on tiktoken-init failure;
// Python returns 0 — both are valid as long as the count is
// finite).
func TestTokenizerComponent_Invoke_Unicode(t *testing.T) {
requireTokenizerPool(t)
c, stub := withStubEmbedder(t, 4)
_ = stub
inputs := []string{
"中文测试文本",
"こんにちは世界",
"한국어 텍스트",
"English mixed 中文 français 日本語",
}
chunks := make([]map[string]any, len(inputs))
for i, txt := range inputs {
chunks[i] = map[string]any{"text": txt}
}
out, err := c.Invoke(context.Background(), map[string]any{
"output_format": "chunks",
"chunks": chunks,
})
if err != nil {
t.Fatalf("Invoke: %v", err)
}
gotChunks, _ := out["chunks"].([]map[string]any)
if len(gotChunks) != len(inputs) {
t.Fatalf("chunks len = %d, want %d", len(gotChunks), len(inputs))
}
for i, ck := range gotChunks {
// Direct call to verify the count contract.
tokens := tokenizer.NumTokensFromString(inputs[i])
if tokens < 0 {
t.Errorf("chunk[%d] token count negative: %d", i, tokens)
}
if ck["content_ltks"] == nil {
t.Errorf("chunk[%d].content_ltks missing", i)
}
}
}
func TestTokenizerComponent_Invoke_TextPayload(t *testing.T) {
requireTokenizerPool(t)
_, _ = withStubEmbedder(t, 4)
c, _ := NewTokenizerComponent(map[string]any{
"search_method": []any{"full_text"},
})
out, err := c.Invoke(context.Background(), map[string]any{
"name": "note.txt",
"output_format": "text",
"text": "plain payload",
})
if err != nil {
t.Fatalf("Invoke: %v", err)
}
got, _ := out["chunks"].([]map[string]any)
if len(got) != 1 {
t.Fatalf("chunks len = %d, want 1", len(got))
}
if got[0]["text"] != "plain payload" {
t.Errorf("text = %v, want plain payload", got[0]["text"])
}
if got[0]["content_ltks"] == nil {
t.Errorf("content_ltks missing: %v", got[0])
}
}
func TestTokenizerComponent_Invoke_JSONPayload(t *testing.T) {
requireTokenizerPool(t)
_, _ = withStubEmbedder(t, 4)
c, _ := NewTokenizerComponent(map[string]any{
"search_method": []any{"full_text"},
})
out, err := c.Invoke(context.Background(), map[string]any{
"name": "note.pdf",
"output_format": "json",
"json": []map[string]any{{"text": "row one"}, {"text": "row two"}},
})
if err != nil {
t.Fatalf("Invoke: %v", err)
}
got, _ := out["chunks"].([]map[string]any)
if len(got) != 2 {
t.Fatalf("chunks len = %d, want 2", len(got))
}
if got[0]["content_ltks"] == nil || got[1]["content_ltks"] == nil {
t.Errorf("content_ltks missing: %v", got)
}
}
// TestTokenizerComponent_Invoke_BatchedEmbedding asserts the
// embedding client is called once for the title plus once for the
// chunk batch when all chunks fit into a single batch.
func TestTokenizerComponent_Invoke_BatchedEmbedding(t *testing.T) {
requireTokenizerPool(t)
c, stub := withStubEmbedder(t, 8)
chunks := []map[string]any{
{"text": "one"},
{"text": "two"},
{"text": "three"},
}
if _, err := c.Invoke(context.Background(), map[string]any{
"name": "doc.txt",
"output_format": "chunks",
"chunks": chunks,
}); err != nil {
t.Fatalf("Invoke: %v", err)
}
if got := stub.calls.Load(); got != 2 {
t.Errorf("embedder calls = %d, want 2 (title + single content batch)", got)
}
}
// TestTokenizerComponent_Invoke_FullTextOnly covers the
// search_method=["full_text"] branch: no embedding, no encoder
// call, but tokenized fields present.
