Add persistent memory to PydanticAI agents with the cortexdb v1 SDK.
PydanticAI Integration
PydanticAI uses typed Pydantic models for prompts, results, and tools. Wire CortexDB recall + capture as agent tools.
Install
pip install cortexdbai[pydanticai]
LLM provider note. This example uses OpenAI for the agent's chat model, but CortexDB itself is LLM-agnostic. The only model CortexDB invokes internally is the one used by
POST /v1/answerandPOST /v1/understanding/synthesize(Claude Opus 4.6 by default, configurable). Your agent's chat model is independent — swapOpenAIChat/gpt-4ofor Anthropic, Gemini, Mistral, Groq, or any local model. CortexDB does not care.
Agent tools + dependencies
import os
from cortexdb import Cortex
from cortexdb.integrations.pydanticai import CortexDBDeps, register_cortexdb_tools
from pydantic_ai import Agent
client = Cortex(
api_url="https://api-v1.cortexdb.ai",
actor="user:alice",
bearer=os.environ["CORTEX_TOKEN"],
)
agent = Agent("openai:gpt-4o", deps_type=CortexDBDeps)
register_cortexdb_tools(agent) # adds cortexdb_search / store / forget tools
deps = CortexDBDeps(client=client, scope="org:acme/user:alice")
result = agent.run_sync("What do you remember about the project?", deps=deps)
The tool functions cortexdb_search / cortexdb_store / cortexdb_forget can also be registered individually via agent.tool(...).
Prefer manual control?
import os
from datetime import datetime, timezone
from uuid import uuid4
from pydantic_ai import Agent, RunContext
from cortexdb.v1 import V1Client
client = V1Client(api_url="https://api-v1.cortexdb.ai", actor="user:alice",
bearer=os.environ["CORTEX_TOKEN"])
SCOPE = "org:acme/user:alice"
agent = Agent("openai:gpt-4o", system_prompt="Use recall_long_term before answering.")
@agent.tool
async def recall_long_term(ctx: RunContext, query: str) -> str:
pack = client.recall(scope=SCOPE, view="holistic", query=query,
include=["events", "beliefs", "facts", "episodes"],
budgets={"max_tokens": 3000})
return pack.get("context_block", "") or "(no relevant context)"
@agent.tool
async def capture(ctx: RunContext, text: str, role: str = "assistant") -> bool:
client.experience(scope=SCOPE, text=text, role=role,
observed_at=datetime.now(timezone.utc).isoformat(),
idempotency_key=f"pai-{role}-{uuid4()}")
return True
result = await agent.run("What did we decide about the renewal?")