package ucca

import (
	"bytes"
	"context"
	"encoding/json"
	"fmt"
	"io"
	"net/http"
	"os"
	"strings"
	"time"
)

// LegalRAGClient provides access to the compliance CE vector search via Qdrant + Ollama bge-m3.
type LegalRAGClient struct {
	qdrantURL        string
	qdrantAPIKey     string
	ollamaURL        string
	embeddingModel   string
	collection       string
	httpClient       *http.Client
	textIndexEnsured map[string]bool // tracks which collections have text index
	hybridEnabled    bool            // use Query API with RRF fusion
}

// LegalSearchResult represents a single search result from the compliance corpus.
type LegalSearchResult struct {
	Text            string  `json:"text"`
	RegulationCode  string  `json:"regulation_code"`
	RegulationName  string  `json:"regulation_name"`
	RegulationShort string  `json:"regulation_short"`
	Category        string  `json:"category"`
	Article         string  `json:"article,omitempty"`
	Paragraph       string  `json:"paragraph,omitempty"`
	Pages           []int   `json:"pages,omitempty"`
	SourceURL       string  `json:"source_url"`
	Score           float64 `json:"score"`
}

// LegalContext represents aggregated legal context for an assessment.
type LegalContext struct {
	Query            string              `json:"query"`
	Results          []LegalSearchResult `json:"results"`
	RelevantArticles []string            `json:"relevant_articles"`
	Regulations      []string            `json:"regulations"`
	GeneratedAt      time.Time           `json:"generated_at"`
}

// RegulationInfo describes an available regulation in the corpus.
type CERegulationInfo struct {
	ID       string `json:"id"`
	NameDE   string `json:"name_de"`
	NameEN   string `json:"name_en"`
	Short    string `json:"short"`
	Category string `json:"category"`
}

// NewLegalRAGClient creates a new Legal RAG client using Ollama bge-m3 embeddings.
func NewLegalRAGClient() *LegalRAGClient {
	qdrantURL := os.Getenv("QDRANT_URL")
	if qdrantURL == "" {
		qdrantURL = "http://localhost:6333"
	}
	// Strip trailing slash
	qdrantURL = strings.TrimRight(qdrantURL, "/")

	qdrantAPIKey := os.Getenv("QDRANT_API_KEY")

	ollamaURL := os.Getenv("OLLAMA_URL")
	if ollamaURL == "" {
		ollamaURL = "http://localhost:11434"
	}

	hybridEnabled := os.Getenv("RAG_HYBRID_SEARCH") != "false" // enabled by default

	return &LegalRAGClient{
		qdrantURL:        qdrantURL,
		qdrantAPIKey:     qdrantAPIKey,
		ollamaURL:        ollamaURL,
		embeddingModel:   "bge-m3",
		collection:       "bp_compliance_ce",
		textIndexEnsured: make(map[string]bool),
		hybridEnabled:    hybridEnabled,
		httpClient: &http.Client{
			Timeout: 60 * time.Second,
		},
	}
}

// ollamaEmbeddingRequest for Ollama embedding API.
type ollamaEmbeddingRequest struct {
	Model  string `json:"model"`
	Prompt string `json:"prompt"`
}

// ollamaEmbeddingResponse from Ollama embedding API.
type ollamaEmbeddingResponse struct {
	Embedding []float64 `json:"embedding"`
}

// qdrantSearchRequest for Qdrant REST API.
type qdrantSearchRequest struct {
	Vector      []float64     `json:"vector"`
	Limit       int           `json:"limit"`
	WithPayload bool          `json:"with_payload"`
	Filter      *qdrantFilter `json:"filter,omitempty"`
}

type qdrantFilter struct {
	Should []qdrantCondition `json:"should,omitempty"`
	Must   []qdrantCondition `json:"must,omitempty"`
}

type qdrantCondition struct {
	Key   string      `json:"key"`
	Match qdrantMatch `json:"match"`
}

type qdrantMatch struct {
	Value string `json:"value"`
}

// qdrantSearchResponse from Qdrant REST API.
type qdrantSearchResponse struct {
	Result []qdrantSearchHit `json:"result"`
}

type qdrantSearchHit struct {
	ID      interface{}            `json:"id"`
	Score   float64                `json:"score"`
	Payload map[string]interface{} `json:"payload"`
}

