Files
Enterprise-Knowledge-Base/internal/agent/tools/list_knowledge_chunks.go
T
ochan.kwon edcf7116cd feat: use language-neutral English prompts for multilingual LLM responses
Convert all LLM-facing prompts, templates, and tool output labels to
language-neutral English so the model responds in the user's input
language. Update frontend relevance/match-type mappings to match.

Output language strategy:
- User-facing: reply in user's input language
- Vector-indexed: match source document language
- LLM-internal: fixed English
2026-03-06 21:08:12 +08:00

317 lines
9.1 KiB
Go

package tools
import (
"context"
"encoding/json"
"fmt"
"strings"
"github.com/Tencent/WeKnora/internal/types"
"github.com/Tencent/WeKnora/internal/types/interfaces"
)
var listKnowledgeChunksTool = BaseTool{
name: ToolListKnowledgeChunks,
description: `Retrieve full chunk content for a document by knowledge_id.
## Use After grep_chunks or knowledge_search:
1. grep_chunks(["keyword", "variant"]) → get knowledge_id
2. list_knowledge_chunks(knowledge_id) → read full content
## When to Use:
- Need full content of chunks from a known document
- Want to see context around specific chunks
- Check how many chunks a document has
## Parameters:
- knowledge_id (required): Document ID
- limit (optional): Chunks per page (default 20, max 100)
- offset (optional): Start position (default 0)
## Output:
Full chunk content with chunk_id, chunk_index, and content text.`,
schema: json.RawMessage(`{
"type": "object",
"properties": {
"knowledge_id": {
"type": "string",
"description": "Document ID to retrieve chunks from"
},
"limit": {
"type": "integer",
"description": "Chunks per page (default 20, max 100)",
"default": 20,
"minimum": 1,
"maximum": 100
},
"offset": {
"type": "integer",
"description": "Start position (default 0)",
"default": 0,
"minimum": 0
}
},
"required": ["knowledge_id", "limit", "offset"]
}`),
}
// ListKnowledgeChunksInput defines the input parameters for list knowledge chunks tool
type ListKnowledgeChunksInput struct {
KnowledgeID string `json:"knowledge_id"`
Limit int `json:"limit"`
Offset int `json:"offset"`
}
// ListKnowledgeChunksTool retrieves chunk snapshots for a specific knowledge document.
type ListKnowledgeChunksTool struct {
BaseTool
chunkService interfaces.ChunkService
knowledgeService interfaces.KnowledgeService
searchTargets types.SearchTargets // Pre-computed unified search targets with KB-tenant mapping
}
// NewListKnowledgeChunksTool creates a new tool instance.
func NewListKnowledgeChunksTool(
knowledgeService interfaces.KnowledgeService,
chunkService interfaces.ChunkService,
searchTargets types.SearchTargets,
) *ListKnowledgeChunksTool {
return &ListKnowledgeChunksTool{
BaseTool: listKnowledgeChunksTool,
chunkService: chunkService,
knowledgeService: knowledgeService,
searchTargets: searchTargets,
}
}
// Execute performs the chunk fetch against the chunk service.
func (t *ListKnowledgeChunksTool) Execute(ctx context.Context, args json.RawMessage) (*types.ToolResult, error) {
// Parse args from json.RawMessage
var input ListKnowledgeChunksInput
if err := json.Unmarshal(args, &input); err != nil {
return &types.ToolResult{
Success: false,
Error: fmt.Sprintf("Failed to parse args: %v", err),
}, err
}
knowledgeID := input.KnowledgeID
ok := knowledgeID != ""
if !ok || strings.TrimSpace(knowledgeID) == "" {
return &types.ToolResult{
Success: false,
Error: "knowledge_id is required",
}, fmt.Errorf("knowledge_id is required")
}
knowledgeID = strings.TrimSpace(knowledgeID)
// Get knowledge info without tenant filter to support shared KB
knowledge, err := t.knowledgeService.GetKnowledgeByIDOnly(ctx, knowledgeID)
if err != nil {
return &types.ToolResult{
Success: false,
Error: fmt.Sprintf("Knowledge not found: %v", err),
}, err
}
// Verify the knowledge's KB is in searchTargets (permission check)
if !t.searchTargets.ContainsKB(knowledge.KnowledgeBaseID) {
return &types.ToolResult{
Success: false,
Error: fmt.Sprintf("Knowledge base %s is not accessible", knowledge.KnowledgeBaseID),
}, fmt.Errorf("knowledge base not in search targets")
}
// Use the knowledge's actual tenant_id for chunk query (supports cross-tenant shared KB)
effectiveTenantID := knowledge.TenantID
chunkLimit := 20
if input.Limit > 0 {
chunkLimit = input.Limit
}
offset := 0
if input.Offset > 0 {
offset = input.Offset
}
if offset < 0 {
offset = 0
}
pagination := &types.Pagination{
Page: offset/chunkLimit + 1,
PageSize: chunkLimit,
}
chunks, total, err := t.chunkService.GetRepository().ListPagedChunksByKnowledgeID(ctx,
