vector-search-chromadb/chromadb.go - answer-plugins - Git at Google

 /*
  * Licensed to the Apache Software Foundation (ASF) under one
  * or more contributor license agreements.  See the NOTICE file
  * distributed with this work for additional information
  * regarding copyright ownership.  The ASF licenses this file
  * to you 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 chromadb_vector_search

 import (
 	"bytes"
 	"context"
 	"embed"
 	"encoding/json"
 	"fmt"
 	"io"
 	"net/http"
 	"strconv"
 	"strings"
 	"sync"

 	"github.com/apache/answer-plugins/util"
 	"github.com/apache/answer-plugins/vector-search-chromadb/i18n"
 	"github.com/apache/answer/plugin"
 	"github.com/segmentfault/pacman/log"
 )

 //go:embed info.yaml
 var Info embed.FS

 const collectionName = "answer_vector_embeddings"

 // VectorSearchEngine implements plugin.VectorSearch using ChromaDB REST API.
 type VectorSearchEngine struct {
 	Config              *VectorSearchConfig
 	httpClient          *http.Client
 	collectionID        string
 	syncer              plugin.VectorSearchSyncer
 	syncing             bool
 	lock                sync.Mutex
 	embeddingDimensions int
 }

 // VectorSearchConfig holds all plugin configuration.
 type VectorSearchConfig struct {
 	Endpoint            string  `json:"endpoint"`
 	APIHost             string  `json:"api_host"`
 	APIKey              string  `json:"api_key"`
 	EmbeddingModel      string  `json:"embedding_model"`
 	EmbeddingLevel      string  `json:"embedding_level"`
 	SimilarityThreshold float64 `json:"similarity_threshold"`
 }

 func init() {
 	plugin.Register(&VectorSearchEngine{
 		Config: &VectorSearchConfig{},
 		lock:   sync.Mutex{},
 	})
 }

 func (e *VectorSearchEngine) Info() plugin.Info {
 	info := &util.Info{}
 	info.GetInfo(Info)

 	return plugin.Info{
 		Name:        plugin.MakeTranslator(i18n.InfoName),
 		SlugName:    info.SlugName,
 		Description: plugin.MakeTranslator(i18n.InfoDescription),
 		Author:      info.Author,
 		Version:     info.Version,
 		Link:        info.Link,
 	}
 }

 // Description returns metadata about this vector search engine.
 func (e *VectorSearchEngine) Description() plugin.VectorSearchDesc {
 	return plugin.VectorSearchDesc{
 		Icon: "",
 		Link: "https://docs.trychroma.com/",
 	}
 }

 // RegisterSyncer stores the syncer and triggers a full sync.
 func (e *VectorSearchEngine) RegisterSyncer(ctx context.Context, syncer plugin.VectorSearchSyncer) {
 	log.Debugf("chromadb: RegisterSyncer called, configured=%v", e.httpClient != nil)
 	e.syncer = syncer
 	if e.httpClient != nil {
 		e.sync()
 	}
 }

 // SearchSimilar performs a cosine similarity search via ChromaDB REST API.
 func (e *VectorSearchEngine) SearchSimilar(ctx context.Context, query string, topK int) ([]plugin.VectorSearchResult, error) {
 	if e.httpClient == nil || e.collectionID == "" {
 		return nil, fmt.Errorf("chromadb: not initialized")
 	}
 	if topK <= 0 {
 		topK = 10
 	}

 	log.Debugf("chromadb: SearchSimilar query=%q topK=%d", query, topK)

 	embedding, err := plugin.GenerateEmbedding(ctx, e.Config.APIHost, e.Config.APIKey, e.Config.EmbeddingModel, query)
 	if err != nil {
 		return nil, fmt.Errorf("generate query embedding: %w", err)
 	}

 	log.Debugf("chromadb: search embedding generated, dimensions=%d", len(embedding))

 	embeddingF64 := float32ToFloat64(embedding)

 	reqBody := map[string]interface{}{
 		"query_embeddings": [][]float64{embeddingF64},
 		"n_results":        topK,
 		"include":          []string{"metadatas", "distances"},
 	}

