Agents Overview

SynapseKit agents are async-first, tool-using AI systems that reason and act to complete tasks.

Core concepts

Concept	Class	Description
Tool	BaseTool	A single action the agent can take
Registry	ToolRegistry	Looks up tools by name, generates schemas
Memory	AgentMemory	Records Thought→Action→Observation steps
ReAct	ReActAgent	Prompt-based reasoning loop, any LLM
Function Calling	FunctionCallingAgent	Native OpenAI/Anthropic tool use
Executor	AgentExecutor	Unified runner — picks the right agent

Quick start

import asyncio
from synapsekit import AgentExecutor, AgentConfig, CalculatorTool
from synapsekit.llm.openai import OpenAILLM
from synapsekit.llm.base import LLMConfig

llm = OpenAILLM(LLMConfig(model="gpt-4o-mini", api_key="sk-..."))

executor = AgentExecutor(AgentConfig(
    llm=llm,
    tools=[CalculatorTool()],
    agent_type="function_calling",
))

answer = asyncio.run(executor.run("What is 2 ** 10 + 24?"))
print(answer)  # "The answer is 1048."

Built-in tools

Tool	Class	Extra	Description
Calculator	CalculatorTool	none	Safe math eval
Python REPL	PythonREPLTool	none	Execute Python code
File Read	FileReadTool	none	Read local files
Web Search	WebSearchTool	synapsekit[search]	DuckDuckGo search
SQL Query	SQLQueryTool	none (SQLite) / sqlalchemy	SQL SELECT queries

Agent types

"react" — Works with any LLM. Uses a structured text prompt (Thought/Action/Observation). No native function calling required.

"function_calling" — Requires OpenAILLM or AnthropicLLM. Uses native tool_calls / tool_use for more reliable tool selection.

Sync usage

executor = AgentExecutor(AgentConfig(llm=llm, tools=[CalculatorTool()]))
answer = executor.run_sync("What is sqrt(144)?")