| """Lazily constructed shared resources.
|
|
|
| The original `agent_tools.py` opened Qdrant, loaded a CrossEncoder and called
|
| `setup_data_stores()` — which calls `exit()` on missing files — at module import
|
| time. Importing it from a web server would kill the worker on a bad path and
|
| hold the embedded Qdrant lock for the process lifetime. Everything here is
|
| built on first use instead, and raises rather than exiting.
|
| """
|
|
|
| from __future__ import annotations
|
|
|
| from functools import lru_cache
|
|
|
| import qdrant_client
|
| from qdrant_client.models import Distance, VectorParams
|
|
|
| from ..config import get_settings
|
|
|
|
|
| @lru_cache(maxsize=1)
|
| def get_qdrant() -> qdrant_client.QdrantClient:
|
| settings = get_settings()
|
| if settings.qdrant_url:
|
| return qdrant_client.QdrantClient(
|
| url=settings.qdrant_url,
|
| api_key=settings.qdrant_api_key,
|
| check_compatibility=False,
|
| )
|
| if not settings.qdrant_path.exists():
|
| raise RuntimeError(
|
| f"No Qdrant store at {settings.qdrant_path}. Run the ingestion scripts "
|
| f"or set QDRANT_URL to a server."
|
| )
|
| return qdrant_client.QdrantClient(path=str(settings.qdrant_path))
|
|
|
|
|
| def collection_dimension() -> int:
|
| settings = get_settings()
|
| info = get_qdrant().get_collection(settings.collection_name)
|
| params = info.config.params
|
| vectors = params.vectors
|
| if isinstance(vectors, VectorParams):
|
| return int(vectors.size)
|
| if isinstance(vectors, dict):
|
| return int(next(iter(vectors.values())).size)
|
| raise RuntimeError(f"Cannot determine vector size for '{settings.collection_name}'")
|
|
|
|
|
| def collection_distance() -> Distance | None:
|
| settings = get_settings()
|
| vectors = get_qdrant().get_collection(settings.collection_name).config.params.vectors
|
| if isinstance(vectors, VectorParams):
|
| return vectors.distance
|
| return None
|
|
|
|
|
| @lru_cache(maxsize=1)
|
| def get_reranker():
|
| from sentence_transformers import CrossEncoder
|
|
|
| return CrossEncoder(get_settings().reranker_model)
|
|
|
|
|
| @lru_cache(maxsize=1)
|
| def get_sql_database():
|
| import sqlite3
|
|
|
| import pandas as pd
|
| from langchain_community.utilities import SQLDatabase
|
|
|
| from ..config import PROJECT_ROOT
|
|
|
| settings = get_settings()
|
| if not settings.sqlite_path.exists():
|
| csv_path = PROJECT_ROOT / "data" / "alphabet_financials_structured.csv"
|
| if not csv_path.exists():
|
| raise RuntimeError(
|
| f"No SQLite database at {settings.sqlite_path} and no CSV at {csv_path}"
|
| )
|
| settings.sqlite_path.parent.mkdir(parents=True, exist_ok=True)
|
| frame = pd.read_csv(csv_path)
|
| with sqlite3.connect(settings.sqlite_path) as conn:
|
| frame.to_sql(settings.table_name, conn, if_exists="replace", index=False)
|
|
|
| return SQLDatabase.from_uri(
|
| f"sqlite:///{settings.sqlite_path}",
|
| include_tables=[settings.table_name],
|
| )
|
|
|
