llm: Separate llamaServer and ollamaServer code paths

Originally, llamaServer represented old memory estimates, which
could be used with either the old or new engine. ollamaServer was
used only for the new estimates and new engine. Since these
implementations did not map directly to engine, there was engine-
specific code in common code paths.

Now that new estimates are always used for the new engine, there is
a direct mapping between server type and engine. This separates out
most of the engine-specific code into the correct implementation
to make things easier to understand.

llm/server.go

@@ -84,13 +84,12 @@ type LlamaServer interface {
 
 // llmServer is an instance of a runner hosting a single model
 type llmServer struct {
-	port        int
-	cmd         *exec.Cmd
-	done        chan error // Channel to signal when the process exits
-	status      *StatusWriter
-	options     api.Options
-	numParallel int
-	modelPath   string
+	port      int
+	cmd       *exec.Cmd
+	done      chan error // Channel to signal when the process exits
+	status    *StatusWriter
+	options   api.Options
+	modelPath string
 
 	loadRequest LoadRequest       // Parameters used to initialize the runner
 	mem         *ml.BackendMemory // Memory allocations for this model
@@ -100,10 +99,6 @@ type llmServer struct {
 	llamaModel     *llama.Model
 	llamaModelLock *sync.Mutex
 
-	// textProcessor handles text encoding/decoding for the model in the Ollama engine
-	// nil if this server is running the llama.cpp based engine
-	textProcessor model.TextProcessor
-
 	totalLayers  uint64
 	loadStart    time.Time // Record how long it took the model to load
 	loadProgress float32
@@ -119,6 +114,8 @@ type llamaServer struct {
 
 type ollamaServer struct {
 	llmServer
+
+	textProcessor model.TextProcessor // textProcessor handles text encoding/decoding
 }
 
 // LoadModel will load a model from disk. The model must be in the GGML format.
@@ -242,8 +239,6 @@ func NewLlamaServer(systemInfo ml.SystemInfo, gpus []ml.DeviceInfo, modelPath st
 		loadRequest:    loadRequest,
 		llamaModel:     llamaModel,
 		llamaModelLock: &sync.Mutex{},
-		textProcessor:  textProcessor,
-		numParallel:    numParallel,
 		sem:            semaphore.NewWeighted(int64(numParallel)),
 		totalLayers:    f.KV().BlockCount() + 1,
 		loadStart:      time.Now(),
@@ -278,7 +273,7 @@ func NewLlamaServer(systemInfo ml.SystemInfo, gpus []ml.DeviceInfo, modelPath st
 	}()
 
 	if textProcessor != nil {
-		return &ollamaServer{llmServer: s}, nil
+		return &ollamaServer{llmServer: s, textProcessor: textProcessor}, nil
 	} else {
 		return &llamaServer{llmServer: s, ggml: f}, nil
 	}
@@ -1681,68 +1676,59 @@ func (s *llmServer) Embedding(ctx context.Context, input string) ([]float32, err
 	return e.Embedding, nil
 }
 
-type TokenizeRequest struct {
-	Content string `json:"content"`
-}
-
-type TokenizeResponse struct {
-	Tokens []int `json:"tokens"`
-}
-
-func (s *llmServer) Tokenize(ctx context.Context, content string) ([]int, error) {
+func (s *llamaServer) Tokenize(ctx context.Context, content string) ([]int, error) {
 	s.llamaModelLock.Lock()
 	defer s.llamaModelLock.Unlock()
 
-	if s.llamaModel != nil {
-		return s.llamaModel.Tokenize(content, false, true)
+	if s.llamaModel == nil {
+		return nil, fmt.Errorf("no tokenizer configured")
 	}
-	if s.textProcessor != nil {
-		tokens, err := s.textProcessor.Encode(content, false)
-		if err != nil {
-			return nil, err
-		}
-		toks := make([]int, len(tokens))
-		for i, t := range tokens {
-			toks[i] = int(t)
-		}
-		return toks, nil
+
+	return s.llamaModel.Tokenize(content, false, true)
+}
+
+func (s *ollamaServer) Tokenize(ctx context.Context, content string) ([]int, error) {
+	tokens, err := s.textProcessor.Encode(content, false)
+	if err != nil {
+		return nil, err
 	}
-	// not reached
-	return nil, fmt.Errorf("no tokenizer configured")
+
+	toks := make([]int, len(tokens))
+	for i, t := range tokens {
+		toks[i] = int(t)
+	}
+
+	return toks, nil
 }
 
-type DetokenizeRequest struct {
-	Tokens []int `json:"tokens"`
-}
-
-type DetokenizeResponse struct {
-	Content string `json:"content"`
-}
-
-func (s *llmServer) Detokenize(ctx context.Context, tokens []int) (string, error) {
+func (s *llamaServer) Detokenize(ctx context.Context, tokens []int) (string, error) {
 	s.llamaModelLock.Lock()
 	defer s.llamaModelLock.Unlock()
 
-	if s.llamaModel != nil {
-		var resp string
-		for _, token := range tokens {
-			resp += s.llamaModel.TokenToPiece(token)
-		}
-		return resp, nil
+	if s.llamaModel == nil {
+		return "", fmt.Errorf("no tokenizer configured")
 	}
-	if s.textProcessor != nil {
-		toks := make([]int32, len(tokens))
-		for i, t := range tokens {
-			toks[i] = int32(t)
-		}
-		content, err := s.textProcessor.Decode(toks)
-		if err != nil {
-			return "", err
-		}
-		return content, nil
+
+	var resp string
+	for _, token := range tokens {
+		resp += s.llamaModel.TokenToPiece(token)
 	}
-	// not reached
-	return "", fmt.Errorf("no tokenizer configured")
+
+	return resp, nil
+}
+
+func (s *ollamaServer) Detokenize(ctx context.Context, tokens []int) (string, error) {
+	toks := make([]int32, len(tokens))
+	for i, t := range tokens {
+		toks[i] = int32(t)
+	}
+
+	content, err := s.textProcessor.Decode(toks)
+	if err != nil {
+		return "", err
+	}
+
+	return content, nil
 }
 
 func (s *llmServer) Close() error {