chore(deps): update transformers requirement

Updates the requirements on [transformers](https://github.com/huggingface/transformers) to permit the latest version.
- [Release notes](https://github.com/huggingface/transformers/releases)
- [Commits](https://github.com/huggingface/transformers/compare/v5.9.0...v5.10.2)

---
updated-dependencies:
- dependency-name: transformers
  dependency-version: 5.10.2
  dependency-type: direct:production
...

Signed-off-by: dependabot[bot] <support@github.com>

Makefile

@@ -180,7 +180,7 @@ osx-signed: build
 
 ## Run
 run: ## run local-ai
-	CGO_LDFLAGS="$(CGO_LDFLAGS)" $(GOCMD) run ./cmd/local-ai
+	CGO_LDFLAGS="$(CGO_LDFLAGS)" $(GOCMD) run ./
 
 prepare-test: protogen-go build-mock-backend
 

README.md

@@ -149,16 +149,6 @@ local-ai run https://gist.githubusercontent.com/.../phi-2.yaml
 local-ai run oci://localai/phi-2:latest
 ```
 
-To test a running LocalAI server from the terminal, open an interactive chat session from another shell. Inside the prompt, `/models` lists installed models and `/model <name>` switches between them.
-
-```bash
-# Terminal 1
-local-ai run llama-3.2-1b-instruct:q4_k_m
-
-# Terminal 2
-local-ai chat --model llama-3.2-1b-instruct:q4_k_m
-```
-
 > **Automatic Backend Detection**: LocalAI automatically detects your GPU capabilities and downloads the appropriate backend. For advanced options, see [GPU Acceleration](https://localai.io/features/gpu-acceleration/).
 
 For more details, see the [Getting Started guide](https://localai.io/basics/getting_started/).

backend/cpp/ds4/Makefile

@@ -1,10 +1,10 @@
 # ds4 backend Makefile.
 #
-# Upstream pin lives below as DS4_VERSION?=91bafb5acd5a6cf00b1e55ef68bf40ddd207bee7
+# Upstream pin lives below as DS4_VERSION?=c463029c205c2ec8d7ab6c0df4a3f52979091286
 # (.github/bump_deps.sh) can find and update it - matches the
 # llama-cpp / ik-llama-cpp / turboquant convention.
 
-DS4_VERSION?=91bafb5acd5a6cf00b1e55ef68bf40ddd207bee7
+DS4_VERSION?=c463029c205c2ec8d7ab6c0df4a3f52979091286
 DS4_REPO?=https://github.com/antirez/ds4
 
 CURRENT_MAKEFILE_DIR := $(dir $(abspath $(lastword $(MAKEFILE_LIST))))

backend/cpp/ik-llama-cpp/Makefile

@@ -1,5 +1,5 @@
 
-IK_LLAMA_VERSION?=e6f8112f3ba126eed3ff5b30cdd08085414a7516
+IK_LLAMA_VERSION?=6b9de3dbaa21ae95ea80638e5ee836795cc48c93
 LLAMA_REPO?=https://github.com/ikawrakow/ik_llama.cpp
 
 CMAKE_ARGS?=

backend/cpp/llama-cpp/Makefile

@@ -1,5 +1,5 @@
 
-LLAMA_VERSION?=039e20a2db9e87b2477c76cc04905f3e1acad77f
+LLAMA_VERSION?=9e3b928fd8c9d14dbf15a8768b9fdd7e5c721d66
 LLAMA_REPO?=https://github.com/ggerganov/llama.cpp
 
 CMAKE_ARGS?=

backend/cpp/llama-cpp/grpc-server.cpp

@@ -381,15 +381,6 @@ json parse_options(bool streaming, const backend::PredictOptions* predict, const
             });
     }
 
-    // for each video in the request, add the video data
-    for (int i = 0; i < predict->videos_size(); i++) {
-        data["video_data"].push_back(json
-            {
-                {"id", i},
-                {"data",    predict->videos(i)},
-            });
-    }
-
     data["stop"] = predict->stopprompts();
     // data["n_probs"] = predict->nprobs();
     //TODO: images,
@@ -1512,7 +1503,7 @@ public:
                     msg_json["role"] = msg.role();
 
                     bool is_last_user_msg = (i == last_user_msg_idx);
-                    bool has_images_or_audio = (request->images_size() > 0 || request->audios_size() > 0 || request->videos_size() > 0);
+                    bool has_images_or_audio = (request->images_size() > 0 || request->audios_size() > 0);
 
                     // Handle content - can be string, null, or array
                     // For multimodal content, we'll embed images/audio from separate fields
@@ -1563,16 +1554,6 @@ public:
                                     content_array.push_back(audio_chunk);
                                 }
                             }
-                            if (request->videos_size() > 0) {
-                                for (int j = 0; j < request->videos_size(); j++) {
-                                    json video_chunk;
-                                    video_chunk["type"] = "input_video";
-                                    json input_video;
-                                    input_video["data"] = request->videos(j);
-                                    video_chunk["input_video"] = input_video;
-                                    content_array.push_back(video_chunk);
-                                }
-                            }
                             msg_json["content"] = content_array;
                         } else {
                             // Use content as-is (already array or not last user message)
@@ -1607,16 +1588,6 @@ public:
                                 content_array.push_back(audio_chunk);
                             }
                         }
-                        if (request->videos_size() > 0) {
-                            for (int j = 0; j < request->videos_size(); j++) {
-                                json video_chunk;
-                                video_chunk["type"] = "input_video";
-                                json input_video;
-                                input_video["data"] = request->videos(j);
-                                video_chunk["input_video"] = input_video;
-                                content_array.push_back(video_chunk);
-                            }
-                        }
                         msg_json["content"] = content_array;
                     } else if (msg.role() == "tool") {
                         // Tool role messages must have content field set, even if empty
@@ -2068,16 +2039,6 @@ public:
                         files.push_back(decoded_data);
                     }
                 }
-
-                const auto &video_data = data.find("video_data");
-                if (video_data != data.end() && video_data->is_array())
-                {
-                    for (const auto &video : *video_data)
-                    {
-                        auto decoded_data = base64_decode(video["data"].get<std::string>());
-                        files.push_back(decoded_data);
-                    }
-                }
             }
 
             const bool has_mtmd = ctx_server.impl->mctx != nullptr;
@@ -2330,7 +2291,7 @@ public:
                     }
 
                     bool is_last_user_msg = (i == last_user_msg_idx);
-                    bool has_images_or_audio = (request->images_size() > 0 || request->audios_size() > 0 || request->videos_size() > 0);
+                    bool has_images_or_audio = (request->images_size() > 0 || request->audios_size() > 0);
 
                     // Handle content - can be string, null, or array
                     // For multimodal content, we'll embed images/audio from separate fields
@@ -2383,16 +2344,6 @@ public:
                                     content_array.push_back(audio_chunk);
                                 }
                             }
-                            if (request->videos_size() > 0) {
-                                for (int j = 0; j < request->videos_size(); j++) {
-                                    json video_chunk;
-                                    video_chunk["type"] = "input_video";
-                                    json input_video;
-                                    input_video["data"] = request->videos(j);
-                                    video_chunk["input_video"] = input_video;
-                                    content_array.push_back(video_chunk);
-                                }
-                            }
                             msg_json["content"] = content_array;
                         } else {
                             // Use content as-is (already array or not last user message)
@@ -2432,16 +2383,6 @@ public:
                                 content_array.push_back(audio_chunk);
                             }
                         }
-                        if (request->videos_size() > 0) {
-                            for (int j = 0; j < request->videos_size(); j++) {
-                                json video_chunk;
-                                video_chunk["type"] = "input_video";
-                                json input_video;
-                                input_video["data"] = request->videos(j);
-                                video_chunk["input_video"] = input_video;
-                                content_array.push_back(video_chunk);
-                            }
-                        }
                         msg_json["content"] = content_array;
                         SRV_INF("[CONTENT DEBUG] Predict: Message %d created content array with media\n", i);
                     } else if (!msg.tool_calls().empty()) {
@@ -2904,16 +2845,6 @@ public:
                         files.push_back(decoded_data);
                     }
                 }
-
-                const auto &video_data = data.find("video_data");
-                if (video_data != data.end() && video_data->is_array())
-                {
-                    for (const auto &video : *video_data)
-                    {
-                        auto decoded_data = base64_decode(video["data"].get<std::string>());
-                        files.push_back(decoded_data);
-                    }
-                }
             }
 
             // process files

backend/go/crispasr/Makefile

@@ -8,7 +8,7 @@ JOBS?=$(shell nproc --ignore=1)
 
 # CrispASR version (release tag)
 CRISPASR_REPO?=https://github.com/CrispStrobe/CrispASR
-CRISPASR_VERSION?=c29f6653a516a3001d923944dad8892072cc7334
+CRISPASR_VERSION?=f7838a306687f22c281d29c250f879a4ab3df2d7
 SO_TARGET?=libgocrispasr.so
 
 CMAKE_ARGS+=-DBUILD_SHARED_LIBS=OFF

backend/go/stablediffusion-ggml/Makefile

@@ -8,7 +8,7 @@ JOBS?=$(shell nproc --ignore=1)
 
 # stablediffusion.cpp (ggml)
 STABLEDIFFUSION_GGML_REPO?=https://github.com/leejet/stable-diffusion.cpp
-STABLEDIFFUSION_GGML_VERSION?=19bdfe22d255d5b4dff39d449318b9bc5ea2317f
+STABLEDIFFUSION_GGML_VERSION?=b3d56d0ba1bd437886079e339118e8e75bb79ee7
 
 CMAKE_ARGS+=-DGGML_MAX_NAME=128
 

backend/go/whisper/Makefile

@@ -8,7 +8,7 @@ JOBS?=$(shell nproc --ignore=1)
 
 # whisper.cpp version
 WHISPER_REPO?=https://github.com/ggml-org/whisper.cpp
-WHISPER_CPP_VERSION?=df7638d8229a243af8a4b5a8ae557e0d74e0a0ae
+WHISPER_CPP_VERSION?=a8ec021f2750a473ff4a8f3883bc9fdf5feafa84
 SO_TARGET?=libgowhisper.so
 
 CMAKE_ARGS+=-DBUILD_SHARED_LIBS=OFF

backend/python/transformers/requirements-cpu.txt

@@ -2,7 +2,7 @@ torch==2.7.1
 llvmlite==0.43.0
 numba==0.60.0
 accelerate
-transformers>=5.9.0
+transformers>=5.10.2
 bitsandbytes
 sentence-transformers==5.5.1
 diffusers

backend/python/transformers/requirements-cublas12.txt

@@ -2,7 +2,7 @@ torch==2.7.1
 accelerate
 llvmlite==0.43.0
 numba==0.60.0
-transformers>=5.9.0
+transformers>=5.10.2
 bitsandbytes
 sentence-transformers==5.5.1
 diffusers

backend/python/transformers/requirements-cublas13.txt

@@ -2,7 +2,7 @@
 torch==2.9.0
 llvmlite==0.43.0
 numba==0.60.0
-transformers>=5.9.0
+transformers>=5.10.2
 bitsandbytes
 sentence-transformers==5.5.1
 diffusers

backend/python/transformers/requirements-hipblas.txt

@@ -1,7 +1,7 @@
 --extra-index-url https://download.pytorch.org/whl/rocm7.0
 torch==2.10.0+rocm7.0
 accelerate
-transformers>=5.9.0
+transformers>=5.10.2
 llvmlite==0.43.0
 numba==0.60.0
 bitsandbytes

backend/python/transformers/requirements-intel.txt

@@ -3,7 +3,7 @@ torch
 optimum[openvino]
 llvmlite==0.43.0
 numba==0.60.0
-transformers>=5.9.0
+transformers>=5.10.2
 bitsandbytes
 sentence-transformers==5.5.1
 diffusers

backend/python/transformers/requirements-mps.txt

@@ -2,7 +2,7 @@ torch==2.7.1
 llvmlite==0.43.0
