feat: detect thinking support from backend automatically if not explicitly set (#8167)

detect thinking support from backend automatically if not explicitly set

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
This commit is contained in:
Ettore Di Giacinto authored and GitHub committed 2026-01-23 00:38:28 +01:00
1 parent b10045adc2
commit c0b21a921b
11 files changed
+169

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+7
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@@ -32,6 +32,8 @@ service Backend {
rpc GetMetrics(MetricsRequest) returns (MetricsResponse);
rpc VAD(VADRequest) returns (VADResponse) {}
rpc ModelMetadata(ModelOptions) returns (ModelMetadataResponse) {}
}
// Define the empty request
@@ -410,3 +412,8 @@ message Detection {
message DetectResponse {
repeated Detection Detections = 1;
}
message ModelMetadataResponse {
bool supports_thinking = 1;
string rendered_template = 2; // The rendered chat template with enable_thinking=true (empty if not applicable)
}
+41
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@@ -2476,6 +2476,47 @@ public:
response->set_prompt_tokens_processed(res_metrics->n_prompt_tokens_processed_total);
return grpc::Status::OK;
}
grpc::Status ModelMetadata(ServerContext* /*context*/, const backend::ModelOptions* /*request*/, backend::ModelMetadataResponse* response) override {
// Check if model is loaded
if (params_base.model.path.empty()) {
return grpc::Status(grpc::StatusCode::FAILED_PRECONDITION, "Model not loaded");
}
// Check if chat templates are initialized
if (ctx_server.impl->chat_params.tmpls == nullptr) {
// If templates are not initialized, we can't detect thinking support
// Return false as default
response->set_supports_thinking(false);
response->set_rendered_template("");
return grpc::Status::OK;
}
// Detect thinking support using llama.cpp's function
bool supports_thinking = common_chat_templates_support_enable_thinking(ctx_server.impl->chat_params.tmpls.get());
response->set_supports_thinking(supports_thinking);
// Render the template with enable_thinking=true so Go code can detect thinking tokens
// This allows reusing existing detection functions in Go
std::string rendered_template = "";
if (params_base.use_jinja) {
// Render the template with enable_thinking=true to see what the actual prompt looks like
common_chat_templates_inputs dummy_inputs;
common_chat_msg msg;
msg.role = "user";
msg.content = "test";
dummy_inputs.messages = {msg};
dummy_inputs.enable_thinking = true;
dummy_inputs.use_jinja = params_base.use_jinja;
const auto rendered = common_chat_templates_apply(ctx_server.impl->chat_params.tmpls.get(), dummy_inputs);
rendered_template = rendered.prompt;
}
response->set_rendered_template(rendered_template);
return grpc::Status::OK;
}
};
+12
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@@ -61,6 +61,18 @@ func ModelInference(ctx context.Context, s string, messages schema.Messages, ima
return nil, err
}
// Detect thinking support after model load (only if not already detected)
// This needs to happen after LoadModel succeeds so the backend can render templates
if (c.ReasoningConfig.DisableReasoning == nil && c.ReasoningConfig.DisableReasoningTagPrefill == nil) && c.TemplateConfig.UseTokenizerTemplate {
modelOpts := grpcModelOpts(*c, o.SystemState.Model.ModelsPath)
config.DetectThinkingSupportFromBackend(ctx, c, inferenceModel, modelOpts)
// Update the config in the loader so it persists for future requests
cl.UpdateModelConfig(c.Name, func(cfg *config.ModelConfig) {
cfg.ReasoningConfig.DisableReasoning = c.ReasoningConfig.DisableReasoning
cfg.ReasoningConfig.DisableReasoningTagPrefill = c.ReasoningConfig.DisableReasoningTagPrefill
})
}
var protoMessages []*proto.Message
// if we are using the tokenizer template, we need to convert the messages to proto messages
// unless the prompt has already been tokenized (non-chat endpoints + functions)
+52
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@@ -1,10 +1,16 @@
package config
import (
"context"
"github.com/mudler/LocalAI/pkg/grpc"
pb "github.com/mudler/LocalAI/pkg/grpc/proto"
"github.com/mudler/LocalAI/pkg/reasoning"
"github.com/mudler/LocalAI/pkg/xsysinfo"
"github.com/mudler/xlog"
gguf "github.com/gpustack/gguf-parser-go"
"github.com/gpustack/gguf-parser-go/util/ptr"
)
const (
@@ -71,6 +77,8 @@ func guessGGUFFromFile(cfg *ModelConfig, f *gguf.GGUFFile, defaultCtx int) {
cfg.modelTemplate = chatTemplate.ValueString()
}
// Thinking support detection is done after model load via DetectThinkingSupportFromBackend
// template estimations
if cfg.HasTemplate() {
// nothing to guess here
@@ -92,3 +100,47 @@ func guessGGUFFromFile(cfg *ModelConfig, f *gguf.GGUFFile, defaultCtx int) {
cfg.KnownUsecaseStrings = append(cfg.KnownUsecaseStrings, "FLAG_CHAT")
}
// DetectThinkingSupportFromBackend calls the ModelMetadata gRPC method to detect
// if the model supports thinking mode and if the template ends with a thinking start token.