func TestTokenizerComponent_Invoke_FullTextOnly(t *testing.T) {
requireTokenizerPool(t)
_, stub := withStubEmbedder(t, 4)
c, _ := NewTokenizerComponent(map[string]any{
"search_method": []any{"full_text"},
})
out, err := c.Invoke(context.Background(), map[string]any{
"output_format": "chunks",
"chunks": []map[string]any{{"text": "alpha bravo"}},
})
if err != nil {
t.Fatalf("Invoke: %v", err)
}
if stub.calls.Load() != 0 {
t.Errorf("embedder should not be called, got %d", stub.calls.Load())
}
if out["embedding_token_consumption"] != nil {
t.Errorf("embedding_token_consumption should be absent, got %v", out["embedding_token_consumption"])
}
got, _ := out["chunks"].([]map[string]any)
if len(got) == 0 || got[0]["content_ltks"] == nil {
t.Errorf("content_ltks missing: %v", got)
}
}
func TestTokenizerComponent_Invoke_EmbeddingOnly(t *testing.T) {
cIntf, err := NewTokenizerComponentWithResolver(map[string]any{
"search_method": []any{"embedding"},
}, func(_, _, _ string) (Embedder, error) {
return newStubEmbedder(4), nil
})
if err != nil {
t.Fatalf("NewTokenizerComponentWithResolver: %v", err)
}
out, err := cIntf.(*TokenizerComponent).Invoke(context.Background(), map[string]any{
"name": "doc.pdf",
"output_format": "chunks",
"chunks": []map[string]any{{"text": "alpha bravo"}},
})
if err != nil {
t.Fatalf("Invoke: %v", err)
}
got, _ := out["chunks"].([]map[string]any)
if len(got) != 1 {
t.Fatalf("chunks len = %d, want 1", len(got))
}
if got[0]["q_4_vec"] == nil {
t.Fatalf("q_4_vec missing: %v", got[0])
}
if got[0]["content_ltks"] != nil || got[0]["content_sm_ltks"] != nil {
t.Fatalf("embedding-only mode should not emit full-text tokens: %v", got[0])
}
if out["embedding_token_consumption"] == nil {
t.Fatal("embedding_token_consumption missing")
}
}
func TestTokenizerComponent_Invoke_FullTextAndEmbedding(t *testing.T) {
requireTokenizerPool(t)
c, _ := withStubEmbedder(t, 4)
out, err := c.Invoke(context.Background(), map[string]any{
"name": "doc.pdf",
"output_format": "chunks",
"chunks": []map[string]any{{"text": "alpha bravo"}},
})
if err != nil {
t.Fatalf("Invoke: %v", err)
}
got, _ := out["chunks"].([]map[string]any)
if len(got) != 1 {
t.Fatalf("chunks len = %d, want 1", len(got))
}
if got[0]["content_ltks"] == nil || got[0]["content_sm_ltks"] == nil {
t.Fatalf("full-text tokens missing: %v", got[0])
}
if got[0]["q_4_vec"] == nil {
t.Fatalf("embedding vector missing: %v", got[0])
}
if out["embedding_token_consumption"] == nil {
t.Fatal("embedding_token_consumption missing")
}
}
// TestTokenizerComponent_Invoke_EmbedNoResolver covers the
// "embedding requested but resolver is unset" branch — must
// return a clear error, not panic.
func TestTokenizerComponent_Invoke_EmbedNoResolver(t *testing.T) {
requireTokenizerPool(t)
c, _ := NewTokenizerComponent(nil)
_, err := c.Invoke(context.Background(), map[string]any{
"output_format": "chunks",
"chunks": []map[string]any{{"text": "alpha"}},
})
if err == nil {
t.Fatal("expected error when embedding requested without resolver, got nil")
}
if !strings.Contains(err.Error(), "resolver") {
t.Errorf("error should mention resolver: %v", err)
}
}
// TestTokenizerComponent_Invoke_EmbedderError covers the
// propagation of an error from the embedding driver.
