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LXMFy bot to interact with Ollama
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Ivan 45613362e7
 Add context file loading and system prompt building functionality to bot.py 
- Introduced CONTEXT_FILES environment variable to specify context file paths.
- Added load_context_files function to read and combine content from specified files.
- Implemented build_system_prompt function to merge base prompt with loaded context.
- Updated bot logic to utilize the new FULL_SYSTEM_PROMPT variable for system messages.
- Improved formatting and readability in various sections of the code.
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lxmfy_ollama_bot Add context file loading and system prompt building functionality to bot.py 2025-11-21 16:29:20 -06:00
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.env-example Add CONTEXT_FILES variable to .env-example for specifying context file paths to attach to system prompt. 2025-11-21 16:28:02 -06:00
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pyproject.toml Update dependencies and version for lxmfy-ollama-bot to 1.5.0, including updates to lxmfy, rns, and their respective package versions in poetry.lock. 2025-11-21 16:28:38 -06:00
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README.md

ollama-bot

DeepSource Build and Publish Docker Image

Interact with Ollama LLMs using LXMFy bot framework.

showcase

Setup

curl -o .env https://raw.githubusercontent.com/lxmfy/ollama-bot/main/.env-example

edit .env with your Ollama API URL, Model, and LXMF address.

Installation and Running

Using Makefile

Requires poetry and make to be installed.

make install
make run

Using pipx

pipx install git+https://github.com/lxmfy/ollama-bot.git
lxmfy-ollama-bot

Using Poetry directly

poetry install
poetry run lxmfy-ollama-bot

Docker

Using Makefile

make docker-pull
make docker-run

Using Docker directly

First, pull the latest image:

docker pull ghcr.io/lxmfy/ollama-bot:latest

Then, run the bot, mounting your .env file:

docker run -d \
  --name ollama-bot \
  --restart unless-stopped \
  --network host \
  -v $(pwd)/.env:/app/.env \
  ghcr.io/lxmfy/ollama-bot:latest

Commands

Command prefix: /

/help - show help message
/about - show bot information

Chat

Send any message without the / prefix to chat with the AI model.

The bot will automatically respond using the configured Ollama model.

Note: This only uses /api/generate ollama endpoint so bot wont remember your last message.