LLM Runtime

Applies to SDK 0.16+ · Last updated: 2026-06-12

AgentNodeRuntime connects any OpenAI, Anthropic, or Gemini agent to AgentNode with zero configuration. It registers 5 meta-tools, injects a system prompt, and runs the tool loop automatically. The LLM discovers, installs, and runs capabilities on its own.

Quick start

terminal

$ pip install agentnode-sdk

OpenAI

openai_agent.pypython

from openai import OpenAI
from agentnode_sdk import AgentNodeRuntime

runtime = AgentNodeRuntime()
client = OpenAI()

result = runtime.run(
    provider="openai",
    client=client,
    model="gpt-4o",
    messages=[{"role": "user", "content": "Count the words in 'Hello world'"}],
)
print(result.content)

Anthropic

anthropic_agent.pypython

from anthropic import Anthropic
from agentnode_sdk import AgentNodeRuntime

runtime = AgentNodeRuntime()
client = Anthropic()

result = runtime.run(
    provider="anthropic",
    client=client,
    model="claude-sonnet-4-6",
    messages=[{"role": "user", "content": "Search for PDF tools on AgentNode"}],
)

Gemini

gemini_agent.pypython

from google import genai
from agentnode_sdk import AgentNodeRuntime

runtime = AgentNodeRuntime()
client = genai.Client()

result = runtime.run(
    provider="gemini",
    client=client,
    model="gemini-2.5-flash",
    messages=[{"role": "user", "content": "What AgentNode tools are available?"}],
)

OpenRouter / any OpenAI-compatible provider

Use Mistral, DeepSeek, Qwen, Llama, and more via OpenRouter or any OpenAI-compatible endpoint:

openrouter_agent.pypython

from openai import OpenAI
from agentnode_sdk import AgentNodeRuntime

runtime = AgentNodeRuntime()
client = OpenAI(
    api_key="sk-or-...",
    base_url="https://openrouter.ai/api/v1",
)

result = runtime.run(
    provider="openai",
    client=client,
    model="mistralai/mistral-large",
    messages=[{"role": "user", "content": "Find and install a PDF reader tool"}],
)

Manual tool calling

For any provider that supports tool calling, get tool definitions and dispatch calls manually with handle():

manual.pypython

runtime = AgentNodeRuntime()

# Get tool definitions in your provider's format
tools = runtime.as_openai_tools()    # OpenAI function-calling format
tools = runtime.as_anthropic_tools() # Anthropic format
tools = runtime.as_gemini_tools()    # Gemini format
tools = runtime.as_generic_tools()   # Generic / baseline format

# When the LLM makes a tool call, dispatch it:
result = runtime.handle("agentnode_search", {"query": "pdf extraction"})
# → {"success": true, "result": {"total": 5, "results": [...]}}

Constructor

init.pypython

AgentNodeRuntime(
    client=None,                     # Optional AgentNodeClient
    api_key=None,                    # Optional API key
    minimum_trust_level="verified",  # "verified" | "trusted" | "curated"
)

5 meta-tools

These tools are automatically registered when you create a Runtime. The LLM calls them as needed during the tool loop.

Tool	Description
agentnode_capabilities	List installed packages (local, no API call)
agentnode_search	Search the registry (max 5 results)
agentnode_install	Install a package by slug
agentnode_run	Execute an installed tool
agentnode_acquire	Search + install in one step

API reference

Method	Description
tool_specs()	Internal typed tool definitions (list[ToolSpec])
as_openai_tools()	Tools in OpenAI function-calling format
as_anthropic_tools()	Tools in Anthropic format
as_gemini_tools()	Tools in Google Gemini format
as_generic_tools()	Tools in generic/baseline format
system_prompt()	AgentNode system prompt block (append to yours)
tool_bundle()	Combined {"tools": [...], "system_prompt": "..."}
handle(name, args)	Dispatch a tool call. Returns dict. Never throws.
run(provider, client, ...)	Auto-loop with tool dispatch. Never throws.

run() parameters

Parameter	Type	Default	Description
provider	str	—	"openai", "anthropic", or "gemini"
client	Any	—	Provider SDK client instance
messages	list[dict]	—	Conversation messages
model	str	""	Model name (e.g. "gpt-4o")
max_tool_rounds	int	8	Max tool call rounds before stopping
inject_system_prompt	bool	True	Append AgentNode prompt to system message

Trust levels

minimum_trust_level controls which packages can be installed and run through the Runtime. Higher levels are stricter:

Level	Accepts
"verified"	verified, trusted, curated
"trusted"	trusted, curated
"curated"	curated only

Three surfaces

CLI	For humans — search, install, publish
SDK / Client	For programmatic access — search, resolve, install, run
Runtime	For LLM agents — tool registration, dispatch, auto-loop