 numba==0.60.0
 accelerate
-transformers>=5.9.0
+transformers>=5.10.2
 bitsandbytes
 sentence-transformers==5.5.1
 diffusers

core/cli/chat/chat.go

@@ -1,30 +0,0 @@
-package chat
-
-import (
-	"context"
-	"io"
-	"strings"
-)
-
-type Options struct {
-	Model   string
-	BaseURL string
-	APIKey  string
-	In      io.Reader
-	Out     io.Writer
-}
-
-func Run(ctx context.Context, opts Options) error {
-	if opts.In == nil {
-		opts.In = strings.NewReader("")
-	}
-	if opts.Out == nil {
-		opts.Out = io.Discard
-	}
-
-	session, err := newChatSession(ctx, newLocalAIChatClient(opts.BaseURL, opts.APIKey), opts.Model)
-	if err != nil {
-		return err
-	}
-	return runTerminalChat(ctx, session, opts.In, opts.Out)
-}

core/cli/chat/chat_suite_test.go

@@ -1,13 +0,0 @@
-package chat
-
-import (
-	"testing"
-
-	. "github.com/onsi/ginkgo/v2"
-	. "github.com/onsi/gomega"
-)
-
-func TestChat(t *testing.T) {
-	RegisterFailHandler(Fail)
-	RunSpecs(t, "Chat Suite")
-}

core/cli/chat/chat_test.go

@@ -1,172 +0,0 @@
-package chat
-
-import (
-	"bytes"
-	"encoding/json"
-	"fmt"
-	"io"
-	"net/http"
-	"net/http/httptest"
-	"strings"
-
-	. "github.com/onsi/ginkgo/v2"
-	. "github.com/onsi/gomega"
-)
-
-var _ = Describe("Run chat", func() {
-	It("streams a single chat response", func() {
-		var capturedModel string
-		var capturedAuth string
-		server := httptest.NewServer(http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
-			if r.URL.Path == "/v1/models" {
-				w.Header().Set("Content-Type", "application/json")
-				writeResponse(w, `{"object":"list","data":[{"id":"test-model","object":"model"}]}`)
-				return
-			}
-
-			Expect(r.URL.Path).To(Equal("/v1/chat/completions"))
-			capturedAuth = r.Header.Get("Authorization")
-
-			var body struct {
-				Model    string `json:"model"`
-				Messages []struct {
-					Role    string `json:"role"`
-					Content string `json:"content"`
-				} `json:"messages"`
-			}
-			Expect(json.NewDecoder(r.Body).Decode(&body)).To(Succeed())
-			capturedModel = body.Model
-			Expect(body.Messages).To(HaveLen(1))
-			Expect(body.Messages[0].Role).To(Equal("user"))
-			Expect(body.Messages[0].Content).To(Equal("hello"))
-
-			w.Header().Set("Content-Type", "text/event-stream")
-			writeResponse(w, "data: {\"choices\":[{\"index\":0,\"delta\":{\"content\":\"hi\"}}]}\n\n")
-			writeResponse(w, "data: {\"choices\":[{\"index\":0,\"delta\":{\"content\":\"!\"}}]}\n\n")
-			writeResponse(w, "data: [DONE]\n\n")
-		}))
-		defer server.Close()
-
-		var out bytes.Buffer
-		err := Run(GinkgoT().Context(), Options{
-			Model:   "test-model",
-			BaseURL: server.URL + "/v1",
-			APIKey:  "secret",
-			In:      strings.NewReader("hello\n/exit\n"),
-			Out:     &out,
-		})
-
-		Expect(err).ToNot(HaveOccurred())
-		Expect(capturedModel).To(Equal("test-model"))
-		Expect(capturedAuth).To(Equal("Bearer secret"))
-		Expect(out.String()).To(ContainSubstring("assistant: hi!"))
-		Expect(out.String()).To(ContainSubstring("bye"))
-	})
-
-	It("auto-selects the only available model", func() {
-		server := chatTestServer([]string{"solo"}, nil)
-		defer server.Close()
-
-		var out bytes.Buffer
-		err := Run(GinkgoT().Context(), Options{
-			BaseURL: server.URL + "/v1",
-			In:      strings.NewReader("/exit\n"),
-			Out:     &out,
-		})
-
-		Expect(err).ToNot(HaveOccurred())
-		Expect(out.String()).To(ContainSubstring("LocalAI chat (solo)"))
-	})
-
-	It("returns an actionable error when no models are installed", func() {
-		server := chatTestServer(nil, nil)
-		defer server.Close()
-
-		err := Run(GinkgoT().Context(), Options{
-			BaseURL: server.URL + "/v1",
-			In:      strings.NewReader(""),
-		})
-
-		Expect(err).To(HaveOccurred())
-		Expect(err.Error()).To(ContainSubstring("no chat models are installed"))
-		Expect(err.Error()).To(ContainSubstring("local-ai models install <model>"))
-	})
-
-	It("returns an actionable error when multiple models are available without a selection", func() {
-		server := chatTestServer([]string{"alpha", "beta"}, nil)
-		defer server.Close()
-
-		err := Run(GinkgoT().Context(), Options{
-			BaseURL: server.URL + "/v1",
-			In:      strings.NewReader(""),
-		})
-
-		Expect(err).To(HaveOccurred())
-		Expect(err.Error()).To(ContainSubstring("multiple models are available"))
-		Expect(err.Error()).To(ContainSubstring("--model"))
-		Expect(err.Error()).To(ContainSubstring("alpha"))
-		Expect(err.Error()).To(ContainSubstring("beta"))
-	})
-
-	It("lists and switches models inside the chat", func() {
-		requestedModels := []string{}
-		server := chatTestServer([]string{"alpha", "beta"}, func(model string) {
-			requestedModels = append(requestedModels, model)
-		})
-		defer server.Close()
-
-		var out bytes.Buffer
-		err := Run(GinkgoT().Context(), Options{
-			Model:   "alpha",
-			BaseURL: server.URL + "/v1",
-			In:      strings.NewReader("/models\n/model beta\nhello\n/exit\n"),
-			Out:     &out,
-		})
-
-		Expect(err).ToNot(HaveOccurred())
-		Expect(out.String()).To(ContainSubstring("* alpha"))
-		Expect(out.String()).To(ContainSubstring("  beta"))
-		Expect(out.String()).To(ContainSubstring("switched to beta; conversation cleared"))
-		Expect(requestedModels).To(Equal([]string{"beta"}))
-	})
-})
-
-func chatTestServer(models []string, onChat func(model string)) *httptest.Server {
-	return httptest.NewServer(http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
-		switch r.URL.Path {
-		case "/v1/models":
-			w.Header().Set("Content-Type", "application/json")
-			writeResponse(w, `{"object":"list","data":[`)
-			for i, model := range models {
-				if i > 0 {
-					writeResponse(w, ",")
-				}
-				writeResponsef(w, `{"id":%q,"object":"model"}`, model)
-			}
-			writeResponse(w, `]}`)
-		case "/v1/chat/completions":
-			var body struct {
-				Model string `json:"model"`
-			}
-			Expect(json.NewDecoder(r.Body).Decode(&body)).To(Succeed())
-			if onChat != nil {
-				onChat(body.Model)
-			}
-			w.Header().Set("Content-Type", "text/event-stream")
-			writeResponse(w, "data: {\"choices\":[{\"index\":0,\"delta\":{\"content\":\"ok\"}}]}\n\n")
-			writeResponse(w, "data: [DONE]\n\n")
-		default:
-			w.WriteHeader(http.StatusNotFound)
-		}
-	}))
-}
-
-func writeResponse(w io.Writer, text string) {
-	_, err := fmt.Fprint(w, text)
-	Expect(err).ToNot(HaveOccurred())
-}
-
-func writeResponsef(w io.Writer, format string, args ...any) {
-	_, err := fmt.Fprintf(w, format, args...)
-	Expect(err).ToNot(HaveOccurred())
-}

core/cli/chat/client.go

@@ -1,114 +0,0 @@
-package chat
-
-import (
-	"context"
-	"errors"
-	"fmt"
-	"io"
-	"sort"
-	"strings"
-
-	openai "github.com/sashabaranov/go-openai"
-)
-
-type chatClient interface {
-	ListModels(ctx context.Context) ([]string, error)
-	StreamChat(ctx context.Context, model string, messages []chatMessage, out io.Writer) (string, error)
-}
-
-type localAIChatClient struct {
-	client *openai.Client
-}
-
-func newLocalAIChatClient(baseURL string, apiKey string) *localAIChatClient {
-	cfg := openai.DefaultConfig(apiKey)
-	cfg.BaseURL = baseURL
-	return &localAIChatClient{client: openai.NewClientWithConfig(cfg)}
-}
-
-func (c *localAIChatClient) ListModels(ctx context.Context) ([]string, error) {
-	resp, err := c.client.ListModels(ctx)
-	if err != nil {
-		return nil, err
-	}
-
-	models := make([]string, 0, len(resp.Models))
-	for _, model := range resp.Models {
-		if model.ID != "" {
-			models = append(models, model.ID)
-		}
-	}
-	sort.Strings(models)
-	return models, nil
-}
-
-func (c *localAIChatClient) StreamChat(ctx context.Context, model string, messages []chatMessage, out io.Writer) (string, error) {
-	stream, err := c.client.CreateChatCompletionStream(ctx, openai.ChatCompletionRequest{
-		Model:    model,
-		Messages: openAIChatMessages(messages),
-	})
-	if err != nil {
-		return "", friendlyChatError(err, model)
-	}
-	defer func() {
-		_ = stream.Close()
-	}()
-
-	var answer strings.Builder
-	for {
-		resp, err := stream.Recv()
-		if errors.Is(err, io.EOF) {
-			break
-		}
-		if err != nil {
-			return answer.String(), friendlyChatError(err, model)
-		}
-		if len(resp.Choices) == 0 {
-			continue
-		}
-
-		token := resp.Choices[0].Delta.Content
-		if token == "" {
-			continue
-		}
-		answer.WriteString(token)
-		if _, err := fmt.Fprint(out, token); err != nil {
-			return answer.String(), err
-		}
-	}
-
-	return answer.String(), nil
-}
-
-func openAIChatMessages(messages []chatMessage) []openai.ChatCompletionMessage {
-	converted := make([]openai.ChatCompletionMessage, len(messages))
-	for i, message := range messages {
-		converted[i] = openai.ChatCompletionMessage{
-			Role:    message.Role,
-			Content: message.Content,
-		}
-	}
-	return converted
-}
-
-func friendlyChatError(err error, model string) error {
-	var apiErr *openai.APIError
-	if errors.As(err, &apiErr) {
-		switch apiErr.HTTPStatusCode {
-		case 404:
-			return fmt.Errorf("model %q is not available. Run `local-ai models list`, install a model with `local-ai models install <model>`, or switch with `/model <name>`", model)
-		case 403:
-			return fmt.Errorf("model %q is disabled. Enable it from LocalAI settings or choose another model with `/model <name>`", model)
-		}
-		if apiErr.Message != "" {
-			return errors.New(apiErr.Message)
-		}
-	}
-
-	msg := err.Error()
-	if strings.Contains(msg, "model") && strings.Contains(msg, "not found") {
-		return fmt.Errorf("model %q is not available. Run `local-ai models list`, install a model with `local-ai models install <model>`, or switch with `/model <name>`", model)
-	}
-
-	return err
-}

core/cli/chat/models.go

@@ -1,17 +0,0 @@
-package chat
-
-import "strings"
-
-func formatChatModelList(models []string, current string) string {
-	var b strings.Builder
-	for _, model := range models {
-		prefix := "  "
-		if model == current {
-			prefix = "* "
-		}
-		b.WriteString(prefix)
-		b.WriteString(model)
-		b.WriteByte('\n')
-	}
-	return b.String()
-}

core/cli/chat/session.go

@@ -1,120 +0,0 @@
-package chat
-
-import (
-	"context"
-	"errors"
-	"fmt"
-	"io"
-	"strings"
-)
-
-const (
-	chatRoleUser      = "user"
-	chatRoleAssistant = "assistant"
-)
-
-type chatMessage struct {
-	Role    string
-	Content string
-}
-
-type chatSession struct {
-	client   chatClient
-	model    string
-	models   []string
-	messages []chatMessage
-}
-
-func newChatSession(ctx context.Context, client chatClient, requestedModel string) (*chatSession, error) {
-	models, err := client.ListModels(ctx)
-	if err != nil {
-		return nil, fmt.Errorf("list models: %w", err)
-	}
-
-	model, err := resolveChatModel(requestedModel, models)
-	if err != nil {
-		return nil, err
-	}
-
-	return &chatSession{
-		client: client,
-		model:  model,
-		models: models,
-	}, nil
-}
-
-func (s *chatSession) CurrentModel() string {
-	return s.model
-}
-
-func (s *chatSession) Models() []string {
-	models := make([]string, len(s.models))
-	copy(models, s.models)
-	return models
-}
-
-func (s *chatSession) Clear() {
-	s.messages = nil
-}
-
-func (s *chatSession) SwitchModel(model string) error {
-	if !modelExists(s.models, model) {
-		return fmt.Errorf("model %q is not available. Use /models to see installed models", model)
-	}
-	s.model = model
-	s.Clear()
-	return nil
-}
-
-func (s *chatSession) Send(ctx context.Context, prompt string, out io.Writer) error {
-	s.messages = append(s.messages, chatMessage{
-		Role:    chatRoleUser,
-		Content: prompt,
-	})
-
-	answer, err := s.client.StreamChat(ctx, s.model, s.messages, out)
-	if err != nil {
-		return err
-	}
-
-	s.messages = append(s.messages, chatMessage{
-		Role:    chatRoleAssistant,
-		Content: answer,
-	})
-	return nil
-}
-
-func resolveChatModel(requested string, models []string) (string, error) {
-	switch {
-	case requested == "" && len(models) == 0:
-		return "", errors.New(`no chat models are installed.
