feat(cli): ollama-parity — tq pull/list/run/serve#42
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Addresses Reddit feedback (smahs9, Eyelbee): the embedded niche is
real, but developer experience was behind ollama's "one command to
chat" standard. This adds that layer without touching any C code.
New subcommands in tools/tq:
- tq pull MODEL — download from HuggingFace by short alias
(e.g., llama3.2:1b) to ~/.cache/quantcpp/
- tq list — show cached + available models with aliases
(supports --json for scripting)
- tq run MODEL — auto-pull + interactive chat via ./build/quant
- tq serve MODEL — auto-pull + OpenAI API server via quant-server
Short aliases added:
- smollm2 / smollm2:135m → SmolLM2-135M
- qwen3.5 / qwen3.5:0.8b → Qwen3.5-0.8B
- llama3.2 / llama3.2:1b → Llama-3.2-1B
Implementation approach:
- Zero C changes — entirely a Python shim in tools/tq
- Reuses existing bindings/python quantcpp._MODEL_REGISTRY and
quantcpp.download() (which already has progress bar + cache)
- Subprocess-invokes ./build/quant and ./build/quant-server
- Accepts local .gguf paths as well as registry aliases
Verified end-to-end:
- tq list (shows cached/remote status + aliases)
- tq pull llama3.2:1b (downloads 770 MB with progress bar)
- tq run smollm2:135m "prompt" (31 tok/s single-thread)
- tq serve smollm2:135m --port 8766 (OpenAI /health + /v1/models work)
Also: made numpy import optional (was top-level, broke non-bench
commands if numpy wasn't installed).
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
unamedkr
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Apr 11, 2026
PR #42 added these commands to tools/tq, but that's only available to people who clone the repo. For PyPI users running `pip install quantcpp`, the entry point is `quantcpp = quantcpp.cli:main`, which only had a single chat shortcut. This adds proper ollama-style subcommands to bindings/python/quantcpp/ cli.py so PyPI users get the same DX: pip install quantcpp quantcpp pull llama3.2:1b quantcpp list quantcpp run llama3.2:1b quantcpp serve llama3.2:1b --port 8080 Short aliases (smollm2:135m, qwen3.5:0.8b, llama3.2:1b) match the tools/tq registry. Backwards-compatible: bare `quantcpp` and `quantcpp "question"` still work. Bumped version 0.11.0 → 0.12.0. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
unamedkr
added a commit
that referenced
this pull request
Apr 11, 2026
PR #42 added these commands to tools/tq, but that's only available to people who clone the repo. For PyPI users running `pip install quantcpp`, the entry point is `quantcpp = quantcpp.cli:main`, which only had a single chat shortcut. This adds proper ollama-style subcommands to bindings/python/quantcpp/ cli.py so PyPI users get the same DX: pip install quantcpp quantcpp pull llama3.2:1b quantcpp list quantcpp run llama3.2:1b quantcpp serve llama3.2:1b --port 8080 Short aliases (smollm2:135m, qwen3.5:0.8b, llama3.2:1b) match the tools/tq registry. Backwards-compatible: bare `quantcpp` and `quantcpp "question"` still work. Bumped version 0.11.0 → 0.12.0. Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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Addresses Reddit feedback from smahs9 ("stop justifying, focus on embedded use case") and Eyelbee ("why not just llama.cpp?"). The embedded niche is real but DX was behind ollama's standard. This closes the gap with zero C code changes — pure Python shim over existing bindings.
New commands
```bash
tq pull llama3.2:1b # download 770 MB from HuggingFace with progress bar
tq list # see cached + available models
tq run llama3.2:1b # auto-pull + interactive chat
tq serve llama3.2:1b # auto-pull + OpenAI-compatible HTTP server on :8080
```
Short aliases
Verified end-to-end
🤖 Generated with Claude Code