nocturnusai 0.2.0

Python SDK for NocturnusAI — a logic-based inference engine and knowledge database

NocturnusAI Python SDK

Python SDK for NocturnusAI — a logic-based inference engine and knowledge database for agentic AI systems.

Install

pip install nocturnusai

With LangChain integration:

pip install "nocturnusai[langchain]"

Quick start

import asyncio
from nocturnusai import NocturnusAIClient

async def main():
    async with NocturnusAIClient("http://localhost:9300") as client:
        # Store facts
        await client.tell("likes(alice, bob)")
        await client.tell("likes(bob, carol)")

        # Define rules
        await client.teach("friends(?x, ?y) :- likes(?x, ?y), likes(?y, ?x)")

        # Run inference
        results = await client.ask("friends(?x, ?y)")
        print(results)  # ['friends(alice, bob)', 'friends(bob, alice)']

asyncio.run(main())

Sync usage:

from nocturnusai import SyncNocturnusAIClient

with SyncNocturnusAIClient("http://localhost:9300") as client:
    client.tell("likes(alice, bob)")
    print(client.ask("likes(?x, bob)"))

LangChain integration

from langchain_openai import ChatOpenAI
from langchain.agents import create_react_agent, AgentExecutor
from nocturnusai.langchain import get_nocturnusai_tools

tools = get_nocturnusai_tools("http://localhost:9300")
llm = ChatOpenAI(model="gpt-4o")
agent = AgentExecutor(agent=create_react_agent(llm, tools, prompt), tools=tools)

MCP (Model Context Protocol)

from nocturnusai import NocturnusAIMCPClient

async with NocturnusAIMCPClient("http://localhost:9300") as mcp:
    await mcp.initialize()
    tools = await mcp.list_tools()
    result = await mcp.call_tool("tell", {"statement": "likes(alice, bob)"})

Or configure via mcp-config.json for Claude Desktop, Cursor, Windsurf, and VS Code — see mcp-configs/ in the main repo.

Starting NocturnusAI

# Docker (recommended)
docker run -p 9300:9300 ghcr.io/auctalis/nocturnusai:latest

# Or one-line install
curl -fsSL https://raw.githubusercontent.com/Auctalis/nocturnusai/main/install.sh | bash

Documentation

• Full API reference
• Demos and examples
• MCP configuration