spectron-openai-agents-sdk 0.1.1

Spectron agent memory for the OpenAI Agents SDK

Spectron for the OpenAI Agents SDK

Give agents built with the OpenAI Agents SDK a durable, shared memory backed by Spectron, SurrealDB's memory and knowledge layer.

Spectron stores facts, past turns, preferences, and knowledge as a graph with temporal awareness, and lets several agents read and write the same memory. This package wires that into the Agents SDK so an agent can remember across runs and recall what it needs before it answers.

How it works

There are two ways to use memory, and they compose:

1. Function tools the agent calls itself. The agent decides when to remember, recall, context, reflect, or forget. This is the pattern used by the mem0 and cognee integrations.
2. Automatic memory around a run. run_with_memory recalls memory relevant to the input, injects it into the prompt, runs the agent, and stores the result. The agent needs no memory tools of its own.

Both talk to Spectron through a single SpectronClient, scoped by a MemoryScope (agent_id, session_id, user_id).

Installation

pip install spectron-openai-agents-sdk

This pulls in the Spectron SDK (surrealdb), which the integration uses to reach a deployment.

Set the connection and model credentials:

export OPENAI_API_KEY="your-openai-api-key"
export SPECTRON_ENDPOINT="https://your-spectron-endpoint"
export SPECTRON_CONTEXT="your-memory-context"
export SPECTRON_API_KEY="your-api-key"   # optional for local, unsecured instances

Usage

Memory as function tools

from agents import Agent, Runner
from spectron_openai_agents_sdk import get_spectron_tools

agent = Agent(
    name="assistant",
    instructions=(
        "You are a helpful assistant. Use recall to check memory before you "
        "answer, and use remember to store anything worth keeping."
    ),
    tools=get_spectron_tools(session_id="user-123"),
)

Runner.run_sync(agent, "My name is Ada and I work on databases.")

result = Runner.run_sync(agent, "What do you know about me?")
print(result.final_output)

get_spectron_tools builds the tools from SPECTRON_* environment variables by default. Pass a client= to use an explicit SpectronClient, and include= to choose a subset of operations.

Automatic memory around a run

import asyncio
from agents import Agent
from spectron_openai_agents_sdk import MemoryScope, run_with_memory

agent = Agent(name="assistant", instructions="You are a helpful assistant.")
scope = MemoryScope(session_id="user-123")

async def main():
    await run_with_memory(agent, "My name is Ada.", scope=scope)

    result = await run_with_memory(agent, "What is my name?", scope=scope)
    print(result.final_output)

asyncio.run(main())

Persisting output with hooks

To save an agent's output while running it yourself, attach SpectronMemoryHooks:

from agents import Runner
from spectron_openai_agents_sdk import SpectronClient, SpectronMemoryHooks, MemoryScope

client = SpectronClient.from_env()
hooks = SpectronMemoryHooks(client, MemoryScope(session_id="user-123"))

await Runner.run(agent, "Summarize our project decisions.", hooks=hooks)

Operations

Operation	Purpose
remember	Store a fact, preference, or event.
recall	Search memory for content relevant to a query.
context	Assemble a single ranked context block for a query.
reflect	Synthesize stored memory into a higher-level summary.
forget	Remove matching memory.

Multi-agent shared memory

Agents that share a MemoryScope read and write the same Spectron memory, so knowledge one agent stores is available to another. See examples/04_multi_agent_shared_memory.py.

Examples

Runnable scripts live in examples/:

• 01_quickstart.py stores a fact and recalls it with the memory tools.
• 02_function_tools.py exercises the full tool set.
• 03_automatic_memory.py uses run_with_memory with no memory tools on the agent.
• 04_multi_agent_shared_memory.py shares one memory across two agents.

Configuration notes

This integration targets the Spectron client in surrealdb 3.x, which exposes Spectron and AsyncSpectron. The SDK is imported lazily, only when a client is built from settings or the environment, and all SDK calls live in src/spectron_openai_agents_sdk/client.py. If a future SDK release changes a method name or constructor argument, that file is the single place to adjust; the tools, hooks, and examples do not change.

The five operations map onto SDK methods as remember, recall, context (the SDK's query_context), reflect, and forget. Scope is applied per call: session_id maps to the SDK session_id, user_id to on_behalf_of, and agent_id to scopes on writes and lens on reads.

License

Licensed under the Apache License 2.0.