 	respBody, err := e.doRequest(ctx, "POST",
 		fmt.Sprintf("/api/v1/collections/%s/query", e.collectionID), reqBody)
 	if err != nil {
 		return nil, fmt.Errorf("chromadb query failed: %w", err)
 	}

 	var queryResp struct {
 		IDs       [][]string               `json:"ids"`
 		Distances [][]float64              `json:"distances"`
 		Metadatas [][]map[string]string    `json:"metadatas"`
 	}
 	if err := json.Unmarshal(respBody, &queryResp); err != nil {
 		return nil, fmt.Errorf("parse query response: %w", err)
 	}

 	if len(queryResp.IDs) == 0 || len(queryResp.IDs[0]) == 0 {
 		return nil, nil
 	}

 	results := make([]plugin.VectorSearchResult, 0, len(queryResp.IDs[0]))
 	for i, id := range queryResp.IDs[0] {
 		// ChromaDB cosine distance: 0 = identical, 2 = opposite. Convert to similarity score.
 		score := 1.0 - queryResp.Distances[0][i]/2.0
 		if e.Config.SimilarityThreshold > 0 && score < e.Config.SimilarityThreshold {
 			log.Debugf("chromadb: skipping result %s score=%.4f below threshold=%.4f", id, score, e.Config.SimilarityThreshold)
 			continue
 		}

 		meta := queryResp.Metadatas[0][i]
 		results = append(results, plugin.VectorSearchResult{
 			ObjectID:   id,
 			ObjectType: meta["object_type"],
 			Metadata:   meta["metadata"],
 			Score:      score,
 		})
 	}

 	log.Debugf("chromadb: SearchSimilar returning %d results", len(results))
 	return results, nil
 }

 // UpdateContent upserts a single document via ChromaDB REST API.
 func (e *VectorSearchEngine) UpdateContent(ctx context.Context, content *plugin.VectorSearchContent) error {
 	if e.httpClient == nil || e.collectionID == "" {
 		return fmt.Errorf("chromadb: not initialized")
 	}

 	log.Debugf("chromadb: UpdateContent objectID=%s objectType=%s", content.ObjectID, content.ObjectType)

 	embedding, err := plugin.GenerateEmbedding(ctx, e.Config.APIHost, e.Config.APIKey, e.Config.EmbeddingModel, content.Content)
 	if err != nil {
 		return fmt.Errorf("generate embedding for %s: %w", content.ObjectID, err)
 	}

 	log.Debugf("chromadb: embedding generated for %s, dimensions=%d", content.ObjectID, len(embedding))

 	embeddingF64 := float32ToFloat64(embedding)

 	reqBody := map[string]interface{}{
 		"ids":        []string{content.ObjectID},
 		"embeddings": [][]float64{embeddingF64},
 		"metadatas": []map[string]string{{
 			"object_type": content.ObjectType,
 			"title":       content.Title,
 			"metadata":    content.Metadata,
 		}},
 		"documents": []string{content.Content},
 	}

 	_, err = e.doRequest(ctx, "POST",
 		fmt.Sprintf("/api/v1/collections/%s/upsert", e.collectionID), reqBody)
 	if err != nil {
 		return fmt.Errorf("upsert document %s: %w", content.ObjectID, err)
 	}

 	log.Debugf("chromadb: upserted document %s successfully", content.ObjectID)
 	return nil
 }

 // DeleteContent removes a document by object ID.
 func (e *VectorSearchEngine) DeleteContent(ctx context.Context, objectID string) error {
 	if e.httpClient == nil || e.collectionID == "" {
 		return fmt.Errorf("chromadb: not initialized")
 	}

 	log.Debugf("chromadb: DeleteContent objectID=%s", objectID)

 	reqBody := map[string]interface{}{
 		"ids": []string{objectID},
 	}

 	_, err := e.doRequest(ctx, "POST",
 		fmt.Sprintf("/api/v1/collections/%s/delete", e.collectionID), reqBody)
 	if err != nil {
 		return fmt.Errorf("delete document %s: %w", objectID, err)
 	}

