PW Agent 🧠

CLI coding assistant powered by your Ollama GPUs via PastaWater.

Install

The recommended way to install pw-agent is using pipx to keep it isolated from your other Python packages:

pipx install pw-agent

Alternatively, you can use standard pip: pip install pw-agent

Usage

pw-agent

First run guides you through setup — paste your API token, pick a GPU, start chatting.

Features

  • Interactive REPL with real-time streaming and a premium dashboard status bar.
  • Plan vs Build Modes: Use /plan for read-only analysis and /build for execution.
  • Context Discovery: Automatically finds PW_AGENT.md for project-specific rules.
  • Tab Autocomplete for commands, file paths, and GPU slots.
  • Session Control: Fresh sessions by default; use -c to resume where you left off.
  • File Injection: /add file.py or @file.py — inject files into the LLM's context.
  • Batch Processing: Model can run multiple tool calls in a single turn.
  • GPU Fleet Control: /models to view GPUs and /use N to switch connections or slots.
  • AI Commits: /commit to generate and apply git commit messages based on your diff.
  • Safety First: -y flag for auto-approve; otherwise, every file edit requires confirmation.

Connect

  • Cloud mode: Use your PastaWater API token to access your remote fleet.
  • Direct mode: Point at a local Ollama instance (--brain http://localhost:11434).

Get your token at pastawater.io/settings

Model compatibility (tool calling)

Agentic tool use needs both a capable model AND an Ollama whose tool-call parser tolerates that model's output drift.

Model Ollama Tool calling Notes
qwen3-coder:30b >= 0.31.2 verified ~20 GB resident on a single 24 GB card
qwen3-coder:30b 0.21.x broken intermittent qwen tool call parsing failed: EOF — session degrades to plain chat
llama3.1:8b any recent works weaker coder; fine for pipeline text tasks

Failure signals (v1.51.0+): a session that ends without executing any tool due to parse failure/stall emits {"type":"result","subtype":"degraded", "degraded_reason":...,"is_error":true} and exits with code 3; a missing model or dead endpoint fails preflight with the installed-model list and exits with code 2. Only one large model fits a 24 GB card at a time — requesting a second large tag while one is resident forces CPU offload.

Project links

Key dates

PyPI data
Data sourced directly from PyPI's database.
  • Released:
Newer release available (1.52.0)

1 maintainer

PyPI data
Data sourced directly from PyPI's database.
Avatar for levmor from gravatar.com levmor

Credits

Author: PastaWater

License

MIT License

Requires

Python >=3.10

Classifiers

Report project as malware

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