package agent

import (
	"context"
	"encoding/json"
	"fmt"
	"io"
	"net/http"
	"net/url"
	"regexp"
	"strings"
	"time"

	"github.com/gooseek/backend/internal/llm"
	"github.com/gooseek/backend/internal/prompts"
	"github.com/gooseek/backend/internal/search"
	"github.com/gooseek/backend/internal/session"
	"github.com/gooseek/backend/internal/types"
	"github.com/google/uuid"
	"golang.org/x/sync/errgroup"
)

type Mode string

const (
	ModeSpeed    Mode = "speed"
	ModeBalanced Mode = "balanced"
	ModeQuality  Mode = "quality"
)

type OrchestratorConfig struct {
	LLM                llm.Client
	SearchClient       *search.SearXNGClient
	Mode               Mode
	FocusMode          FocusMode
	Sources            []string
	FileIDs            []string
	FileContext        string
	CollectionID       string
	CollectionContext  string
	SystemInstructions string
	Locale             string
	MemoryContext      string
	UserMemory         string
	AnswerMode         string
	ResponsePrefs      *ResponsePrefs
	LearningMode       bool
	EnableDeepResearch bool
	EnableClarifying   bool
	DiscoverSvcURL      string
	Crawl4AIURL         string
	CollectionSvcURL    string
	FileSvcURL          string
	TravelSvcURL        string
	TravelPayoutsToken  string
	TravelPayoutsMarker string
	PhotoCache          *PhotoCacheService
}

type DigestResponse struct {
	SummaryRu    string          `json:"summaryRu"`
	Citations    []DigestCitation `json:"citations"`
	FollowUp     []string        `json:"followUp"`
	SourcesCount int             `json:"sourcesCount"`
	ClusterTitle string          `json:"clusterTitle"`
}

type DigestCitation struct {
	Index  int    `json:"index"`
	URL    string `json:"url"`
	Title  string `json:"title"`
	Domain string `json:"domain"`
}

type PreScrapedArticle struct {
	Title   string
	Content string
	URL     string
}

type ResponsePrefs struct {
	Format string `json:"format,omitempty"`
	Length string `json:"length,omitempty"`
	Tone   string `json:"tone,omitempty"`
}

type OrchestratorInput struct {
	ChatHistory []llm.Message
	FollowUp    string
	Config      OrchestratorConfig
}

func RunOrchestrator(ctx context.Context, sess *session.Session, input OrchestratorInput) error {
	if input.Config.AnswerMode == "travel" {
		return RunTravelOrchestrator(ctx, sess, input)
	}

	if input.Config.AnswerMode == "learning" || input.Config.LearningMode {
		return RunLearningOrchestrator(ctx, sess, input)
	}

	detectedLang := detectLanguage(input.FollowUp)
	isArticleSummary := strings.HasPrefix(strings.TrimSpace(input.FollowUp), "Summary: ")

	if input.Config.FocusMode == "" {
		input.Config.FocusMode = DetectFocusMode(input.FollowUp)
	}

	if input.Config.EnableDeepResearch && input.Config.Mode == ModeQuality {
		return runDeepResearchMode(ctx, sess, input, detectedLang)
	}

	if input.Config.Mode == ModeSpeed && !isArticleSummary {
		return runSpeedMode(ctx, sess, input, detectedLang)
	}

	return runFullMode(ctx, sess, input, detectedLang, isArticleSummary)
}

func runDeepResearchMode(ctx context.Context, sess *session.Session, input OrchestratorInput, lang string) error {
	sess.EmitBlock(types.NewResearchBlock(uuid.New().String()))

	researcher := NewDeepResearcher(DeepResearchConfig{
		LLM:              input.Config.LLM,
		SearchClient:     input.Config.SearchClient,
		FocusMode:        input.Config.FocusMode,
		Locale:           input.Config.Locale,
		MaxSearchQueries: 30,
		MaxSources:       100,
		MaxIterations:    5,
		Timeout:          5 * time.Minute,
	}, sess)

	result, err := researcher.Research(ctx, input.FollowUp)
	if err != nil {
		sess.EmitError(err)
		return err
	}

	sess.EmitBlock(types.NewSourceBlock(uuid.New().String(), result.Sources))

	if len(result.FollowUpQueries) > 0 {
		sess.EmitBlock(types.NewWidgetBlock(uuid.New().String(), "related_questions", map[string]interface{}{
			"questions": result.FollowUpQueries,
		}))
	}

	sess.EmitResearchComplete()
	sess.EmitEnd()

	return nil
}

func generateClarifyingQuestions(ctx context.Context, llmClient llm.Client, query string) ([]string, error) {
	prompt := fmt.Sprintf(`Analyze this query and determine if clarifying questions would help provide a better answer.