-
-Install a model first, for example:
-  local-ai models list
-  local-ai models install <model>
-  local-ai run
-
-Then start a chat session:
-  local-ai chat --model <model>`)
-	case requested == "" && len(models) == 1:
-		return models[0], nil
-	case requested == "" && len(models) > 1:
-		var b strings.Builder
-		b.WriteString("multiple models are available; choose one with --model:\n")
-		b.WriteString(formatChatModelList(models, ""))
-		return "", errors.New(b.String())
-	case !modelExists(models, requested):
-		return "", fmt.Errorf("model %q is not available. Use `local-ai models list` and `local-ai models install <model>`, or pass an installed model with --model", requested)
-	default:
-		return requested, nil
-	}
-}
-
-func modelExists(models []string, name string) bool {
-	for _, model := range models {
-		if model == name {
-			return true
-		}
-	}
-	return false
-}

core/cli/chat/session_test.go

@@ -1,56 +0,0 @@
-package chat
-
-import (
-	"context"
-	"io"
-
-	. "github.com/onsi/ginkgo/v2"
-	. "github.com/onsi/gomega"
-)
-
-var _ = Describe("Chat session", func() {
-	It("keeps model switching and message history out of the terminal adapter", func() {
-		client := &fakeChatClient{
-			models: []string{"alpha", "beta"},
-			answer: "pong",
-		}
-
-		session, err := newChatSession(context.Background(), client, "alpha")
-		Expect(err).ToNot(HaveOccurred())
-		Expect(session.CurrentModel()).To(Equal("alpha"))
-
-		Expect(session.SwitchModel("beta")).To(Succeed())
-		Expect(session.CurrentModel()).To(Equal("beta"))
-		Expect(session.Send(context.Background(), "ping", io.Discard)).To(Succeed())
-
-		Expect(client.requests).To(HaveLen(1))
-		Expect(client.requests[0].model).To(Equal("beta"))
-		Expect(client.requests[0].messages).To(HaveLen(1))
-		Expect(client.requests[0].messages[0].Content).To(Equal("ping"))
-	})
-})
-
-type fakeChatClient struct {
-	models   []string
-	answer   string
-	requests []fakeChatRequest
-}
-
-type fakeChatRequest struct {
-	model    string
-	messages []chatMessage
-}
-
-func (c *fakeChatClient) ListModels(context.Context) ([]string, error) {
-	return c.models, nil
-}
-
-func (c *fakeChatClient) StreamChat(_ context.Context, model string, messages []chatMessage, out io.Writer) (string, error) {
-	copied := make([]chatMessage, len(messages))
-	copy(copied, messages)
-	c.requests = append(c.requests, fakeChatRequest{model: model, messages: copied})
-	if _, err := io.WriteString(out, c.answer); err != nil {
-		return "", err
-	}
-	return c.answer, nil
-}

core/cli/chat/terminal.go

@@ -1,93 +0,0 @@
-package chat
-
-import (
-	"bufio"
-	"context"
-	"fmt"
-	"io"
-	"strings"
-)
-
-func runTerminalChat(ctx context.Context, session *chatSession, in io.Reader, out io.Writer) error {
-	scanner := bufio.NewScanner(in)
-	scanner.Buffer(make([]byte, 0, 64*1024), 4*1024*1024)
-
-	if err := writeChat(out, "LocalAI chat (%s)\n", session.CurrentModel()); err != nil {
-		return err
-	}
-	if err := writeChat(out, "Type /exit to quit, /clear to reset the conversation, /models to list models.\n"); err != nil {
-		return err
-	}
-
-	for {
-		if err := writeChat(out, "\n> "); err != nil {
-			return err
-		}
-		if !scanner.Scan() {
-			break
-		}
-
-		prompt := strings.TrimSpace(scanner.Text())
-		switch prompt {
-		case "":
-			continue
-		case "/bye", "/exit", "/quit":
-			return writeChat(out, "bye\n")
-		case "/clear":
-			session.Clear()
-			if err := writeChat(out, "conversation cleared\n"); err != nil {
-				return err
-			}
-			continue
-		case "/models":
-			if err := printChatModels(out, session.Models(), session.CurrentModel()); err != nil {
-				return err
-			}
-			continue
-		}
-
-		if nextModel, ok := strings.CutPrefix(prompt, "/model "); ok {
-			nextModel = strings.TrimSpace(nextModel)
-			if nextModel == "" {
-				if err := writeChat(out, "usage: /model <name>\n"); err != nil {
-					return err
-				}
-				continue
-			}
-			if err := session.SwitchModel(nextModel); err != nil {
-				if writeErr := writeChat(out, "%s\n", err); writeErr != nil {
-					return writeErr
-				}
-				continue
-			}
-			if err := writeChat(out, "switched to %s; conversation cleared\n", session.CurrentModel()); err != nil {
-				return err
-			}
-			continue
-		}
-
-		if err := writeChat(out, "assistant: "); err != nil {
-			return err
-		}
-		if err := session.Send(ctx, prompt, out); err != nil {
-			return err
-		}
-		if err := writeChat(out, "\n"); err != nil {
-			return err
-		}
-	}
-
-	return scanner.Err()
-}
-
-func printChatModels(out io.Writer, models []string, current string) error {
-	if len(models) == 0 {
-		return writeChat(out, "no models installed\n")
-	}
-	return writeChat(out, "%s", formatChatModelList(models, current))
-}
-
-func writeChat(out io.Writer, format string, args ...any) error {
-	_, err := fmt.Fprintf(out, format, args...)
-	return err
-}

core/cli/chat_cmd.go

@@ -1,25 +0,0 @@
-package cli
-
-import (
-	"context"
-	"os"
-
-	chatcli "github.com/mudler/LocalAI/core/cli/chat"
-	cliContext "github.com/mudler/LocalAI/core/cli/context"
-)
-
-type ChatCMD struct {
-	Model    string `short:"m" help:"Model name to use. Defaults to the only model returned by the server when exactly one is available"`
-	Endpoint string `env:"LOCALAI_CHAT_ENDPOINT" default:"http://127.0.0.1:8080" help:"LocalAI server endpoint. The /v1 path is added automatically when omitted"`
-	APIKey   string `env:"LOCALAI_API_KEY,API_KEY" help:"API key to use when the LocalAI server requires authentication"`
-}
-
-func (c *ChatCMD) Run(ctx *cliContext.Context) error {
-	return chatcli.Run(context.Background(), chatcli.Options{
-		Model:   c.Model,
-		BaseURL: chatAPIBaseURL(c.Endpoint),
-		APIKey:  c.APIKey,
-		In:      os.Stdin,
-		Out:     os.Stdout,
-	})
-}

core/cli/chat_cmd_test.go

@@ -1,27 +0,0 @@
-package cli
-
-import (
-	. "github.com/onsi/ginkgo/v2"
-	. "github.com/onsi/gomega"
-)
-
-var _ = Describe("Chat command wiring", func() {
-	Describe("chatAPIBaseURL", func() {
-		It("adds /v1 to a root endpoint", func() {
-			Expect(chatAPIBaseURL("http://127.0.0.1:8080")).To(Equal("http://127.0.0.1:8080/v1"))
-		})
-
-		It("keeps endpoints that already include /v1", func() {
-			Expect(chatAPIBaseURL("http://127.0.0.1:8080/v1")).To(Equal("http://127.0.0.1:8080/v1"))
-			Expect(chatAPIBaseURL("http://127.0.0.1:8080/v1/")).To(Equal("http://127.0.0.1:8080/v1"))
-		})
-
-		It("adds a default http scheme", func() {
-			Expect(chatAPIBaseURL("127.0.0.1:8080")).To(Equal("http://127.0.0.1:8080/v1"))
-		})
-
-		It("preserves non-root paths before /v1", func() {
-			Expect(chatAPIBaseURL("http://127.0.0.1:8080/localai")).To(Equal("http://127.0.0.1:8080/localai/v1"))
-		})
-	})
-})

core/cli/chat_endpoint.go

@@ -1,29 +0,0 @@
-package cli
-
-import (
-	"net/url"
-	"strings"
-)
-
-func chatAPIBaseURL(endpoint string) string {
-	if !strings.Contains(endpoint, "://") {
-		endpoint = "http://" + endpoint
-	}
-
-	u, err := url.Parse(endpoint)
-	if err != nil {
-		return strings.TrimRight(endpoint, "/") + "/v1"
-	}
-
-	path := strings.TrimRight(u.Path, "/")
-	if path == "" {
-		u.Path = "/v1"
-	} else if path != "/v1" && !strings.HasSuffix(path, "/v1") {
-		u.Path = path + "/v1"
-	} else {
-		u.Path = path
-	}
-	u.RawQuery = ""
-	u.Fragment = ""
-	return u.String()
-}

core/cli/cli.go

@@ -9,7 +9,6 @@ var CLI struct {
 	cliContext.Context `embed:""`
 
 	Run             RunCMD             `cmd:"" help:"Run LocalAI, this the default command if no other command is specified. Run 'local-ai run --help' for more information" default:"withargs"`
-	Chat            ChatCMD            `cmd:"" help:"Open an interactive chat session against a running LocalAI server"`
 	Federated       FederatedCLI       `cmd:"" help:"Run LocalAI in federated mode"`
 	Models          ModelsCMD          `cmd:"" help:"Manage LocalAI models and definitions"`
 	Backends        BackendsCMD        `cmd:"" help:"Manage LocalAI backends and definitions"`

core/cli/run.go

@@ -30,8 +30,6 @@ type RunCMD struct {
 	ModelArgs []string `arg:"" optional:"" name:"models" help:"Model configuration URLs to load"`
 
 	ExternalBackends             []string      `env:"LOCALAI_EXTERNAL_BACKENDS,EXTERNAL_BACKENDS" help:"A list of external backends to load from gallery on boot" group:"backends"`
-	WebRTCNAT1To1IPs             []string      `env:"LOCALAI_WEBRTC_NAT_1TO1_IPS,WEBRTC_NAT_1TO1_IPS" help:"IPs advertised as the host ICE candidates for /v1/realtime WebRTC instead of every local interface. Set to the reachable host/LAN IP when running under Docker host networking or NAT, where pion otherwise offers unreachable bridge addresses and the connection drops after ICE consent checks fail." group:"api"`
-	WebRTCICEInterfaces          []string      `env:"LOCALAI_WEBRTC_ICE_INTERFACES,WEBRTC_ICE_INTERFACES" help:"Restrict /v1/realtime WebRTC ICE candidate gathering to these network interfaces (e.g. eth0), filtering out docker0/veth noise." group:"api"`
 	BackendsPath                 string        `env:"LOCALAI_BACKENDS_PATH,BACKENDS_PATH" type:"path" default:"${basepath}/backends" help:"Path containing backends used for inferencing" group:"backends"`
 	BackendsSystemPath           string        `env:"LOCALAI_BACKENDS_SYSTEM_PATH,BACKEND_SYSTEM_PATH" type:"path" default:"/var/lib/local-ai/backends" help:"Path containing system backends used for inferencing" group:"backends"`
 	ModelsPath                   string        `env:"LOCALAI_MODELS_PATH,MODELS_PATH" type:"path" default:"${basepath}/models" help:"Path containing models used for inferencing" group:"storage"`
@@ -227,8 +225,6 @@ func (r *RunCMD) Run(ctx *cliContext.Context) error {
 		config.WithApiKeys(r.APIKeys),
 		config.WithModelsURL(append(r.Models, r.ModelArgs...)...),
 		config.WithExternalBackends(r.ExternalBackends...),
-		config.WithWebRTCNAT1To1IPs(r.WebRTCNAT1To1IPs...),
-		config.WithWebRTCICEInterfaces(r.WebRTCICEInterfaces...),
 		config.WithOpaqueErrors(r.OpaqueErrors),
 		config.WithEnforcedPredownloadScans(!r.DisablePredownloadScan),
 		config.WithSubtleKeyComparison(r.UseSubtleKeyComparison),
@@ -656,12 +652,12 @@ func (r *RunCMD) Run(ctx *cliContext.Context) error {
 // waitForServerReady polls the given address until the HTTP server is
 // accepting connections or the context is cancelled.