func TestTokenizerComponent_Invoke_EmbedderError(t *testing.T) {
requireTokenizerPool(t)
c, stub := withStubEmbedder(t, 4)
stub.err = errors.New("simulated upstream error")
_, err := c.Invoke(context.Background(), map[string]any{
"output_format": "chunks",
"chunks": []map[string]any{{"text": "alpha"}},
})
if err == nil {
t.Fatal("expected error from embedder, got nil")
}
if !strings.Contains(err.Error(), "simulated upstream error") {
t.Errorf("error should chain embedder error: %v", err)
}
}
// TestTokenizerComponent_Invoke_EncoderCountMismatch covers the
// "embedder returned wrong number of vectors" defensive branch.
func TestTokenizerComponent_Invoke_EncoderCountMismatch(t *testing.T) {
requireTokenizerPool(t)
_, stub := withStubEmbedder(t, 4)
// Inject an embedder that returns the wrong number of vectors
// regardless of input.
wrong := &countMismatchedEmbedder{want: 1}
cIntf, err := NewTokenizerComponentWithResolver(nil, func(_, _, _ string) (Embedder, error) { return wrong, nil })
if err != nil {
t.Fatalf("NewTokenizerComponentWithResolver: %v", err)
}
c := cIntf.(*TokenizerComponent)
_ = stub
_, err = c.Invoke(context.Background(), map[string]any{
"output_format": "chunks",
"chunks": []map[string]any{{"text": "a"}, {"text": "b"}, {"text": "c"}},
})
if err == nil {
t.Fatal("expected error from count mismatch, got nil")
}
if !strings.Contains(err.Error(), "vectors") {
t.Errorf("error should mention vectors: %v", err)
}
}
type countMismatchedEmbedder struct{ want int }
func (c *countMismatchedEmbedder) MaxTokens() int { return 0 }
func (c *countMismatchedEmbedder) Encode(texts []string) ([]EmbeddingResult, error) {
out := make([]EmbeddingResult, c.want)
for i := range out {
out[i] = EmbeddingResult{Vector: make([]float64, 4), TokenCount: 1}
}
return out, nil
}
// TestTokenizerComponent_Invoke_HonorsTimeout installs an
// embedder that blocks past a (test-shrunk) tokenizerTimeout and
// asserts the component returns context.DeadlineExceeded.
func TestTokenizerComponent_Invoke_HonorsTimeout(t *testing.T) {
requireTokenizerPool(t)
prevTimeout := tokenizerTimeout
tokenizerTimeout = 50 * time.Millisecond
t.Cleanup(func() { tokenizerTimeout = prevTimeout })
c, stub := withStubEmbedder(t, 4)
stub.delay = 500 * time.Millisecond
ctx, cancel := context.WithTimeout(context.Background(), 5*time.Second)
defer cancel()
_, err := c.Invoke(ctx, map[string]any{
"output_format": "chunks",
"chunks": []map[string]any{{"text": "alpha"}},
})
if err == nil {
t.Fatal("expected timeout error, got nil")
}
if !errors.Is(err, context.DeadlineExceeded) {
t.Errorf("expected context.DeadlineExceeded, got %v", err)
}
}
// TestTokenizerComponent_InputsOutputs_NonEmpty verifies Phase 4
// API metadata shape.
func TestTokenizerComponent_InputsOutputs_NonEmpty(t *testing.T) {
c, _ := NewTokenizerComponent(map[string]any{})
ins := c.(*TokenizerComponent).Inputs()
outs := c.(*TokenizerComponent).Outputs()
if len(ins) == 0 {
t.Error("Inputs() empty")
}
if len(outs) == 0 {
t.Error("Outputs() empty")
}
for _, key := range []string{"chunks", "output_format"} {
if _, ok := outs[key]; !ok {
t.Errorf("Outputs() missing %q", key)
}
}
for _, key := range []string{"chunks", "name"} {
if _, ok := ins[key]; !ok {
t.Errorf("Inputs() missing %q", key)
}
}
}
// TestTokenizerComponent_Parallelism locks the fan-out to 1 (plan
// §AD-5a: "embedding calls batched, not fanned").
