Agno

Verified as a sealed mission 2026-09-27 — general questions, live weather and BBC News through HexaEight-verified services, search of this machine’s documents, “who am I”, and conversation memory across turns.

As a sealed mission

HexaEight decides who may ask and which command may run; Agno does the work. It is a direct mission — the same one-card mission every framework uses — and the answer is Agno’s, headed Answered by Agno.

hexaeight-activate enable agno                       # from your agent's folder
hexaeight-activate enable agno --venv ~/my-env       # or use an environment you already have

Then choose runmission → Agno_v1_Runner in the workspace. Requires agent r30, harness engine r41 and Activate 1.0.68 or later, and Python 3.10–3.13 (or uv). The mission bundle is the integration-agno-v1 release; the runner, pinned requirements and install-by-hand steps are in integration_examples/agno.

the one command	python3 runner.py --question-file question.txt — pinned to runner.py’s sha256
the Agno half	an Agent with the tools as plain functions
model	Agno’s Claude on the turn’s route, authenticated with the turn’s token — no provider key in the file
pinned	agno==3.0.11, anthropic==1.8.0
its own output	to agno-run.log in the turn’s folder, with one [tool] line per tool call

The reply is Agno’s final assistant message only. Its content also carries text the model wrote before a tool call (“Let me check…”), which is working, not the answer.

To serve it to other people’s software, run the same enable inside a runner’s folder — see Serving it to other people and systems.

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As a process engine

Verified 2026-08-19 — PASS, 9s. Session persistence: native SqliteDb.

The shortest integration of the ten. Agno owns persistence entirely — hand it a session_id and it rehydrates history itself.

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The runner

import sys, os
sys.path.insert(0, os.path.expanduser("~/agenttests"))
import azcfg, hetool
from agno.agent import Agent
from agno.models.openai import OpenAIChat
from agno.db.sqlite import SqliteDb

DB = os.path.expanduser("~/agenttests/agno/agno.db")

def get_working_folder() -> str:
    """Return the agent's current working folder (absolute path)."""
    return hetool.get_working_folder()

def run_shell(command: str) -> str:
    """Run a shell command in the working folder and return its output."""
    return hetool.run_shell(command)

def invoke(sid, message):
    c = azcfg.load()
    agent = Agent(
        model=OpenAIChat(id=c["model"], base_url=c["base_url"], api_key=c["api_key"]),
        db=SqliteDb(db_file=DB),
        session_id=sid,
        add_history_to_context=True,
        tools=[get_working_folder, run_shell],
        instructions="Be concise. Use tools for operational questions.",
    )
    return str(agent.run(message).content).strip()

That is the entire runner — no load, no save, no transcript handling.

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Engine definition

{
  "type": "process",
  "file": "/home/you/agno/.venv/bin/python3",
  "nativeSession": true,
  "argsNew":    ["/home/you/he_adapter.py", "/home/you/agno_session.py", "",            "{message}"],
  "argsResume": ["/home/you/he_adapter.py", "/home/you/agno_session.py", "{sessionId}", "{message}"],
  "replyField": "result",
  "sessionIdField": "session_id",
  "approve": false,
  "workdir": "/home/you/work",
  "proxy": { "shape": "openai", "baseUrlEnv": "OPENAI_BASE_URL", "keyEnv": "OPENAI_API_KEY",
             "modelEnv": "OPENAI_MODEL", "model": "<route>|<provider model>" }
}

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Adoption

1. Keep your agent definition as it is.
2. Pass HBIA’s sid straight through as Agno’s session_id.
3. Add db=SqliteDb(...) and add_history_to_context=True.
4. Build OpenAIChat from azcfg.load().
5. Seal the engine, point external.engine at it, restart.

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Gotchas

add_history_to_context=True is not the default. Without it Agno stores the session but does not feed prior turns to the model — persistence that looks like it works and produces an agent with no memory. This is the single most likely thing to get wrong here.

OpenAIChat(id=...), not model=.... The keyword is id.

One SQLite file, many sessions. Keyed by session_id, so a swarm sharing a filesystem shares history correctly — but SQLite over NFS is a known hazard. Keep the db on local disk.

Plain callables as tools, with real docstrings — Agno reads the signature and docstring.