Antikythera Agent SDK
General-purpose agent runtime with multi-agent orchestration, MCP tool integration, and WebAssembly support.
Installation
pip install antikythera-agent
For WASM execution support:
pip install antikythera-agent[wasm]
Quick Start
Create an Agent
from antikythera_agent import Agent, PromptManager, PromptConfig
prompts = PromptManager()
prompts.register(PromptConfig(
id="assistant",
name="Assistant",
content="You are a helpful assistant.",
))
agent = Agent(
provider="openai",
model="gpt-4o",
system_prompt=prompts.get_content("assistant")
)
result = agent.run("Hello, how can you help me?")
print(result.output)
Multi-Agent Orchestration
from antikythera_agent import Orchestrator, PromptManager, PromptConfig
prompts = PromptManager()
prompts.register(PromptConfig(
id="coder",
name="Coder",
content="You are a software engineer.",
tags=["engineering"]
))
prompts.register(PromptConfig(
id="reviewer",
name="Reviewer",
content="You are a code reviewer.",
tags=["quality"]
))
orchestrator = Orchestrator(execution_mode="auto", max_concurrent_tasks=4)
orchestrator.register_agent(AgentProfileConfig(
id="coder",
name="Coder",
role="developer",
system_prompt=prompts.get_content("coder")
))
orchestrator.register_agent(AgentProfileConfig(
id="reviewer",
name="Reviewer",
role="reviewer",
system_prompt=prompts.get_content("reviewer")
))
result = orchestrator.dispatch("Write and review code")
WASM Runtime (Server-Side)
from antikythera_agent import WasmRuntime
runtime = WasmRuntime()
result = runtime.call_checked("init", '{"max_steps": 10}')
print(result)
Load Prompts from JSON
from antikythera_agent import PromptManager
# Load from file
prompts = PromptManager.from_file("prompts.json")
# Or load from string
prompts = PromptManager.from_json('[{"id":"agent","name":"Agent","content":"You are helpful."}]')
Requirements
- Python 3
- wasmtime (optional, for WASM execution; the supported minimum is pinned in pyproject.toml)
License
MIT
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