 	log.Debugf("chromadb: deleted document %s", objectID)
 	return nil
 }

 // ConfigFields returns the plugin configuration form fields.
 func (e *VectorSearchEngine) ConfigFields() []plugin.ConfigField {
 	return []plugin.ConfigField{
 		{
 			Name:        "endpoint",
 			Type:        plugin.ConfigTypeInput,
 			Title:       plugin.MakeTranslator(i18n.ConfigEndpointTitle),
 			Description: plugin.MakeTranslator(i18n.ConfigEndpointDescription),
 			Required:    true,
 			UIOptions: plugin.ConfigFieldUIOptions{
 				InputType: plugin.InputTypeText,
 			},
 			Value: e.Config.Endpoint,
 		},
 		{
 			Name:        "api_host",
 			Type:        plugin.ConfigTypeInput,
 			Title:       plugin.MakeTranslator(i18n.ConfigAPIHostTitle),
 			Description: plugin.MakeTranslator(i18n.ConfigAPIHostDescription),
 			Required:    true,
 			UIOptions: plugin.ConfigFieldUIOptions{
 				InputType: plugin.InputTypeText,
 			},
 			Value: e.Config.APIHost,
 		},
 		{
 			Name:        "api_key",
 			Type:        plugin.ConfigTypeInput,
 			Title:       plugin.MakeTranslator(i18n.ConfigAPIKeyTitle),
 			Description: plugin.MakeTranslator(i18n.ConfigAPIKeyDescription),
 			Required:    true,
 			UIOptions: plugin.ConfigFieldUIOptions{
 				InputType: plugin.InputTypePassword,
 			},
 			Value: e.Config.APIKey,
 		},
 		{
 			Name:        "embedding_model",
 			Type:        plugin.ConfigTypeInput,
 			Title:       plugin.MakeTranslator(i18n.ConfigEmbeddingModelTitle),
 			Description: plugin.MakeTranslator(i18n.ConfigEmbeddingModelDescription),
 			Required:    true,
 			UIOptions: plugin.ConfigFieldUIOptions{
 				InputType: plugin.InputTypeText,
 			},
 			Value: e.Config.EmbeddingModel,
 		},
 		{
 			Name:        "embedding_level",
 			Type:        plugin.ConfigTypeSelect,
 			Title:       plugin.MakeTranslator(i18n.ConfigEmbeddingLevelTitle),
 			Description: plugin.MakeTranslator(i18n.ConfigEmbeddingLevelDescription),
 			Required:    true,
 			Options: []plugin.ConfigFieldOption{
 				{Label: plugin.MakeTranslator(i18n.ConfigEmbeddingLevelOptionQuestion), Value: "question"},
 				{Label: plugin.MakeTranslator(i18n.ConfigEmbeddingLevelOptionAnswer), Value: "answer"},
 			},
 			Value: e.Config.EmbeddingLevel,
 		},
 		{
 			Name:        "similarity_threshold",
 			Type:        plugin.ConfigTypeInput,
 			Title:       plugin.MakeTranslator(i18n.ConfigSimilarityThresholdTitle),
 			Description: plugin.MakeTranslator(i18n.ConfigSimilarityThresholdDescription),
 			Required:    false,
 			UIOptions: plugin.ConfigFieldUIOptions{
 				InputType: plugin.InputTypeText,
 			},
 			Value: fmt.Sprintf("%.2f", e.Config.SimilarityThreshold),
 		},
 	}
 }

 // ConfigReceiver applies configuration from the admin UI.
 func (e *VectorSearchEngine) ConfigReceiver(config []byte) error {
 	log.Debugf("chromadb: ConfigReceiver called")

 	var raw map[string]interface{}
 	if err := json.Unmarshal(config, &raw); err != nil {
 		return fmt.Errorf("unmarshal config: %w", err)
 	}
 	if threshStr, ok := raw["similarity_threshold"].(string); ok {
 		if thresh, err := strconv.ParseFloat(threshStr, 64); err == nil {
 			raw["similarity_threshold"] = thresh
 		}
 	}
 	fixed, _ := json.Marshal(raw)

 	conf := &VectorSearchConfig{}
 	if err := json.Unmarshal(fixed, conf); err != nil {
 		return fmt.Errorf("unmarshal config: %w", err)
 	}

 	e.Config = conf

 	log.Debugf("chromadb: config parsed: endpoint=%s model=%s level=%s threshold=%.2f",
 		conf.Endpoint, conf.EmbeddingModel, conf.EmbeddingLevel, conf.SimilarityThreshold)

 	if !plugin.StatusManager.IsEnabled("chromadb_vector_search") {
 		log.Debugf("chromadb: plugin not active, skipping initialization")
 		return nil
 	}

