itigges22/ATLAS

Health v2 · maintenance only

Adoption not part of the score

2078 stars · 186 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

ATLAS is a local-first coding agent that wraps compact open models with planning, candidate generation, quality scoring, sandboxed testing, and repair loops. It runs model-agnostically on your own hardware (e.g., GGUF models on NVIDIA GPUs) without hosted APIs or per-token fees.

Use cases

• run a coding agent entirely on local hardware
• make small open models handle real software tasks
• verify generated code with sandboxed compile-test-repair loops
• avoid per-token API costs for AI-assisted coding
• adaptively allocate more compute for harder coding tasks

When to choose

• you want a privacy-preserving, local coding agent with no cloud dependency
• you run compact open-weight models (e.g., GGUF) and want frontier-style verification around them
• you prefer AGPL-licensed tooling with sandboxed code execution

When to avoid

• you need a hosted agent with frontier proprietary models out of the box
• you lack local GPU/hardware to run models efficiently
• you need a lightweight autocomplete assistant rather than an agentic pipeline

Facets

application · maturity active

agent-framework llm-inference developer-tools testing cli developer-tools large-language-models self-hosted python cli cross-platform self-hosted coding-agent local-first gguf model-agnostic tui sandboxed-execution test-time-compute ai-agents

Member repositories

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markdown · JSON · MCP: product_card(name="itigges22/ATLAS")