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Local LLM agent powered by ollama — memory, plan mode, subagents

Project description

ollaAgent

A local LLM agent powered by ollama — with persistent memory, plan mode, and parallel subagents.

Python License: MIT

Features

Feature Description
Agent Loop Iterative tool-calling loop with run_python, run_bash, read_file, write_file, list_files
Persistent Memory JSON-backed memory with /memory add/list/search/clear commands
Session Saving Conversation history auto-saved to .agents/sessions/ on exit
Plan Mode /plan <task> — generates a structured step-by-step plan without executing tools
Subagents /subagent — runs multiple ollama instances in parallel via multiprocessing.Pool
Permission Control Configurable allow/deny patterns for bash commands
Cloudflare Access Supports CF-Access headers for tunneled ollama endpoints

Requirements

  • Python 3.11+
  • ollama running locally (or via Cloudflare Access)
  • uv

Installation

git clone https://github.com/github010000/ollaAgent
cd ollaAgent
uv sync

Usage

# Start the agent (default model: qwen3-coder-next:latest)
ollaagent

# With a specific model
ollaagent --model qwen2.5-coder:7b

# With a remote ollama host
ollaagent --host https://your-ollama.example.com

Built-in Commands

Command Description
/plan <task> Generate a step-by-step plan (no execution)
/subagent Run tasks in parallel across multiple ollama instances
/memory add <text> Add an entry to persistent memory
/memory list List all memory entries
/memory search <query> Search memory by keyword
/memory clear Clear all memory entries
/exit Exit the agent

Subagent Usage

Single model across all tasks:

/subagent
> --model llama3:8b task one | task two | task three

Per-task model assignment:

> @qwen2.5-coder:7b write a sorting algorithm | @llama3:8b explain it

Configuration

Create a .env file in the project root:

OLLAMA_HOST=http://localhost:11434
CF_ACCESS_CLIENT_ID=
CF_ACCESS_CLIENT_SECRET=

Project Structure

ollaAgent/
├── agent.py          # Main agent loop & CLI entry point
├── memory.py         # Persistent memory (JSON)
├── plan_mode.py      # Plan-only mode (tools=[])
├── subagent.py       # Parallel subagents via multiprocessing
├── tool_bash.py      # Bash tool with permission control
├── permissions.py    # Allow/deny pattern matching
├── config_loader.py  # YAML config & system prompt builder
└── ollama_client.py  # Ollama client factory

Running Tests

uv run pytest

License

MIT — see LICENSE for details.

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