// --- Hybrid Search (Query API with RRF fusion) ---

// qdrantQueryRequest for Qdrant Query API with prefetch + fusion.
type qdrantQueryRequest struct {
	Prefetch    []qdrantPrefetch `json:"prefetch"`
	Query       *qdrantFusion    `json:"query"`
	Limit       int              `json:"limit"`
	WithPayload bool             `json:"with_payload"`
	Filter      *qdrantFilter    `json:"filter,omitempty"`
}

type qdrantPrefetch struct {
	Query  []float64     `json:"query"`
	Limit  int           `json:"limit"`
	Filter *qdrantFilter `json:"filter,omitempty"`
}

type qdrantFusion struct {
	Fusion string `json:"fusion"`
}

// qdrantQueryResponse from Qdrant Query API (same shape as search).
type qdrantQueryResponse struct {
	Result []qdrantSearchHit `json:"result"`
}

// qdrantTextIndexRequest for creating a full-text index on a payload field.
type qdrantTextIndexRequest struct {
	FieldName   string                 `json:"field_name"`
	FieldSchema qdrantTextFieldSchema  `json:"field_schema"`
}

type qdrantTextFieldSchema struct {
	Type      string `json:"type"`
	Tokenizer string `json:"tokenizer"`
	MinLen    int    `json:"min_token_len,omitempty"`
	MaxLen    int    `json:"max_token_len,omitempty"`
}

// ensureTextIndex creates a full-text index on chunk_text if not already done for this collection.
func (c *LegalRAGClient) ensureTextIndex(ctx context.Context, collection string) error {
	if c.textIndexEnsured[collection] {
		return nil
	}

	indexReq := qdrantTextIndexRequest{
		FieldName: "chunk_text",
		FieldSchema: qdrantTextFieldSchema{
			Type:      "text",
			Tokenizer: "word",
			MinLen:    2,
			MaxLen:    40,
		},
	}

	jsonBody, err := json.Marshal(indexReq)
	if err != nil {
		return fmt.Errorf("failed to marshal text index request: %w", err)
	}

	url := fmt.Sprintf("%s/collections/%s/index", c.qdrantURL, collection)
	req, err := http.NewRequestWithContext(ctx, "PUT", url, bytes.NewReader(jsonBody))
	if err != nil {
		return fmt.Errorf("failed to create text index request: %w", err)
	}
	req.Header.Set("Content-Type", "application/json")
	if c.qdrantAPIKey != "" {
		req.Header.Set("api-key", c.qdrantAPIKey)
	}

	resp, err := c.httpClient.Do(req)
	if err != nil {
		return fmt.Errorf("text index request failed: %w", err)
	}
	defer resp.Body.Close()

	// 200 = created, 409 = already exists — both are fine
	if resp.StatusCode != http.StatusOK && resp.StatusCode != http.StatusConflict {
		body, _ := io.ReadAll(resp.Body)
		return fmt.Errorf("text index creation failed %d: %s", resp.StatusCode, string(body))
	}

	c.textIndexEnsured[collection] = true
	return nil
}

// searchHybrid performs RRF-fused hybrid search (dense + full-text) via Qdrant Query API.
func (c *LegalRAGClient) searchHybrid(ctx context.Context, collection string, embedding []float64, regulationIDs []string, topK int) ([]qdrantSearchHit, error) {
	// Ensure text index exists
	if err := c.ensureTextIndex(ctx, collection); err != nil {
		// Non-fatal: log and fall back to dense-only
		return nil, err
	}

