Files
tm_back/internal/company/recommendation.go
T
Mazyar a2661651c9
continuous-integration/drone/push Build is passing
Enhance company service with AI recommendation caching and onboarding improvements
- Updated the `companyService` to include Redis caching for AI recommendations, improving performance and reducing redundant AI calls.
- Introduced asynchronous AI onboarding triggered after company profile updates, enhancing user experience by offloading processing.
- Added configuration for recommendation cache TTL in the `AISummarizerConfig`, allowing for flexible cache management.
- Implemented methods for caching, retrieving, and invalidating AI recommendations in the `companyService`, ensuring efficient data handling.

This update enhances the company's AI recommendation capabilities, providing faster responses and a more efficient onboarding process.
2026-06-23 13:24:45 +03:30

304 lines
8.6 KiB
Go

package company
import (
"context"
"encoding/base64"
"encoding/json"
"errors"
"fmt"
"io"
"strings"
"github.com/redis/go-redis/v9"
"tm/pkg/ai_summarizer"
)
var ErrAIRecommendationNotConfigured = errors.New("AI recommendation service is not configured")
const aiRecommendationCacheKeyPrefix = "ai:recommendations:"
func aiRecommendationCacheKey(companyID string) string {
return aiRecommendationCacheKeyPrefix + companyID
}
// AIRecommendationClient defines the interface for company tender recommendation AI operations.
type AIRecommendationClient interface {
StartOnboarding(ctx context.Context, reqBody ai_summarizer.OnboardingRequest) (*ai_summarizer.OnboardingResponse, error)
FetchRecommendations(ctx context.Context, reqBody ai_summarizer.RecommendRequest) ([]ai_summarizer.RecommendedTender, error)
}
type onboardingDocumentPayload struct {
Filename string `json:"filename"`
ContentType string `json:"content_type"`
Content string `json:"content"`
}
// StartAIOnboarding sends company profile data to the AI team to start recommendation onboarding.
func (s *companyService) StartAIOnboarding(ctx context.Context, companyID string) (*OnboardingResponse, error) {
if s.aiRecommendationClient == nil {
return nil, ErrAIRecommendationNotConfigured
}
if strings.TrimSpace(companyID) == "" {
return nil, errors.New("company ID is required")
}
company, err := s.repository.GetByID(ctx, companyID)
if err != nil {
s.logger.Error("Failed to load company for AI onboarding", map[string]interface{}{
"company_id": companyID,
"error": err.Error(),
})
return nil, errors.New("company not found")
}
documents, err := s.buildOnboardingDocuments(company.DocumentFileIDs)
if err != nil {
s.logger.Error("Failed to prepare company documents for AI onboarding", map[string]interface{}{
"company_id": companyID,
"error": err.Error(),
})
return nil, fmt.Errorf("failed to prepare company documents: %w", err)
}
websiteURL := ""
if company.Website != nil {
websiteURL = strings.TrimSpace(*company.Website)
}
s.logger.Info("Starting AI company onboarding", map[string]interface{}{
"company_id": companyID,
"documents_count": len(company.DocumentFileIDs),
"has_website_url": websiteURL != "",
})
result, err := s.aiRecommendationClient.StartOnboarding(ctx, ai_summarizer.OnboardingRequest{
CompanyID: companyID,
Documents: documents,
WebsiteURL: websiteURL,
})
if err != nil {
s.logger.Error("AI onboarding request failed", map[string]interface{}{
"company_id": companyID,
"error": err.Error(),
})
return nil, fmt.Errorf("failed to start AI onboarding: %w", err)
}
s.invalidateAIRecommendationCache(ctx, companyID)
return &OnboardingResponse{Status: result.Status}, nil
}
// triggerAIOnboardingAsync starts AI onboarding in the background after company profile changes.
func (s *companyService) triggerAIOnboardingAsync(companyID string) {
if s.aiRecommendationClient == nil {
return
}
companyID = strings.TrimSpace(companyID)
if companyID == "" {
return
}
go func() {
ctx := context.Background()
s.logger.Info("Starting async AI company onboarding", map[string]interface{}{
"company_id": companyID,
})
if _, err := s.StartAIOnboarding(ctx, companyID); err != nil {
s.logger.Error("Async AI company onboarding failed", map[string]interface{}{
"company_id": companyID,
"error": err.Error(),
})
return
}
s.logger.Info("Async AI company onboarding completed", map[string]interface{}{
"company_id": companyID,
})
}()
}
// GetAIRecommendations retrieves ranked tender recommendations from the AI team.
func (s *companyService) GetAIRecommendations(ctx context.Context, companyID string) ([]RecommendedTenderResponse, error) {
if s.aiRecommendationClient == nil {
return nil, ErrAIRecommendationNotConfigured
