TiDB

TiDB speaks the MySQL wire protocol, so Memori integrates with it through the same SQLAlchemy / PyMySQL path as MySQL. Memori auto-detects TiDB from SELECT VERSION() and routes it through a dedicated TiDB integration path that reuses the MySQL storage family.

Install

pip install memori pymysql sqlalchemy certifi

Quick Start

from memori import Memori
import certifi
from sqlalchemy import create_engine
from sqlalchemy.orm import sessionmaker

engine = create_engine(
    "mysql+pymysql://user:password@host:4000/memori_db?charset=utf8mb4",
    connect_args={"ssl": {"ca": certifi.where()}},
    pool_pre_ping=True,
    pool_recycle=1800,
)
SessionLocal = sessionmaker(bind=engine)

mem = Memori(conn=SessionLocal)
mem.config.storage.build()

Connection Strings

Use the connection string provided by your TiDB deployment or TiDB Cloud instance. For TiDB Cloud Serverless with SQLAlchemy + PyMySQL, pass TLS through connect_args={"ssl": {"ca": certifi.where()}} so the driver uses a trusted CA bundle. Memori does not require a separate adapter.

Complete Example

import os
import certifi
from sqlalchemy import create_engine
from sqlalchemy.orm import sessionmaker
from memori import Memori
from openai import OpenAI

engine = create_engine(
    os.getenv("DATABASE_CONNECTION_STRING"),
    connect_args={"ssl": {"ca": certifi.where()}} if os.getenv("DATABASE_USE_TLS") else {},
    pool_pre_ping=True,
    pool_recycle=1800,
)
SessionLocal = sessionmaker(bind=engine)

client = OpenAI(api_key=os.getenv("OPENAI_API_KEY"))
mem = Memori(conn=SessionLocal).llm.register(client)
mem.attribution(entity_id="user_123", process_id="my_agent")
mem.config.storage.build()

response = client.chat.completions.create(
    model="gpt-4.1-mini",
    messages=[{"role": "user", "content": "I work on distributed systems."}]
)
print(response.choices[0].message.content)

mem.augmentation.wait()
facts = mem.recall("distributed systems")
print(facts)

Why TiDB?

• MySQL compatibility: Works with the same client stack most Python apps already use.
• Distributed SQL: Good match for multi-tenant memory services that need horizontal growth.
• Operational simplicity: Easy path from local prototyping to TiDB Cloud without changing Memori code.

Notes

• TiDB currently follows the same Memori storage family as MySQL. This keeps the integration low-risk and smooth for other MySQL-compatible systems.
• TiDB Cloud Serverless requires secure transport. With SQLAlchemy + PyMySQL, the simplest working setup is certifi plus connect_args={"ssl": {"ca": certifi.where()}}.
• If you later want TiDB-specific optimizations, such as native vector support, those can be layered in separately without changing the basic BYODB path.