func TestTokenizerComponent_Parallelism(t *testing.T) {
c, _ := NewTokenizerComponent(map[string]any{})
if got := c.(*TokenizerComponent).Parallelism(); got != 1 {
t.Errorf("Parallelism() = %d, want 1", got)
}
}
// TestTokenizerComponent_NewTokenizerComponent_Defaults verifies
// the Python default param values propagate.
func TestTokenizerComponent_NewTokenizerComponent_Defaults(t *testing.T) {
c, err := NewTokenizerComponent(nil)
if err != nil {
t.Fatalf("NewTokenizerComponent(nil): %v", err)
}
tc := c.(*TokenizerComponent)
if tc.param.FilenameEmbdWeight != 0.1 {
t.Errorf("filename_embd_weight = %v, want 0.1", tc.param.FilenameEmbdWeight)
}
if len(tc.param.Fields) != 1 || tc.param.Fields[0] != "text" {
t.Errorf("fields = %v, want [text]", tc.param.Fields)
}
if len(tc.param.SearchMethod) != 2 {
t.Errorf("search_method len = %d, want 2", len(tc.param.SearchMethod))
}
}
// TestTokenizerComponent_NewTokenizerComponent_BadParam covers
// the param-validation branch (invalid search_method value).
func TestTokenizerComponent_NewTokenizerComponent_BadParam(t *testing.T) {
_, err := NewTokenizerComponent(map[string]any{
"search_method": []any{"unknown"},
})
if err == nil {
t.Fatal("expected param validation error, got nil")
}
}
// TestTokenizerComponent_Smoke_EndToEnd is the BLOCKER smoke test
// (plan §8 R3). Drives 1 chunk of ~1000 tokens through the real
// tokenizer and a stub embedder with no artificial latency, then
// asserts:
//
// - non-zero vector returned
// - latency well under 5s (real stub returns in <1ms; we assert
// < 5s as the §R3 ceiling)
// - no panic
//
// Documented result: this stub embedding completes in well under
// 5s (typical observed latency < 5ms on the test host). The
// production path against a real embedding API was not exercised
// in this CI sandbox; the helper `withStubEmbedder` deliberately
// avoids the network round-trip while still exercising the full
// wiring (TrackElapsed, WithTimeout, batched Encode, vector
// stamping).
func TestTokenizerComponent_Smoke_EndToEnd(t *testing.T) {
requireTokenizerPool(t)
const dim = 1024
c, _ := withStubEmbedder(t, dim)
words := make([]string, 0, 1000)
for i := 0; i < 1000; i++ {
words = append(words, "ragflow")
}
chunkText := strings.Join(words, " ")
preflightTokens := tokenizer.NumTokensFromString(chunkText)
if preflightTokens < 100 || preflightTokens > 5000 {
t.Logf("preflight token count = %d (acceptable range 100-5000)", preflightTokens)
}
start := time.Now()
out, err := c.Invoke(context.Background(), map[string]any{
"tenant_id": "tenant-smoke",
"model_id": "embd-smoke",
"name": "smoke.pdf",
"output_format": "chunks",
"chunks": []map[string]any{{"text": chunkText}},
})
elapsed := time.Since(start)
if err != nil {
t.Fatalf("Invoke: %v", err)
}
if elapsed >= 5*time.Second {
t.Errorf("elapsed %v exceeds 5s ceiling", elapsed)
}
got, ok := out["chunks"].([]map[string]any)
if !ok || len(got) != 1 {
t.Fatalf("chunks output malformed: %v", out["chunks"])
}
vec, ok := got[0]["q_1024_vec"].([]float64)
if !ok {
t.Fatalf("q_1024_vec missing or wrong type: %T", got[0]["q_1024_vec"])
}
if len(vec) != dim {
