nimble-triage
Pipe your logs through a local decision model. In the default full mode, every
entry gets a severity, a category and a needs-attention flag,
computed by Nimble through Ollama's
/v1/systemone endpoint. No API key is required. By default, logs are sent only
to Ollama running on your own machine.
$ nimble-triage --format pretty app.log
error auth 0.06 ERROR auth: invalid password for user alice@example.com
! warning network 1.00 WARN tls: certificate for api.example.com expires in 3 days
info other 0.05 INFO http GET /health 200 2ms
error? application 0.11 ERROR payment-worker: retry 1/5 failed, retrying in 2s
! critical database 1.00 CRITICAL kernel: Out of memory: Killed process 4121 (postgres)
5 entries, 2 need attention
! marks entries that meet the attention threshold. The number is the model's
attention score, and ? marks a severity confidence below 0.6. Scores help
rank entries but should not be interpreted as calibrated guarantees.
Requirements
-
Python 3.10 or newer
-
Ollama 0.35.0 or newer (the first release with
/v1/systemone) -
The Nimble model, about a 9 GB download (16 GB of RAM recommended):
ollama pull nimble
Install
pipx install nimble-triage # recommended for command-line tools
# or
pip install nimble-triage
nimble-triage has no dependencies outside the Python standard library.
Usage
# Full classification
nimble-triage application.log # JSON Lines to stdout
nimble-triage -f pretty app.log # aligned, coloured output
nimble-triage -f pretty -a app.log # only entries that need attention
tail -f app.log | nimble-triage -f pretty -a # live
grep -v DEBUG app.log | nimble-triage # pre-filter to save time
nimble-triage app.log | jq 'select(.needs_attention)'
nimble-triage --continue-on-error app.log # keep going after failed entries
# Faster attention classification
nimble-triage --mode attention application.log
# Full classification, but print only flagged entries
nimble-triage --flagged-only application.log
# Fast classification and print only flagged entries
nimble-triage --mode attention --flagged-only application.log
# Fast scan: find flagged entries, then add severity and category
nimble-triage --mode scan application.log
| Option | Default | Meaning |
|---|---|---|
FILE ... |
stdin | Log files to read. - also means stdin. |
-f, --format |
jsonl |
jsonl or pretty |
-t, --threshold |
0.5 |
Attention probability at or above which an entry is flagged |
--model |
nimble |
Ollama model to use |
--host |
$OLLAMA_HOST or http://localhost:11434 |
Where Ollama is running |
--timeout |
120 |
Seconds to wait for each answer |
--continue-on-error |
off | Report failed entries to stderr and continue; exit with code 1 if any fail |
-m, --mode {full,attention,scan} |
full |
Select full, attention-only, or attention-first scan mode |
-a, --flagged-only |
off | Print only entries at or above the attention threshold |
JSON Lines output
One object per non-blank input line:
{"severity": "warning", "severity_confidence": 0.9624, "category": "network", "category_confidence": 0.94, "attention_probability": 0.9996, "needs_attention": true, "line": "WARN tls: certificate for api.example.com expires in 3 days"}
severity: one ofdebug,info,warning,error,criticalcategory: one ofauth,database,network,performance,security,application,other*_confidence,attention_probability: numbers between 0 and 1needs_attention:attention_probability >= --threshold
Severity and needs-attention are separate judgements: a certificate that expires in three days is only a warning but needs a human, while a single failed login is an error that does not.
Attention mode output
--mode attention sends only the needs-attention question to Nimble instead of
all three questions. Use it when severity and category are not required.
{"attention_probability": 0.9996, "needs_attention": true, "line": "WARN tls: certificate expires in 3 days"}
Scan mode
--mode scan first asks only whether each entry needs attention. Entries below
the threshold are discarded. Flagged entries receive a second request for
severity and category, then use the same output schema as full mode. Scan mode
is useful when only a small proportion of the input is expected to need action.
Because scan mode asks the questions in separate requests, its scores and
classifications can differ slightly from full mode.
Exit codes
| Code | Meaning |
|---|---|
| 0 | Success |
| 1 | Runtime error, or at least one failed entry with --continue-on-error |
| 2 | Invalid command-line arguments |
| 130 | Interrupted with Ctrl-C |
By default, nimble-triage stops on the first model or response error. Use
--continue-on-error for long streams where partial results are preferable.
Errors are written to stderr, successful results remain on stdout, and the
command exits with code 1 if any entry failed.
How it works
In full mode, each log line is sent to Ollama's /v1/systemone endpoint with
three typed questions: two choice questions for severity and category, and
one noul (yes/no) question for attention.
With --mode attention, each line is sent with only the attention question.
With --mode scan, each line receives the attention question first, and only
flagged entries receive the severity and category questions.
Nimble is a decision model: rather than generating text, it scores the options
and returns probabilities. The wording of the questions lives in
questions.py and is the main lever on
accuracy.
Privacy
Log entries are sent only to the Ollama server selected by --host or
OLLAMA_HOST. The default is http://localhost:11434, which keeps requests on
the local machine. If you configure another hostname, your logs are transmitted
to that server. Use HTTPS and review logs for credentials or personal data
before sending them to a remote host.
Limits
- Speed: each line is one model call, roughly 1 to 3 seconds per line on an
Apple M4 with 16 GB. nimble-triage is intended for tens to hundreds of
entries, not entire log archives. Filter large inputs before processing.
Use
--mode attentionwhen severity and category are not required. It sends one model question per entry instead of three and can substantially reduce processing time. Use--mode scanto add severity and category only to entries that meet the attention threshold. - Independent entries: each non-blank line is classified independently. Multiline stack traces and surrounding log context are not grouped together.
- Long lines: entries are cut to their first 8,000 characters before being sent to Ollama.
- Uncalibrated scores: confidence and attention scores are model outputs,
not guarantees of correctness. Tune
--thresholdagainst representative logs before relying on it. - Human review: use the results to decide what to inspect first. Do not use nimble-triage as the only source for alerting, security decisions, or incident response.
Development
git clone https://github.com/GauravGupta035/nimble-triage
cd nimble-triage
python3 -m venv .venv && source .venv/bin/activate
pip install -e ".[dev]"
pytest # runs without Ollama
License
MIT
Metadata
Release files for nimble-triage 0.3.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| nimble_triage-0.3.0.tar.gz | 18.6 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| nimble_triage-0.3.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 32.9 kB
Release files / nimble_triage-0.3.0.tar.gz
| Download URL | nimble_triage-0.3.0.tar.gz |
|---|---|
| Size | 18.6 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
c87c4887fdc13886a2bfc2dc348902efe743826630c971a6ca7aac4491ee18b6
|
|
BLAKE2b-256 checksum How to use checksums |
2470892b93ad09d3ff1f84098675d7cfb99f745d3cf002aa65e430471db6b314
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Oct 7, 2026.
Transparency logRelease files / nimble_triage-0.3.0-py3-none-any.whl
| Download URL | nimble_triage-0.3.0-py3-none-any.whl |
|---|---|
| Size | 14.2 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
ba6f1e1eda11e16b8ae7b1b26d0076d66de416eee7fc676f22cf21c395f211f1
|
|
BLAKE2b-256 checksum How to use checksums |
5c2cd9cd3c44b5f0a7d333f168c5e61256b0a478816b61030e6bf51a9ba5229f
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Oct 7, 2026.
Transparency log