axis-core 0.10.0b0

A modular, observable AI agent framework

axis-core

A modular, observable AI agent framework for building production-ready agents in Python.

Highlights

• Lifecycle execution engine: Initialize -> Observe -> Plan -> Act -> Evaluate -> Finalize
• Pluggable adapters for models, memory, planners, and telemetry
• Built-in model fallback that branches on normalized provider failure reasons
• Transcript integrity normalization for tool-call/tool-result pairing before model calls
• Optional context-window guard with tool-result-first pruning before model calls
• Adapter compatibility transforms for provider-specific tool schema and tool-call ID constraints
• Tool system with @tool, schema generation, destructive-action confirmation hooks, and idempotency helpers for retry-safe side effects
• Optional per-agent tool allow/deny policy with glob patterns and deny-overrides-allow semantics
• Runtime policy enforcement (timeouts, retries, rate limits, cache)
• Checkpoint/resume support for phase-boundary recovery
• Budget controls for cost, token, and cycle limits
• Provider-agnostic usage normalization for budget and telemetry accounting
• Type hints with strict mypy coverage

Installation

# Core package
pip install axis-core

# Provider and adapter extras
pip install axis-core[anthropic]
pip install axis-core[openai]
pip install axis-core[openrouter]
pip install axis-core[redis]
pip install axis-core[sqlite]
pip install synaptic-core

# Everything
pip install axis-core[full]

Requires Python 3.10+.

Project Init Wizard

Use the setup wizard to install optional adapter packages and write defaults to .env.

axis-core init

Useful non-interactive flags:

• --yes: run without prompts
• --install <bundle>: install optional adapter bundle (anthropic, openai, openrouter, redis, sqlite, synaptic)
• --memory <name> / --planner <name>: set default adapters
• --synaptic-db-path <path>: set AXIS_SYNAPTIC_PATH when using synaptic memory
• --bootstrap-synaptic-db: initialize Synaptic SQLite schema during setup

CLI Runtime

Use ask for one-shot prompts and chat for interactive sessions.

# Single prompt
axis-core ask "Summarize the latest deployment status"

# Interactive chat (resume by id)
axis-core chat --session-id ops-room

# Show which agent source/config the CLI resolves
axis-core doctor

Runtime flags are shared across ask and chat:

• --model <name>
• --planner <name>
• --memory <name>
• --system "<prompt>"
• --from <module>:<callable_or_object>: load a project agent/factory explicitly
• --standalone: ignore project-bound agent config and use CLI defaults/env
• --timeout <seconds>

The session command namespace is reserved for future session-admin operations.

Project-Bound CLI (Optional)

To make axis-core ask/chat/doctor use your project's canonical agent, configure:

[tool.axis_core]
agent = "main:create_agent"

When present, the CLI loads that object/factory first. If not present, it falls back to the standalone CLI behavior (defaults from env/flags).

Quick Start

import asyncio
from axis_core import Agent, Budget, tool


@tool
def get_weather(city: str) -> str:
    return f"Weather in {city}: Sunny, 72F"


def create_agent() -> Agent:
    return Agent(
        tools=[get_weather],
        model="claude-sonnet-4-20250514",
        fallback=["gpt-4o"],
        planner="sequential",
        budget=Budget(max_cost_usd=0.50),
        system="You are a concise assistant.",
    )


async def main() -> None:
    agent = create_agent()

    result = await agent.run_async("What is the weather in Tokyo?")
    print(result.output)
    print(result.stats)


asyncio.run(main())

Streaming

for event in agent.stream("Solve 42 * 137"):
    if event.is_token:
        print(event.token, end="", flush=True)
    elif event.is_final:
        print("\nDone")

Transcript Guards

Axis normalizes transcript tool-call/tool-result pairing before model calls to reduce provider request failures in long-running or resumed sessions.

Optional controls:

• AXIS_TRANSCRIPT_STRICT=true: reject unresolved tool-call/tool-result pairing instead of silently repairing/dropping invalid entries.
• AXIS_MAX_TOOL_RESULT_CHARS=<positive-int>: cap persisted tool-result content passed to model calls.
• AXIS_CONTEXT_GUARD_ENABLED=true: enable token-threshold checks before model calls.
• AXIS_CONTEXT_WINDOW_TOKENS=<positive-int>: set the context-window token budget used by guard and pruning checks.
• AXIS_CONTEXT_GUARD_WARN_TOKENS=<positive-int>: emit warning telemetry when remaining tokens drop below threshold.
• AXIS_CONTEXT_GUARD_BLOCK_TOKENS=<positive-int>: block model calls when remaining tokens drop below threshold.
• AXIS_CONTEXT_PRUNE_ENABLED=true: opt in to tool-result-first transcript pruning before block decisions.

Tool Idempotency

Tool execution now propagates a stable per-step idempotency key through retry attempts:

• Available in ToolContext.idempotency_key for tools that accept ctx: ToolContext.
• Injected into the idempotency_key argument automatically when a tool function declares it.

For in-tool dedupe, use run_idempotent(...) to memoize side-effect results by key:

from axis_core import ToolContext, tool
from axis_core.tool import run_idempotent


@tool
async def send_invoice(ctx: ToolContext, customer_id: str) -> str:
    async def send_once() -> str:
        # external side effect
        return f"invoice:{customer_id}"

    return await run_idempotent(ctx, send_once)

Tool Policy

Use ToolPolicy to allow and deny tool names per agent. Deny patterns always override allow patterns.

from axis_core import Agent, ToolPolicy

agent = Agent(
    tools=[...],
    tool_policy=ToolPolicy(
        allow=("safe_*",),
        deny=("safe_delete_*",),
    ),
)

Runtime Hardening Guarantees

• Model fallback decisions branch on normalized failure reasons (rate_limit, timeout, connection_error, service_unavailable, transient_provider_error) so non-recoverable causes fail fast instead of attempting fallback.
• OpenAI and Anthropic adapters sanitize provider-problematic tool schema fields and normalize tool-call identifiers before provider submission.
• Usage accounting is normalized across providers (prompt/completion and input/output variants) before budget tracking.

Documentation

• Getting Started
• Examples
• Tools Guide
• Models Guide
• Runtime Operations
• Budget and Limits
• Agent Reference
• Config Reference
• Errors Reference
• Environment Variables
• Contributing

Supported Providers

Provider	Installation	Notes
Anthropic	pip install axis-core[anthropic]	Claude models via Anthropic adapter
OpenAI	pip install axis-core[openai]	Chat Completions + Responses routing
OpenRouter	pip install axis-core[openrouter]	OpenAI-compatible base URL path

For OpenRouter:

OPENAI_API_KEY=<openrouter-api-key>
OPENAI_BASE_URL=https://openrouter.ai/api/v1

Status

v0.10.0b (Beta pre-release)

• Beta means APIs are stabilizing, but breaking changes are still possible before 1.0.0.
• See CHANGELOG.md for release notes.

Development

pip install -e ".[dev,anthropic,openai]"
pytest
ruff check axis_core tests --fix
mypy axis_core --strict

For full contributor workflow and quality gates, see CONTRIBUTING.md.

License

Apache License 2.0. See LICENSE.