	// Build prefetch with dense vector (retrieve top-20 for re-ranking)
	prefetchLimit := 20
	if topK > 20 {
		prefetchLimit = topK * 4
	}

	queryReq := qdrantQueryRequest{
		Prefetch: []qdrantPrefetch{
			{Query: embedding, Limit: prefetchLimit},
		},
		Query:       &qdrantFusion{Fusion: "rrf"},
		Limit:       topK,
		WithPayload: true,
	}

	// Add regulation filter
	if len(regulationIDs) > 0 {
		conditions := make([]qdrantCondition, len(regulationIDs))
		for i, regID := range regulationIDs {
			conditions[i] = qdrantCondition{
				Key:   "regulation_id",
				Match: qdrantMatch{Value: regID},
			}
		}
		queryReq.Filter = &qdrantFilter{Should: conditions}
	}

	jsonBody, err := json.Marshal(queryReq)
	if err != nil {
		return nil, fmt.Errorf("failed to marshal query request: %w", err)
	}

	url := fmt.Sprintf("%s/collections/%s/points/query", c.qdrantURL, collection)
	req, err := http.NewRequestWithContext(ctx, "POST", url, bytes.NewReader(jsonBody))
	if err != nil {
		return nil, fmt.Errorf("failed to create query request: %w", err)
	}
	req.Header.Set("Content-Type", "application/json")
	if c.qdrantAPIKey != "" {
		req.Header.Set("api-key", c.qdrantAPIKey)
	}

	resp, err := c.httpClient.Do(req)
	if err != nil {
		return nil, fmt.Errorf("query request failed: %w", err)
	}
	defer resp.Body.Close()

	if resp.StatusCode != http.StatusOK {
		body, _ := io.ReadAll(resp.Body)
		return nil, fmt.Errorf("qdrant query returned %d: %s", resp.StatusCode, string(body))
	}

	var queryResp qdrantQueryResponse
	if err := json.NewDecoder(resp.Body).Decode(&queryResp); err != nil {
		return nil, fmt.Errorf("failed to decode query response: %w", err)
	}

	return queryResp.Result, nil
}

// generateEmbedding calls Ollama bge-m3 to get a 1024-dim vector for the query.
func (c *LegalRAGClient) generateEmbedding(ctx context.Context, text string) ([]float64, error) {
	// Truncate to 2000 chars for bge-m3
	if len(text) > 2000 {
		text = text[:2000]
	}

	reqBody := ollamaEmbeddingRequest{
		Model:  c.embeddingModel,
		Prompt: text,
	}

	jsonBody, err := json.Marshal(reqBody)
	if err != nil {
		return nil, fmt.Errorf("failed to marshal embedding request: %w", err)
	}

	req, err := http.NewRequestWithContext(ctx, "POST", c.ollamaURL+"/api/embeddings", bytes.NewReader(jsonBody))
	if err != nil {
		return nil, fmt.Errorf("failed to create embedding request: %w", err)
	}
	req.Header.Set("Content-Type", "application/json")

	resp, err := c.httpClient.Do(req)
	if err != nil {
		return nil, fmt.Errorf("embedding request failed: %w", err)
	}
	defer resp.Body.Close()

	if resp.StatusCode != http.StatusOK {
		body, _ := io.ReadAll(resp.Body)
		return nil, fmt.Errorf("ollama returned %d: %s", resp.StatusCode, string(body))
	}

	var embResp ollamaEmbeddingResponse
	if err := json.NewDecoder(resp.Body).Decode(&embResp); err != nil {
		return nil, fmt.Errorf("failed to decode embedding response: %w", err)
	}

	if len(embResp.Embedding) == 0 {
		return nil, fmt.Errorf("no embedding returned from ollama")
	}

	return embResp.Embedding, nil
}

// SearchCollection queries a specific Qdrant collection for relevant passages.
// If collection is empty, it falls back to the default collection (bp_compliance_ce).
func (c *LegalRAGClient) SearchCollection(ctx context.Context, collection string, query string, regulationIDs []string, topK int) ([]LegalSearchResult, error) {
	if collection == "" {
		collection = c.collection
	}
	return c.searchInternal(ctx, collection, query, regulationIDs, topK)
}