 func waitForServerReady(address string, ctx context.Context) {
+	// Ensure the address has a host component for dialing.
+	// Echo accepts ":8080" but net.Dial needs a resolvable host.
 	host, port, err := net.SplitHostPort(address)
 	if err == nil && host == "" {
 		address = "127.0.0.1:" + port
 	}
-	ticker := time.NewTicker(250 * time.Millisecond)
-	defer ticker.Stop()
 
 	for {
 		select {
@@ -669,17 +665,11 @@ func waitForServerReady(address string, ctx context.Context) {
 			return
 		default:
 		}
-
 		conn, err := net.DialTimeout("tcp", address, 500*time.Millisecond)
 		if err == nil {
 			conn.Close()
 			return
 		}
-
-		select {
-		case <-ctx.Done():
-			return
-		case <-ticker.C:
-		}
+		time.Sleep(250 * time.Millisecond)
 	}
 }

core/config/application_config.go

@@ -12,19 +12,10 @@ import (
 )
 
 type ApplicationConfig struct {
-	Context          context.Context
-	ConfigFile       string
-	SystemState      *system.SystemState
-	ExternalBackends []string
-
-	// WebRTCNAT1To1IPs, when set, are advertised as the host ICE candidates for
-	// /v1/realtime WebRTC instead of every local interface address. Needed when
-	// the routable address differs from what pion gathers — e.g. Docker host
-	// networking (where pion also offers unreachable bridge IPs) or NAT.
-	WebRTCNAT1To1IPs []string
-	// WebRTCICEInterfaces, when set, restricts ICE candidate gathering to these
-	// network interfaces (e.g. eth0), filtering out docker0/veth noise.
-	WebRTCICEInterfaces                 []string
+	Context                             context.Context
+	ConfigFile                          string
+	SystemState                         *system.SystemState
+	ExternalBackends                    []string
 	UploadLimitMB, Threads, ContextSize int
 	F16                                 bool
 	Debug                               bool
@@ -90,6 +81,7 @@ type ApplicationConfig struct {
 	// file is mode 0600.
 	MITMCADir string
 
+
 	// PIIPatternOverrides applies persisted per-id deltas (action,
 	// disabled) to the live redactor at startup. Loaded from
 	// runtime_settings.json and applied right after pii.NewRedactor.
@@ -124,11 +116,11 @@ type ApplicationConfig struct {
 	// --require-backend-integrity / LOCALAI_REQUIRE_BACKEND_INTEGRITY.
 	RequireBackendIntegrity bool
 
-	SingleBackend     bool // Deprecated: use MaxActiveBackends = 1 instead
-	MaxActiveBackends int  // Maximum number of active backends (0 = unlimited, 1 = single backend mode)
-	WatchDogIdle      bool
-	WatchDogBusy      bool
-	WatchDog          bool
+	SingleBackend           bool // Deprecated: use MaxActiveBackends = 1 instead
+	MaxActiveBackends       int  // Maximum number of active backends (0 = unlimited, 1 = single backend mode)
+	WatchDogIdle bool
+	WatchDogBusy bool
+	WatchDog     bool
 
 	// Memory Reclaimer settings (works with GPU if available, otherwise RAM)
 	MemoryReclaimerEnabled   bool    // Enable memory threshold monitoring
@@ -319,18 +311,6 @@ func WithExternalBackends(backends ...string) AppOption {
 	}
 }
 
-func WithWebRTCNAT1To1IPs(ips ...string) AppOption {
-	return func(o *ApplicationConfig) {
-		o.WebRTCNAT1To1IPs = ips
-	}
-}
-
-func WithWebRTCICEInterfaces(interfaces ...string) AppOption {
-	return func(o *ApplicationConfig) {
-		o.WebRTCICEInterfaces = interfaces
-	}
-}
-
 func WithMachineTag(tag string) AppOption {
 	return func(o *ApplicationConfig) {
 		o.MachineTag = tag
@@ -722,6 +702,7 @@ func WithMITMCADir(dir string) AppOption {
 	}
 }
 
+
 func WithDynamicConfigDir(dynamicConfigsDir string) AppOption {
 	return func(o *ApplicationConfig) {
 		o.DynamicConfigsDir = dynamicConfigsDir

core/http/endpoints/openai/chat.go

@@ -103,12 +103,7 @@ func applyAutoparserOverride(
 	// blocks like "<think></think>" that some models emit when reasoning
 	// is disabled.
 	if deltaReasoning == "" && deltaContent != "" {
-		// Complete-response extraction: only honor a prefilled <think> start
-		// token when deltaContent actually closes the reasoning block. Without
-		// it the model answered directly and the whole answer must stay in
-		// content rather than be swallowed as unclosed reasoning. See
-		// reason.ExtractReasoningComplete.
-		deltaReasoning, deltaContent = reason.ExtractReasoningComplete(deltaContent, thinkingStartToken, reasoningConfig)
+		deltaReasoning, deltaContent = reason.ExtractReasoningWithConfig(deltaContent, thinkingStartToken, reasoningConfig)
 	}
 	xlog.Debug("[ChatDeltas] non-SSE no-tools: overriding result with C++ autoparser deltas",
 		"content_len", len(deltaContent), "reasoning_len", len(deltaReasoning))

core/http/endpoints/openai/chat_test.go

@@ -186,114 +186,6 @@ var _ = Describe("applyAutoparserOverride", func() {
 			Expect(result).To(Equal(existing))
 		})
 	})
-
-	// Regression tests for the prefilled-thinking-token path (thinkingStartToken
-	// != ""). This is the configuration the gallery qwen3 family runs in: the
-	// chat template injects <think> into the prompt, so DetectThinkingStartToken
-	// returns "<think>" and the model's output begins *inside* a reasoning block
-	// — it emits a closing </think> but no opening tag.
-	//
-	// The defensive Go-side fallback prepends the start token so the standard
-	// extractor can pair it with the model's </think>. But on a *complete*
-	// response that contains NO closing tag (the model answered directly with no
-	// reasoning at all), prepending <think> manufactures an unclosed block that
-	// swallows the entire answer into reasoning, leaving content empty. That is
-	// the bug: short/direct answers (session names, JSON summaries) come back
-	// with an empty content field.
-	Context("autoparser delivered content with empty reasoning and a prefilled thinking token", func() {
-		const startToken = "<think>"
-
-		It("keeps a tag-less direct answer as content instead of swallowing it as reasoning", func() {
-			// Model answered directly: no <think>, no </think> anywhere.
-			chatDeltas := []*pb.ChatDelta{
-				{Content: "hello", ReasoningContent: ""},
-			}
-
-			result := applyAutoparserOverride(chatDeltas, startToken, reason.Config{}, nil)
-
-			Expect(result).To(HaveLen(1))
-			Expect(result[0].Message.Content).ToNot(BeNil())
-			Expect(*(result[0].Message.Content.(*string))).To(Equal("hello"),
-				"a complete answer with no closing reasoning tag must stay in content")
-			Expect(result[0].Message.Reasoning).To(BeNil(),
-				"no reasoning block was emitted, so Reasoning must not be set")
-		})
-
-		It("keeps a tag-less JSON answer as content (the summary case)", func() {
-			raw := `{"short":"Tests pass","long":"go test ./... succeeded."}`
-			chatDeltas := []*pb.ChatDelta{
-				{Content: raw, ReasoningContent: ""},
-			}
-
-			result := applyAutoparserOverride(chatDeltas, startToken, reason.Config{}, nil)
-
-			Expect(result).To(HaveLen(1))
-			Expect(*(result[0].Message.Content.(*string))).To(Equal(raw))
-			Expect(result[0].Message.Reasoning).To(BeNil())
-		})
-
-		It("still splits reasoning when the model emits the closing tag (prefill paired with </think>)", func() {
-			// The legitimate prefill case: <think> was in the prompt, so the
-			// output carries only the closing tag. The closing tag is the proof
-			// that a reasoning block exists, so extraction must run.
-			raw := "The user wants a greeting.\n</think>\n\nHello there!"
-			chatDeltas := []*pb.ChatDelta{
-				{Content: raw, ReasoningContent: ""},
-			}
-
-			result := applyAutoparserOverride(chatDeltas, startToken, reason.Config{}, nil)
-
-			Expect(result).To(HaveLen(1))
-			content := *(result[0].Message.Content.(*string))
-			Expect(content).To(ContainSubstring("Hello there!"))
-			Expect(content).ToNot(ContainSubstring("</think>"))
-			Expect(content).ToNot(ContainSubstring("The user wants a greeting"))
-			Expect(result[0].Message.Reasoning).ToNot(BeNil())
-			Expect(*result[0].Message.Reasoning).To(ContainSubstring("The user wants a greeting"))
-		})
-
-		It("still splits a fully-tagged <think>…</think> block with a prefill token set", func() {
-			raw := "<think>Reasoning here.</think>Final answer."
-			chatDeltas := []*pb.ChatDelta{
-				{Content: raw, ReasoningContent: ""},
-			}
-
-			result := applyAutoparserOverride(chatDeltas, startToken, reason.Config{}, nil)
-
-			Expect(result).To(HaveLen(1))
-			Expect(*(result[0].Message.Content.(*string))).To(Equal("Final answer."))
-			Expect(result[0].Message.Reasoning).ToNot(BeNil())
-			Expect(*result[0].Message.Reasoning).To(ContainSubstring("Reasoning here"))
-		})
-
-		// End-to-end regression for the real production failure: a request with
-		// enable_thinking=false against a <think>-capable model (qwen3 family).