Query: %s

If the query is:
- Clear and specific → respond with "CLEAR"
- Ambiguous or could benefit from clarification → provide 2-3 short clarifying questions

Format:
CLEAR
or
QUESTION: [question 1]
QUESTION: [question 2]
QUESTION: [question 3]`, query)

	result, err := llmClient.GenerateText(ctx, llm.StreamRequest{
		Messages: []llm.Message{{Role: "user", Content: prompt}},
	})
	if err != nil {
		return nil, err
	}

	if strings.Contains(strings.ToUpper(result), "CLEAR") {
		return nil, nil
	}

	var questions []string
	for _, line := range strings.Split(result, "\n") {
		line = strings.TrimSpace(line)
		if strings.HasPrefix(line, "QUESTION:") {
			q := strings.TrimSpace(strings.TrimPrefix(line, "QUESTION:"))
			if q != "" {
				questions = append(questions, q)
			}
		}
	}

	return questions, nil
}

func generateRelatedQuestions(ctx context.Context, llmClient llm.Client, query, answer string, locale string) []string {
	langInstruction := ""
	if locale == "ru" {
		langInstruction = "Generate questions in Russian."
	}

	prompt := fmt.Sprintf(`Based on this query and answer, generate 3-4 related follow-up questions the user might want to explore.

Query: %s

Answer summary: %s

%s
Format: One question per line, no numbering or bullets.`, query, truncateForPrompt(answer, 500), langInstruction)

	result, err := llmClient.GenerateText(ctx, llm.StreamRequest{
		Messages: []llm.Message{{Role: "user", Content: prompt}},
	})
	if err != nil {
		return nil
	}

	var questions []string
	for _, line := range strings.Split(result, "\n") {
		line = strings.TrimSpace(line)
		if line != "" && len(line) > 10 && strings.Contains(line, "?") {
			line = strings.TrimLeft(line, "0123456789.-•* ")
			if line != "" {
				questions = append(questions, line)
			}
		}
	}

	if len(questions) > 4 {
		questions = questions[:4]
	}

	return questions
}

func truncateForPrompt(s string, maxLen int) string {
	if len(s) <= maxLen {
		return s
	}
	return s[:maxLen] + "..."
}

func buildEnhancedContext(input OrchestratorInput) string {
	var ctx strings.Builder

	if input.Config.UserMemory != "" {
		ctx.WriteString("## User Preferences\n")
		ctx.WriteString(input.Config.UserMemory)
		ctx.WriteString("\n\n")
	}

	if input.Config.CollectionContext != "" {
		ctx.WriteString("## Collection Context\n")
		ctx.WriteString(input.Config.CollectionContext)
		ctx.WriteString("\n\n")
	}

	if input.Config.FileContext != "" {
		ctx.WriteString("## Uploaded Files Content\n")
		ctx.WriteString(input.Config.FileContext)
		ctx.WriteString("\n\n")
	}

	if input.Config.MemoryContext != "" {
		ctx.WriteString("## Previous Context\n")
		ctx.WriteString(input.Config.MemoryContext)
		ctx.WriteString("\n\n")
	}

	return ctx.String()
}

func fetchPreGeneratedDigest(ctx context.Context, discoverURL, articleURL string) (*DigestResponse, error) {
	if discoverURL == "" {
		return nil, nil
	}

	reqURL := fmt.Sprintf("%s/api/v1/discover/digest?url=%s",
		strings.TrimSuffix(discoverURL, "/"),
		url.QueryEscape(articleURL))

	req, err := http.NewRequestWithContext(ctx, "GET", reqURL, nil)
	if err != nil {
		return nil, err
	}