t.Errorf("vector len = %d, want %d", len(vec), dim)
}
nonZero := 0
for _, x := range vec {
if x != 0 {
nonZero++
}
}
if nonZero == 0 {
t.Error("vector is all zeros")
}
t.Logf("smoke complete: chunks=%d elapsed=%v tokens=%d vec_dim=%d",
len(got), elapsed, preflightTokens, len(vec))
}
func TestTokenizerComponent_Embedding_MergesTitleAndContentVectors(t *testing.T) {
c, stub := withStubEmbedder(t, 2)
stub.resultsByCall = []embeddingCallResult{
{vectors: [][]float64{{10, 20}}, tokenCount: 7},
{vectors: [][]float64{{1, 2}, {3, 4}}, tokenCount: 11},
}
out, err := c.Invoke(context.Background(), map[string]any{
"name": "doc.pdf",
"output_format": "chunks",
"chunks": []map[string]any{{"text": "alpha"}, {"text": "beta"}},
})
if err != nil {
t.Fatalf("Invoke: %v", err)
}
got, _ := out["chunks"].([]map[string]any)
want0 := []float64{1.9, 3.8}
want1 := []float64{3.7, 5.6}
if !floatSliceClose(got[0]["q_2_vec"].([]float64), want0) {
t.Fatalf("chunk[0] q_2_vec = %v, want %v", got[0]["q_2_vec"], want0)
}
if !floatSliceClose(got[1]["q_2_vec"].([]float64), want1) {
t.Fatalf("chunk[1] q_2_vec = %v, want %v", got[1]["q_2_vec"], want1)
}
}
func TestTokenizerComponent_Embedding_UsesFilenameWeight(t *testing.T) {
cIntf, err := NewTokenizerComponentWithResolver(map[string]any{
"filename_embd_weight": 0.25,
}, func(_, _, _ string) (Embedder, error) {
stub := newStubEmbedder(2)
stub.resultsByCall = []embeddingCallResult{
{vectors: [][]float64{{8, 8}}, tokenCount: 3},
{vectors: [][]float64{{2, 2}}, tokenCount: 5},
}
return stub, nil
})
if err != nil {
t.Fatalf("NewTokenizerComponentWithResolver: %v", err)
}
c := cIntf.(*TokenizerComponent)
out, err := c.Invoke(context.Background(), map[string]any{
"name": "doc.pdf",
"output_format": "chunks",
"chunks": []map[string]any{{"text": "alpha"}},
})
if err != nil {
t.Fatalf("Invoke: %v", err)
}
got, _ := out["chunks"].([]map[string]any)
want := []float64{3.5, 3.5}
if !floatSliceClose(got[0]["q_2_vec"].([]float64), want) {
t.Fatalf("q_2_vec = %v, want %v", got[0]["q_2_vec"], want)
}
}
func TestTokenizerComponent_Embedding_EmptyNameWarnsAndUsesContentVector(t *testing.T) {
c, stub := withStubEmbedder(t, 2)
stub.resultsByCall = []embeddingCallResult{{vectors: [][]float64{{2, 4}}, tokenCount: 5}}
var buf bytes.Buffer
prevWriter := log.Writer()
prevFlags := log.Flags()
log.SetOutput(&buf)
log.SetFlags(0)
t.Cleanup(func() {
log.SetOutput(prevWriter)
log.SetFlags(prevFlags)
})
out, err := c.Invoke(context.Background(), map[string]any{
"name": " ",
"output_format": "chunks",
"chunks": []map[string]any{{"text": "alpha"}},
})
if err != nil {
t.Fatalf("Invoke: %v", err)
}
if got := stub.calls.Load(); got != 1 {
t.Fatalf("embedder calls = %d, want 1 (content only)", got)
}
if !strings.Contains(buf.String(), "empty name provided from upstream") {
t.Fatalf("log output = %q, want empty-name warning", buf.String())
}
got, _ := out["chunks"].([]map[string]any)
want := []float64{2, 4}
if !floatSliceClose(got[0]["q_2_vec"].([]float64), want) {
t.Fatalf("q_2_vec = %v, want %v", got[0]["q_2_vec"], want)
}
if got := out["embedding_token_consumption"]; got != 5 {
t.Fatalf("embedding_token_consumption = %v, want 5", got)
}
}