 	// Auto-detect embedding dimensions via probe call.
 	log.Debugf("chromadb: detecting embedding dimensions via probe call")
 	probeEmbedding, err := plugin.GenerateEmbedding(context.Background(), conf.APIHost, conf.APIKey, conf.EmbeddingModel, "dimension probe")
 	if err != nil {
 		return fmt.Errorf("detect embedding dimensions: %w", err)
 	}
 	e.embeddingDimensions = len(probeEmbedding)
 	log.Infof("chromadb: auto-detected embedding dimensions=%d for model=%s", e.embeddingDimensions, conf.EmbeddingModel)

 	e.httpClient = &http.Client{}

 	// Ensure endpoint doesn't have trailing slash.
 	e.Config.Endpoint = strings.TrimRight(e.Config.Endpoint, "/")

 	if err := e.ensureCollection(context.Background()); err != nil {
 		return fmt.Errorf("ensure collection: %w", err)
 	}

 	log.Debugf("chromadb: ConfigReceiver completed successfully, collectionID=%s", e.collectionID)
 	return nil
 }

 // ensureCollection creates or gets the ChromaDB collection.
 func (e *VectorSearchEngine) ensureCollection(ctx context.Context) error {
 	// Try to get existing collection.
 	respBody, err := e.doRequest(ctx, "GET",
 		fmt.Sprintf("/api/v1/collections/%s", collectionName), nil)
 	if err == nil {
 		var col struct {
 			ID string `json:"id"`
 		}
 		if json.Unmarshal(respBody, &col) == nil && col.ID != "" {
 			e.collectionID = col.ID
 			log.Debugf("chromadb: found existing collection %s id=%s", collectionName, col.ID)
 			return nil
 		}
 	}

 	// Create new collection.
 	log.Debugf("chromadb: creating collection %s", collectionName)
 	reqBody := map[string]interface{}{
 		"name": collectionName,
 		"metadata": map[string]string{
 			"hnsw:space": "cosine",
 		},
 	}

 	respBody, err = e.doRequest(ctx, "POST", "/api/v1/collections", reqBody)
 	if err != nil {
 		return fmt.Errorf("create collection: %w", err)
 	}

 	var col struct {
 		ID string `json:"id"`
 	}
 	if err := json.Unmarshal(respBody, &col); err != nil {
 		return fmt.Errorf("parse create collection response: %w", err)
 	}
 	e.collectionID = col.ID
 	log.Debugf("chromadb: created collection %s id=%s", collectionName, col.ID)
 	return nil
 }

 // doRequest sends an HTTP request to the ChromaDB server.
 func (e *VectorSearchEngine) doRequest(ctx context.Context, method, path string, body interface{}) ([]byte, error) {
 	var bodyReader io.Reader
 	if body != nil {
 		data, err := json.Marshal(body)
 		if err != nil {
 			return nil, fmt.Errorf("marshal request body: %w", err)
 		}
 		bodyReader = bytes.NewReader(data)
 	}

 	url := e.Config.Endpoint + path
 	req, err := http.NewRequestWithContext(ctx, method, url, bodyReader)
 	if err != nil {
 		return nil, fmt.Errorf("create request: %w", err)
 	}
 	req.Header.Set("Content-Type", "application/json")

 	resp, err := e.httpClient.Do(req)
 	if err != nil {
 		return nil, fmt.Errorf("http request failed: %w", err)
 	}
 	defer resp.Body.Close()

 	respData, err := io.ReadAll(resp.Body)
 	if err != nil {
 		return nil, fmt.Errorf("read response body: %w", err)
 	}