	client := &http.Client{Timeout: 3 * time.Second}
	resp, err := client.Do(req)
	if err != nil {
		return nil, err
	}
	defer resp.Body.Close()

	if resp.StatusCode != http.StatusOK {
		return nil, nil
	}

	var digest DigestResponse
	if err := json.NewDecoder(resp.Body).Decode(&digest); err != nil {
		return nil, err
	}

	if digest.SummaryRu != "" && len(digest.Citations) > 0 {
		return &digest, nil
	}

	return nil, nil
}

func preScrapeArticleURL(ctx context.Context, crawl4aiURL, articleURL string) (*PreScrapedArticle, error) {
	if crawl4aiURL != "" {
		article, err := scrapeWithCrawl4AI(ctx, crawl4aiURL, articleURL)
		if err == nil && article != nil {
			return article, nil
		}
	}

	return scrapeDirectly(ctx, articleURL)
}

func scrapeWithCrawl4AI(ctx context.Context, crawl4aiURL, articleURL string) (*PreScrapedArticle, error) {
	reqBody := fmt.Sprintf(`{
		"urls": ["%s"],
		"crawler_config": {
			"type": "CrawlerRunConfig",
			"params": {
				"cache_mode": "default",
				"page_timeout": 20000
			}
		}
	}`, articleURL)

	req, err := http.NewRequestWithContext(ctx, "POST", crawl4aiURL+"/crawl", strings.NewReader(reqBody))
	if err != nil {
		return nil, err
	}
	req.Header.Set("Content-Type", "application/json")

	client := &http.Client{Timeout: 25 * time.Second}
	resp, err := client.Do(req)
	if err != nil {
		return nil, err
	}
	defer resp.Body.Close()

	if resp.StatusCode != http.StatusOK {
		return nil, fmt.Errorf("Crawl4AI returned status %d", resp.StatusCode)
	}

	body, err := io.ReadAll(resp.Body)
	if err != nil {
		return nil, err
	}

	markdown := extractMarkdownFromCrawl4AI(string(body))
	title := extractTitleFromCrawl4AI(string(body))

	if len(markdown) > 100 {
		content := markdown
		if len(content) > 15000 {
			content = content[:15000]
		}
		return &PreScrapedArticle{
			Title:   title,
			Content: content,
			URL:     articleURL,
		}, nil
	}

	return nil, fmt.Errorf("insufficient content from Crawl4AI")
}

func scrapeDirectly(ctx context.Context, articleURL string) (*PreScrapedArticle, error) {
	req, err := http.NewRequestWithContext(ctx, "GET", articleURL, nil)
	if err != nil {
		return nil, err
	}
	req.Header.Set("User-Agent", "GooSeek-Agent/1.0")
	req.Header.Set("Accept", "text/html")

	client := &http.Client{Timeout: 10 * time.Second}
	resp, err := client.Do(req)
	if err != nil {
		return nil, err
	}
	defer resp.Body.Close()

	if resp.StatusCode != http.StatusOK {
		return nil, fmt.Errorf("HTTP %d", resp.StatusCode)
	}

	body, err := io.ReadAll(resp.Body)
	if err != nil {
		return nil, err
	}

	html := string(body)
	title := extractHTMLTitle(html)
	content := extractTextContent(html)

	if len(content) < 100 {
		return nil, fmt.Errorf("insufficient content")
	}

	if len(content) > 15000 {
		content = content[:15000]
	}

	return &PreScrapedArticle{
		Title:   title,
		Content: content,
		URL:     articleURL,
	}, nil
}

var (
	titleRegex   = regexp.MustCompile(`<title[^>]*>([^<]+)</title>`)
	scriptRegex  = regexp.MustCompile(`(?s)<script[^>]*>.*?</script>`)
	styleRegex   = regexp.MustCompile(`(?s)<style[^>]*>.*?</style>`)
	tagRegex     = regexp.MustCompile(`<[^>]+>`)
	spaceRegex   = regexp.MustCompile(`\s+`)
)

func extractHTMLTitle(html string) string {
	matches := titleRegex.FindStringSubmatch(html)
	if len(matches) > 1 {
		return strings.TrimSpace(matches[1])
	}
	return ""
}

func extractTextContent(html string) string {
	bodyStart := strings.Index(strings.ToLower(html), "<body")
	bodyEnd := strings.Index(strings.ToLower(html), "</body>")