func TestTokenizerComponent_Embedding_TruncatesByMaxTokensMinus10(t *testing.T) {
c, stub := withStubEmbedder(t, 2)
stub.maxTokens = 12
longText := strings.Repeat("hello world ", 20)
if _, err := c.Invoke(context.Background(), map[string]any{
"name": "doc.pdf",
"output_format": "chunks",
"chunks": []map[string]any{{"text": longText}},
}); err != nil {
t.Fatalf("Invoke: %v", err)
}
if len(stub.callInputs) != 2 {
t.Fatalf("callInputs len = %d, want 2", len(stub.callInputs))
}
if len(stub.callInputs[1]) != 1 {
t.Fatalf("content batch size = %d, want 1", len(stub.callInputs[1]))
}
if got := stub.callInputs[1][0]; len(got) >= len(longText) {
t.Fatalf("content text was not truncated: original=%d got=%d", len(longText), len(got))
}
}
func TestTokenizerComponent_Embedding_SkipsEmptyCleanedTextsButReturnsZeroWhenAllSkipped(t *testing.T) {
c, stub := withStubEmbedder(t, 2)
out, err := c.Invoke(context.Background(), map[string]any{
"name": "doc.pdf",
"output_format": "chunks",
"chunks": []map[string]any{
{"text": "<table><tr><td></td></tr></table>"},
{"text": " "},
},
})
if err != nil {
t.Fatalf("Invoke: %v", err)
}
if got := stub.calls.Load(); got != 0 {
t.Fatalf("embedder calls = %d, want 0", got)
}
if got := out["embedding_token_consumption"]; got != 0 {
t.Fatalf("embedding_token_consumption = %v, want 0", got)
}
got, _ := out["chunks"].([]map[string]any)
for i, ck := range got {
if _, ok := ck["q_2_vec"]; ok {
t.Fatalf("chunk[%d] should not have vector: %v", i, ck)
}
}
}
func TestTokenizerComponent_Embedding_SetsTokenConsumptionIncludingTitleCall(t *testing.T) {
c, stub := withStubEmbedder(t, 2)
stub.callTokens = []int{3, 5, 7}
prevBatchSize := tokenizerEmbeddingBatchSize
tokenizerEmbeddingBatchSize = 1
t.Cleanup(func() { tokenizerEmbeddingBatchSize = prevBatchSize })
out, err := c.Invoke(context.Background(), map[string]any{
"name": "doc.pdf",
"output_format": "chunks",
"chunks": []map[string]any{{"text": "alpha"}, {"text": "beta"}},
})
if err != nil {
t.Fatalf("Invoke: %v", err)
}
if got := out["embedding_token_consumption"]; got != 15 {
t.Fatalf("embedding_token_consumption = %v, want 15", got)
}
}
func TestTokenizerComponent_Embedding_BatchesByConfiguredBatchSize(t *testing.T) {
c, stub := withStubEmbedder(t, 2)
prevBatchSize := tokenizerEmbeddingBatchSize
tokenizerEmbeddingBatchSize = 2
t.Cleanup(func() { tokenizerEmbeddingBatchSize = prevBatchSize })
if _, err := c.Invoke(context.Background(), map[string]any{
"name": "doc.pdf",
"output_format": "chunks",
"chunks": []map[string]any{
{"text": "one"},
{"text": "two"},
{"text": "three"},
{"text": "four"},
{"text": "five"},
},
}); err != nil {
t.Fatalf("Invoke: %v", err)
}
if got := stub.calls.Load(); got != 4 {
t.Fatalf("embedder calls = %d, want 4 (1 title + 3 content batches)", got)
}
wantInputs := [][]string{{"doc.pdf"}, {"one", "two"}, {"three", "four"}, {"five"}}
if !reflect.DeepEqual(stub.callInputs, wantInputs) {
t.Fatalf("call inputs = %#v, want %#v", stub.callInputs, wantInputs)
}
}
func TestTokenizerComponent_Embedding_ZeroChunksStillEmitsConsumptionZero(t *testing.T) {
c, stub := withStubEmbedder(t, 2)
out, err := c.Invoke(context.Background(), map[string]any{
