Files
Jordan Ritter 534cd1efa7 fix(showcase): D5 integration fixes across 12 frameworks
Per-framework fixes to pass D5 e2e-deep probes:
- agno: deduplicate agent_server routes
- claude-sdk-python: handle ParsedContentBlockStopEvent (SDK v0.97+)
- claude-sdk-typescript: remove orphan tool-rendering page
- crewai-crews: add backend tool_rendering agent + shared_state fix
- google-adk: add AGUIToolset to all ADK agents for frontend tools
- langgraph-typescript: remove stale import
- langroid: emit ToolCallResultEvent for backend tools + fix adapter
- llamaindex: v2 provider import, book_call stub, PYTHONPATH fix
- ms-agent-python: disable Responses API store for aimock compat
- pydantic-ai: simplify gen-ui page component
- spring-ai: raise tool iteration cap (1→5) + fix connection pooling
- strands: shared tools symlink + requirements update
2026-04-29 19:40:10 -07:00

59 lines
1.6 KiB
Python

"""Query data tool implementation — reads db.csv at module load time."""
from __future__ import annotations
import csv
import logging
from pathlib import Path
from typing import Any
_logger = logging.getLogger(__name__)
_csv_path = Path(__file__).resolve().parent.parent / "data" / "db.csv"
_MOCK_DATA = [
{
"date": "2026-01-05",
"category": "Revenue",
"subcategory": "Enterprise Subscriptions",
"amount": "28000",
"type": "income",
"notes": "3 new enterprise customers",
},
{
"date": "2026-01-10",
"category": "Expenses",
"subcategory": "Engineering Salaries",
"amount": "42000",
"type": "expense",
"notes": "7 engineers + 2 contractors",
},
{
"date": "2026-02-03",
"category": "Revenue",
"subcategory": "Pro Tier Upgrades",
"amount": "22500",
"type": "income",
"notes": "31 upgrades + reduced churn",
},
]
try:
with open(_csv_path) as _f:
_cached_data: list[dict[str, Any]] = list(csv.DictReader(_f))
if not _cached_data:
_logger.warning("CSV at %s is empty, falling back to mock data", _csv_path)
_cached_data = _MOCK_DATA
except (FileNotFoundError, OSError) as exc:
_logger.warning("Could not load CSV at %s (%s), falling back to mock data", _csv_path, exc)
_cached_data = _MOCK_DATA
def query_data_impl(query: str) -> list[dict[str, Any]]:
"""Query the database. Takes natural language.
Always call before showing a chart or graph. Returns the full
dataset as a list of dicts (rows from the CSV).
"""
return _cached_data