	if bodyStart != -1 && bodyEnd != -1 && bodyEnd > bodyStart {
		html = html[bodyStart:bodyEnd]
	}

	html = scriptRegex.ReplaceAllString(html, "")
	html = styleRegex.ReplaceAllString(html, "")
	html = tagRegex.ReplaceAllString(html, " ")
	html = spaceRegex.ReplaceAllString(html, " ")

	return strings.TrimSpace(html)
}

func extractMarkdownFromCrawl4AI(response string) string {
	if idx := strings.Index(response, `"raw_markdown"`); idx != -1 {
		start := idx + len(`"raw_markdown"`)
		if colonIdx := strings.Index(response[start:], ":"); colonIdx != -1 {
			start += colonIdx + 1
			for start < len(response) && (response[start] == ' ' || response[start] == '"') {
				start++
			}
			end := strings.Index(response[start:], `"`)
			if end > 0 {
				return response[start : start+end]
			}
		}
	}
	return ""
}

func extractTitleFromCrawl4AI(response string) string {
	if idx := strings.Index(response, `"title"`); idx != -1 {
		start := idx + len(`"title"`)
		if colonIdx := strings.Index(response[start:], ":"); colonIdx != -1 {
			start += colonIdx + 1
			for start < len(response) && (response[start] == ' ' || response[start] == '"') {
				start++
			}
			end := strings.Index(response[start:], `"`)
			if end > 0 {
				return response[start : start+end]
			}
		}
	}
	return ""
}

func runSpeedMode(ctx context.Context, sess *session.Session, input OrchestratorInput, detectedLang string) error {
	classification := fastClassify(input.FollowUp, input.ChatHistory)
	searchQuery := classification.StandaloneFollowUp
	if searchQuery == "" {
		searchQuery = input.FollowUp
	}
	queries := generateSearchQueries(searchQuery)

	researchBlockID := uuid.New().String()
	sess.EmitBlock(types.NewResearchBlock(researchBlockID))

	var searchResults []types.Chunk
	var mediaResult *search.MediaSearchResult

	g, gctx := errgroup.WithContext(ctx)

	g.Go(func() error {
		results, err := parallelSearch(gctx, input.Config.SearchClient, queries)
		if err != nil {
			return nil
		}
		searchResults = results
		return nil
	})

	g.Go(func() error {
		result, err := input.Config.SearchClient.SearchMedia(gctx, searchQuery, &search.MediaSearchOptions{
			MaxImages: 6,
			MaxVideos: 4,
		})
		if err != nil {
			return nil
		}
		mediaResult = result
		return nil
	})

	_ = g.Wait()

	if len(searchResults) > 0 {
		sess.EmitBlock(types.NewSourceBlock(uuid.New().String(), searchResults))
	}

	if mediaResult != nil {
		if len(mediaResult.Images) > 0 {
			sess.EmitBlock(types.NewWidgetBlock(uuid.New().String(), "image_gallery", map[string]interface{}{
				"images": mediaResult.Images,
				"layout": "carousel",
			}))
		}
		if len(mediaResult.Videos) > 0 {
			sess.EmitBlock(types.NewWidgetBlock(uuid.New().String(), "videos", map[string]interface{}{
				"items": mediaResult.Videos,
				"title": "",
			}))
		}
	}

	sess.EmitResearchComplete()

	queryComplexity := search.EstimateQueryComplexity(searchQuery)
	adaptiveTopK := search.ComputeAdaptiveTopK(len(searchResults), queryComplexity, "speed")
	rankedResults := search.RerankBM25(searchResults, searchQuery, adaptiveTopK)

	finalContext := buildContext(rankedResults, 15, 250)

	writerPrompt := prompts.GetWriterPrompt(prompts.WriterConfig{
		Context:            finalContext,
		SystemInstructions: input.Config.SystemInstructions,
		Mode:               string(input.Config.Mode),
		Locale:             input.Config.Locale,
		MemoryContext:      input.Config.MemoryContext,
		AnswerMode:         input.Config.AnswerMode,
		DetectedLanguage:   detectedLang,
		IsArticleSummary:   false,
	})

