Spectron agent memory for Pydantic AI.
Spectron is SurrealDB's memory and knowledge layer for AI agents. This package connects it to Pydantic AI through that framework's own extension points, so an agent can remember facts across runs, recall them when they are relevant, and keep a durable record of its conversations.
It gives you three surfaces, which you can use on their own or together:
- Memory tools (
SpectronToolset): exposerecall,context,remember, and more as tools the agent calls when it decides to. - Auto-recall (
spectron_history_processor): inject relevant memory before each model request, with no tool call required. - Persistence (
store_run,store_messages): write a run's messages back to Spectron so conversations survive across sessions.
Spectron is in early preview. Its Python client ships in the base SurrealDB SDK
(surrealdb, v3 alpha or newer), which installs automatically as a dependency
of this package. Until you have access to a Spectron instance, you can still
install this package, wire it into an agent, and run the test suite: every
Spectron call goes through a small client protocol that is easy to fake.
pip install spectron-pydantic-aiTo run against a live Spectron instance and a model provider (the Spectron
client is bundled in surrealdb, installed automatically):
pip install "spectron-pydantic-ai" "pydantic-ai-slim[openai]"import asyncio
from pydantic_ai import Agent
from spectron_pydantic_ai import SpectronMemory, SpectronToolset
async def main():
memory = SpectronMemory.connect(
context="your-context",
endpoint="https://your-spectron-instance",
api_key="your-api-key",
on_behalf_of="ada",
)
agent = Agent("openai:gpt-4o", toolsets=[SpectronToolset(memory)])
result = await agent.run("Remember that I prefer window seats.")
print(result.output)
asyncio.run(main())Inject relevant memory before every run without giving the agent a tool. The processor reads the latest user message, recalls related memories, and prepends them as context.
from pydantic_ai import Agent
from pydantic_ai.capabilities import ProcessHistory
from spectron_pydantic_ai import spectron_history_processor
processor = spectron_history_processor(memory)
agent = Agent("openai:gpt-4o", capabilities=[ProcessHistory(processor)])Use mode="context" to load the current working set instead of searching by the
latest message.
Note on versions: Pydantic AI registers history processors through the
capabilitiesargument withProcessHistory, as shown above. Older releases used ahistory_processors=[...]argument instead. The processor function returned byspectron_history_processorworks with both; only the way you attach it to the agent differs. Check the version installed in your project.
Store a run's messages so the next session can recall them:
from spectron_pydantic_ai import store_run
result = await agent.run("I am planning a trip to Tokyo.")
await store_run(memory, result)SpectronMemory carries a scope (session_id, scope, on_behalf_of) that is
added to every operation — scope is applied as scopes on writes and lens
on reads. One connection can serve many users and sessions by creating narrowed
views:
base = SpectronMemory(client)
alice = base.scoped(on_behalf_of="alice", session_id="s1")
bob = base.scoped(on_behalf_of="bob", session_id="s2")| Name | Purpose |
|---|---|
SpectronMemory |
Scoped wrapper over the Spectron client. connect(...), scoped(...), and the memory verbs (remember, remember_many, recall, query_context, reflect, forget, inspect, upload). |
SpectronToolset |
Pydantic AI toolset exposing memory operations as tools. |
spectron_history_processor |
Build a history processor for auto-recall. |
store_run, store_messages |
Persist messages back to Spectron. |
SpectronClient |
Protocol describing the client this package needs. |
SpectronError, SpectronImportError |
Exceptions raised by the package. |
The toolset exposes recall, context, and remember by default. Pass
tools=ALL_TOOLS (or a subset) to also expose reflect and forget:
from spectron_pydantic_ai import ALL_TOOLS, SpectronToolset
toolset = SpectronToolset(memory, tools=ALL_TOOLS)See the examples directory for runnable scripts covering the
toolset, auto-recall, and a persistent multi-turn chat.
This project uses uv.
uv sync
uv run ruff check .
uv run ruff format --check .
uv run pyright
uv run pytestApache License 2.0. See LICENSE.