-		//
-		// In non-thinking mode the model emits no reasoning block, so llama.cpp's
-		// autoparser correctly returns ChatDeltas with Content set and
-		// ReasoningContent EMPTY (verified against stock llama-server: the same
-		// model with chat_template_kwargs.enable_thinking=false returns
-		// reasoning_content=null and content="hello"). But thinkingStartToken is
-		// detected per-model from the enable_thinking=TRUE render
-		// (grpc-server renders with enable_thinking=true; DetectThinkingStartToken
-		// does not evaluate the jinja {% if enable_thinking %} conditional), so it
-		// is "<think>" even for this non-thinking request. The old code prepended
-		// it and swallowed the answer. This is the case that broke session
-		// summaries and auto-titles and was NOT covered before.
-		It("preserves content for a non-thinking-mode request (enable_thinking=false, empty reasoning_content)", func() {
-			// What llama.cpp's autoparser actually returns in non-thinking mode.
-			chatDeltas := []*pb.ChatDelta{
-				{Content: `{"short":"Go tests passed for internal/session"}`, ReasoningContent: ""},
-			}
-
-			result := applyAutoparserOverride(chatDeltas, startToken, reason.Config{}, nil)
-
-			Expect(result).To(HaveLen(1))
-			Expect(*(result[0].Message.Content.(*string))).To(Equal(`{"short":"Go tests passed for internal/session"}`),
-				"non-thinking-mode answers must reach the client intact, not be swallowed as reasoning")
-			Expect(result[0].Message.Reasoning).To(BeNil())
-		})
-	})
 })
 
 var _ = Describe("mergeToolCallDeltas", func() {

core/http/endpoints/openai/realtime.go

@@ -1579,7 +1579,7 @@ func triggerResponseAtTurn(ctx context.Context, session *Session, conv *Conversa
 		// ExtractReasoningWithConfig is a no-op when no tag pair matches,
 		// so it's safe to apply unconditionally in the no-reasoning branch.
 		if deltaReasoning == "" && deltaContent != "" {
-			deltaReasoning, deltaContent = reasoning.ExtractReasoningComplete(deltaContent, thinkingStartToken, config.ReasoningConfig)
+			deltaReasoning, deltaContent = reasoning.ExtractReasoningWithConfig(deltaContent, thinkingStartToken, config.ReasoningConfig)
 		}
 		reasoningText = deltaReasoning
 		responseWithoutReasoning = deltaContent
@@ -1587,7 +1587,7 @@ func triggerResponseAtTurn(ctx context.Context, session *Session, conv *Conversa
 		cleanedResponse = deltaContent
 		toolCalls = deltaToolCalls
 	} else {
-		reasoningText, responseWithoutReasoning = reasoning.ExtractReasoningComplete(rawResponse, thinkingStartToken, config.ReasoningConfig)
+		reasoningText, responseWithoutReasoning = reasoning.ExtractReasoningWithConfig(rawResponse, thinkingStartToken, config.ReasoningConfig)
 		textContent = functions.ParseTextContent(responseWithoutReasoning, config.FunctionsConfig)
 		cleanedResponse = functions.CleanupLLMResult(responseWithoutReasoning, config.FunctionsConfig)
 		toolCalls = functions.ParseFunctionCall(cleanedResponse, config.FunctionsConfig)

core/http/endpoints/openai/realtime_webrtc.go

@@ -48,8 +48,7 @@ func RealtimeCalls(application *application.Application) echo.HandlerFunc {
 			return c.JSON(http.StatusInternalServerError, map[string]string{"error": "codec registration failed"})
 		}
 
-		se := webRTCSettingEngine(application.ApplicationConfig())
-		api := webrtc.NewAPI(webrtc.WithMediaEngine(m), webrtc.WithSettingEngine(se))
+		api := webrtc.NewAPI(webrtc.WithMediaEngine(m))
 
 		pc, err := api.NewPeerConnection(webrtc.Configuration{})
 		if err != nil {

core/http/endpoints/openai/realtime_webrtc_ice.go

@@ -1,47 +0,0 @@
-package openai
-
-import (
-	"github.com/mudler/LocalAI/core/config"
-	"github.com/mudler/xlog"
-	"github.com/pion/webrtc/v4"
-)
-
-// webRTCSettingEngine builds the pion SettingEngine for /v1/realtime WebRTC.
-//
-// With a default (empty) SettingEngine, pion gathers a host ICE candidate for
-// every local interface. Under Docker host networking that includes bridge
-// addresses (docker0/veth, 172.x) that a remote browser cannot route to; the
-// connection often establishes on a good pair and then drops once ICE consent
-// checks fail on the unreachable ones. The two opt-in knobs below let an
-// operator advertise only the reachable address.
-func webRTCSettingEngine(cfg *config.ApplicationConfig) webrtc.SettingEngine {
-	s := webrtc.SettingEngine{}
-	if cfg == nil {
-		return s
-	}
-	if len(cfg.WebRTCNAT1To1IPs) > 0 {
-		s.SetNAT1To1IPs(cfg.WebRTCNAT1To1IPs, webrtc.ICECandidateTypeHost)
-		xlog.Debug("realtime webrtc: advertising NAT 1:1 host IPs", "ips", cfg.WebRTCNAT1To1IPs)
-	}
-	if filter := iceInterfaceFilter(cfg.WebRTCICEInterfaces); filter != nil {
-		s.SetInterfaceFilter(filter)
-		xlog.Debug("realtime webrtc: restricting ICE interfaces", "interfaces", cfg.WebRTCICEInterfaces)
-	}
-	return s
-}
-
-// iceInterfaceFilter returns an interface allow-list predicate for pion, or nil
-// when no interfaces are configured (pion's default: gather from all).
-func iceInterfaceFilter(allowed []string) func(string) bool {
-	if len(allowed) == 0 {
-		return nil
-	}
-	set := make(map[string]struct{}, len(allowed))
-	for _, name := range allowed {
-		set[name] = struct{}{}
-	}
-	return func(iface string) bool {
-		_, ok := set[iface]
-		return ok
-	}
-}

core/http/endpoints/openai/realtime_webrtc_ice_test.go

@@ -1,39 +0,0 @@
-package openai
-
-import (
-	"github.com/mudler/LocalAI/core/config"
-	. "github.com/onsi/ginkgo/v2"
-	. "github.com/onsi/gomega"
-)
-
-var _ = Describe("webRTC ICE settings", func() {
-	Describe("iceInterfaceFilter", func() {
-		It("returns nil when no interfaces are configured", func() {
-			Expect(iceInterfaceFilter(nil)).To(BeNil())
-			Expect(iceInterfaceFilter([]string{})).To(BeNil())
-		})
-
-		It("admits only the configured interfaces", func() {
-			f := iceInterfaceFilter([]string{"eth0", "wlan0"})
-			Expect(f).NotTo(BeNil())
-			Expect(f("eth0")).To(BeTrue())
-			Expect(f("wlan0")).To(BeTrue())
-			Expect(f("docker0")).To(BeFalse())
-			Expect(f("veth123")).To(BeFalse())
-		})
-	})
-
-	Describe("webRTCSettingEngine", func() {
-		It("does not panic on a nil config", func() {
-			Expect(func() { webRTCSettingEngine(nil) }).NotTo(Panic())
-		})
-
-		It("builds an engine with NAT 1:1 IPs and an interface filter configured", func() {
-			cfg := &config.ApplicationConfig{
-				WebRTCNAT1To1IPs:    []string{"192.168.1.10"},
-				WebRTCICEInterfaces: []string{"eth0"},
-			}
-			Expect(func() { webRTCSettingEngine(cfg) }).NotTo(Panic())
-		})
-	})
-})

core/http/endpoints/openresponses/responses.go

@@ -1356,7 +1356,7 @@ func handleOpenResponsesNonStream(c echo.Context, responseID string, createdAt i
 	thinkingStartToken := reason.DetectThinkingStartToken(template, &cfg.ReasoningConfig)
 
 	// Extract reasoning from result before cleaning
-	reasoningContent, cleanedResult := reason.ExtractReasoningComplete(result, thinkingStartToken, cfg.ReasoningConfig)
+	reasoningContent, cleanedResult := reason.ExtractReasoningWithConfig(result, thinkingStartToken, cfg.ReasoningConfig)
 
 	// Parse tool calls if using functions
 	var outputItems []schema.ORItemField
@@ -1996,7 +1996,7 @@ func handleOpenResponsesStream(c echo.Context, responseID string, createdAt int6
 				finalCleanedResult = extractor.CleanedContent()
 			}
 			if finalReasoning == "" && finalCleanedResult == "" {
-				finalReasoning, finalCleanedResult = reason.ExtractReasoningComplete(result, thinkingStartToken, cfg.ReasoningConfig)
+				finalReasoning, finalCleanedResult = reason.ExtractReasoningWithConfig(result, thinkingStartToken, cfg.ReasoningConfig)
 			}
 
 			// Close reasoning item if it exists and wasn't closed yet
@@ -2493,7 +2493,7 @@ func handleOpenResponsesStream(c echo.Context, responseID string, createdAt int6
 		finalCleanedResult = extractor.CleanedContent()
 	}
 	if finalReasoning == "" && finalCleanedResult == "" {
-		finalReasoning, finalCleanedResult = reason.ExtractReasoningComplete(result, thinkingStartToken, cfg.ReasoningConfig)
+		finalReasoning, finalCleanedResult = reason.ExtractReasoningWithConfig(result, thinkingStartToken, cfg.ReasoningConfig)
 	}
 
 	// Close reasoning item if it exists and wasn't closed yet

core/http/react-ui/src/hooks/useChat.js

@@ -216,12 +216,6 @@ export function useChat(initialModel = '') {
             audio_url: { url: `data:${file.type};base64,${file.base64}` },
           })
           userFiles.push({ name: file.name, type: 'audio' })
-        } else if (file.type?.startsWith('video/')) {
-          messageContent.push({
-            type: 'video_url',
-            video_url: { url: `data:${file.type};base64,${file.base64}` },
-          })
-          userFiles.push({ name: file.name, type: 'video' })
         } else {
 			// Text/PDF files - append to content
 			if (file.textContent) {

core/http/react-ui/src/pages/Chat.jsx

@@ -265,7 +265,7 @@ function UserMessageContent({ content, files }) {
         <div className="chat-message-files">
           {files.map((f, i) => (
             <span key={i} className="chat-file-inline">
-              <i className={`fas ${f.type === 'image' ? 'fa-image' : f.type === 'audio' ? 'fa-headphones' : f.type === 'video' ? 'fa-film' : 'fa-file'}`} />
+              <i className={`fas ${f.type === 'image' ? 'fa-image' : f.type === 'audio' ? 'fa-headphones' : 'fa-file'}`} />
               {f.name}
             </span>
           ))}
@@ -274,9 +274,6 @@ function UserMessageContent({ content, files }) {
       {Array.isArray(content) && content.filter(c => c.type === 'image_url').map((img, i) => (
         <img key={i} src={img.image_url.url} alt="attached" className="chat-inline-image" />
       ))}
-      {Array.isArray(content) && content.filter(c => c.type === 'video_url').map((vid, i) => (
-        <video key={i} src={vid.video_url.url} controls className="chat-inline-video" />
-      ))}
     </>
   )
 }
@@ -714,7 +711,7 @@ export default function Chat() {
     for (const file of e.target.files) {
       const base64 = await fileToBase64(file)
       const entry = { name: file.name, type: file.type, base64 }
-      if (!file.type.startsWith('image/') && !file.type.startsWith('audio/') && !file.type.startsWith('video/')) {
+      if (!file.type.startsWith('image/') && !file.type.startsWith('audio/')) {
         entry.textContent = await file.text().catch(() => '')
       }
       newFiles.push(entry)
@@ -1247,7 +1244,7 @@ export default function Chat() {
           <div className="chat-files">
             {files.map((f, i) => (
               <span key={i} className="chat-file-badge">
-                <i className={`fas ${f.type?.startsWith('image/') ? 'fa-image' : f.type?.startsWith('audio/') ? 'fa-headphones' : f.type?.startsWith('video/') ? 'fa-film' : 'fa-file'}`} />
+                <i className={`fas ${f.type?.startsWith('image/') ? 'fa-image' : f.type?.startsWith('audio/') ? 'fa-headphones' : 'fa-file'}`} />
                 {f.name}
                 <button onClick={() => setFiles(prev => prev.filter((_, idx) => idx !== i))}>
                   <i className="fas fa-xmark" />
@@ -1346,7 +1343,7 @@ export default function Chat() {
               ref={fileInputRef}
               type="file"
               multiple
-              accept="image/*,audio/*,video/*,application/pdf,.txt,.md,.csv,.json"
+              accept="image/*,audio/*,application/pdf,.txt,.md,.csv,.json"
               style={{ display: 'none' }}
               onChange={handleFileChange}
             />

core/services/agentpool/agent_pool.go

@@ -466,11 +466,10 @@ func (s *AgentPoolService) Chat(name, message string) (string, error) {
 				s.collectAndCopyMetadata(metadata, chatUserID)
 			}
 
-			content := s.appendLocalAGIKBCitations(response.Response, name, message, response.State)
 			msg := map[string]any{
 				"id":        messageID + "-agent",
 				"sender":    "agent",
-				"content":   content,
+				"content":   response.Response,
 				"timestamp": time.Now().Format(time.RFC3339),
 			}
 			if len(metadata) > 0 {
@@ -490,79 +489,6 @@ func (s *AgentPoolService) Chat(name, message string) (string, error) {
 	return messageID, nil
 }
 
-func (s *AgentPoolService) appendLocalAGIKBCitations(response, agentKey, message string, states []coreTypes.ActionState) string {
-	if strings.TrimSpace(response) == "" {
-		return response
-	}
-
-	userID, collection := splitAgentKey(agentKey)
-	cfg := s.localAGI.pool.GetConfig(agentKey)
-	if cfg == nil || !cfg.EnableKnowledgeBase {
-		return response
-	}
-
-	citations := kbCitationsFromActionStates(states)
-	if len(citations) == 0 && cfg.KBAutoSearch {
-		maxResults := cfg.KnowledgeBaseResults
-		if maxResults <= 0 {
-			maxResults = 5
-		}
-		ctx, cancel := context.WithTimeout(context.Background(), 30*time.Second)
-		defer cancel()
-		kbResult := agents.KBAutoSearchPrompt(ctx, s.apiURL, s.apiKey, collection, message, maxResults, userID)
-		citations = kbResult.Citations
-	}
-
-	return agents.AppendKBCitations(response, collection, userID, citations)
-}
-
-func splitAgentKey(agentKey string) (userID, name string) {
-	if uid, n, ok := strings.Cut(agentKey, ":"); ok {
-		return uid, n
-	}
-	return "", agentKey
-}
-
-func kbCitationsFromActionStates(states []coreTypes.ActionState) []agents.KBCitation {
-	var citations []agents.KBCitation
-	for _, state := range states {
-		citations = append(citations, kbCitationsFromMetadata(state.Metadata)...)
