entity

type AgenticMetadata struct {
	// Intent classification result
	Intent string `json:"intent"`

	// Sub-queries from decomposition
	SubQueries []string `json:"sub_queries"`

	// Extracted entity IDs
	EntityIDs []string `json:"entity_ids"`

	// Whether HyDE was applied
	HydeApplied bool `json:"hyde_applied"`

	// Cache hit status (nil = not checked, false = miss, true = hit)
	CacheHit *bool `json:"cache_hit,omitempty"`

	// Whether tool execution was performed
	ToolExecuted bool `json:"tool_executed"`

	// CRAG evaluation result (relevant/ambiguous/irrelevant)
	CRAGEvaluation string `json:"crag_evaluation"`

	// RAGAS evaluation scores
	RAGScores *RAGEScores `json:"rag_scores,omitempty"`

	// Original query before rewriting (if any)
	OriginalQueryText string `json:"original_query_text"`

	// Rewritten query text
	RewrittenQueryText string `json:"rewritten_query_text"`

	// Hypothetical document from HyDE
	HypotheticalDocument string `json:"hypothetical_document"`

	// Filter constraints extracted from query
	Filters map[string]any `json:"filters,omitempty"`

	// Step-back query for broader context
	StepBackQuery string `json:"step_back_query"`

	// Custom fields for extensibility
	Custom map[string]any `json:"custom,omitempty"`
}

type Chunk struct {
	ID         string         `json:"id"`
	DocumentID string         `json:"document_id"`         // ID of the root document
	ParentID   string         `json:"parent_id,omitempty"` // For Parent-Child Indexing (Hierarchical)
	Level      int            `json:"level"`               // 0: Root, 1: Parent, 2: Child
	Content    string         `json:"content"`
	Metadata   map[string]any `json:"metadata"`
	CreatedAt  time.Time      `json:"created_at"`
	StartIndex int            `json:"start_index"`
	EndIndex   int            `json:"end_index"`
	VectorID   string         `json:"vector_id,omitempty"`
}

type Document struct {
	ID          string         `json:"id"`           // Unique identifier for the document
	Content     string         `json:"content"`      // The actual content of the document
	Metadata    map[string]any `json:"metadata"`     // Additional metadata about the document
	CreatedAt   time.Time      `json:"created_at"`   // Creation timestamp
	UpdatedAt   time.Time      `json:"updated_at"`   // Last update timestamp
	Source      string         `json:"source"`       // Source of the document
	ContentType string         `json:"content_type"` // Type of content (e.g., text, pdf, markdown)
}

type PipelineState struct {
	// Query related fields
	Query         *Query `json:"query"`
	OriginalQuery *Query `json:"original_query"`

	// Retrieval related fields
	RetrievedChunks [][]*Chunk     `json:"retrieved_chunks"`
	ParallelResults [][]*Chunk     `json:"parallel_results"`
	RerankScores    []float32      `json:"rerank_scores"`
	Filters         map[string]any `json:"filters"`

	// Generation related fields
	Answer           string `json:"answer"`
	GenerationPrompt string `json:"generation_prompt"`

	// Self-RAG related fields
	SelfRagScore  float32 `json:"self_rag_score"`
	SelfRagReason string  `json:"self_rag_reason"`

	// Agentic RAG metadata (strongly-typed, eliminates blackboard anti-pattern)
	Agentic *AgenticMetadata `json:"agentic"`
}

type Query struct {
	ID        string         `json:"id"`         // Unique identifier for the query
	Text      string         `json:"text"`       // The actual query text
	Metadata  map[string]any `json:"metadata"`   // Additional metadata about the query
	CreatedAt time.Time      `json:"created_at"` // Creation timestamp
}

type RAGEScores struct {
	Faithfulness     float32 `json:"faithfulness"`
	AnswerRelevance  float32 `json:"answer_relevance"`
	ContextPrecision float32 `json:"context_precision"`
	OverallScore     float32 `json:"overall_score"`
	Passed           bool    `json:"passed"`
}

type RetrievalResult struct {
	ID       string         `json:"id"`       // Unique identifier for the retrieval result
	QueryID  string         `json:"query_id"` // ID of the corresponding query
	Chunks   []*Chunk       `json:"chunks"`   // Retrieved chunks
	Scores   []float32      `json:"scores"`   // Relevance scores for the retrieved chunks
	Metadata map[string]any `json:"metadata"` // Additional metadata about the retrieval result
}

type Vector struct {
	ID       string         `json:"id"`       // Unique identifier for the vector
	Values   []float32      `json:"values"`   // The vector values
	ChunkID  string         `json:"chunk_id"` // ID of the corresponding chunk
	Metadata map[string]any `json:"metadata"` // Additional metadata about the vector
}