// Search queries the compliance CE corpus for relevant passages.
func (c *LegalRAGClient) Search(ctx context.Context, query string, regulationIDs []string, topK int) ([]LegalSearchResult, error) {
	return c.searchInternal(ctx, c.collection, query, regulationIDs, topK)
}

// searchInternal performs the actual search against a given collection.
// If hybrid search is enabled, it uses the Qdrant Query API with RRF fusion
// (dense + full-text). Falls back to dense-only /points/search on failure.
func (c *LegalRAGClient) searchInternal(ctx context.Context, collection string, query string, regulationIDs []string, topK int) ([]LegalSearchResult, error) {
	// Generate query embedding via Ollama bge-m3
	embedding, err := c.generateEmbedding(ctx, query)
	if err != nil {
		return nil, fmt.Errorf("failed to generate embedding: %w", err)
	}

	// Try hybrid search first (Query API + RRF), fall back to dense-only
	var hits []qdrantSearchHit

	if c.hybridEnabled {
		hybridHits, err := c.searchHybrid(ctx, collection, embedding, regulationIDs, topK)
		if err == nil {
			hits = hybridHits
		}
		// On error, fall through to dense-only search below
	}

	if hits == nil {
		denseHits, err := c.searchDense(ctx, collection, embedding, regulationIDs, topK)
		if err != nil {
			return nil, err
		}
		hits = denseHits
	}

	// Convert to results using bp_compliance_ce payload schema
	results := make([]LegalSearchResult, len(hits))
	for i, hit := range hits {
		results[i] = LegalSearchResult{
			Text:            getString(hit.Payload, "chunk_text"),
			RegulationCode:  getString(hit.Payload, "regulation_id"),
			RegulationName:  getString(hit.Payload, "regulation_name_de"),
			RegulationShort: getString(hit.Payload, "regulation_short"),
			Category:        getString(hit.Payload, "category"),
			Pages:           getIntSlice(hit.Payload, "pages"),
			SourceURL:       getString(hit.Payload, "source"),
			Score:           hit.Score,
		}
	}

	return results, nil
}

// searchDense performs a dense-only vector search via Qdrant /points/search.
func (c *LegalRAGClient) searchDense(ctx context.Context, collection string, embedding []float64, regulationIDs []string, topK int) ([]qdrantSearchHit, error) {
	searchReq := qdrantSearchRequest{
		Vector:      embedding,
		Limit:       topK,
		WithPayload: true,
	}

	if len(regulationIDs) > 0 {
		conditions := make([]qdrantCondition, len(regulationIDs))
		for i, regID := range regulationIDs {
			conditions[i] = qdrantCondition{
				Key:   "regulation_id",
				Match: qdrantMatch{Value: regID},
			}
		}
		searchReq.Filter = &qdrantFilter{Should: conditions}
	}

	jsonBody, err := json.Marshal(searchReq)
	if err != nil {
		return nil, fmt.Errorf("failed to marshal search request: %w", err)
	}

	url := fmt.Sprintf("%s/collections/%s/points/search", c.qdrantURL, collection)
	req, err := http.NewRequestWithContext(ctx, "POST", url, bytes.NewReader(jsonBody))
	if err != nil {
		return nil, fmt.Errorf("failed to create search request: %w", err)
	}
	req.Header.Set("Content-Type", "application/json")
	if c.qdrantAPIKey != "" {
		req.Header.Set("api-key", c.qdrantAPIKey)
	}

	resp, err := c.httpClient.Do(req)
	if err != nil {
		return nil, fmt.Errorf("search request failed: %w", err)
	}
	defer resp.Body.Close()

