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using a property for Chunk.chunk_id

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Signed-off-by: Francisco Javier Arceo <farceo@redhat.com>
This commit is contained in:
Francisco Javier Arceo 2025-06-25 09:49:44 -04:00
parent f90fce218e
commit fa36b672f1
10 changed files with 163 additions and 86 deletions
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20
llama_stack/providers/inline/vector_io/sqlite_vec/sqlite_vec.py
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@ -31,7 +31,6 @@ from llama_stack.providers.utils.memory.vector_store import (
EmbeddingIndex,
VectorDBWithIndex,
)
from llama_stack.providers.utils.vector_io.chunk_utils import extract_or_generate_chunk_id
logger = logging.getLogger(__name__)
@ -200,9 +199,7 @@ class SQLiteVecIndex(EmbeddingIndex):
batch_embeddings = embeddings[i : i + batch_size]
# Insert metadata
metadata_data = [
(extract_or_generate_chunk_id(chunk), chunk.model_dump_json()) for chunk in batch_chunks
]
metadata_data = [(chunk.chunk_id, chunk.model_dump_json()) for chunk in batch_chunks]
cur.executemany(
f"""
INSERT INTO {self.metadata_table} (id, chunk)
@ -216,7 +213,7 @@ class SQLiteVecIndex(EmbeddingIndex):
embedding_data = [
(
(
extract_or_generate_chunk_id(chunk),
chunk.chunk_id,
serialize_vector(emb.tolist()),
)
)
@ -228,7 +225,7 @@ class SQLiteVecIndex(EmbeddingIndex):
)
# Insert FTS content
fts_data = [(extract_or_generate_chunk_id(chunk), chunk.content) for chunk in batch_chunks]
fts_data = [(chunk.chunk_id, chunk.content) for chunk in batch_chunks]
# DELETE existing entries with same IDs (FTS5 doesn't support ON CONFLICT)
cur.executemany(
f"DELETE FROM {self.fts_table} WHERE id = ?;",
@ -376,13 +373,12 @@ class SQLiteVecIndex(EmbeddingIndex):
vector_response = await self.query_vector(embedding, k, score_threshold)
keyword_response = await self.query_keyword(query_string, k, score_threshold)
# Convert responses to score dictionaries using generate_chunk_id
# Convert responses to score dictionaries using chunk_id
vector_scores = {
extract_or_generate_chunk_id(chunk): score
for chunk, score in zip(vector_response.chunks, vector_response.scores, strict=False)
chunk.chunk_id: score for chunk, score in zip(vector_response.chunks, vector_response.scores, strict=False)
}
keyword_scores = {
extract_or_generate_chunk_id(chunk): score
chunk.chunk_id: score
for chunk, score in zip(keyword_response.chunks, keyword_response.scores, strict=False)
}
@ -405,10 +401,10 @@ class SQLiteVecIndex(EmbeddingIndex):
# Create a map of chunk_id to chunk for both responses
chunk_map = {}
for c in vector_response.chunks:
chunk_id = extract_or_generate_chunk_id(c)
chunk_id = c.chunk_id
chunk_map[chunk_id] = c
for c in keyword_response.chunks:
chunk_id = extract_or_generate_chunk_id(c)
chunk_id = c.chunk_id
chunk_map[chunk_id] = c
# Use the map to look up chunks by their IDs