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rayhpeng
23eacf9533
Phase 2-A prerequisite for event storage: adds the unified run event stream interface (RunEventStore) with an in-memory implementation, RunEventsConfig, gateway integration, and comprehensive tests (27 cases). Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
34 lines
1.1 KiB
Python
34 lines
1.1 KiB
Python
"""Run event storage configuration.
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Controls where run events (messages + execution traces) are persisted.
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Backends:
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- memory: In-memory storage, data lost on restart. Suitable for
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development and testing.
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- db: SQL database via SQLAlchemy ORM. Provides full query capability.
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Suitable for production deployments.
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- jsonl: Append-only JSONL files. Lightweight alternative for
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single-node deployments that need persistence without a database.
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"""
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from __future__ import annotations
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from typing import Literal
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from pydantic import BaseModel, Field
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class RunEventsConfig(BaseModel):
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backend: Literal["memory", "db", "jsonl"] = Field(
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default="memory",
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description="Storage backend for run events. 'memory' for development (no persistence), 'db' for production (SQL queries), 'jsonl' for lightweight single-node persistence.",
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)
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max_trace_content: int = Field(
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default=10240,
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description="Maximum trace content size in bytes before truncation (db backend only).",
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)
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track_token_usage: bool = Field(
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default=True,
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description="Whether RunJournal should accumulate token counts to RunRow.",
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)
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