 	if resp.StatusCode >= 400 {
 		return nil, fmt.Errorf("chromadb returned %d: %s", resp.StatusCode, string(respData))
 	}

 	return respData, nil
 }

 // float32ToFloat64 converts a []float32 slice to []float64 for JSON serialization.
 func float32ToFloat64(f32 []float32) []float64 {
 	f64 := make([]float64, len(f32))
 	for i, v := range f32 {
 		f64[i] = float64(v)
 	}
 	return f64
 }
	/*
	* Licensed to the Apache Software Foundation (ASF) under one
	* or more contributor license agreements. See the NOTICE file
	* distributed with this work for additional information
	* regarding copyright ownership. The ASF licenses this file
	* to you 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 chromadb_vector_search

	import (
	"bytes"
	"context"
	"embed"
	"encoding/json"
	"fmt"
	"io"
	"net/http"
	"strconv"
	"strings"
	"sync"

	"github.com/apache/answer-plugins/util"
	"github.com/apache/answer-plugins/vector-search-chromadb/i18n"
	"github.com/apache/answer/plugin"
	"github.com/segmentfault/pacman/log"
	)

	//go:embed info.yaml
	var Info embed.FS

	const collectionName = "answer_vector_embeddings"

	// VectorSearchEngine implements plugin.VectorSearch using ChromaDB REST API.
	type VectorSearchEngine struct {
	Config *VectorSearchConfig
	httpClient *http.Client
	collectionID string
	syncer plugin.VectorSearchSyncer
	syncing bool
	lock sync.Mutex
	embeddingDimensions int
	}

	// VectorSearchConfig holds all plugin configuration.
	type VectorSearchConfig struct {
	Endpoint string `json:"endpoint"`
	APIHost string `json:"api_host"`
	APIKey string `json:"api_key"`
	EmbeddingModel string `json:"embedding_model"`
	EmbeddingLevel string `json:"embedding_level"`
	SimilarityThreshold float64 `json:"similarity_threshold"`
	}

	func init() {
	plugin.Register(&VectorSearchEngine{
	Config: &VectorSearchConfig{},
	lock: sync.Mutex{},
	})
	}

	func (e *VectorSearchEngine) Info() plugin.Info {
	info := &util.Info{}
	info.GetInfo(Info)

	return plugin.Info{
	Name: plugin.MakeTranslator(i18n.InfoName),
	SlugName: info.SlugName,
	Description: plugin.MakeTranslator(i18n.InfoDescription),
	Author: info.Author,
	Version: info.Version,
	Link: info.Link,
	}
	}

	// Description returns metadata about this vector search engine.
	func (e *VectorSearchEngine) Description() plugin.VectorSearchDesc {
	return plugin.VectorSearchDesc{
	Icon: "",
	Link: "https://docs.trychroma.com/",
	}
	}

	// RegisterSyncer stores the syncer and triggers a full sync.
	func (e *VectorSearchEngine) RegisterSyncer(ctx context.Context, syncer plugin.VectorSearchSyncer) {
	log.Debugf("chromadb: RegisterSyncer called, configured=%v", e.httpClient != nil)
	e.syncer = syncer
	if e.httpClient != nil {
	e.sync()
	}
	}

	// SearchSimilar performs a cosine similarity search via ChromaDB REST API.
	func (e *VectorSearchEngine) SearchSimilar(ctx context.Context, query string, topK int) ([]plugin.VectorSearchResult, error) {
	if e.httpClient == nil \|\| e.collectionID == "" {
	return nil, fmt.Errorf("chromadb: not initialized")
	}
	if topK <= 0 {
	topK = 10
	}

	log.Debugf("chromadb: SearchSimilar query=%q topK=%d", query, topK)

	embedding, err := plugin.GenerateEmbedding(ctx, e.Config.APIHost, e.Config.APIKey, e.Config.EmbeddingModel, query)
	if err != nil {
	return nil, fmt.Errorf("generate query embedding: %w", err)
	}

	log.Debugf("chromadb: search embedding generated, dimensions=%d", len(embedding))

	embeddingF64 := float32ToFloat64(embedding)

