set long 999999
set pagesize 1000
set linesize 200

/* --------------------------------

HNSW INDEX 

-------------------------------- */ 

-- crear indice HNSW para busquedas vectoriales aproximadas
CREATE VECTOR INDEX markdown_chunks_hnsw_idx
ON markdown_chunks (embedding)
ORGANIZATION INMEMORY NEIGHBOR GRAPH
DISTANCE COSINE
WITH TARGET ACCURACY 90
PARAMETERS (
    TYPE HNSW,
    NEIGHBORS 32,
    EFCONSTRUCTION 200
);

DROP INDEX IF EXISTS markdown_chunks_hnsw_idx;

/* --------------------------------

IVF INDEX 

-------------------------------- */ 

-- crear indice IVF con DOC_ID incluido para filtros por documento
CREATE VECTOR INDEX markdown_chunks_ivf_idx
ON markdown_chunks (embedding)
INCLUDE (doc_id)
ORGANIZATION NEIGHBOR PARTITIONS
DISTANCE COSINE
WITH TARGET ACCURACY 90
PARAMETERS (
    TYPE IVF,
    NEIGHBOR PARTITIONS 4,
    MIN_VECTORS_PER_PARTITION 1
);

DROP INDEX IF EXISTS markdown_chunks_ivf_idx;
/* --------------------------------

TEXT INDEX + VECTOR SEARCH

-------------------------------- */ 
-- hybrid indexes / text indexes para busquedas textuales y combinadas
DROP INDEX IF EXISTS markdown_chunks_text_idx;

CREATE SEARCH INDEX markdown_chunks_text_idx
ON markdown_chunks (chunk_text)
FOR TEXT;

select
    doc_id,
    chunk_id,
    SCORE(1) as text_score,
    VECTOR_DISTANCE(embedding, 
                    VECTOR_EMBEDDING(MULTILINGUAL_E5_BASE 
                                    USING 'Sucursales adheridas' as DATA
                                    )
                    ) as vector_distance,
    chunk_text    
from markdown_chunks
where contains(chunk_text, '(Mastercard ACCUM NEAR((Dúo,Clásica),1))', 1) > 0 
order by vector_distance
fetch first 3 rows only;

-- Promoción 
-- FUZZY(Promción) 
-- ABOUT(Promoción)
-- NEAR((tarjetas, físicas, billeteras, electrónicas), 5)
-- Black OR Albirroja
-- BENDITA ACCUM STYLE                             
-- (Mastercard ACCUM NEAR((Dúo,Clásica),1))

/* --------------------------------

HYBRID VECTOR INDEX

-------------------------------- */ 

-- crear indice hibrido para combinar busqueda textual y semantica
DROP INDEX IF EXISTS markdown_chunks_hybrid_idx;

CREATE HYBRID VECTOR INDEX markdown_chunks_hybrid_idx
ON markdown_chunks (chunk_text)
PARAMETERS ('MODEL MULTILINGUAL_E5_BASE
             VECTOR_IDXTYPE HNSW
             MEMORY 128M')
PARALLEL 2;


-- ejemplo de consulta usando el indice hibrido
SELECT JSON_SERIALIZE(
    DBMS_HYBRID_VECTOR.SEARCH(
        JSON('{
            "hybrid_index_name" : "markdown_chunks_hybrid_idx",
            "search_fusion"     : "UNION",
            "search_scorer"     : "rsf",                        
            "vector" : {
                "search_text"  : "Vigencia",
                "search_mode"  : "CHUNK"                
            },
            "text" : {
                "contains"     : "Shopping NEAR San NEAR Lorenzo"
            },
            "return" : {
                "values" : [
                    "chunk_id",
                    "chunk_text",
                    "score",
                    "vector_score",
                    "text_score"
                ],
                "topN" : 5
            }
        }')
    ) RETURNING CLOB PRETTY
) AS hybrid_results;


SELECT jt.*
FROM
   JSON_TABLE(
        dbms_hybrid_vector.search(
                json_object(
                  'hybrid_index_name' VALUE 'markdown_chunks_hybrid_idx',      
                  'search_fusion'     VALUE 'INTERSECT',
                  'search_scorer'     VALUE 'rsf',
                  'vector'            VALUE json_object('search_text' VALUE 'COMERCIOS ADHERIDOS'), 
                  'text'              VALUE json_object('contains'    VALUE 'BENDITA ACCUM STYLE'),
                  'return' VALUE json_object(
                                  'values' VALUE json_array('rowid', 'score', 'vector_score', 'vector_rank', 'text_score', 'text_rank', 'chunk_text'),
                                  'topN'   VALUE 3
                                )
                  RETURNING JSON
                )
            ),
        '$[*]' COLUMNS idx for ORDINALITY,
                score        NUMBER PATH '$.score',                
                vector_score NUMBER PATH '$.vector_score',                
                vector_rank  NUMBER PATH '$.vector_rank',
                text_score   NUMBER PATH '$.text_score',
                text_rank    NUMBER PATH '$.text_rank',
                chunk_text   VARCHAR2(4000) PATH '$.chunk_text'
    ) jt;