	messages := []llm.Message{
		{Role: llm.RoleSystem, Content: writerPrompt},
	}
	messages = append(messages, input.ChatHistory...)
	messages = append(messages, llm.Message{Role: llm.RoleUser, Content: input.FollowUp})

	return streamResponse(ctx, sess, input.Config.LLM, messages, 2048, input.FollowUp, input.Config.Locale)
}

func runFullMode(ctx context.Context, sess *session.Session, input OrchestratorInput, detectedLang string, isArticleSummary bool) error {
	if input.Config.EnableClarifying && !isArticleSummary && input.Config.Mode == ModeQuality {
		clarifying, err := generateClarifyingQuestions(ctx, input.Config.LLM, input.FollowUp)
		if err == nil && len(clarifying) > 0 {
		sess.EmitBlock(types.NewWidgetBlock(uuid.New().String(), "clarifying", map[string]interface{}{
			"questions": clarifying,
			"query":     input.FollowUp,
		}))
		return nil
		}
	}

	enhancedContext := buildEnhancedContext(input)
	if enhancedContext != "" {
		input.Config.MemoryContext = enhancedContext + input.Config.MemoryContext
	}

	var preScrapedArticle *PreScrapedArticle
	var articleURL string

	if isArticleSummary {
		articleURL = strings.TrimSpace(strings.TrimPrefix(strings.TrimSpace(input.FollowUp), "Summary: "))

		digestCtx, digestCancel := context.WithTimeout(ctx, 3*time.Second)
		scrapeCtx, scrapeCancel := context.WithTimeout(ctx, 25*time.Second)

		digestCh := make(chan *DigestResponse, 1)
		scrapeCh := make(chan *PreScrapedArticle, 1)

		go func() {
			defer digestCancel()
			digest, _ := fetchPreGeneratedDigest(digestCtx, input.Config.DiscoverSvcURL, articleURL)
			digestCh <- digest
		}()

		go func() {
			defer scrapeCancel()
			article, _ := preScrapeArticleURL(scrapeCtx, input.Config.Crawl4AIURL, articleURL)
			scrapeCh <- article
		}()

		digest := <-digestCh
		preScrapedArticle = <-scrapeCh

		if digest != nil {
			chunks := make([]types.Chunk, len(digest.Citations))
			for i, c := range digest.Citations {
				chunks[i] = types.Chunk{
					Content: c.Title,
					Metadata: map[string]string{
						"url":    c.URL,
						"title":  c.Title,
						"domain": c.Domain,
					},
				}
			}
			sess.EmitBlock(types.NewSourceBlock(uuid.New().String(), chunks))
			sess.EmitResearchComplete()

			summaryText := digest.SummaryRu
			if len(digest.FollowUp) > 0 {
				summaryText += "\n\n---\n"
				for _, q := range digest.FollowUp {
					summaryText += "> " + q + "\n"
				}
			}
			sess.EmitBlock(types.NewTextBlock(uuid.New().String(), summaryText))
			sess.EmitEnd()
			return nil
		}
	}

	classification, err := classify(ctx, input.Config.LLM, input.FollowUp, input.ChatHistory, input.Config.Locale, detectedLang)
	if err != nil {
		classification = &ClassificationResult{
			StandaloneFollowUp: input.FollowUp,
			SkipSearch:         false,
		}
	}

	if isArticleSummary && classification.SkipSearch {
		classification.SkipSearch = false
	}

	g, gctx := errgroup.WithContext(ctx)

	var searchResults []types.Chunk
	var mediaResult *search.MediaSearchResult

	mediaQuery := classification.StandaloneFollowUp
	if mediaQuery == "" {
		mediaQuery = input.FollowUp
	}

	effectiveFollowUp := input.FollowUp
	if isArticleSummary && preScrapedArticle != nil && preScrapedArticle.Title != "" {
		effectiveFollowUp = fmt.Sprintf("Summary: %s\nArticle title: %s", preScrapedArticle.URL, preScrapedArticle.Title)
		if classification.StandaloneFollowUp != "" {
			classification.StandaloneFollowUp = preScrapedArticle.Title + " " + classification.StandaloneFollowUp
		} else {
			classification.StandaloneFollowUp = preScrapedArticle.Title
		}
	}