	reqBody := map[string]interface{}{
	"query_embeddings": [][]float64{embeddingF64},
	"n_results": topK,
	"include": []string{"metadatas", "distances"},
	}

	respBody, err := e.doRequest(ctx, "POST",
	fmt.Sprintf("/api/v1/collections/%s/query", e.collectionID), reqBody)
	if err != nil {
	return nil, fmt.Errorf("chromadb query failed: %w", err)
	}

	var queryResp struct {
	IDs [][]string `json:"ids"`
	Distances [][]float64 `json:"distances"`
	Metadatas [][]map[string]string `json:"metadatas"`
	}
	if err := json.Unmarshal(respBody, &queryResp); err != nil {
	return nil, fmt.Errorf("parse query response: %w", err)
	}

	if len(queryResp.IDs) == 0 \|\| len(queryResp.IDs[0]) == 0 {
	return nil, nil
	}

	results := make([]plugin.VectorSearchResult, 0, len(queryResp.IDs[0]))
	for i, id := range queryResp.IDs[0] {
	// ChromaDB cosine distance: 0 = identical, 2 = opposite. Convert to similarity score.
	score := 1.0 - queryResp.Distances[0][i]/2.0
	if e.Config.SimilarityThreshold > 0 && score < e.Config.SimilarityThreshold {
	log.Debugf("chromadb: skipping result %s score=%.4f below threshold=%.4f", id, score, e.Config.SimilarityThreshold)
	continue
	}

	meta := queryResp.Metadatas[0][i]
	results = append(results, plugin.VectorSearchResult{
	ObjectID: id,
	ObjectType: meta["object_type"],
	Metadata: meta["metadata"],
	Score: score,
	})
	}

	log.Debugf("chromadb: SearchSimilar returning %d results", len(results))
	return results, nil
	}

	// UpdateContent upserts a single document via ChromaDB REST API.
	func (e VectorSearchEngine) UpdateContent(ctx context.Context, content plugin.VectorSearchContent) error {
	if e.httpClient == nil \|\| e.collectionID == "" {
	return fmt.Errorf("chromadb: not initialized")
	}

	log.Debugf("chromadb: UpdateContent objectID=%s objectType=%s", content.ObjectID, content.ObjectType)

	embedding, err := plugin.GenerateEmbedding(ctx, e.Config.APIHost, e.Config.APIKey, e.Config.EmbeddingModel, content.Content)
	if err != nil {
	return fmt.Errorf("generate embedding for %s: %w", content.ObjectID, err)
	}

	log.Debugf("chromadb: embedding generated for %s, dimensions=%d", content.ObjectID, len(embedding))

	embeddingF64 := float32ToFloat64(embedding)

	reqBody := map[string]interface{}{
	"ids": []string{content.ObjectID},
	"embeddings": [][]float64{embeddingF64},
	"metadatas": []map[string]string{{
	"object_type": content.ObjectType,
	"title": content.Title,
	"metadata": content.Metadata,
	}},
	"documents": []string{content.Content},
	}

	_, err = e.doRequest(ctx, "POST",
	fmt.Sprintf("/api/v1/collections/%s/upsert", e.collectionID), reqBody)
	if err != nil {
	return fmt.Errorf("upsert document %s: %w", content.ObjectID, err)
	}

	log.Debugf("chromadb: upserted document %s successfully", content.ObjectID)
	return nil
	}

	// DeleteContent removes a document by object ID.
	func (e *VectorSearchEngine) DeleteContent(ctx context.Context, objectID string) error {
	if e.httpClient == nil \|\| e.collectionID == "" {
	return fmt.Errorf("chromadb: not initialized")
	}

	log.Debugf("chromadb: DeleteContent objectID=%s", objectID)

	reqBody := map[string]interface{}{
	"ids": []string{objectID},
	}

	_, err := e.doRequest(ctx, "POST",
	fmt.Sprintf("/api/v1/collections/%s/delete", e.collectionID), reqBody)
	if err != nil {
	return fmt.Errorf("delete document %s: %w", objectID, err)
	}

