Build multiple CPU variants and pick the best

This reduces the built-in linux version to not use any vector extensions
which enables the resulting builds to run under Rosetta on MacOS in
Docker.  Then at runtime it checks for the actual CPU vector
extensions and loads the best CPU library available

llm/llm.go

@@ -139,7 +139,22 @@ func Init(workdir string) error {
 }
 
 func newLlmServer(gpuInfo gpu.GpuInfo, model string, adapters, projectors []string, opts api.Options) (extServer, error) {
-	for _, shim := range getShims(gpuInfo) {
+	shims := getShims(gpuInfo)
+
+	// Check to see if the user has requested a specific library instead of auto-detecting
+	demandLib := os.Getenv("OLLAMA_LLM_LIBRARY")
+	if demandLib != "" {
+		libPath := availableShims[demandLib]
+		if libPath == "" {
+			log.Printf("Invalid OLLAMA_LLM_LIBRARY %s - not found", demandLib)
+		} else {
+			log.Printf("Loading OLLAMA_LLM_LIBRARY=%s", demandLib)
+			shims = []string{libPath}
+		}
+	}
+
+	for _, shim := range shims {
+		// TODO - only applies on Darwin (switch to fully dynamic there too...)
 		if shim == "default" {
 			break
 		}