merge: integrate github/main — LocalRunner, real GeminiRunner, llm clientHEADmain

Merges 12 commits from github/main (formerly master) that were developed
independently. Key additions:
- LocalRunner: OpenAI-compatible local LLM execution (Ollama, LM Studio)
- Real GeminiRunner with full sandbox parity to ClaudeRunner
- llm.Client for enriching CI failures and elaboration via local model
- retry.ParseRetryAfter moved to shared package
- tokens_in/tokens_out columns in executions table

Conflict resolutions:
- Kept local main's VAPID/push, stories, projects, agent events schema
- Merged both sets of Config fields (local + LocalModel from github/main)
- Unified activePerAgent accounting (decActiveAgent helper)
- Removed duplicate helpers from claude.go (now in helpers.go)
- Fixed double-decrement bug in handleRunResult vs decActiveAgent

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

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
+}