	log.Debugf("chromadb: deleted document %s", objectID)
	return nil
	}

	// ConfigFields returns the plugin configuration form fields.
	func (e *VectorSearchEngine) ConfigFields() []plugin.ConfigField {
	return []plugin.ConfigField{
	{
	Name: "endpoint",
	Type: plugin.ConfigTypeInput,
	Title: plugin.MakeTranslator(i18n.ConfigEndpointTitle),
	Description: plugin.MakeTranslator(i18n.ConfigEndpointDescription),
	Required: true,
	UIOptions: plugin.ConfigFieldUIOptions{
	InputType: plugin.InputTypeText,
	},
	Value: e.Config.Endpoint,
	},
	{
	Name: "api_host",
	Type: plugin.ConfigTypeInput,
	Title: plugin.MakeTranslator(i18n.ConfigAPIHostTitle),
	Description: plugin.MakeTranslator(i18n.ConfigAPIHostDescription),
	Required: true,
	UIOptions: plugin.ConfigFieldUIOptions{
	InputType: plugin.InputTypeText,
	},
	Value: e.Config.APIHost,
	},
	{
	Name: "api_key",
	Type: plugin.ConfigTypeInput,
	Title: plugin.MakeTranslator(i18n.ConfigAPIKeyTitle),
	Description: plugin.MakeTranslator(i18n.ConfigAPIKeyDescription),
	Required: true,
	UIOptions: plugin.ConfigFieldUIOptions{
	InputType: plugin.InputTypePassword,
	},
	Value: e.Config.APIKey,
	},
	{
	Name: "embedding_model",
	Type: plugin.ConfigTypeInput,
	Title: plugin.MakeTranslator(i18n.ConfigEmbeddingModelTitle),
	Description: plugin.MakeTranslator(i18n.ConfigEmbeddingModelDescription),
	Required: true,
	UIOptions: plugin.ConfigFieldUIOptions{
	InputType: plugin.InputTypeText,
	},
	Value: e.Config.EmbeddingModel,
	},
	{
	Name: "embedding_level",
	Type: plugin.ConfigTypeSelect,
	Title: plugin.MakeTranslator(i18n.ConfigEmbeddingLevelTitle),
	Description: plugin.MakeTranslator(i18n.ConfigEmbeddingLevelDescription),
	Required: true,
	Options: []plugin.ConfigFieldOption{
	{Label: plugin.MakeTranslator(i18n.ConfigEmbeddingLevelOptionQuestion), Value: "question"},
	{Label: plugin.MakeTranslator(i18n.ConfigEmbeddingLevelOptionAnswer), Value: "answer"},
	},
	Value: e.Config.EmbeddingLevel,
	},
	{
	Name: "similarity_threshold",
	Type: plugin.ConfigTypeInput,
	Title: plugin.MakeTranslator(i18n.ConfigSimilarityThresholdTitle),
	Description: plugin.MakeTranslator(i18n.ConfigSimilarityThresholdDescription),
	Required: false,
	UIOptions: plugin.ConfigFieldUIOptions{
	InputType: plugin.InputTypeText,
	},
	Value: fmt.Sprintf("%.2f", e.Config.SimilarityThreshold),
	},
	}
	}

	// ConfigReceiver applies configuration from the admin UI.
	func (e *VectorSearchEngine) ConfigReceiver(config []byte) error {
	log.Debugf("chromadb: ConfigReceiver called")

	var raw map[string]interface{}
	if err := json.Unmarshal(config, &raw); err != nil {
	return fmt.Errorf("unmarshal config: %w", err)
	}
	if threshStr, ok := raw["similarity_threshold"].(string); ok {
	if thresh, err := strconv.ParseFloat(threshStr, 64); err == nil {
	raw["similarity_threshold"] = thresh
	}
	}
	fixed, _ := json.Marshal(raw)

	conf := &VectorSearchConfig{}
	if err := json.Unmarshal(fixed, conf); err != nil {
	return fmt.Errorf("unmarshal config: %w", err)
	}

	e.Config = conf

	log.Debugf("chromadb: config parsed: endpoint=%s model=%s level=%s threshold=%.2f",
	conf.Endpoint, conf.EmbeddingModel, conf.EmbeddingLevel, conf.SimilarityThreshold)

	if !plugin.StatusManager.IsEnabled("chromadb_vector_search") {
	log.Debugf("chromadb: plugin not active, skipping initialization")
	return nil
	}

