diff options
| author | Dmitry Vyukov <dvyukov@google.com> | 2026-01-15 20:53:57 +0100 |
|---|---|---|
| committer | Dmitry Vyukov <dvyukov@google.com> | 2026-01-20 21:12:57 +0000 |
| commit | 7f5908e77ae0e7fef4b7901341b8c2c4bbb74b28 (patch) | |
| tree | 2ccbc85132a170d046837de6bdd8be3317f94060 /pkg/aflow/flow/assessment | |
| parent | 2494e18d5ced59fc7f0522749041e499d3082a9e (diff) | |
pkg/aflow: make LLM model per-agent rather than per-flow
Having LLM model per-agent is even more flexible than per-flow.
We can have some more complex tasks during patch generation with the most elaborate model,
but also some simpler ones with less elaborate models.
Diffstat (limited to 'pkg/aflow/flow/assessment')
| -rw-r--r-- | pkg/aflow/flow/assessment/kcsan.go | 2 | ||||
| -rw-r--r-- | pkg/aflow/flow/assessment/moderation.go | 2 |
2 files changed, 2 insertions, 2 deletions
diff --git a/pkg/aflow/flow/assessment/kcsan.go b/pkg/aflow/flow/assessment/kcsan.go index 67d695eb9..6bfc7bb12 100644 --- a/pkg/aflow/flow/assessment/kcsan.go +++ b/pkg/aflow/flow/assessment/kcsan.go @@ -23,7 +23,6 @@ func init() { ai.WorkflowAssessmentKCSAN, "assess if a KCSAN report is about a benign race that only needs annotations or not", &aflow.Flow{ - Model: aflow.GoodBalancedModel, Root: &aflow.Pipeline{ Actions: []aflow.Action{ kernel.Checkout, @@ -31,6 +30,7 @@ func init() { codesearcher.PrepareIndex, &aflow.LLMAgent{ Name: "expert", + Model: aflow.GoodBalancedModel, Reply: "Explanation", Outputs: aflow.LLMOutputs[struct { Confident bool `jsonschema:"If you are confident in the verdict of the analysis or not."` diff --git a/pkg/aflow/flow/assessment/moderation.go b/pkg/aflow/flow/assessment/moderation.go index 8d9ac4a0b..b13ee1e7d 100644 --- a/pkg/aflow/flow/assessment/moderation.go +++ b/pkg/aflow/flow/assessment/moderation.go @@ -33,7 +33,6 @@ func init() { ai.WorkflowModeration, "assess if a bug report is consistent and actionable or not", &aflow.Flow{ - Model: aflow.GoodBalancedModel, Root: &aflow.Pipeline{ Actions: []aflow.Action{ aflow.NewFuncAction("extract-crash-type", extractCrashType), @@ -42,6 +41,7 @@ func init() { codesearcher.PrepareIndex, &aflow.LLMAgent{ Name: "expert", + Model: aflow.GoodBalancedModel, Reply: "Explanation", Outputs: aflow.LLMOutputs[struct { Confident bool `jsonschema:"If you are confident in the verdict of the analysis or not."` |