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chore: mypy violations cleanup for inline::{telemetry,tool_runtime,vector_io} (#1711)

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# What does this PR do?

Clean up mypy violations for inline::{telemetry,tool_runtime,vector_io}.
This also makes API accept a tool call result without any content (like
RAG tool already may produce).

Signed-off-by: Ihar Hrachyshka <ihar.hrachyshka@gmail.com>
This commit is contained in:
Ihar Hrachyshka 2025-03-20 13:01:10 -04:00 • committed by GitHub
parent 355134f51d
commit 515c16e352
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GPG key ID: B5690EEEBB952194
15 changed files with 51 additions and 44 deletions
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9
llama_stack/providers/inline/vector_io/sqlite_vec/sqlite_vec.py
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@ -15,9 +15,10 @@ import numpy as np
import sqlite_vec
from numpy.typing import NDArray
from llama_stack.apis.inference.inference import Inference
from llama_stack.apis.vector_dbs import VectorDB
from llama_stack.apis.vector_io import Chunk, QueryChunksResponse, VectorIO
from llama_stack.providers.datatypes import Api, VectorDBsProtocolPrivate
from llama_stack.providers.datatypes import VectorDBsProtocolPrivate
from llama_stack.providers.utils.memory.vector_store import EmbeddingIndex, VectorDBWithIndex
logger = logging.getLogger(__name__)
@ -78,6 +79,8 @@ class SQLiteVecIndex(EmbeddingIndex):
embedding (serialized to raw bytes) into the virtual table using the assigned rowid.
If any insert fails, the transaction is rolled back to maintain consistency.
"""
assert all(isinstance(chunk.content, str) for chunk in chunks), "SQLiteVecIndex only supports text chunks"
cur = self.connection.cursor()
try:
# Start transaction
@ -89,6 +92,7 @@ class SQLiteVecIndex(EmbeddingIndex):
metadata_data = [
(generate_chunk_id(chunk.metadata["document_id"], chunk.content), chunk.model_dump_json())
for chunk in batch_chunks
if isinstance(chunk.content, str)
]
# Insert metadata (ON CONFLICT to avoid duplicates)
cur.executemany(
@ -103,6 +107,7 @@ class SQLiteVecIndex(EmbeddingIndex):
embedding_data = [
(generate_chunk_id(chunk.metadata["document_id"], chunk.content), serialize_vector(emb.tolist()))
for chunk, emb in zip(batch_chunks, batch_embeddings, strict=True)
if isinstance(chunk.content, str)
]
# Insert embeddings in batch
cur.executemany(f"INSERT INTO {self.vector_table} (id, embedding) VALUES (?, ?);", embedding_data)
@ -154,7 +159,7 @@ class SQLiteVecVectorIOAdapter(VectorIO, VectorDBsProtocolPrivate):
and creates a cache of VectorDBWithIndex instances (each wrapping a SQLiteVecIndex).
"""
def __init__(self, config, inference_api: Api.inference) -> None:
def __init__(self, config, inference_api: Inference) -> None:
self.config = config
self.inference_api = inference_api
self.cache: Dict[str, VectorDBWithIndex] = {}