	// Auto-detect embedding dimensions via probe call.
	log.Debugf("chromadb: detecting embedding dimensions via probe call")
	probeEmbedding, err := plugin.GenerateEmbedding(context.Background(), conf.APIHost, conf.APIKey, conf.EmbeddingModel, "dimension probe")
	if err != nil {
	return fmt.Errorf("detect embedding dimensions: %w", err)
	}
	e.embeddingDimensions = len(probeEmbedding)
	log.Infof("chromadb: auto-detected embedding dimensions=%d for model=%s", e.embeddingDimensions, conf.EmbeddingModel)

	e.httpClient = &http.Client{}

	// Ensure endpoint doesn't have trailing slash.
	e.Config.Endpoint = strings.TrimRight(e.Config.Endpoint, "/")

	if err := e.ensureCollection(context.Background()); err != nil {
	return fmt.Errorf("ensure collection: %w", err)
	}

	log.Debugf("chromadb: ConfigReceiver completed successfully, collectionID=%s", e.collectionID)
	return nil
	}

	// ensureCollection creates or gets the ChromaDB collection.
	func (e *VectorSearchEngine) ensureCollection(ctx context.Context) error {
	// Try to get existing collection.
	respBody, err := e.doRequest(ctx, "GET",
	fmt.Sprintf("/api/v1/collections/%s", collectionName), nil)
	if err == nil {
	var col struct {
	ID string `json:"id"`
	}
	if json.Unmarshal(respBody, &col) == nil && col.ID != "" {
	e.collectionID = col.ID
	log.Debugf("chromadb: found existing collection %s id=%s", collectionName, col.ID)
	return nil
	}
	}

	// Create new collection.
	log.Debugf("chromadb: creating collection %s", collectionName)
	reqBody := map[string]interface{}{
	"name": collectionName,
	"metadata": map[string]string{
	"hnsw:space": "cosine",
	},
	}

	respBody, err = e.doRequest(ctx, "POST", "/api/v1/collections", reqBody)
	if err != nil {
	return fmt.Errorf("create collection: %w", err)
	}

	var col struct {
	ID string `json:"id"`
	}
	if err := json.Unmarshal(respBody, &col); err != nil {
	return fmt.Errorf("parse create collection response: %w", err)
	}
	e.collectionID = col.ID
	log.Debugf("chromadb: created collection %s id=%s", collectionName, col.ID)
	return nil
	}

	// doRequest sends an HTTP request to the ChromaDB server.
	func (e *VectorSearchEngine) doRequest(ctx context.Context, method, path string, body interface{}) ([]byte, error) {
	var bodyReader io.Reader
	if body != nil {
	data, err := json.Marshal(body)
	if err != nil {
	return nil, fmt.Errorf("marshal request body: %w", err)
	}
	bodyReader = bytes.NewReader(data)
	}

	url := e.Config.Endpoint + path
	req, err := http.NewRequestWithContext(ctx, method, url, bodyReader)
	if err != nil {
	return nil, fmt.Errorf("create request: %w", err)
	}
	req.Header.Set("Content-Type", "application/json")

	resp, err := e.httpClient.Do(req)
	if err != nil {
	return nil, fmt.Errorf("http request failed: %w", err)
	}
	defer resp.Body.Close()

	respData, err := io.ReadAll(resp.Body)
	if err != nil {
	return nil, fmt.Errorf("read response body: %w", err)
	}

	if resp.StatusCode >= 400 {
	return nil, fmt.Errorf("chromadb returned %d: %s", resp.StatusCode, string(respData))
	}

	return respData, nil
	}

	// float32ToFloat64 converts a []float32 slice to []float64 for JSON serialization.
	func float32ToFloat64(f32 []float32) []float64 {
	f64 := make([]float64, len(f32))
	for i, v := range f32 {
	f64[i] = float64(v)
	}
	return f64
	}