Skip to main content

A command-line interface for Ollama API

Project description

mdllama

Build and Publish mdllama DEB and RPM

Publish to PyPI on mdllama.py Update

PPA development (GH Pages)

A CLI tool that lets you chat with Ollama models right from your terminal, with built-in Markdown rendering.

mdllama makes it easy to interact with Ollama's AI models directly from your command line, meanwhile providing you with real-time Markdown rendering

Features

  • Chat with Ollama models from the terminal
  • Built-in Markdown rendering
  • Simple installation and removal (see below)

Screenshots

Chat Interface

Chat

Help

Help

Demo

Note: If the video does not play, you can download it here.

Installation

Install using package manager (recommended)

Debian/Ubuntu Installation

  1. Add the PPA to your sources list:

    echo 'deb [trusted=yes] https://packages.qincai.xyz/debian stable main' | sudo tee /etc/apt/sources.list.d/qincai-mdllama.list
    sudo apt update
    
  2. Install mdllama:

    sudo apt install python3-mdllama
    

Fedora Installation

  1. Download the latest RPM from: https://packages.qincai.xyz/fedora/

    Or, to install directly:

    sudo dnf install https://packages.qincai.xyz/fedora/mdllama-<version>.noarch.rpm
    

    Replace <version> with the latest version number.

  2. (Optional, highly recommended) To enable as a repository for updates, create /etc/yum.repos.d/qincai-mdllama.repo:

    [qincai-mdllama]
    name=Raymont's Personal RPMs
    baseurl=https://packages.qincai.xyz/fedora/
    enabled=1
    metadata_expire=0
    gpgcheck=0
    

    Then install with:

    sudo dnf install mdllama
    

3, Install the ollama library from pip:

pip install ollama

You can also install it globally with:

sudo pip install ollama

[!NOTE] The ollama library is not installed by default in the RPM package since there is no system ollama package avaliable (python3-ollama). You need to install it manually using pip in order to use mdllama with Ollama models.


Traditional Bash Script Installation (Linux)

To install mdllama using the traditional bash script, run:

bash <(curl -fsSL https://raw.githubusercontent.com/QinCai-rui/mdllama/refs/heads/main/install.sh)

To uninstall mdllama, run:

bash <(curl -fsSL https://raw.githubusercontent.com/QinCai-rui/mdllama/refs/heads/main/uninstall.sh)

Windows & macOS Installation

Install via pip (recommended for Windows/macOS):

pip install mdllama

License

This project is licensed under the GNU General Public License v3.0. See the LICENSE file for details.


Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

mdllama-2.2.6.tar.gz (54.1 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

mdllama-2.2.6-py3-none-any.whl (41.8 kB view details)

Uploaded Python 3

File details

Details for the file mdllama-2.2.6.tar.gz.

File metadata

  • Download URL: mdllama-2.2.6.tar.gz
  • Upload date:
  • Size: 54.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.12.9

File hashes

Hashes for mdllama-2.2.6.tar.gz
Algorithm Hash digest
SHA256 b8327703ac4c023ef83e19fe030c5c06ccfebc9382d3c7c3832fdc20cb97267d
MD5 e6ac424b498c598fd90d20227bba98ec
BLAKE2b-256 e6d1ebbca2646ae80100e12cecb93eab111b219ab98c93100df50adb8e012712

See more details on using hashes here.

Provenance

The following attestation bundles were made for mdllama-2.2.6.tar.gz:

Publisher: publish-to-pypi.yml on QinCai-rui/mdllama

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file mdllama-2.2.6-py3-none-any.whl.

File metadata

  • Download URL: mdllama-2.2.6-py3-none-any.whl
  • Upload date:
  • Size: 41.8 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.12.9

File hashes

Hashes for mdllama-2.2.6-py3-none-any.whl
Algorithm Hash digest
SHA256 7d6fe84d94b8a3f9afec178a34fb9e125070741d38845ef93a106532952acd8d
MD5 0b7f879cf4b4d129e600a052f500fd75
BLAKE2b-256 1eafddff6be63ec84273827878cddc4b8c344933b2ecddf4f7117edd2084998d

See more details on using hashes here.

Provenance

The following attestation bundles were made for mdllama-2.2.6-py3-none-any.whl:

Publisher: publish-to-pypi.yml on QinCai-rui/mdllama

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page