AdapterCI
Regression CI for fine-tuned local models. Runs entirely against your own OpenAI-compatible endpoint (Ollama, LM Studio, llama.cpp, vLLM). Only metric names and floats are ever sent to the AdapterCI API — no prompts, no completions, no weights.
Install
pip install adapterci
Quickstart
adapterci init # writes adapterci.yaml
# edit adapterci.yaml: api_key, project, endpoint, baseline_model, candidate_model
adapterci # runs the suite, pushes scores, exits 1 on regression
Golden sets
Add domain-specific test cases in a local JSONL file (never uploaded):
{"prompt": "Summarize in one sentence: ...", "check": "contains", "expected": "..."}
check can be contains, regex, numeric_answer, or json_schema_keys.
Pointing at a different API (staging/local testing)
export ADAPTERCI_API_BASE=http://localhost:8787
License
MIT
1 maintainer
Metadata
1 maintainer
Release files for adapterci 0.1.0
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Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| adapterci-0.1.0.tar.gz | 4.0 kB | Without provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| adapterci-0.1.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 8.8 kB
Release files / adapterci-0.1.0.tar.gz
| Download URL | adapterci-0.1.0.tar.gz |
|---|---|
| Size | 4.0 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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No |
| Uploaded via |
twine/7.0.0 CPython/3.12.0
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Release files / adapterci-0.1.0-py3-none-any.whl
| Download URL | adapterci-0.1.0-py3-none-any.whl |
|---|---|
| Size | 4.8 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
761b1f8c0094cec14911a4136bd6ae294f269bf70bf7da67493270ca94fc5344
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.12.0
|
Security for adapterci 0.1.0
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