open-jet 0.4.1

Claude Code for local devices: chat with self-hosted models, run agent tools, and manage context safely ─ all without an internet connection.

Open-Jet

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An AI coding agent that runs entirely on your machine.

This is Claude Code for local LLMs. OpenJet handles the model, runtime, and setup for you, so you can run a terminal coding agent on your own machine without fighting configuration. It reads files, edits code, runs commands, and keeps your work out of the cloud.

open-jet ships the full OpenJet package:

• the CLI and chat TUI
• the Python SDK
• the benchmarking entrypoints

Install it with:

pip install open-jet

OpenJet handles the model, runtime, and local setup without making you wire together llama.cpp, model files, and device-specific settings by hand. You get a coding agent in your terminal that can read files, edit code, run commands, and stay local.

This is not an SDK-only wheel. It installs the full OpenJet package, with openjet.sdk exposed as a supported import surface.

Product Surfaces

OpenJet has three primary surfaces in one package:

• CLI + chat TUI for interactive local agent work
• Python SDK for embedded sessions, hardware profiling, and auto-configuration
• Benchmarking for llama-bench runs and sweep comparisons

Typical entrypoints:

open-jet
open-jet benchmark --sweep

from openjet.sdk import OpenJetSession, recommend_hardware_config

What You Get

• Read and edit local code from a terminal agent
• Run shell commands through the same session flow
• Resume sessions instead of losing context when the terminal closes
• Work on constrained hardware with hardware-aware model selection
• Use the Python SDK to embed the same runtime in your own app
• Run benchmarks against your current model/runtime profile

SDK Import Path

Use:

from openjet.sdk import recommend_hardware_config

or:

from openjet.sdk import OpenJetSession, create_agent

SDK Surface

The supported SDK surface includes:

from openjet.sdk import (
    HardwareRecommendation,
    HardwareRecommendationInput,
    OpenJetSession,
    RecommendedLlamaConfig,
    RecommendedModel,
    SDKEvent,
    SDKEventKind,
    SDKResponse,
    ToolResult,
    create_agent,
    recommend_hardware_config,
)

That covers two main use cases:

• hardware/model recommendation for local llama.cpp setups
• embedded session/chat usage from your own Python application

Hardware Recommendation API

recommend_hardware_config() takes hardware input and returns:

• a recommended model
• recommended llama device settings
• recommended GPU layer count
• recommended context window size
• a token generation estimate for the recommended setup

Example:

from openjet.sdk import recommend_hardware_config

result = recommend_hardware_config(
    {
        "total_ram_gb": 16,
        "gpu": "cuda",
        "vram_mb": 24576,
        "label": "RTX 4090 box",
    }
)

print(result.model.label)
print(result.model.target_path)
print(result.llama.device)
print(result.llama.gpu_layers)
print(result.llama.context_window_tokens)

Typed input also works:

from openjet.sdk import HardwareRecommendationInput, recommend_hardware_config

result = recommend_hardware_config(
    HardwareRecommendationInput(
        total_ram_gb=8.0,
        gpu="cpu",
        hardware_profile="other",
        hardware_override="desktop_8",
    )
)

Session API

Use OpenJetSession when you want to embed OpenJet into another Python service, worker, or app.

Basic example:

import asyncio

from openjet.sdk import OpenJetSession


async def main() -> None:
    session = await OpenJetSession.create()
    try:
        result = await session.run("Summarize the current README")
        print(result.text)
    finally:
        await session.close()


asyncio.run(main())

The session API includes:

• OpenJetSession.create(...)
• session.stream(...)
• session.run(...)
• session.set_airgapped(...)
• session.add_turn_context(...)
• session.clear_turn_context(...)
• create_agent(...)

The event/response types exposed for integrations are:

• SDKEvent
• SDKEventKind
• SDKResponse
• ToolResult

CLI

This package also installs the CLI:

openjet

or:

open-jet

The CLI and the SDK share the same underlying package and runtime code.

Package Contents

This wheel currently includes:

• openjet.sdk for Python integrations
• CLI entrypoints: openjet and open-jet
• benchmark entrypoints via open-jet benchmark
• the local/session runtime used by both the SDK and the CLI

If you only need one narrow SDK feature, the package still installs the full declared dependency set for this distribution.

Repository

• Repository: github.com/l-forster/open-jet
• Issues: github.com/l-forster/open-jet/issues

License

open-jet core is licensed under Apache-2.0.

This package covers the permissive core SDK and CLI. Any future hosted, team, or enterprise offerings may be licensed separately.

External contributions are accepted under the contributor terms in the repository's CONTRIBUTING.md and CLA.md.