-	}
-	return citations
-}
-
-func kbCitationsFromMetadata(metadata map[string]any) []agents.KBCitation {
-	if len(metadata) == 0 {
-		return nil
-	}
-
-	fileName := metadata["file_name"]
-	source := metadata["source"]
-	if fileName == nil && source == nil {
-		return nil
-	}
-
-	citation := agents.KBCitation{
-		FileName: metadataString(fileName),
-		EntryKey: metadataString(source),
-	}
-	if citation.FileName == "" && citation.EntryKey == "" {
-		return nil
-	}
-	return []agents.KBCitation{citation}
-}
-
-func metadataString(value any) string {
-	switch v := value.(type) {
-	case string:
-		return v
-	case fmt.Stringer:
-		return v.String()
-	default:
-		return ""
-	}
-}
-
 // userOutputsDir returns the per-user outputs directory, creating it if needed.
 // If userID is empty, falls back to the shared outputs directory.
 func (s *AgentPoolService) userOutputsDir(userID string) string {

core/services/agents/citations.go

@@ -1,127 +0,0 @@
-package agents
-
-import (
-	"fmt"
-	"net/url"
-	"strings"
-	"sync"
-)
-
-type kbCitationList struct {
-	mu        sync.Mutex
-	citations []KBCitation
-}
-
-func (l *kbCitationList) AddKBCitations(citations []KBCitation) {
-	if len(citations) == 0 {
-		return
-	}
-	l.mu.Lock()
-	defer l.mu.Unlock()
-	l.citations = append(l.citations, citations...)
-}
-
-func (l *kbCitationList) Citations() []KBCitation {
-	l.mu.Lock()
-	defer l.mu.Unlock()
-	out := make([]KBCitation, len(l.citations))
-	copy(out, l.citations)
-	return out
-}
-
-// AppendKBCitations appends a markdown Sources block for KB citations.
-func AppendKBCitations(response, collection, userID string, citations []KBCitation) string {
-	if strings.TrimSpace(response) == "" || len(citations) == 0 {
-		return response
-	}
-
-	var lines []string
-	seen := make(map[string]struct{})
-	for _, citation := range citations {
-		key := strings.TrimSpace(citation.EntryKey)
-		if key == "" {
-			key = strings.TrimSpace(citation.FileName)
-		}
-		if key == "" {
-			continue
-		}
-		if _, ok := seen[key]; ok {
-			continue
-		}
-		seen[key] = struct{}{}
-
-		displayName := kbCitationDisplayName(citation)
-		if displayName == "" {
-			continue
-		}
-
-		sourceURL := kbCitationRawFileURL(collection, citation.EntryKey, userID)
-		number := len(lines) + 1
-		if sourceURL == "" {
-			lines = append(lines, fmt.Sprintf("[%d] %s", number, displayName))
-			continue
-		}
-		lines = append(lines, fmt.Sprintf("[%d] [%s](%s)", number, escapeMarkdownLinkText(displayName), sourceURL))
-	}
-
-	if len(lines) == 0 {
-		return response
-	}
-
-	var sb strings.Builder
-	sb.WriteString(strings.TrimRight(response, "\n"))
-	sb.WriteString("\n\nSources:\n")
-	for _, line := range lines {
-		sb.WriteString(line)
-		sb.WriteString("\n")
-	}
-	return strings.TrimRight(sb.String(), "\n")
-}
-
-func kbCitationDisplayName(citation KBCitation) string {
-	if fileName := strings.TrimSpace(citation.FileName); fileName != "" {
-		return fileName
-	}
-
-	segments := strings.Split(strings.Trim(strings.TrimSpace(citation.EntryKey), "/"), "/")
-	for i := len(segments) - 1; i >= 0; i-- {
-		if segment := strings.TrimSpace(segments[i]); segment != "" {
-			return segment
-		}
-	}
-	return ""
-}
-
-func kbCitationRawFileURL(collection, entryKey, userID string) string {
-	collection = strings.TrimSpace(collection)
-	entryKey = strings.Trim(strings.TrimSpace(entryKey), "/")
-	if collection == "" || entryKey == "" {
-		return ""
-	}
-
-	var escapedEntrySegments []string
-	for _, segment := range strings.Split(entryKey, "/") {
-		if segment == "" {
-			continue
-		}
-		escapedEntrySegments = append(escapedEntrySegments, url.PathEscape(segment))
-	}
-	if len(escapedEntrySegments) == 0 {
-		return ""
-	}
-
-	sourceURL := "/api/agents/collections/" + url.PathEscape(collection) + "/entries-raw/" + strings.Join(escapedEntrySegments, "/")
-	if userID != "" {
-		query := url.Values{}
-		query.Set("user_id", userID)
-		sourceURL += "?" + query.Encode()
-	}
-	return sourceURL
-}
-
-func escapeMarkdownLinkText(text string) string {
-	text = strings.ReplaceAll(text, `\`, `\\`)
-	text = strings.ReplaceAll(text, "[", `\[`)
-	text = strings.ReplaceAll(text, "]", `\]`)
-	return text
-}

core/services/agents/executor.go

@@ -167,12 +167,10 @@ func ExecuteChatWithLLM(ctx context.Context, llm cogito.LLM, cfg *AgentConfig, m
 		}
 	}
 
-	kbCitations := &kbCitationList{}
 	if cfg.EnableKnowledgeBase && (kbMode == KBModeAutoSearch || kbMode == KBModeBoth) {
-		kbResult := KBAutoSearchPrompt(ctx, effectiveURL, effectiveKey, cfg.Name, message, cfg.KnowledgeBaseResults, userID)
-		if kbResult.Prompt != "" {
-			fragment = fragment.AddMessage(cogito.SystemMessageRole, kbResult.Prompt)
-			kbCitations.AddKBCitations(kbResult.Citations)
+		kbResults := KBAutoSearchPrompt(ctx, effectiveURL, effectiveKey, cfg.Name, message, cfg.KnowledgeBaseResults, userID)
+		if kbResults != "" {
+			fragment = fragment.AddMessage(cogito.SystemMessageRole, kbResults)
 		}
 	}
 
@@ -199,7 +197,7 @@ func ExecuteChatWithLLM(ctx context.Context, llm cogito.LLM, cfg *AgentConfig, m
 		}
 		cogitoOpts = append(cogitoOpts, cogito.WithTools(
 			cogito.NewToolDefinition(
-				KBSearchMemoryTool{APIURL: effectiveURL, APIKey: effectiveKey, Collection: cfg.Name, MaxResults: kbResults, UserID: userID, CitationCollector: kbCitations},
+				KBSearchMemoryTool{APIURL: effectiveURL, APIKey: effectiveKey, Collection: cfg.Name, MaxResults: kbResults, UserID: userID},
 				KBSearchMemoryArgs{},
 				"search_memory",
 				"Search the knowledge base for relevant information",
@@ -338,8 +336,6 @@ func ExecuteChatWithLLM(ctx context.Context, llm cogito.LLM, cfg *AgentConfig, m
 	if cfg.StripThinkingTags && response != "" {
 		response = stripThinkingTags(response)
 	}
-	responseForMemory := response
-	response = AppendKBCitations(response, cfg.Name, userID, kbCitations.Citations())
 
 	// Save conversation to KB when long-term memory is enabled.