// This should be called after the model is loaded.
// The results are stored in cfg.SupportsThinking and cfg.ThinkingForcedOpen.
func DetectThinkingSupportFromBackend(ctx context.Context, cfg *ModelConfig, backendClient grpc.Backend, modelOptions *pb.ModelOptions) {
if backendClient == nil {
xlog.Debug("[gguf] DetectThinkingSupportFromBackend: backend client is nil, skipping detection")
return
}
if modelOptions == nil {
xlog.Debug("[gguf] DetectThinkingSupportFromBackend: model options is nil, skipping detection")
return
}
// Only detect for llama-cpp backend when using tokenizer templates
if cfg.Backend != "llama-cpp" || !cfg.TemplateConfig.UseTokenizerTemplate {
xlog.Debug("[gguf] DetectThinkingSupportFromBackend: skipping detection", "backend", cfg.Backend, "useTokenizerTemplate", cfg.TemplateConfig.UseTokenizerTemplate)
return
}
metadata, err := backendClient.ModelMetadata(ctx, modelOptions)
if err != nil {
xlog.Warn("[gguf] DetectThinkingSupportFromBackend: failed to get model metadata", "error", err)
return
}
if metadata != nil {
cfg.ReasoningConfig.DisableReasoning = ptr.To(!metadata.SupportsThinking)
// Use the rendered template to detect if thinking token is at the end
// This reuses the existing DetectThinkingStartToken function
if metadata.RenderedTemplate != "" {
thinkingStartToken := reasoning.DetectThinkingStartToken(metadata.RenderedTemplate, &cfg.ReasoningConfig)
thinkingForcedOpen := thinkingStartToken != ""
cfg.ReasoningConfig.DisableReasoningTagPrefill = ptr.To(!thinkingForcedOpen)
xlog.Debug("[gguf] DetectThinkingSupportFromBackend: thinking support detected", "supports_thinking", metadata.SupportsThinking, "thinking_forced_open", thinkingForcedOpen, "thinking_start_token", thinkingStartToken)
} else {
cfg.ReasoningConfig.DisableReasoningTagPrefill = ptr.To(true)
xlog.Debug("[gguf] DetectThinkingSupportFromBackend: thinking support detected", "supports_thinking", metadata.SupportsThinking, "thinking_forced_open", false)
}
}
}
+11
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@@ -246,6 +246,17 @@ func (bcl *ModelConfigLoader) RemoveModelConfig(m string) {
delete(bcl.configs, m)
}
// UpdateModelConfig updates an existing model config in the loader.
