pydantic-ai-chdb

A Pydantic AI capability for chDB, the in-process ClickHouse engine: give agents analytical SQL over local files, object storage, and remote databases — no server to start, no connection string, no credentials.

Installation

pip install pydantic-ai-chdb

Usage

from pydantic_ai import Agent
from pydantic_ai_chdb import ChDBCapability

agent = Agent(
    "openai:gpt-4o-mini",
    capabilities=[ChDBCapability(attachments={"events": "data/events.parquet"})],
)

result = agent.run_sync("What are the top 5 event types by count?")
print(result.output)

The capability registers the chDB tool suite — run_select_query (read-only ClickHouse SQL with {name:Type} parameter binding), list_databases, list_tables, describe_table, get_sample_data, list_functions, and (on writable sessions) attach_file — plus schema-first usage instructions for the system prompt. Tool names and descriptions come from the descriptors bundled with the chdb package, its single source of truth across bindings.

Typed errors become retries

The capability's on_tool_execute_error hook maps typed chdb.agents.errors.ChDBError failures to ModelRetry, so the model sees the engine's error type, code, and message —

chDB UNKNOWN_IDENTIFIER (code 47): Unknown expression identifier `SELEC` ...

— and corrects the query within the agent's retry budget instead of the run dying on an exception. Non-chDB errors propagate unchanged.

Safety defaults

• Read-only by default. Sessions are locked with the ClickHouse readonly=2 setting: INSERT/CREATE/ALTER/DROP are rejected by the engine while SELECT and the file()/s3()/url() table functions keep working. Pass read_only=False for a writable session (this also exposes attach_file).
• Capped results. max_rows (default 1000) and max_bytes (default 1 MB) bound every payload; truncated results carry a truncated flag. max_execution_time adds an engine-side wall-clock limit.
• Optional source allowlist. With file_allowlist=["/data/"], file-like sources may only read under the listed prefixes and DSN-based sources (postgresql(), mysql(), remote(), …) are refused.

Sharing and lifecycle

To control the engine's lifecycle yourself — or to share one session across capabilities and other chDB bindings — create it explicitly and inject it:

from chdb.agents import ChDBTool
from pydantic_ai_chdb import ChDBCapability

engine = ChDBTool("analytics_dir", read_only=False)
capability = ChDBCapability(engine=engine)
...
engine.close()

capability.close() closes only an engine the capability created itself.

Spec-based construction works out of the box: ChDBCapability.from_spec(path="analytics_dir", read_only=True).

Requires Pydantic AI V2. This package is maintained by the chDB team.