tm_back/internal/company/recommendation.go

package company

import (
	"context"
	"encoding/base64"
	"encoding/json"
	"errors"
	"fmt"
	"io"
	"strings"
	"time"

	"github.com/redis/go-redis/v9"
	"golang.org/x/sync/errgroup"

	"tm/pkg/ai_summarizer"
)

var ErrAIRecommendationNotConfigured = errors.New("AI recommendation service is not configured")

const aiRecommendationCacheKeyPrefix = "ai:recommendations:"

const (
	recommendationFetchMaxAttempts  = 6
	recommendationFetchInitialDelay = 10 * time.Second
)

func normalizeRecommendationCompanyIDs(companyIDs []string) []string {
	normalized := make([]string, 0, len(companyIDs))
	seen := make(map[string]struct{}, len(companyIDs))
	for _, companyID := range companyIDs {
		clean := strings.TrimSpace(companyID)
		if clean == "" {
			continue
		}
		if _, ok := seen[clean]; ok {
			continue
		}
		seen[clean] = struct{}{}
		normalized = append(normalized, clean)
	}
	return normalized
}

func mergeRecommendedTenders(recommendationLists ...[]RecommendedTenderResponse) []RecommendedTenderResponse {
	merged := make([]RecommendedTenderResponse, 0)
	seen := make(map[string]struct{})
	for _, recommendations := range recommendationLists {
		for _, recommendation := range recommendations {
			tenderID := strings.TrimSpace(recommendation.TenderID)
			if tenderID == "" {
				continue
			}
			if _, ok := seen[tenderID]; ok {
				continue
			}
			seen[tenderID] = struct{}{}
			recommendation.TenderID = tenderID
			recommendation.Analysis = strings.TrimSpace(recommendation.Analysis)
			merged = append(merged, recommendation)
		}
	}
	return merged
}

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
	}

	companyID = strings.TrimSpace(companyID)
	if companyID == "" {
		return nil, errors.New("company ID is required")
	}

	s.invalidateAIRecommendationCache(ctx, companyID)

	result, err := s.startAIOnboardingInternal(ctx, companyID)
	if err != nil {
		return nil, err
	}

	s.scheduleRecommendationRefreshAfterOnboarding(companyID)

	return result, nil
}

// triggerAIOnboardingAsync re-indexes the company on the AI service and refreshes the recommendation cache.
// This is the only path (besides StartAIOnboarding) that calls the AI recommend endpoint.
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 and recommendation refresh", map[string]interface{}{
			"company_id": companyID,
		})

		s.invalidateAIRecommendationCache(ctx, companyID)

		if _, err := s.startAIOnboardingInternal(ctx, companyID); err != nil {
			s.logger.Error("Async AI company onboarding failed", map[string]interface{}{
				"company_id": companyID,
				"error":      err.Error(),
			})
			return
		}

		if err := s.fetchAndCacheAIRecommendationsWithRetry(ctx, companyID); err != nil {
			s.logger.Error("Failed to refresh AI recommendations after onboarding", map[string]interface{}{
				"company_id": companyID,
				"error":      err.Error(),
			})
			return
		}

		s.logger.Info("Async AI company onboarding and recommendation refresh completed", map[string]interface{}{
			"company_id": companyID,
		})
	}()
}

func (s *companyService) startAIOnboardingInternal(ctx context.Context, companyID string) (*OnboardingResponse, error) {
	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),
		"links_count":     len(company.Links),
		"has_website_url": websiteURL != "",
	})

	result, err := s.aiRecommendationClient.StartOnboarding(ctx, ai_summarizer.OnboardingRequest{
		CompanyID:  companyID,
		Documents:  documents,
		WebsiteURL: websiteURL,
		Links:      companyLinkURLs(company.Links),
	})
	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)
	}

	return &OnboardingResponse{Status: result.Status}, nil
}

// GetAIRecommendations returns cached recommendations only. The AI service is not called on read;
// cache is populated when a company is created, updated, or onboarded.
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 _, 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")
	}

	if cached, ok := s.getCachedAIRecommendations(ctx, companyID); ok {
		return cached, nil
	}

	s.logger.Info("AI recommendations cache miss; returning empty list", map[string]interface{}{
		"company_id": companyID,
	})

	return []RecommendedTenderResponse{}, nil
}

func (s *companyService) validateRecommendationCompanyIDs(ctx context.Context, companyIDs []string) error {
	companies, err := s.repository.GetByIDs(ctx, companyIDs)
	if err != nil {
		s.logger.Error("Failed to load companies for merged AI recommendations", map[string]interface{}{
			"company_ids": companyIDs,
			"error":       err.Error(),
		})
		return errors.New("company not found")
	}
	if len(companies) != len(companyIDs) {
		s.logger.Error("Some companies were not found for merged AI recommendations", map[string]interface{}{
			"requested_count": len(companyIDs),
			"loaded_count":    len(companies),
		})
		return errors.New("company not found")
	}
	return nil
}

func (s *companyService) getCachedAIRecommendationsOrEmpty(ctx context.Context, companyID string) []RecommendedTenderResponse {
	if cached, ok := s.getCachedAIRecommendations(ctx, companyID); ok {
		return cached
	}

	s.logger.Info("AI recommendations cache miss; returning empty list", map[string]interface{}{
		"company_id": companyID,
	})
	return []RecommendedTenderResponse{}
}