// This is useful for updating runtime-detected properties like thinking support.
func (bcl *ModelConfigLoader) UpdateModelConfig(m string, updater func(*ModelConfig)) {
bcl.Lock()
defer bcl.Unlock()
if cfg, exists := bcl.configs[m]; exists {
updater(&cfg)
bcl.configs[m] = cfg
}
}
// Preload prepare models if they are not local but url or huggingface repositories
func (bcl *ModelConfigLoader) Preload(modelPath string) error {
bcl.Lock()
+2
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@@ -57,4 +57,6 @@ type Backend interface {
GetTokenMetrics(ctx context.Context, in *pb.MetricsRequest, opts ...grpc.CallOption) (*pb.MetricsResponse, error)
VAD(ctx context.Context, in *pb.VADRequest, opts ...grpc.CallOption) (*pb.VADResponse, error)
ModelMetadata(ctx context.Context, in *pb.ModelOptions, opts ...grpc.CallOption) (*pb.ModelMetadataResponse, error)
}
+4
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@@ -77,6 +77,10 @@ func (llm *Base) TokenizeString(opts *pb.PredictOptions) (pb.TokenizationRespons
return pb.TokenizationResponse{}, fmt.Errorf("unimplemented")
}
func (llm *Base) ModelMetadata(opts *pb.ModelOptions) (*pb.ModelMetadataResponse, error) {
return nil, fmt.Errorf("unimplemented")
}
// backends may wish to call this to capture the gopsutil info, then enhance with additional memory usage details?
func (llm *Base) Status() (pb.StatusResponse, error) {
return pb.StatusResponse{
+22
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@@ -537,3 +537,25 @@ func (c *Client) Detect(ctx context.Context, in *pb.DetectOptions, opts ...grpc.
client := pb.NewBackendClient(conn)
return client.Detect(ctx, in, opts...)
}
func (c *Client) ModelMetadata(ctx context.Context, in *pb.ModelOptions, opts ...grpc.CallOption) (*pb.ModelMetadataResponse, error) {
if !c.parallel {
c.opMutex.Lock()
defer c.opMutex.Unlock()
}
c.setBusy(true)
defer c.setBusy(false)
c.wdMark()
defer c.wdUnMark()
conn, err := grpc.Dial(c.address, grpc.WithTransportCredentials(insecure.NewCredentials()),
grpc.WithDefaultCallOptions(
grpc.MaxCallRecvMsgSize(50*1024*1024), // 50MB
grpc.MaxCallSendMsgSize(50*1024*1024), // 50MB
))
if err != nil {
return nil, err
}
defer conn.Close()
client := pb.NewBackendClient(conn)
return client.ModelMetadata(ctx, in, opts...)
}
+4
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@@ -99,6 +99,10 @@ func (e *embedBackend) VAD(ctx context.Context, in *pb.VADRequest, opts ...grpc.
return e.s.VAD(ctx, in)
}
func (e *embedBackend) ModelMetadata(ctx context.Context, in *pb.ModelOptions, opts ...grpc.CallOption) (*pb.ModelMetadataResponse, error) {
return e.s.ModelMetadata(ctx, in)
}
func (e *embedBackend) GetTokenMetrics(ctx context.Context, in *pb.MetricsRequest, opts ...grpc.CallOption) (*pb.MetricsResponse, error) {
return e.s.GetMetrics(ctx, in)
}
+2
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@@ -28,6 +28,8 @@ type AIModel interface {
StoresFind(*pb.StoresFindOptions) (pb.StoresFindResult, error)
VAD(*pb.VADRequest) (pb.VADResponse, error)
ModelMetadata(*pb.ModelOptions) (*pb.ModelMetadataResponse, error)
}
func newReply(s string) *pb.Reply {
+12
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@@ -263,6 +263,18 @@ func (s *server) VAD(ctx context.Context, in *pb.VADRequest) (*pb.VADResponse, e
return &res, nil
}
func (s *server) ModelMetadata(ctx context.Context, in *pb.ModelOptions) (*pb.ModelMetadataResponse, error) {
if s.llm.Locking() {
s.llm.Lock()
defer s.llm.Unlock()
}
res, err := s.llm.ModelMetadata(in)
if err != nil {
return nil, err
}
return res, nil
}
func StartServer(address string, model AIModel) error {
lis, err := net.Listen("tcp", address)
if err != nil {