	if resp.StatusCode != http.StatusOK {
		body, _ := io.ReadAll(resp.Body)
		return nil, fmt.Errorf("qdrant returned %d: %s", resp.StatusCode, string(body))
	}

	var searchResp qdrantSearchResponse
	if err := json.NewDecoder(resp.Body).Decode(&searchResp); err != nil {
		return nil, fmt.Errorf("failed to decode search response: %w", err)
	}

	return searchResp.Result, nil
}

// GetLegalContextForAssessment retrieves relevant legal context for an assessment.
func (c *LegalRAGClient) GetLegalContextForAssessment(ctx context.Context, assessment *Assessment) (*LegalContext, error) {
	// Build query from assessment data
	queryParts := []string{}

	// Add domain context
	if assessment.Domain != "" {
		queryParts = append(queryParts, fmt.Sprintf("KI-Anwendung im Bereich %s", assessment.Domain))
	}

	// Add data type context
	if assessment.Intake.DataTypes.Article9Data {
		queryParts = append(queryParts, "besondere Kategorien personenbezogener Daten Art. 9 DSGVO")
	}
	if assessment.Intake.DataTypes.PersonalData {
		queryParts = append(queryParts, "personenbezogene Daten")
	}
	if assessment.Intake.DataTypes.MinorData {
		queryParts = append(queryParts, "Daten von Minderjährigen")
	}

	// Add purpose context
	if assessment.Intake.Purpose.EvaluationScoring {
		queryParts = append(queryParts, "automatisierte Bewertung Scoring")
	}
	if assessment.Intake.Purpose.DecisionMaking {
		queryParts = append(queryParts, "automatisierte Entscheidung Art. 22 DSGVO")
	}
	if assessment.Intake.Purpose.Profiling {
		queryParts = append(queryParts, "Profiling")
	}

	// Add risk-specific context
	if assessment.DSFARecommended {
		queryParts = append(queryParts, "Datenschutz-Folgenabschätzung Art. 35 DSGVO")
	}
	if assessment.Art22Risk {
		queryParts = append(queryParts, "automatisierte Einzelentscheidung rechtliche Wirkung")
	}

	// Build final query
	query := strings.Join(queryParts, " ")
	if query == "" {
		query = "DSGVO Anforderungen KI-System Datenschutz"
	}

	// Determine which regulations to search based on triggered rules
	regulationIDs := c.determineRelevantRegulations(assessment)

	// Search compliance corpus
	results, err := c.Search(ctx, query, regulationIDs, 5)
	if err != nil {
		return nil, err
	}

	// Extract unique regulations
	regSet := make(map[string]bool)
	for _, r := range results {
		regSet[r.RegulationCode] = true
	}

	regulations := make([]string, 0, len(regSet))
	for r := range regSet {
		regulations = append(regulations, r)
	}

	// Build relevant articles from page references
	articles := make([]string, 0)
	for _, r := range results {
		if len(r.Pages) > 0 {
			key := fmt.Sprintf("%s S. %v", r.RegulationShort, r.Pages)
			articles = append(articles, key)
		}
	}

	return &LegalContext{
		Query:            query,
		Results:          results,
		RelevantArticles: articles,
		Regulations:      regulations,
		GeneratedAt:      time.Now().UTC(),
	}, nil
}

// determineRelevantRegulations determines which regulations to search based on the assessment.
func (c *LegalRAGClient) determineRelevantRegulations(assessment *Assessment) []string {
	ids := []string{"eu_2016_679"} // Always include GDPR

