Unified Agent Core — declarative agent manifests, pluggable registries, and interfaces for the AgentForge harness.
Project description
agent-core
Unified Agent Core — a declarative, provider-agnostic runtime for building LLM agents from YAML manifests. It's the shared core that powers AgentForge and, unmodified, the naturalist assistant in FloraLens — proving one runtime can serve very different products.
Features
- Declarative manifests — define an agent (model, prompt, tools, limits, guardrails, io-schema) in YAML; load + validate fail-fast.
- Pluggable registries — register model providers, tools, prompts, memory backends, and guardrails; extend without editing the core.
- LangGraph ReAct runtime with live token streaming over an SSE-friendly trace bus.
- Model providers — OpenAI, Anthropic, and an offline Echo provider for deterministic tests.
- Built-in tools — web search, HTTP fetch, sandboxed code execution, embedding search; plus MCP auto-binding for external tool servers.
- Multi-agent supervisor — expose sub-agents to a supervisor as tools.
- Guardrails & io-schema enforced at runtime; memory (in-memory / mem0); opt-in durable SQLite checkpointer for multi-turn threads.
- Evaluation harness — dev/held-out suites, programmatic/rubric/LLM-judge scoring, and a regression gate.
Install
pip install "pdz-agent-core[openai]" # + OpenAI provider; imported as `agent_core`
# extras: [anthropic] [mem0] [mcp] [dev]
Quickstart
from agent_core import build_default_registries, compile_agent, load_manifest_dict
manifest = {
"id": "echo_agent",
"model": {"provider": "echo", "name": "test-model"},
"prompt_ref": "prompts/echo_agent.md",
"tools": [],
}
agent = compile_agent(load_manifest_dict(manifest), build_default_registries())
async for event in agent.astream("hello"):
print(event.type, event.detail)
Documentation
Full architecture, API, and the cross-product reuse write-up live in the
AgentForge repo under docs/.
License
MIT © pdz1804
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