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 | bashUsage
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 helpVersioning
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
1 maintainer
Metadata
1 maintainer
Release files for hcli-hai 4.1.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| hcli_hai-4.1.0.tar.gz | 146.6 kB | Without provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| hcli_hai-4.1.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 203.3 kB
Release files / hcli_hai-4.1.0.tar.gz
| Download URL | hcli_hai-4.1.0.tar.gz |
|---|---|
| Size | 146.6 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
8da1eb625ed72a03b2eda800402e7da20d6e22dcbe3fa67a8126395a9bb827d7
|
|
BLAKE2b-256 checksum How to use checksums |
80e380dd1d09d0a00d393e6849cc34ff5837edb240012a8209e401d951597ff5
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.14.8
|
Release files / hcli_hai-4.1.0-py3-none-any.whl
| Download URL | hcli_hai-4.1.0-py3-none-any.whl |
|---|---|
| Size | 56.6 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
1a2d5b2db4520fec232361e684349a2a50d24c38e26bcc1865360c55ecce1203
|
|
BLAKE2b-256 checksum How to use checksums |
8572873107d86347bc95cf232f14252a69d798acfb3b0285aec14da5b6a29dd1
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.14.8
|
Security for hcli-hai 4.1.0
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.