// GetMergedAIRecommendations unions cached AI recommendations across multiple companies.
func (s *companyService) GetMergedAIRecommendations(ctx context.Context, companyIDs []string) ([]RecommendedTenderResponse, error) {
	if s.aiRecommendationClient == nil {
		return nil, ErrAIRecommendationNotConfigured
	}

	normalized := normalizeRecommendationCompanyIDs(companyIDs)
	if len(normalized) == 0 {
		return []RecommendedTenderResponse{}, nil
	}

	if err := s.validateRecommendationCompanyIDs(ctx, normalized); err != nil {
		return nil, err
	}

	recommendationLists := make([][]RecommendedTenderResponse, len(normalized))
	group, groupCtx := errgroup.WithContext(ctx)
	for i, companyID := range normalized {
		i := i
		companyID := companyID
		group.Go(func() error {
			recommendationLists[i] = s.getCachedAIRecommendationsOrEmpty(groupCtx, companyID)
			return nil
		})
	}
	if err := group.Wait(); err != nil {
		return nil, err
	}

	return mergeRecommendedTenders(recommendationLists...), nil
}

func (s *companyService) scheduleRecommendationRefreshAfterOnboarding(companyID string) {
	if s.aiRecommendationClient == nil {
		return
	}

	companyID = strings.TrimSpace(companyID)
	if companyID == "" {
		return
	}

	go func() {
		ctx := context.Background()
		if err := s.fetchAndCacheAIRecommendationsWithRetry(ctx, companyID); err != nil {
			s.logger.Error("Failed to refresh AI recommendation cache after onboarding", map[string]interface{}{
				"company_id": companyID,
				"error":      err.Error(),
			})
		}
	}()
}

// fetchAndCacheAIRecommendationsWithRetry waits for the AI service to finish indexing after onboarding.
// Empty results are not cached so reads keep returning empty until real recommendations exist.
func (s *companyService) fetchAndCacheAIRecommendationsWithRetry(ctx context.Context, companyID string) error {
	delay := recommendationFetchInitialDelay

	for attempt := 1; attempt <= recommendationFetchMaxAttempts; attempt++ {
		if attempt > 1 {
			s.logger.Info("Retrying AI recommendation fetch after onboarding", map[string]interface{}{
				"company_id": companyID,
				"attempt":    attempt,
				"delay_sec":  int(delay.Seconds()),
			})
		} else {
			s.logger.Info("Waiting before first AI recommendation fetch after onboarding", map[string]interface{}{
				"company_id": companyID,
				"delay_sec":  int(delay.Seconds()),
			})
		}

		select {
		case <-ctx.Done():
			return ctx.Err()
		case <-time.After(delay):
		}

		if attempt > 1 {
			delay *= 2
		}

		responses, err := s.fetchAIRecommendations(ctx, companyID)
		if err != nil {
			if attempt == recommendationFetchMaxAttempts {
				return err
			}
			continue
		}

		if len(responses) == 0 {
			if attempt == recommendationFetchMaxAttempts {
				s.logger.Warn("AI returned no recommendations after onboarding retries; cache not updated", map[string]interface{}{
					"company_id": companyID,
					"attempts":   attempt,
				})
				return nil
			}
			continue
		}

		s.cacheAIRecommendations(ctx, companyID, responses)
		s.logger.Info("AI recommendation cache populated after onboarding", map[string]interface{}{
			"company_id": companyID,
			"count":      len(responses),
			"attempt":    attempt,
		})
		return nil
	}

	return nil
}

func (s *companyService) fetchAIRecommendations(ctx context.Context, companyID string) ([]RecommendedTenderResponse, error) {
	s.logger.Info("Fetching AI tender recommendations from AI service", 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,
		})
	}

	return responses, nil
}

func (s *companyService) getCachedAIRecommendations(ctx context.Context, companyID string) ([]RecommendedTenderResponse, bool) {
	if s.redisClient == nil {
		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
	}

	if len(responses) == 0 {
		_ = 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 || len(responses) == 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
	}

	expiration := s.recommendationCacheExpiration()
	if err := s.redisClient.Set(ctx, aiRecommendationCacheKey(companyID), string(encoded), expiration); err != nil {
		s.logger.Warn("Failed to store AI recommendation cache", map[string]interface{}{
			"company_id": companyID,
			"error":      err.Error(),
		})
	}
}

func (s *companyService) recommendationCacheExpiration() time.Duration {
	if s.recommendationCacheTTL > 0 {
		return s.recommendationCacheTTL
	}
	return 0
}

func (s *companyService) invalidateAIRecommendationCache(ctx context.Context, companyID string) {
	if s.redisClient == nil {
		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
}