	// Check triggered rules for regulation hints
	for _, rule := range assessment.TriggeredRules {
		gdprRef := rule.GDPRRef
		if strings.Contains(gdprRef, "AI Act") || strings.Contains(gdprRef, "KI-VO") {
			if !contains(ids, "eu_2024_1689") {
				ids = append(ids, "eu_2024_1689")
			}
		}
		if strings.Contains(gdprRef, "NIS2") || strings.Contains(gdprRef, "NIS-2") {
			if !contains(ids, "eu_2022_2555") {
				ids = append(ids, "eu_2022_2555")
			}
		}
		if strings.Contains(gdprRef, "CRA") || strings.Contains(gdprRef, "Cyber Resilience") {
			if !contains(ids, "eu_2024_2847") {
				ids = append(ids, "eu_2024_2847")
			}
		}
		if strings.Contains(gdprRef, "Maschinenverordnung") || strings.Contains(gdprRef, "Machinery") {
			if !contains(ids, "eu_2023_1230") {
				ids = append(ids, "eu_2023_1230")
			}
		}
	}

	// Add AI Act if AI-related controls are required
	for _, ctrl := range assessment.RequiredControls {
		if strings.HasPrefix(ctrl.ID, "AI-") {
			if !contains(ids, "eu_2024_1689") {
				ids = append(ids, "eu_2024_1689")
			}
			break
		}
	}

	// Add CRA/NIS2 if security controls are required
	for _, ctrl := range assessment.RequiredControls {
		if strings.HasPrefix(ctrl.ID, "CRYPTO-") || strings.HasPrefix(ctrl.ID, "IAM-") || strings.HasPrefix(ctrl.ID, "SEC-") {
			if !contains(ids, "eu_2022_2555") {
				ids = append(ids, "eu_2022_2555")
			}
			if !contains(ids, "eu_2024_2847") {
				ids = append(ids, "eu_2024_2847")
			}
			break
		}
	}

	return ids
}

// ListAvailableRegulations returns the list of regulations available in the corpus.
func (c *LegalRAGClient) ListAvailableRegulations() []CERegulationInfo {
	return []CERegulationInfo{
		CERegulationInfo{ID: "eu_2023_1230", NameDE: "EU-Maschinenverordnung 2023/1230", NameEN: "EU Machinery Regulation 2023/1230", Short: "Maschinenverordnung", Category: "regulation"},
		CERegulationInfo{ID: "eu_2024_1689", NameDE: "EU KI-Verordnung (AI Act)", NameEN: "EU AI Act 2024/1689", Short: "AI Act", Category: "regulation"},
		CERegulationInfo{ID: "eu_2024_2847", NameDE: "Cyber Resilience Act", NameEN: "Cyber Resilience Act 2024/2847", Short: "CRA", Category: "regulation"},
		CERegulationInfo{ID: "eu_2022_2555", NameDE: "NIS-2-Richtlinie", NameEN: "NIS2 Directive 2022/2555", Short: "NIS2", Category: "regulation"},
		CERegulationInfo{ID: "eu_2016_679", NameDE: "Datenschutz-Grundverordnung (DSGVO)", NameEN: "General Data Protection Regulation (GDPR)", Short: "DSGVO/GDPR", Category: "regulation"},
		CERegulationInfo{ID: "eu_blue_guide_2022", NameDE: "EU Blue Guide 2022", NameEN: "EU Blue Guide 2022", Short: "Blue Guide", Category: "guidance"},
		CERegulationInfo{ID: "nist_sp_800_218", NameDE: "NIST Secure Software Development Framework", NameEN: "NIST SSDF SP 800-218", Short: "NIST SSDF", Category: "guidance"},
		CERegulationInfo{ID: "nist_csf_2_0", NameDE: "NIST Cybersecurity Framework 2.0", NameEN: "NIST CSF 2.0", Short: "NIST CSF", Category: "guidance"},
		CERegulationInfo{ID: "oecd_ai_principles", NameDE: "OECD Empfehlung zu Kuenstlicher Intelligenz", NameEN: "OECD Recommendation on AI", Short: "OECD AI", Category: "guidance"},
		CERegulationInfo{ID: "enisa_supply_chain_good_practices", NameDE: "ENISA Supply Chain Cybersecurity", NameEN: "ENISA Good Practices for Supply Chain Cybersecurity", Short: "ENISA Supply Chain", Category: "guidance"},
		CERegulationInfo{ID: "enisa_threat_landscape_supply_chain", NameDE: "ENISA Threat Landscape Supply Chain", NameEN: "ENISA Threat Landscape for Supply Chain Attacks", Short: "ENISA Threat SC", Category: "guidance"},
		CERegulationInfo{ID: "enisa_ics_scada_dependencies", NameDE: "ENISA ICS/SCADA Abhaengigkeiten", NameEN: "ENISA ICS/SCADA Communication Dependencies", Short: "ENISA ICS/SCADA", Category: "guidance"},
		CERegulationInfo{ID: "cisa_secure_by_design", NameDE: "CISA Secure by Design", NameEN: "CISA Secure by Design", Short: "CISA SbD", Category: "guidance"},
		CERegulationInfo{ID: "enisa_cybersecurity_state_2024", NameDE: "ENISA State of Cybersecurity 2024", NameEN: "ENISA State of Cybersecurity in the Union 2024", Short: "ENISA 2024", Category: "guidance"},
	}
}

