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| author | Peter Stone <thepeterstone@gmail.com> | 2026-05-01 22:14:37 -1000 |
|---|---|---|
| committer | GitHub <noreply@github.com> | 2026-05-01 22:14:37 -1000 |
| commit | 99115d8158137083239c45e5a860b718ff4cefa1 (patch) | |
| tree | 1bf3bd0505eea79375c67af83c7c5fe8c0f274ff /internal/executor/classifier.go | |
| parent | c2aa026f6ce1c9e216b99d74f294fc133d5fcddd (diff) | |
| parent | 50f8fe8c1ff8b82e0bd399e5776e58bda3e57d1c (diff) | |
Merge pull request #1 from thepeterstone/claude/local-oss-model-agents-MEBqj
Local OSS models as a third runner (epic)
Diffstat (limited to 'internal/executor/classifier.go')
| -rw-r--r-- | internal/executor/classifier.go | 33 |
1 files changed, 33 insertions, 0 deletions
diff --git a/internal/executor/classifier.go b/internal/executor/classifier.go index 7a474b6..049dc4f 100644 --- a/internal/executor/classifier.go +++ b/internal/executor/classifier.go @@ -6,6 +6,8 @@ import ( "fmt" "os/exec" "strings" + + "github.com/thepeterstone/claudomator/internal/llm" ) type Classification struct { @@ -19,7 +21,12 @@ type SystemStatus struct { RateLimited map[string]bool } +// Classifier picks a model for an incoming task. When LLM is non-nil the +// classifier routes through the local OpenAI-compatible client (cheap, +// private, fast). Otherwise it falls back to invoking the Gemini CLI +// at GeminiBinaryPath. type Classifier struct { + LLM *llm.Client GeminiBinaryPath string } @@ -62,6 +69,10 @@ func (c *Classifier) Classify(ctx context.Context, taskName, instructions string agentType, taskName, instructions, agentType, ) + if c.LLM != nil { + return c.classifyViaLLM(ctx, prompt, agentType) + } + binary := c.GeminiBinaryPath if binary == "" { binary = "gemini" @@ -123,3 +134,25 @@ func (c *Classifier) Classify(ctx context.Context, taskName, instructions string return &cls, nil } + +// classifyViaLLM routes classification through the local OpenAI-compatible +// client with response_format=json_object, so we get clean JSON without the +// markdown-fence cleanup needed for the Gemini CLI fallback. +func (c *Classifier) classifyViaLLM(ctx context.Context, prompt, agentType string) (*Classification, error) { + resp, err := c.LLM.Chat(ctx, llm.ChatRequest{ + Messages: []llm.Message{{Role: "user", Content: prompt}}, + ResponseJSON: true, + }) + if err != nil { + return nil, fmt.Errorf("classifier (local llm): %w", err) + } + body := strings.TrimSpace(resp.Content) + var cls Classification + if err := json.Unmarshal([]byte(body), &cls); err != nil { + return nil, fmt.Errorf("classifier (local llm): parse JSON: %w\nbody: %s", err, body) + } + if cls.AgentType == "" { + cls.AgentType = agentType + } + return &cls, nil +} |