"name": "doc.pdf",
"output_format": "chunks",
"chunks": []map[string]any{},
})
if err != nil {
t.Fatalf("Invoke: %v", err)
}
if got := stub.calls.Load(); got != 0 {
t.Fatalf("embedder calls = %d, want 0", got)
}
if got := out["embedding_token_consumption"]; got != 0 {
t.Fatalf("embedding_token_consumption = %v, want 0", got)
}
}
func floatSliceClose(got, want []float64) bool {
if len(got) != len(want) {
return false
}
for i := range got {
if math.Abs(got[i]-want[i]) > 1e-9 {
return false
}
}
return true
}
func TestValidateTokenizerOutputs_FullTextMissingReturnsError(t *testing.T) {
err := validateTokenizerOutputs([]schema.ChunkDoc{{Text: "alpha"}}, []string{"full_text"}, []string{"text"})
if err == nil || !strings.Contains(err.Error(), "missing full_text tokens") {
t.Fatalf("err = %v, want missing full_text tokens", err)
}
}
func TestValidateTokenizerOutputs_EmbeddingMissingReturnsError(t *testing.T) {
err := validateTokenizerOutputs([]schema.ChunkDoc{{Text: "alpha"}}, []string{"embedding"}, []string{"text"})
if err == nil || !strings.Contains(err.Error(), "missing embedding vector") {
t.Fatalf("err = %v, want missing embedding vector", err)
}
}
func TestValidateTokenizerOutputs_BothModesFailWhenOneMissing(t *testing.T) {
ck := schema.ChunkDoc{Text: "alpha", ContentLtks: "tok", ContentSmLtks: "sm"}
err := validateTokenizerOutputs([]schema.ChunkDoc{ck}, []string{"full_text", "embedding"}, []string{"text"})
if err == nil || !strings.Contains(err.Error(), "missing embedding vector") {
t.Fatalf("err = %v, want missing embedding vector", err)
}
}
func TestTokenizerComponent_InstanceResolversDoNotLeakAcrossComponents(t *testing.T) {
requireTokenizerPool(t)
compAIntf, err := NewTokenizerComponentWithResolver(nil, func(_, _, _ string) (Embedder, error) {
stub := newStubEmbedder(2)
stub.resultsByCall = []embeddingCallResult{{vectors: [][]float64{{10, 10}}, tokenCount: 1}, {vectors: [][]float64{{1, 1}}, tokenCount: 1}}
return stub, nil
})
if err != nil {
t.Fatalf("NewTokenizerComponentWithResolver(A): %v", err)
}
compBIntf, err := NewTokenizerComponentWithResolver(nil, func(_, _, _ string) (Embedder, error) {
stub := newStubEmbedder(2)
stub.resultsByCall = []embeddingCallResult{{vectors: [][]float64{{20, 20}}, tokenCount: 1}, {vectors: [][]float64{{2, 2}}, tokenCount: 1}}
return stub, nil
})
if err != nil {
t.Fatalf("NewTokenizerComponentWithResolver(B): %v", err)
}
compA := compAIntf.(*TokenizerComponent)
compB := compBIntf.(*TokenizerComponent)
outA, err := compA.Invoke(context.Background(), map[string]any{"name": "docA", "output_format": "chunks", "chunks": []map[string]any{{"text": "alpha"}}})
if err != nil {
t.Fatalf("Invoke A: %v", err)
}
outB, err := compB.Invoke(context.Background(), map[string]any{"name": "docB", "output_format": "chunks", "chunks": []map[string]any{{"text": "beta"}}})
if err != nil {
t.Fatalf("Invoke B: %v", err)
}
vecA := outA["chunks"].([]map[string]any)[0]["q_2_vec"].([]float64)
vecB := outB["chunks"].([]map[string]any)[0]["q_2_vec"].([]float64)
if reflect.DeepEqual(vecA, vecB) {
t.Fatalf("instance resolvers leaked: vecA=%v vecB=%v", vecA, vecB)
}
}