// FormatLegalContextForPrompt formats the legal context for inclusion in an LLM prompt.
func (c *LegalRAGClient) FormatLegalContextForPrompt(lc *LegalContext) string {
	if lc == nil || len(lc.Results) == 0 {
		return ""
	}

	var buf bytes.Buffer
	buf.WriteString("\n\n**Relevante Rechtsgrundlagen:**\n\n")

	for i, result := range lc.Results {
		buf.WriteString(fmt.Sprintf("%d. **%s** (%s)", i+1, result.RegulationShort, result.RegulationCode))
		if len(result.Pages) > 0 {
			buf.WriteString(fmt.Sprintf(" - Seiten %v", result.Pages))
		}
		buf.WriteString("\n")
		buf.WriteString(fmt.Sprintf("   > %s\n\n", truncateText(result.Text, 300)))
	}

	return buf.String()
}

// ScrollChunkResult represents a single chunk from the scroll/list endpoint.
type ScrollChunkResult struct {
	ID              string `json:"id"`
	Text            string `json:"text"`
	RegulationCode  string `json:"regulation_code"`
	RegulationName  string `json:"regulation_name"`
	RegulationShort string `json:"regulation_short"`
	Category        string `json:"category"`
	Article         string `json:"article,omitempty"`
	Paragraph       string `json:"paragraph,omitempty"`
	SourceURL       string `json:"source_url,omitempty"`
}

// qdrantScrollRequest for the Qdrant scroll API.
type qdrantScrollRequest struct {
	Limit       int         `json:"limit"`
	Offset      interface{} `json:"offset,omitempty"` // string (UUID) or null
	WithPayload bool        `json:"with_payload"`
	WithVectors bool        `json:"with_vectors"`
}

// qdrantScrollResponse from the Qdrant scroll API.
type qdrantScrollResponse struct {
	Result struct {
		Points         []qdrantScrollPoint `json:"points"`
		NextPageOffset interface{}         `json:"next_page_offset"`
	} `json:"result"`
}

type qdrantScrollPoint struct {
	ID      interface{}            `json:"id"`
	Payload map[string]interface{} `json:"payload"`
}

// ScrollChunks iterates over all chunks in a Qdrant collection using the scroll API.
// Pass an empty offset to start from the beginning. Returns chunks, next offset ID, and error.
func (c *LegalRAGClient) ScrollChunks(ctx context.Context, collection string, offset string, limit int) ([]ScrollChunkResult, string, error) {
	scrollReq := qdrantScrollRequest{
		Limit:       limit,
		WithPayload: true,
		WithVectors: false,
	}
	if offset != "" {
		// Qdrant expects integer point IDs — parse the offset string back to a number
		// Try parsing as integer first, fall back to string (for UUID-based collections)
		var offsetInt uint64
		if _, err := fmt.Sscanf(offset, "%d", &offsetInt); err == nil {
			scrollReq.Offset = offsetInt
		} else {
			scrollReq.Offset = offset
		}
	}

