HCLI hai

HCLI hai is a python package wrapper that contains an HCLI sample application (hai); hai is an HCLI for interacting with Ollama (remote or local), xAI, or OpenAI models via terminal input and output streams.

HCLI hai wraps hai (an HCLI) and is intended to be used with an HCLI Client [1] as presented via an HCLI Connector [2].

You can find out more about HCLI on hcli.io [3]

[1] https://github.com/cometaj2/huckle

[2] https://github.com/cometaj2/hcli_core

[3] http://hcli.io

Installation

HCLI hai requires a supported version of Python and pip.

You’ll need an HCLI Connector to run hai. For example, you can use HCLI Core (https://github.com/cometaj2/hcli_core), a WSGI server such as Green Unicorn (https://gunicorn.org/), and an HCLI Client like Huckle (https://github.com/cometaj2/huckle).

pip install hcli-hai
pip install hcli-core
pip install huckle
pip install gunicorn
hcli_core cli install `hcli_hai path`
hcli_core cli run hai | bash

Usage

Open a different shell window.

Setup the huckle env eval in your .bash_profile (or other bash configuration) to avoid having to execute eval everytime you want to invoke HCLIs by name (e.g. hai).

Note that no CLI is actually installed by Huckle. Huckle reads the HCLI semantics exposed by the API via HCLI Connector and ends up behaving like the CLI it targets.

huckle cli install http://127.0.0.1:8000
eval $(huckle env)
hai help

Versioning

This project makes use of semantic versioning (http://semver.org) and may make use of the “devx”, “prealphax”, “alphax” “betax”, and “rcx” extensions where x is a number (e.g. 0.3.0-prealpha1) on github.

Supports

Chatting via input/output streams (e.g. via pipes).
.hai folder structure in a users’s home directory to help track hai configuration and contexts.
Creating, listing, deleting, and changing conversation contexts.
Automatic title creation based on context
Custom context naming to help organize contexts
Behavior setting to allow for persistent chat behavior (e.g. the Do Anything Now (DAN) prompt).
Conversation vibing via detailed plans and HCLI integration to allow for external tool use. - This allows for capabilities enhancements (e.g. web search, git repo interaction, terminal use, etc.).
hcli-problem-details use to help relay RFC 9457 problem details back to the HCLI client.
Assistant audio summary and commentary for the last received context response.

To Do

Add HAI_HOME environment variable support.
Add individualized multiuser conversation context support.
A memory layer for the the AI HCLI (hai).
- Automatic context switching per NLP on received input stream.
- Context blending to mary different contexts.
- Automatic context compression to yield a more substantial memory footprint per context window.
A shell mode for the AI HCLI (hai) to enable shell CLI execution per sought goal.
Changing the vibing behavior should be made possible; it is currently locked in to HCLI integration and planning.
Support multi-process and multi-context to allow for multiple parallel vibes or conversations without conflict.

Bugs

Occasional empty response from summarizing assistant

Metadata

Release files for hcli-hai 4.0.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for hcli-hai 4.0.0
File	Size	Uploaded
hcli_hai-4.0.0.tar.gz	44.3 kB	Oct 13, 2026	Details

Built distribution (wheel)

Table of built distributions (wheels) for hcli-hai 4.0.0
File	Interpreter	ABI	Platform	Reset
hcli_hai-4.0.0-py3-none-any.whl 49.4 kB Oct 13, 2026	Python 3	none	any	Details

Total release size: 93.7 kB

Release files / hcli_hai-4.0.0.tar.gz

Download URL	hcli_hai-4.0.0.tar.gz
Size	44.3 kB
Tags	Source
SHA-256 checksum How to use checksums	`17720cdc0d97f989bd005e44cd55a4b88cc300b8b457c13716a1a38a4cdd1b12`
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Uploaded via	`twine/6.2.0 CPython/3.14.7`

Release files / hcli_hai-4.0.0-py3-none-any.whl

Download URL	hcli_hai-4.0.0-py3-none-any.whl
Size	49.4 kB
Tags	Python 3
SHA-256 checksum How to use checksums	`e428b9655c05510a5e35a8d73e38456733c1e168fa829086cd3d58fbbe61cc32`
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Upload date	Oct 13, 2026
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Uploaded via	`twine/6.2.0 CPython/3.14.7`