 	// Use a detached context: the parent ctx may be cancelled (e.g. in distributed
@@ -348,7 +344,7 @@ func ExecuteChatWithLLM(ctx context.Context, llm cogito.LLM, cfg *AgentConfig, m
 		go func() {
 			ctx, cancel := context.WithTimeout(context.Background(), 30*time.Second)
 			defer cancel()
-			saveConversationToKB(ctx, llm, effectiveURL, effectiveKey, cfg, message, responseForMemory, userID)
+			saveConversationToKB(ctx, llm, effectiveURL, effectiveKey, cfg, message, response, userID)
 		}()
 	}
 

core/services/agents/executor_test.go

@@ -2,8 +2,6 @@ package agents
 
 import (
 	"context"
-	"net/http"
-	"net/http/httptest"
 	"sync"
 	"sync/atomic"
 
@@ -38,34 +36,6 @@ func (m *mockLLM) CreateChatCompletion(ctx context.Context, req openai.ChatCompl
 	}, cogito.LLMUsage{}, nil
 }
 
-type toolCallingMockLLM struct {
-	createResponses []openai.ChatCompletionResponse
-	askResponse     string
-	callCount       atomic.Int32
-}
-
-func (m *toolCallingMockLLM) Ask(ctx context.Context, f cogito.Fragment) (cogito.Fragment, error) {
-	m.callCount.Add(1)
-	return f.AddMessage(cogito.AssistantMessageRole, m.askResponse), nil
-}
-
-func (m *toolCallingMockLLM) CreateChatCompletion(ctx context.Context, req openai.ChatCompletionRequest) (cogito.LLMReply, cogito.LLMUsage, error) {
-	idx := int(m.callCount.Add(1)) - 1
-	if idx >= len(m.createResponses) {
-		return cogito.LLMReply{
-			ChatCompletionResponse: openai.ChatCompletionResponse{
-				Choices: []openai.ChatCompletionChoice{{
-					Message: openai.ChatCompletionMessage{
-						Role:    "assistant",
-						Content: "No more tools needed.",
-					},
-				}},
-			},
-		}, cogito.LLMUsage{}, nil
-	}
-	return cogito.LLMReply{ChatCompletionResponse: m.createResponses[idx]}, cogito.LLMUsage{}, nil
-}
-
 // statusCollector records status callbacks in a thread-safe way.
 type statusCollector struct {
 	mu       sync.Mutex
@@ -103,74 +73,6 @@ var _ = DescribeTable("stripThinkingTags",
 	Entry("adjacent tag pairs", "<thinking>a</thinking><thinking>b</thinking>", ""),
 )
 
-var _ = DescribeTable("appendKBCitations",
-	func(response, collection, userID string, citations []KBCitation, want string) {
-		Expect(AppendKBCitations(response, collection, userID, citations)).To(Equal(want))
-	},
-	Entry("leaves responses without citations unchanged",
-		"answer",
-		"agent",
-		"",
-		nil,
-		"answer",
-	),
-	Entry("leaves blank responses unchanged",
-		"",
-		"agent",
-		"",
-		[]KBCitation{{FileName: "source.pdf", EntryKey: "uuid/source.pdf"}},
-		"",
-	),
-	Entry("appends clickable source links",
-		"answer",
-		"my-agent",
-		"",
-		[]KBCitation{{FileName: "new feature.pdf", EntryKey: "uuid/new feature.pdf"}},
-		"answer\n\nSources:\n[1] [new feature.pdf](/api/agents/collections/my-agent/entries-raw/uuid/new%20feature.pdf)",
-	),
-	Entry("deduplicates citations by entry key",
-		"answer",
-		"agent",
-		"",
-		[]KBCitation{
-			{FileName: "first.pdf", EntryKey: "uuid/shared.pdf"},
-			{FileName: "second.pdf", EntryKey: "uuid/shared.pdf"},
-		},
-		"answer\n\nSources:\n[1] [first.pdf](/api/agents/collections/agent/entries-raw/uuid/shared.pdf)",
-	),
-	Entry("uses plain text when entry key is missing",
-		"answer",
-		"agent",
-		"",
-		[]KBCitation{{FileName: "source.pdf"}},
-		"answer\n\nSources:\n[1] source.pdf",
-	),
-	Entry("uses entry basename when filename is missing",
-		"answer",
-		"agent",
-		"",
-		[]KBCitation{{EntryKey: "uuid/source.pdf"}},
-		"answer\n\nSources:\n[1] [source.pdf](/api/agents/collections/agent/entries-raw/uuid/source.pdf)",
-	),
-	Entry("adds user id query when present",
-		"answer",
-		"agent",
-		"user 1",
-		[]KBCitation{{FileName: "source.pdf", EntryKey: "uuid/source.pdf"}},
-		"answer\n\nSources:\n[1] [source.pdf](/api/agents/collections/agent/entries-raw/uuid/source.pdf?user_id=user+1)",
-	),
-	Entry("escapes collection, path segments, and markdown link text",
-		"answer",
-		"agent one",
-		"",
-		[]KBCitation{{FileName: "source [draft].pdf", EntryKey: "uuid/source [draft].pdf"}},
-		`answer
-
-Sources:
-[1] [source \[draft\].pdf](/api/agents/collections/agent%20one/entries-raw/uuid/source%20%5Bdraft%5D.pdf)`,
-	),
-)
-
 var _ = Describe("ExecuteChatWithLLM", func() {
 	var (
 		ctx context.Context
@@ -282,150 +184,6 @@ var _ = Describe("ExecuteChatWithLLM", func() {
 		})
 	})
 
-	Context("knowledge base citations", func() {
-		It("appends KB sources to the returned response and callback message", func() {
-			mux := http.NewServeMux()
-			mux.HandleFunc("/api/agents/collections/kb-agent/search", func(w http.ResponseWriter, r *http.Request) {
-				Expect(r.URL.Query().Get("user_id")).To(Equal("user-1"))
-				w.Header().Set("Content-Type", "application/json")
-				_, _ = w.Write([]byte(`{
-					"results": [
-						{
-							"content": "KB content",
-							"id": "result-1",
-							"similarity": 0.99,
-							"metadata": {
-								"file_name": "new feature.pdf",
-								"source": "uuid/new feature.pdf"
-							}
-						}
-					],
-					"count": 1
-				}`))
-			})
-			server := httptest.NewServer(mux)
-			defer server.Close()
-
-			var msgContent string
-			cb.OnMessage = func(sender, content, messageID string) {
-				msgContent = content
-			}
-
-			llm := &mockLLM{response: "agent reply"}
-			cfg := &AgentConfig{
-				Name:                "kb-agent",
-				Model:               "test-model",
-				EnableKnowledgeBase: true,
-				KBMode:              KBModeAutoSearch,
-			}
-
-			result, err := ExecuteChatWithLLM(ctx, llm, cfg, "hello", cb, ExecuteChatOpts{
-				APIURL: server.URL,
-				UserID: "user-1",
-			})
-			Expect(err).ToNot(HaveOccurred())
-			Expect(result).To(Equal("agent reply\n\nSources:\n[1] [new feature.pdf](/api/agents/collections/kb-agent/entries-raw/uuid/new%20feature.pdf?user_id=user-1)"))
-			Expect(msgContent).To(Equal(result))
-		})
-
-		It("collects citations from the search_memory tool", func() {
-			mux := http.NewServeMux()
-			mux.HandleFunc("/api/agents/collections/kb-agent/search", func(w http.ResponseWriter, r *http.Request) {
-				w.Header().Set("Content-Type", "application/json")
-				_, _ = w.Write([]byte(`{
-					"results": [
-						{
-							"content": "Tool KB content",
-							"id": "result-1",
-							"similarity": 0.99,
-							"metadata": {
-								"file_name": "tool source.pdf",
-								"source": "uuid/tool source.pdf"
-							}
-						}
-					],
-					"count": 1
-				}`))
-			})
-			server := httptest.NewServer(mux)
-			defer server.Close()
-
-			collector := &kbCitationList{}
-			tool := KBSearchMemoryTool{
-				APIURL:            server.URL,
-				Collection:        "kb-agent",
-				CitationCollector: collector,
-			}
-
-			result, _, err := tool.Run(KBSearchMemoryArgs{Query: "hello"})
-			Expect(err).ToNot(HaveOccurred())
-			Expect(result).To(ContainSubstring("Tool KB content"))
-			Expect(collector.Citations()).To(Equal([]KBCitation{{FileName: "tool source.pdf", EntryKey: "uuid/tool source.pdf"}}))
-		})
-
-		It("appends KB sources found through tools-only search_memory calls", func() {
-			mux := http.NewServeMux()
-			mux.HandleFunc("/api/agents/collections/kb-agent/search", func(w http.ResponseWriter, r *http.Request) {
-				Expect(r.URL.Query().Get("user_id")).To(Equal("user-1"))
-				w.Header().Set("Content-Type", "application/json")
-				_, _ = w.Write([]byte(`{
-					"results": [
-						{
-							"content": "Tool KB content",
-							"id": "result-1",
-							"similarity": 0.99,
-							"metadata": {
-								"file_name": "tool source.pdf",
-								"source": "uuid/tool source.pdf"
-							}
-						}
-					],
-					"count": 1
-				}`))
-			})
-			server := httptest.NewServer(mux)
-			defer server.Close()
-
-			llm := &toolCallingMockLLM{
-				askResponse: "agent reply from tool context",
-				createResponses: []openai.ChatCompletionResponse{
-					{
-						Choices: []openai.ChatCompletionChoice{
-							{
-								Message: openai.ChatCompletionMessage{
-									Role: "assistant",
-									ToolCalls: []openai.ToolCall{
-										{
-											ID:   "call-1",
-											Type: openai.ToolTypeFunction,
-											Function: openai.FunctionCall{
-												Name:      "search_memory",
-												Arguments: `{"query":"hello"}`,
-											},
-										},
-									},
-								},
-							},
-						},
-					},
-				},
-			}
-			cfg := &AgentConfig{
-				Name:                "kb-agent",
-				Model:               "test-model",
-				EnableKnowledgeBase: true,
-				KBMode:              KBModeTools,
-			}
-
-			result, err := ExecuteChatWithLLM(ctx, llm, cfg, "hello", cb, ExecuteChatOpts{
-				APIURL: server.URL,
-				UserID: "user-1",
-			})
-			Expect(err).ToNot(HaveOccurred())
-			Expect(result).To(Equal("agent reply from tool context\n\nSources:\n[1] [tool source.pdf](/api/agents/collections/kb-agent/entries-raw/uuid/tool%20source.pdf?user_id=user-1)"))
-		})
-	})
-
 	Context("context cancellation", func() {
 		It("returns an error when context is already cancelled", func() {
 			cancelledCtx, cancel := context.WithCancel(ctx)

core/services/agents/knowledge.go

@@ -8,7 +8,6 @@ import (
 	"io"
 	"mime/multipart"
 	"net/http"
-	"net/url"
 	"strings"
 	"time"
 
@@ -18,19 +17,10 @@ import (
 	"github.com/mudler/LocalAI/pkg/httpclient"
 )
 
-// Metadata keys populated by localrecall for every stored chunk. The original
-// upload file name lives under file_name (used for display); source holds the
-// collection entry key ("<uuid>/<filename>") used to build the raw-file URL.
-const (
-	kbMetadataFileName = "file_name"
-	kbMetadataSource   = "source"
-)
-
 // KBSearchResult represents a search result from the knowledge base.
-// Field names mirror the collection search endpoint's JSON response.
 type KBSearchResult struct {
 	Content    string            `json:"content"`
-	ID         string            `json:"id"`
+	Score      float64           `json:"score"`
 	Similarity float64           `json:"similarity"`
 	Metadata   map[string]string `json:"metadata"`
 }
@@ -41,48 +31,22 @@ type kbSearchResponse struct {
 	Count   int              `json:"count"`
 }
 
-// KBCitation is a single source document that a KB search drew from. Citations
-// travel alongside the prompt as structured data so the consumer (and UI) can
-// render clickable source links, independent of what the model writes inline.
-type KBCitation struct {
-	// FileName is the original uploaded file name, for display (e.g. "report.pdf").
-	FileName string `json:"file_name"`
-	// EntryKey is the collection entry identifier ("<uuid>/<filename>"), used to
-	// build the raw-file URL and as the de-duplication key.
-	EntryKey string `json:"entry_key"`
-}
-
-// KBSearchContext is the result of an auto-search against the knowledge base:
-// the system-prompt block to feed the model, plus the de-duplicated list of
-// source documents the results were drawn from.
-type KBSearchContext struct {
-	Prompt    string       `json:"prompt"`
-	Citations []KBCitation `json:"citations"`
-}
-
-// KBCitationCollector receives source citations found during KB searches.
-type KBCitationCollector interface {
-	AddKBCitations([]KBCitation)
-}
-
-// KBAutoSearchPrompt queries the knowledge base with the user's message and
-// returns a KBSearchContext: a system prompt block with the relevant results
-// plus the de-duplicated source citations those results came from.
+// KBAutoSearchPrompt queries the knowledge base with the user's message
+// and returns a system prompt block with relevant results.
 // Uses LocalAI's collection search endpoint via the API.