}
companyID = strings.TrimSpace(companyID)
if companyID == "" {
return nil, errors.New("company ID is required")
}
if cached, ok := s.getCachedAIRecommendations(ctx, companyID); ok {
return cached, nil
}
if _, err := s.repository.GetByID(ctx, companyID); err != nil {
s.logger.Error("Failed to load company for AI recommendations", map[string]interface{}{
"company_id": companyID,
"error": err.Error(),
})
return nil, errors.New("company not found")
}
s.logger.Info("Fetching AI tender recommendations", map[string]interface{}{
"company_id": companyID,
})
items, err := s.aiRecommendationClient.FetchRecommendations(ctx, ai_summarizer.RecommendRequest{
CompanyID: companyID,
})
if err != nil {
s.logger.Error("AI recommend request failed", map[string]interface{}{
"company_id": companyID,
"error": err.Error(),
})
return nil, fmt.Errorf("failed to fetch AI recommendations: %w", err)
}
responses := make([]RecommendedTenderResponse, 0, len(items))
for _, item := range items {
responses = append(responses, RecommendedTenderResponse{
Rank: item.Rank,
TenderID: item.TenderID,
Analysis: item.Analysis,
})
}
s.cacheAIRecommendations(ctx, companyID, responses)
return responses, nil
}
func (s *companyService) getCachedAIRecommendations(ctx context.Context, companyID string) ([]RecommendedTenderResponse, bool) {
if s.redisClient == nil || s.recommendationCacheTTL <= 0 {
return nil, false
}
raw, err := s.redisClient.Get(ctx, aiRecommendationCacheKey(companyID))
if err != nil {
if err != redis.Nil {
s.logger.Warn("Failed to read AI recommendation cache", map[string]interface{}{
"company_id": companyID,
"error": err.Error(),
})
}
return nil, false
}
var responses []RecommendedTenderResponse
if err := json.Unmarshal([]byte(raw), &responses); err != nil {
s.logger.Warn("Failed to decode AI recommendation cache", map[string]interface{}{
"company_id": companyID,
"error": err.Error(),
})
_ = s.redisClient.Del(ctx, aiRecommendationCacheKey(companyID))
return nil, false
}
s.logger.Debug("AI tender recommendations served from cache", map[string]interface{}{
"company_id": companyID,
"count": len(responses),
})
return responses, true
}
func (s *companyService) cacheAIRecommendations(ctx context.Context, companyID string, responses []RecommendedTenderResponse) {
if s.redisClient == nil || s.recommendationCacheTTL <= 0 {
return
}
encoded, err := json.Marshal(responses)
if err != nil {
s.logger.Warn("Failed to encode AI recommendations for cache", map[string]interface{}{
"company_id": companyID,
"error": err.Error(),
})
return
}
if err := s.redisClient.Set(ctx, aiRecommendationCacheKey(companyID), string(encoded), s.recommendationCacheTTL); err != nil {
s.logger.Warn("Failed to store AI recommendation cache", map[string]interface{}{
"company_id": companyID,
"error": err.Error(),
})
}
}
func (s *companyService) invalidateAIRecommendationCache(ctx context.Context, companyID string) {
if s.redisClient == nil || s.recommendationCacheTTL <= 0 {
return
}
if err := s.redisClient.Del(ctx, aiRecommendationCacheKey(companyID)); err != nil {
s.logger.Warn("Failed to invalidate AI recommendation cache", map[string]interface{}{
"company_id": companyID,
"error": err.Error(),
})
}
}
func (s *companyService) buildOnboardingDocuments(fileIDs []string) (string, error) {
if len(fileIDs) == 0 {
return "[]", nil
}
if s.fileStore == nil {
return "", errors.New("file storage is not configured")
}
payloads := make([]onboardingDocumentPayload, 0, len(fileIDs))
for _, fileID := range fileIDs {
if strings.TrimSpace(fileID) == "" {
continue
}
reader, info, err := s.fileStore.Download(fileID)
if err != nil {
s.logger.Warn("Skipping company document for AI onboarding", map[string]interface{}{
"file_id": fileID,
"error": err.Error(),
})
continue
}
content, readErr := io.ReadAll(reader)
closeErr := reader.Close()
if readErr != nil {
return "", fmt.Errorf("failed to read document %s: %w", fileID, readErr)
}
if closeErr != nil {
s.logger.Warn("Failed to close company document reader", map[string]interface{}{
"file_id": fileID,
"error": closeErr.Error(),
})
}
filename := fileID
contentType := "application/octet-stream"
if info != nil {
if info.Filename != "" {
filename = info.Filename
}
if info.ContentType != "" {
contentType = info.ContentType
}
}
payloads = append(payloads, onboardingDocumentPayload{
Filename: filename,
ContentType: contentType,
Content: base64.StdEncoding.EncodeToString(content),
})
}
encoded, err := json.Marshal(payloads)
if err != nil {
return "", fmt.Errorf("failed to encode company documents: %w", err)
}
return string(encoded), nil
}