	if !classification.SkipSearch {
		g.Go(func() error {
			results, err := research(gctx, sess, input.Config.LLM, input.Config.SearchClient, ResearchInput{
				ChatHistory:      input.ChatHistory,
				FollowUp:         effectiveFollowUp,
				Classification:   classification,
				Mode:             input.Config.Mode,
				Sources:          input.Config.Sources,
				Locale:           input.Config.Locale,
				DetectedLang:     detectedLang,
				IsArticleSummary: isArticleSummary,
			})
			if err != nil {
				return nil
			}
			searchResults = results
			return nil
		})
	}

	if !isArticleSummary {
		g.Go(func() error {
			result, err := input.Config.SearchClient.SearchMedia(gctx, mediaQuery, &search.MediaSearchOptions{
				MaxImages: 8,
				MaxVideos: 6,
			})
			if err != nil {
				return nil
			}
			mediaResult = result
			return nil
		})
	}

	_ = g.Wait()

	if isArticleSummary && preScrapedArticle != nil {
		alreadyHasURL := false
		for _, r := range searchResults {
			if strings.Contains(r.Metadata["url"], preScrapedArticle.URL) {
				alreadyHasURL = true
				break
			}
		}
		if !alreadyHasURL {
			prependChunk := types.Chunk{
				Content: preScrapedArticle.Content,
				Metadata: map[string]string{
					"url":   preScrapedArticle.URL,
					"title": preScrapedArticle.Title,
				},
			}
			searchResults = append([]types.Chunk{prependChunk}, searchResults...)
		}
	}

	if len(searchResults) > 0 {
		sess.EmitBlock(types.NewSourceBlock(uuid.New().String(), searchResults))
	}

	if mediaResult != nil {
		if len(mediaResult.Images) > 0 {
			sess.EmitBlock(types.NewWidgetBlock(uuid.New().String(), "image_gallery", map[string]interface{}{
				"images": mediaResult.Images,
				"layout": "carousel",
			}))
		}
		if len(mediaResult.Videos) > 0 {
			sess.EmitBlock(types.NewWidgetBlock(uuid.New().String(), "videos", map[string]interface{}{
				"items": mediaResult.Videos,
				"title": "",
			}))
		}
	}

	sess.EmitResearchComplete()

	maxResults := 25
	maxContent := 320
	if isArticleSummary {
		maxResults = 30
		maxContent = 2000
	}

	rankedResults := rankByRelevance(searchResults, input.FollowUp)
	if len(rankedResults) > maxResults {
		rankedResults = rankedResults[:maxResults]
	}

	finalContext := buildContext(rankedResults, maxResults, maxContent)

	writerPrompt := prompts.GetWriterPrompt(prompts.WriterConfig{
		Context:            finalContext,
		SystemInstructions: input.Config.SystemInstructions,
		Mode:               string(input.Config.Mode),
		Locale:             input.Config.Locale,
		MemoryContext:      input.Config.MemoryContext,
		AnswerMode:         input.Config.AnswerMode,
		DetectedLanguage:   detectedLang,
		IsArticleSummary:   isArticleSummary,
	})

	messages := []llm.Message{
		{Role: llm.RoleSystem, Content: writerPrompt},
	}
	messages = append(messages, input.ChatHistory...)
	messages = append(messages, llm.Message{Role: llm.RoleUser, Content: input.FollowUp})

	maxTokens := 4096
	return streamResponse(ctx, sess, input.Config.LLM, messages, maxTokens, input.FollowUp, input.Config.Locale)
}

func streamResponse(ctx context.Context, sess *session.Session, client llm.Client, messages []llm.Message, maxTokens int, query string, locale string) error {
	stream, err := client.StreamText(ctx, llm.StreamRequest{
		Messages: messages,
		Options:  llm.StreamOptions{MaxTokens: maxTokens},
	})
	if err != nil {
		return err
	}

	var responseBlockID string
	var accumulatedText string

	for chunk := range stream {
		if chunk.ContentChunk == "" && responseBlockID == "" {
			continue
		}

		if responseBlockID == "" {
			responseBlockID = uuid.New().String()
			accumulatedText = chunk.ContentChunk
			sess.EmitBlock(types.NewTextBlock(responseBlockID, accumulatedText))
		} else if chunk.ContentChunk != "" {
			accumulatedText += chunk.ContentChunk
			sess.EmitTextChunk(responseBlockID, chunk.ContentChunk)
		}
	}

