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refactor: initialize expert catalog from initdb

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This commit is contained in:
yanweidong
2026-07-23 14:24:01 +08:00
parent bb90ed1d38
commit 6e7be2f3a4
8 changed files with 206 additions and 124 deletions
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2677
backend/internal/models/experts_catalog.json
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File diff suppressed because one or more lines are too long

105
backend/internal/models/migrations.go
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@@ -1,7 +1,6 @@
package models
import (
_ "embed"
"encoding/json"
"fmt"
"strings"
@@ -32,8 +31,6 @@ func runVersionedMigrations(database *gorm.DB) error {
migrations := []versionedMigration{
{version: 1, name: "normalize_project_identifiers", run: normalizeLegacyProjectIdentifiers},
{version: 2, name: "deduplicate_project_tags", run: deduplicateLegacyProjectTags},
{version: 3, name: "seed_ai_experts", run: seedAIExperts},
{version: 4, name: "normalize_ai_expert_categories", run: normalizeAIExpertCategories},
}
for _, migration := range migrations {
// Connection callbacks can provide an initialized Gorm session. Start each
@@ -66,108 +63,6 @@ func runVersionedMigrations(database *gorm.DB) error {
return nil
}
//go:embed experts_catalog.json
var expertCatalogJSON []byte
type embeddedExpertCatalog struct {
Source string `json:"source"`
Reference string `json:"reference"`
License string `json:"license"`
Experts []embeddedExpertCatalogItem `json:"experts"`
}
type embeddedExpertCatalogItem struct {
Slug string `json:"slug"`
Category string `json:"category"`
CategoryName string `json:"categoryName"`
Name string `json:"name"`
Description string `json:"description"`
Emoji string `json:"emoji"`
Color string `json:"color"`
SystemPrompt string `json:"systemPrompt"`
}
func seedAIExperts(tx *gorm.DB) (map[string]int, error) {
catalog, categories, err := loadAIExpertCatalog(tx)
if err != nil {
return nil, err
}
records := make([]SenlinAgentAIExpertItem, 0, len(catalog.Experts))
for _, expert := range catalog.Experts {
category := categories[expert.Category]
records = append(records, SenlinAgentAIExpertItem{
Slug: expert.Slug, CategoryID: category.ID, CategoryIdentity: category.Identity,
Category: expert.Category, CategoryName: expert.CategoryName,
Name: expert.Name, Description: expert.Description, Emoji: expert.Emoji,
Color: expert.Color, SystemPrompt: expert.SystemPrompt, Source: catalog.Source,
Reference: catalog.Reference, SourceLicense: catalog.License, Enabled: true,
})
}
if len(records) > 0 {
if err := tx.CreateInBatches(&records, 25).Error; err != nil {
return nil, err
}
}
return map[string]int{"inserted": len(records)}, nil
}
func normalizeAIExpertCategories(tx *gorm.DB) (map[string]int, error) {
catalog, categories, err := loadAIExpertCatalog(tx)
if err != nil {
return nil, err
}
linked := 0
for _, expert := range catalog.Experts {
category := categories[expert.Category]
result := tx.Model(&SenlinAgentAIExpertItem{}).Where("slug = ?", expert.Slug).Updates(map[string]any{
"category_id": category.ID,
"category_identity": category.Identity,
"reference": catalog.Reference,
})
if result.Error != nil {
return nil, result.Error
}
linked += int(result.RowsAffected)
}
return map[string]int{"categories": len(categories), "linked": linked}, nil
}
func loadAIExpertCatalog(tx *gorm.DB) (embeddedExpertCatalog, map[string]SenlinAgentAIExpertCategory, error) {
var catalog embeddedExpertCatalog
if err := json.Unmarshal(expertCatalogJSON, &catalog); err != nil {
return catalog, nil, fmt.Errorf("decode embedded AI expert catalog: %w", err)
}
categoryNames := make(map[string]string)
categoryOrder := make([]string, 0)
for _, expert := range catalog.Experts {
if _, exists := categoryNames[expert.Category]; exists {
continue
}
categoryNames[expert.Category] = expert.CategoryName
categoryOrder = append(categoryOrder, expert.Category)
}
categories := make(map[string]SenlinAgentAIExpertCategory, len(categoryOrder))
for _, slug := range categoryOrder {
category := SenlinAgentAIExpertCategory{Slug: slug}
if err := tx.Where("slug = ?", slug).
Attrs(SenlinAgentAIExpertCategory{Name: categoryNames[slug]}).
FirstOrCreate(&category).Error; err != nil {
return catalog, nil, err
}
if category.Name != categoryNames[slug] {
category.Name = categoryNames[slug]
if err := tx.Model(&category).Update("name", category.Name).Error; err != nil {
return catalog, nil, err
}
}
categories[slug] = category
}
return catalog, categories, nil
}
func normalizeLegacyProjectIdentifiers(tx *gorm.DB) (map[string]int, error) {
var projects []SenlinAgentProject
if err := tx.Model(&SenlinAgentProject{}).Select("id", "owner_id", "identifier").Order("owner_id asc, id asc").Find(&projects).Error; err != nil {

18
backend/internal/models/migrations_test.go
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@@ -57,28 +57,14 @@ func TestAutoMigrateUpgradesLegacyProjectsAndTagsWithoutLosingAssociations(t *te
var migrationCount int64
require.NoError(t, database.Table("senlin_agent_schema_migrations").Count(&migrationCount).Error)
require.Equal(t, int64(4), migrationCount)
require.Equal(t, int64(2), migrationCount)
var auditDetails []string
require.NoError(t, database.Table("senlin_agent_schema_migrations").Order("version asc").Pluck("details", &auditDetails).Error)
require.Contains(t, auditDetails[0], `"updated":3`)
require.Contains(t, auditDetails[1], `"deduplicated":1`)
require.Contains(t, auditDetails[2], `"inserted":267`)
require.Contains(t, auditDetails[3], `"categories":19`)
require.Contains(t, auditDetails[3], `"linked":267`)
var categoryCount int64
require.NoError(t, database.Model(&SenlinAgentAIExpertCategory{}).Count(&categoryCount).Error)
require.Equal(t, int64(19), categoryCount)
var expertCount int64
require.NoError(t, database.Model(&SenlinAgentAIExpertItem{}).Count(&expertCount).Error)
require.Equal(t, int64(267), expertCount)
var expert SenlinAgentAIExpertItem
require.NoError(t, database.Preload("ExpertCategory").Where("slug = ?", "academic-geographer").First(&expert).Error)
require.Equal(t, "academic", expert.ExpertCategory.Slug)
require.Equal(t, "学术研究", expert.ExpertCategory.Name)
require.Equal(t, "https://ao.aiolaola.com/experts", expert.Reference)
require.NoError(t, AutoMigrate(database), "versioned migrations must be safe to run again")
require.NoError(t, database.Table("senlin_agent_schema_migrations").Count(&migrationCount).Error)
require.Equal(t, int64(4), migrationCount)
require.Equal(t, int64(2), migrationCount)
require.Error(t, database.Exec(`INSERT INTO senlin_agent_projects (owner_id, name, identifier) VALUES (7, 'still duplicate', 'DUP')`).Error)
require.Error(t, database.Exec(`INSERT INTO senlin_agent_tags (project_id, name) VALUES (1, 'UI')`).Error)