effectiveTenantID, knowledgeID, pagination, []types.ChunkType{types.ChunkTypeText, types.ChunkTypeFAQ}, "", "", "", "", "")
if err != nil {
return &types.ToolResult{
Success: false,
Error: fmt.Sprintf("failed to list chunks: %v", err),
}, err
}
if chunks == nil {
return &types.ToolResult{
Success: false,
Error: "chunk query returned no data",
}, fmt.Errorf("chunk query returned no data")
}
totalChunks := total
fetched := len(chunks)
knowledgeTitle := t.lookupKnowledgeTitle(ctx, knowledgeID)
output := t.buildOutput(knowledgeID, knowledgeTitle, totalChunks, fetched, chunks)
formattedChunks := make([]map[string]interface{}, 0, len(chunks))
for idx, c := range chunks {
chunkData := map[string]interface{}{
"seq": idx + 1,
"chunk_id": c.ID,
"chunk_index": c.ChunkIndex,
"content": c.Content,
"chunk_type": c.ChunkType,
"knowledge_id": c.KnowledgeID,
"knowledge_base": c.KnowledgeBaseID,
"start_at": c.StartAt,
"end_at": c.EndAt,
"parent_chunk_id": c.ParentChunkID,
}
// 添加图片信息
if c.ImageInfo != "" {
var imageInfos []types.ImageInfo
if err := json.Unmarshal([]byte(c.ImageInfo), &imageInfos); err == nil && len(imageInfos) > 0 {
imageList := make([]map[string]string, 0, len(imageInfos))
for _, img := range imageInfos {
imgData := make(map[string]string)
if img.URL != "" {
imgData["url"] = img.URL
}
if img.Caption != "" {
imgData["caption"] = img.Caption
}
if img.OCRText != "" {
imgData["ocr_text"] = img.OCRText
}
if len(imgData) > 0 {
imageList = append(imageList, imgData)
}
}
if len(imageList) > 0 {
chunkData["images"] = imageList
}
}
}
formattedChunks = append(formattedChunks, chunkData)
}
return &types.ToolResult{
Success: true,
Output: output,
Data: map[string]interface{}{
"knowledge_id": knowledgeID,
"knowledge_title": knowledgeTitle,
"total_chunks": totalChunks,
"fetched_chunks": fetched,
"page": pagination.Page,
"page_size": pagination.PageSize,
"chunks": formattedChunks,
},
}, nil
}
// lookupKnowledgeTitle looks up the title of a knowledge document
// Uses GetKnowledgeByIDOnly to support cross-tenant shared KB
func (t *ListKnowledgeChunksTool) lookupKnowledgeTitle(ctx context.Context, knowledgeID string) string {
if t.knowledgeService == nil {
return ""
}
knowledge, err := t.knowledgeService.GetKnowledgeByIDOnly(ctx, knowledgeID)
if err != nil || knowledge == nil {
return ""
}
return strings.TrimSpace(knowledge.Title)
}
// buildOutput builds the output for the list knowledge chunks tool
func (t *ListKnowledgeChunksTool) buildOutput(
knowledgeID string,
knowledgeTitle string,
total int64,
fetched int,
chunks []*types.Chunk,
) string {
builder := &strings.Builder{}
builder.WriteString("=== Knowledge Document Chunks ===\n\n")
if knowledgeTitle != "" {
fmt.Fprintf(builder, "Document: %s (%s)\n", knowledgeTitle, knowledgeID)
} else {
fmt.Fprintf(builder, "Document ID: %s\n", knowledgeID)
}
fmt.Fprintf(builder, "Total chunks: %d\n", total)
if fetched == 0 {
builder.WriteString("No chunks found. Please confirm the document has been parsed.\n")
if total > 0 {
builder.WriteString("Document exists but the current page is empty. Please check pagination parameters.\n")
}
return builder.String()
}
fmt.Fprintf(
builder,
"Fetched: %d chunks, range: %d - %d\n\n",
fetched,
chunks[0].ChunkIndex,
chunks[len(chunks)-1].ChunkIndex,
)
builder.WriteString("=== Chunk Content Preview ===\n\n")
for idx, c := range chunks {
fmt.Fprintf(builder, "Chunk #%d (Index %d)\n", idx+1, c.ChunkIndex+1)
fmt.Fprintf(builder, " chunk_id: %s\n", c.ID)
fmt.Fprintf(builder, " Type: %s\n", c.ChunkType)
fmt.Fprintf(builder, " Content: %s\n", summarizeContent(c.Content))
// Output associated image information
if c.ImageInfo != "" {
var imageInfos []types.ImageInfo
if err := json.Unmarshal([]byte(c.ImageInfo), &imageInfos); err == nil && len(imageInfos) > 0 {
fmt.Fprintf(builder, " Associated images (%d):\n", len(imageInfos))
for imgIdx, img := range imageInfos {
fmt.Fprintf(builder, " Image %d:\n", imgIdx+1)
if img.URL != "" {
fmt.Fprintf(builder, " URL: %s\n", img.URL)
}
if img.Caption != "" {
fmt.Fprintf(builder, " Caption: %s\n", img.Caption)
}
if img.OCRText != "" {
fmt.Fprintf(builder, " OCR Text: %s\n", img.OCRText)
}
}
}
}
builder.WriteString("\n")
}
if int64(fetched) < total {
builder.WriteString("Note: The document has more chunks. Adjust offset or make multiple calls to retrieve all content.\n")
}
return builder.String()
}
// summarizeContent summarizes the content of a chunk
func summarizeContent(content string) string {
cleaned := strings.TrimSpace(content)
if cleaned == "" {
return "(empty)"
}
return strings.TrimSpace(string(cleaned))
}