	if responseBlockID != "" {
		sess.UpdateBlock(responseBlockID, []session.Patch{
			{Op: "replace", Path: "/data", Value: accumulatedText},
		})
	}

	go func() {
		relatedCtx, cancel := context.WithTimeout(context.Background(), 5*time.Second)
		defer cancel()

		related := generateRelatedQuestions(relatedCtx, client, query, accumulatedText, locale)
		if len(related) > 0 {
			sess.EmitBlock(types.NewWidgetBlock(uuid.New().String(), "related_questions", map[string]interface{}{
				"questions": related,
			}))
		}
	}()

	sess.EmitEnd()
	return nil
}

func parallelSearch(ctx context.Context, client *search.SearXNGClient, queries []string) ([]types.Chunk, error) {
	results := make([]types.Chunk, 0)
	seen := make(map[string]bool)

	g, gctx := errgroup.WithContext(ctx)
	resultsCh := make(chan []types.SearchResult, len(queries))

	for _, q := range queries {
		query := q
		g.Go(func() error {
			resp, err := client.Search(gctx, query, &search.SearchOptions{
				Categories: []string{"general", "news"},
				PageNo:     1,
			})
			if err != nil {
				resultsCh <- nil
				return nil
			}
			resultsCh <- resp.Results
			return nil
		})
	}

	go func() {
		g.Wait()
		close(resultsCh)
	}()

	for batch := range resultsCh {
		for _, r := range batch {
			if r.URL != "" && !seen[r.URL] {
				seen[r.URL] = true
				results = append(results, r.ToChunk())
			}
		}
	}

	return results, nil
}

func buildContext(chunks []types.Chunk, maxResults, maxContentLen int) string {
	if len(chunks) > maxResults {
		chunks = chunks[:maxResults]
	}

	var sb strings.Builder
	sb.WriteString("<search_results note=\"These are the search results and assistant can cite these\">\n")

	for i, chunk := range chunks {
		content := chunk.Content
		if len(content) > maxContentLen {
			content = content[:maxContentLen] + "…"
		}
		title := chunk.Metadata["title"]
		sb.WriteString("<result index=")
		sb.WriteString(strings.ReplaceAll(title, "\"", "'"))
		sb.WriteString("\" index=\"")
		sb.WriteString(string(rune('0' + i + 1)))
		sb.WriteString("\">")
		sb.WriteString(content)
		sb.WriteString("</result>\n")
	}

	sb.WriteString("</search_results>")
	return sb.String()
}

func rankByRelevance(chunks []types.Chunk, query string) []types.Chunk {
	if len(chunks) == 0 {
		return chunks
	}

	terms := extractQueryTerms(query)
	if len(terms) == 0 {
		return chunks
	}

	type scored struct {
		chunk types.Chunk
		score int
	}

	scored_chunks := make([]scored, len(chunks))
	for i, chunk := range chunks {
		score := 0
		content := strings.ToLower(chunk.Content)
		title := strings.ToLower(chunk.Metadata["title"])

		for term := range terms {
			if strings.Contains(title, term) {
				score += 3
			}
			if strings.Contains(content, term) {
				score += 1
			}
		}

		scored_chunks[i] = scored{chunk: chunk, score: score}
	}

	for i := 0; i < len(scored_chunks)-1; i++ {
		for j := i + 1; j < len(scored_chunks); j++ {
			if scored_chunks[j].score > scored_chunks[i].score {
				scored_chunks[i], scored_chunks[j] = scored_chunks[j], scored_chunks[i]
			}
		}
	}

	result := make([]types.Chunk, len(scored_chunks))
	for i, s := range scored_chunks {
		result[i] = s.chunk
	}

	return result
}

func extractQueryTerms(query string) map[string]bool {
	query = strings.ToLower(query)
	query = strings.TrimPrefix(query, "summary: ")

	words := strings.Fields(query)
	terms := make(map[string]bool)

	for _, w := range words {
		if len(w) >= 2 && !strings.HasPrefix(w, "http") {
			terms[w] = true
		}
	}

	return terms
}