The source headers, LICENSE files, and license metadata had drifted
apart. Align the entire project to MIT:
- Convert every source-file header to the MIT text across all comment
styles (Go, TS, TSX, JS, MJS, SQL, CSS, GraphQL, shell), including
SPDX-License-Identifier tags
- Set the root and cookie-banner LICENSE files to the MIT text with a
"MIT License" title line
- Switch the package.json license fields, Docker image label, and
cookie-banner README to MIT
- Update docs and the genmodels header generator accordingly
- Normalize copyright lines to a single format
(Copyright (c) <year(s)> Probo Inc <hello@probo.com>.): unify the
hello@getprobo.com and hello@probo.inc emails to hello@probo.com and
the comma-separated years to a hyphenated range
Genuine third-party references are intentionally left untouched: the
Lucide icon attributions (Lucide is ISC) and the trivy dependency
license allowlist.
Signed-off-by: Sacha Al Himdani <sacha@probo.com>
The client no longer strips sampling parameters per model, so the
sanitization test and its capturing provider helper assert behavior
that was intentionally removed. Delete them to restore a green build.
Signed-off-by: Émile Ré <emile@probo.com>
The common-pattern enrichment and tracker-mapping agents run on
reasoning models such as gpt-5-nano, which reject an explicit
temperature and fail the whole request with a 400 ("Unsupported
value: 'temperature' does not support 0.1 with this model"). The
model registry already records this capability, but nothing
consulted it before dispatch, and dated provider snapshots like
gpt-5-nano-2025-08-07 did not resolve in the registry.
Resolve dated snapshots to their undated base model in registry
Lookup, and sanitize each chat completion request in the LLM
client by omitting the sampling knobs the target model does not
accept (temperature, top_p, frequency/presence penalties, stop).
Unknown models are left untouched, so models absent from the
registry keep their current behavior.
Signed-off-by: Émile Ré <emile@probo.com>
Expand mixed inline/multiline function calls so each argument
is on its own line, matching the one-argument-per-line rule.
Signed-off-by: Sacha Al Himdani <sacha@getprobo.com>
StreamAccumulator never set its model field, so
Response().Model was always empty for streamed
completions. Add a Model field to stream events
and populate it in all three providers (OpenAI,
Anthropic, Bedrock).
Signed-off-by: Bryan Frimin <bryan@getprobo.com>
