rtk-ai/rtk

Add ollama filter to strip ANSI spinners and keep only final text output

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#624 opened on Mar 16, 2026

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area:clieffort-mediumenhancementhelp wantedpriority:low

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Description

Problem

When running ollama run <model> "prompt" via SSH or in a terminal, the raw output contains hundreds of ANSI escape sequences (spinners ⠋⠙⠹⠸⠼⠴⠦⠧⠇⠏, cursor control [?25l, [?2026h, [K, etc.) before the actual text response.

This is extremely token-wasteful when consumed by an LLM agent — a simple 2-sentence refusal from a model generates ~15KB+ of raw terminal noise vs ~200 bytes of actual content.

Proposed solution

Add an ollama filter (TOML-based or built-in) that:

  1. Strips all ANSI escape sequences and spinner characters
  2. Keeps only the final generated text output
  3. Optionally shows model name and basic stats (tokens/s, duration) in compact form

Example

# Before (raw, ~15KB of ANSI noise)
ollama run phi4:14b "Hello"

# After (rtk filtered, ~50 bytes)
rtk ollama run phi4:14b "Hello"
# → Hello! How can I help you today?

Context

Discovered while running safety audits on local LLMs via SSH — the ANSI overhead from ollama's streaming UI makes LLM-agent consumption impractical without filtering.

Contributor guide

Research direction
Study how existing filters are implemented in rtk (e.g., in the filters module). Identify how ANSI escape sequences are structured and write a regex or parser to strip them while retaining the final text output. Test with real ollama output.
Tech stack
rust
Domain
cli
Issue type
Feature
DifficultyEstimated implementation difficulty for a new contributor, from 1 for very small changes to 5 for expert-level work.
2
Estimated timeA rough time range for an experienced contributor to investigate, implement, test, and prepare a pull request.
1-3 hours
Activity statusHow available the issue appears right now: fresh, active, stale, blocked, or waiting on maintainer input.
Active
ClarityHow clearly the issue explains the expected change, acceptance criteria, and next step.
Clear
Prerequisites
Rust
Newbie friendlinessA 1-100 score estimating how approachable this issue is for first-time contributors.
75