	jsonBody, err := json.Marshal(scrollReq)
	if err != nil {
		return nil, "", fmt.Errorf("failed to marshal scroll request: %w", err)
	}

	url := fmt.Sprintf("%s/collections/%s/points/scroll", c.qdrantURL, collection)
	req, err := http.NewRequestWithContext(ctx, "POST", url, bytes.NewReader(jsonBody))
	if err != nil {
		return nil, "", fmt.Errorf("failed to create scroll request: %w", err)
	}
	req.Header.Set("Content-Type", "application/json")
	if c.qdrantAPIKey != "" {
		req.Header.Set("api-key", c.qdrantAPIKey)
	}

	resp, err := c.httpClient.Do(req)
	if err != nil {
		return nil, "", fmt.Errorf("scroll request failed: %w", err)
	}
	defer resp.Body.Close()

	if resp.StatusCode != http.StatusOK {
		body, _ := io.ReadAll(resp.Body)
		return nil, "", fmt.Errorf("qdrant returned %d: %s", resp.StatusCode, string(body))
	}

	var scrollResp qdrantScrollResponse
	if err := json.NewDecoder(resp.Body).Decode(&scrollResp); err != nil {
		return nil, "", fmt.Errorf("failed to decode scroll response: %w", err)
	}

	// Convert points to results
	chunks := make([]ScrollChunkResult, len(scrollResp.Result.Points))
	for i, pt := range scrollResp.Result.Points {
		// Extract point ID as string
		pointID := ""
		if pt.ID != nil {
			pointID = fmt.Sprintf("%v", pt.ID)
		}

		chunks[i] = ScrollChunkResult{
			ID:              pointID,
			Text:            getString(pt.Payload, "text"),
			RegulationCode:  getString(pt.Payload, "regulation_code"),
			RegulationName:  getString(pt.Payload, "regulation_name"),
			RegulationShort: getString(pt.Payload, "regulation_short"),
			Category:        getString(pt.Payload, "category"),
			Article:         getString(pt.Payload, "article"),
			Paragraph:       getString(pt.Payload, "paragraph"),
			SourceURL:       getString(pt.Payload, "source_url"),
		}

		// Fallback: try alternate payload field names used in ingestion
		if chunks[i].Text == "" {
			chunks[i].Text = getString(pt.Payload, "chunk_text")
		}
		if chunks[i].RegulationCode == "" {
			chunks[i].RegulationCode = getString(pt.Payload, "regulation_id")
		}
		if chunks[i].RegulationName == "" {
			chunks[i].RegulationName = getString(pt.Payload, "regulation_name_de")
		}
		if chunks[i].SourceURL == "" {
			chunks[i].SourceURL = getString(pt.Payload, "source")
		}
	}

	// Extract next offset — Qdrant returns integer point IDs
	nextOffset := ""
	if scrollResp.Result.NextPageOffset != nil {
		switch v := scrollResp.Result.NextPageOffset.(type) {
		case float64:
			nextOffset = fmt.Sprintf("%.0f", v)
		case string:
			nextOffset = v
		default:
			nextOffset = fmt.Sprintf("%v", v)
		}
	}

	return chunks, nextOffset, nil
}

// Helper functions

func getString(m map[string]interface{}, key string) string {
	if v, ok := m[key]; ok {
		if s, ok := v.(string); ok {
			return s
		}
	}
	return ""
}

func getIntSlice(m map[string]interface{}, key string) []int {
	v, ok := m[key]
	if !ok {
		return nil
	}
	arr, ok := v.([]interface{})
	if !ok {
		return nil
	}
	result := make([]int, 0, len(arr))
	for _, item := range arr {
		if f, ok := item.(float64); ok {
			result = append(result, int(f))
		}
	}
	return result
}

func contains(slice []string, item string) bool {
	for _, s := range slice {
		if s == item {
			return true
		}
	}
	return false
}

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