agentivium-core 0.2.0

Core abstractions for Agentivium agent-native systems.

Agentivium Core

agentivium-core defines the small, domain-neutral contracts shared by Agentivium agent-native systems. It provides typed schemas and abstract interfaces for intent parsing, policy validation, planning, tool adaptation, provider-neutral LLM calls, execution tracing, and evaluation.

It is not an agent runtime, a provider-specific LLM wrapper, or a domain implementation. Schedulers, provider clients, policies, and orchestration belong in extension packages.

Install

pip install agentivium-core

For local development:

pip install -e ".[dev]"

Extend the core

Domain packages subclass schemas and implement interfaces:

from agentivium_core.intent import IntentIR, IntentParser


class MyIntentIR(IntentIR):
    domain: str = "my_domain"
    task: str


class MyIntentParser(IntentParser):
    def parse(
        self,
        request: str,
        context: dict[str, object] | None = None,
    ) -> MyIntentIR:
        return MyIntentIR(raw_request=request, task=request)

The dependency direction stays one-way: domain packages import agentivium_core; the core never imports a domain package.

Public API

from agentivium_core.intent import IntentIR, IntentParser
from agentivium_core.planner import ActionPlan, Planner
from agentivium_core.policy import (
    PolicyValidator,
    ValidationIssue,
    ValidationResult,
)
from agentivium_core.tools import ToolAdapter
from agentivium_core.trace import ExecutionTrace
from agentivium_core.eval import EvaluationRecord

Provider-neutral LLM abstraction

agentivium-core defines LLMClient, LLMRequest, LLMResponse, PromptTemplate, StructuredOutputSpec, and LLMCallTrace so downstream packages can use LLMs without coupling core to OpenAI, Anthropic, Gemini, Ollama, vLLM, llama.cpp, or any other provider.

from agentivium_core.llm import (
    LLMClient,
    LLMRequest,
    LLMResponse,
    PromptTemplate,
)


class MyLocalLLMClient(LLMClient):
    def generate(self, request: LLMRequest) -> LLMResponse:
        return LLMResponse(content='{"intent": "example"}', model="local")


template = PromptTemplate(
    name="intent_parser",
    system="You extract structured intent.",
    user_template="Request: {request}",
)

messages = template.render({"request": "Run a small MPI job."})
client = MyLocalLLMClient()
response = client.generate(LLMRequest(messages=messages))
print(response.content)

Production provider clients live in domain or provider packages. Core only defines the contracts and a MockLLMClient for tests and demos.

See the concepts, API reference, extension guide, and examples. The complete v0.1 rationale and boundaries are preserved in the original design guideline.