-func KBAutoSearchPrompt(ctx context.Context, apiURL, apiKey, collection, query string, maxResults int, userID string) KBSearchContext {
+func KBAutoSearchPrompt(ctx context.Context, apiURL, apiKey, collection, query string, maxResults int, userID string) string {
 	if collection == "" || query == "" {
-		return KBSearchContext{}
+		return ""
 	}
 
 	if maxResults <= 0 {
 		maxResults = 5
 	}
 
-	searchURL := strings.TrimRight(apiURL, "/") + "/api/agents/collections/" + url.PathEscape(collection) + "/search"
+	// Call LocalAI's collection search API
+	searchURL := strings.TrimRight(apiURL, "/") + "/api/agents/collections/" + collection + "/search"
 	if userID != "" {
-		query := url.Values{}
-		query.Set("user_id", userID)
-		searchURL += "?" + query.Encode()
+		searchURL += "?user_id=" + userID
 	}
 	reqBody, _ := json.Marshal(map[string]any{
 		"query":       query,
@@ -92,7 +56,7 @@ func KBAutoSearchPrompt(ctx context.Context, apiURL, apiKey, collection, query s
 	req, err := http.NewRequestWithContext(ctx, http.MethodPost, searchURL, strings.NewReader(string(reqBody)))
 	if err != nil {
 		xlog.Warn("KB auto-search: failed to create request", "error", err)
-		return KBSearchContext{}
+		return ""
 	}
 	req.Header.Set("Content-Type", "application/json")
 	if apiKey != "" {
@@ -102,70 +66,41 @@ func KBAutoSearchPrompt(ctx context.Context, apiURL, apiKey, collection, query s
 	resp, err := httpclient.New().Do(req)
 	if err != nil {
 		xlog.Warn("KB auto-search: request failed", "error", err)
-		return KBSearchContext{}
+		return ""
 	}
 	defer resp.Body.Close()
 
 	if resp.StatusCode != http.StatusOK {
 		body, _ := io.ReadAll(resp.Body)
 		xlog.Warn("KB auto-search: non-200 response", "status", resp.StatusCode, "body", string(body))
-		return KBSearchContext{}
+		return ""
 	}
 
 	var searchResp kbSearchResponse
 	if err := json.NewDecoder(resp.Body).Decode(&searchResp); err != nil {
 		xlog.Warn("KB auto-search: failed to decode response", "error", err)
-		return KBSearchContext{}
+		return ""
 	}
 
 	if len(searchResp.Results) == 0 {
-		return KBSearchContext{}
+		return ""
 	}
 
-	// Build the system prompt block, labelling each chunk with its source file
-	// so the model can attribute inline, and collect the structured citations.
+	// Format results as a system prompt block (same format as LocalAGI)
 	var sb strings.Builder
 	sb.WriteString("Given the user input you have the following in memory:\n")
-
-	var citations []KBCitation
-	seen := make(map[string]struct{})
-
-	for _, r := range searchResp.Results {
-		fileName := r.Metadata[kbMetadataFileName]
-		source := r.Metadata[kbMetadataSource]
-
-		label := fileName
-		if label == "" {
-			label = "unknown"
+	for i, r := range searchResp.Results {
+		sb.WriteString(fmt.Sprintf("- %s", r.Content))
+		if len(r.Metadata) > 0 {
+			meta, _ := json.Marshal(r.Metadata)
+			sb.WriteString(fmt.Sprintf(" (%s)", string(meta)))
 		}
-		sb.WriteString(fmt.Sprintf("[Source: %s]\n%s\n", label, r.Content))
-
-		// Citations are de-duplicated per source document: many chunks from the
-		// same file share one source key, so a file is listed only once. Skip
-		// results with no source key — they cannot be linked back to a document.
-		dedupKey := source
-		if dedupKey == "" {
-			dedupKey = fileName
+		if i < len(searchResp.Results)-1 {
+			sb.WriteString("\n")
 		}
-		if dedupKey == "" {
-			continue
-		}
-		if _, ok := seen[dedupKey]; ok {
-			continue
-		}
-		seen[dedupKey] = struct{}{}
-		citations = append(citations, KBCitation{
-			FileName: fileName,
-			EntryKey: source,
-		})
 	}
 
-	sb.WriteString("When answering, cite sources using [Source: filename].")
-
-	return KBSearchContext{
-		Prompt:    sb.String(),
-		Citations: citations,
-	}
+	return sb.String()
 }
 
 // KBSearchMemoryArgs defines the arguments for the search_memory tool.
@@ -175,25 +110,21 @@ type KBSearchMemoryArgs struct {
 
 // KBSearchMemoryTool implements the search_memory MCP tool.
 type KBSearchMemoryTool struct {
-	APIURL            string
-	APIKey            string
-	Collection        string
-	MaxResults        int
-	UserID            string
-	CitationCollector KBCitationCollector
+	APIURL     string
+	APIKey     string
+	Collection string
+	MaxResults int
+	UserID     string
 }
 
 func (t KBSearchMemoryTool) Run(args KBSearchMemoryArgs) (string, any, error) {
 	ctx, cancel := context.WithTimeout(context.Background(), 30*time.Second)
 	defer cancel()
 	result := KBAutoSearchPrompt(ctx, t.APIURL, t.APIKey, t.Collection, args.Query, t.MaxResults, t.UserID)
-	if result.Prompt == "" {
+	if result == "" {
 		return "No results found.", nil, nil
 	}
-	if t.CitationCollector != nil {
-		t.CitationCollector.AddKBCitations(result.Citations)
-	}
-	return result.Prompt, nil, nil
+	return result, nil, nil
 }
 
 // KBAddMemoryArgs defines the arguments for the add_memory tool.
@@ -225,11 +156,9 @@ func (t KBAddMemoryTool) Run(args KBAddMemoryArgs) (string, any, error) {
 
 // KBStoreContent uploads text content to a collection via the multipart upload API.
 func KBStoreContent(ctx context.Context, apiURL, apiKey, collection, content, userID string) error {
-	uploadURL := strings.TrimRight(apiURL, "/") + "/api/agents/collections/" + url.PathEscape(collection) + "/upload"
+	uploadURL := strings.TrimRight(apiURL, "/") + "/api/agents/collections/" + collection + "/upload"
 	if userID != "" {
-		query := url.Values{}
-		query.Set("user_id", userID)
-		uploadURL += "?" + query.Encode()
+		uploadURL += "?user_id=" + userID
 	}
 
 	// Build multipart form with the text content as a file

core/services/nodes/inflight.go

@@ -157,82 +157,3 @@ func (c *InFlightTrackingClient) Rerank(ctx context.Context, in *pb.RerankReques
 	res, err := c.Backend.Rerank(ctx, in, opts...)
 	return res, c.reconcile(err)
 }
-
-func (c *InFlightTrackingClient) VAD(ctx context.Context, in *pb.VADRequest, opts ...ggrpc.CallOption) (*pb.VADResponse, error) {
-	defer c.track(ctx)()
-	res, err := c.Backend.VAD(ctx, in, opts...)
-	return res, c.reconcile(err)
-}
-
-func (c *InFlightTrackingClient) Diarize(ctx context.Context, in *pb.DiarizeRequest, opts ...ggrpc.CallOption) (*pb.DiarizeResponse, error) {
-	defer c.track(ctx)()
-	res, err := c.Backend.Diarize(ctx, in, opts...)
-	return res, c.reconcile(err)
-}
-
-func (c *InFlightTrackingClient) FaceVerify(ctx context.Context, in *pb.FaceVerifyRequest, opts ...ggrpc.CallOption) (*pb.FaceVerifyResponse, error) {
-	defer c.track(ctx)()
-	res, err := c.Backend.FaceVerify(ctx, in, opts...)
-	return res, c.reconcile(err)
-}
-
-func (c *InFlightTrackingClient) FaceAnalyze(ctx context.Context, in *pb.FaceAnalyzeRequest, opts ...ggrpc.CallOption) (*pb.FaceAnalyzeResponse, error) {
-	defer c.track(ctx)()
-	res, err := c.Backend.FaceAnalyze(ctx, in, opts...)
-	return res, c.reconcile(err)
-}
-
-func (c *InFlightTrackingClient) VoiceVerify(ctx context.Context, in *pb.VoiceVerifyRequest, opts ...ggrpc.CallOption) (*pb.VoiceVerifyResponse, error) {
-	defer c.track(ctx)()
-	res, err := c.Backend.VoiceVerify(ctx, in, opts...)
-	return res, c.reconcile(err)
-}
-
-func (c *InFlightTrackingClient) VoiceAnalyze(ctx context.Context, in *pb.VoiceAnalyzeRequest, opts ...ggrpc.CallOption) (*pb.VoiceAnalyzeResponse, error) {
-	defer c.track(ctx)()
-	res, err := c.Backend.VoiceAnalyze(ctx, in, opts...)
-	return res, c.reconcile(err)
-}
-
-func (c *InFlightTrackingClient) VoiceEmbed(ctx context.Context, in *pb.VoiceEmbedRequest, opts ...ggrpc.CallOption) (*pb.VoiceEmbedResponse, error) {
-	defer c.track(ctx)()
-	res, err := c.Backend.VoiceEmbed(ctx, in, opts...)
-	return res, c.reconcile(err)
-}
-
-func (c *InFlightTrackingClient) TokenClassify(ctx context.Context, in *pb.TokenClassifyRequest, opts ...ggrpc.CallOption) (*pb.TokenClassifyResponse, error) {
-	defer c.track(ctx)()
-	res, err := c.Backend.TokenClassify(ctx, in, opts...)
-	return res, c.reconcile(err)
-}
-
-func (c *InFlightTrackingClient) Score(ctx context.Context, in *pb.ScoreRequest, opts ...ggrpc.CallOption) (*pb.ScoreResponse, error) {
-	defer c.track(ctx)()
-	res, err := c.Backend.Score(ctx, in, opts...)
-	return res, c.reconcile(err)
-}
-
-func (c *InFlightTrackingClient) AudioEncode(ctx context.Context, in *pb.AudioEncodeRequest, opts ...ggrpc.CallOption) (*pb.AudioEncodeResult, error) {
-	defer c.track(ctx)()
-	res, err := c.Backend.AudioEncode(ctx, in, opts...)
-	return res, c.reconcile(err)
-}
-
-func (c *InFlightTrackingClient) AudioDecode(ctx context.Context, in *pb.AudioDecodeRequest, opts ...ggrpc.CallOption) (*pb.AudioDecodeResult, error) {
-	defer c.track(ctx)()
-	res, err := c.Backend.AudioDecode(ctx, in, opts...)
-	return res, c.reconcile(err)
-}
-
-func (c *InFlightTrackingClient) AudioTransform(ctx context.Context, in *pb.AudioTransformRequest, opts ...ggrpc.CallOption) (*pb.AudioTransformResult, error) {
-	defer c.track(ctx)()
-	res, err := c.Backend.AudioTransform(ctx, in, opts...)
-	return res, c.reconcile(err)
-}
-
-// AudioTransformStream, AudioToAudioStream and Forward are deliberately left as
-// embedded passthrough: they return a stream client and the inference spans the
-// stream's lifetime, not the constructor call. Wrapping the constructor with
-// track() would increment and immediately decrement (and fire onFirstComplete)
-// before any audio flows. Tracking those correctly needs the done() func tied to
-// stream close, which the current Backend interface doesn't surface here.

core/services/nodes/inflight_test.go

@@ -304,105 +304,6 @@ var _ = Describe("InFlightTrackingClient", func() {
 		})
 	})
 
-	Describe("non-LLM inference methods track in-flight", func() {
-		// silero-vad and friends only ever expose a single non-Predict method.
-		// If that method isn't wrapped, the load-time reservation released by
-		// onFirstComplete never fires and in-flight is stuck at 1 forever.
-		assertTracked := func(call func() error) {
-			var firstFired int
-			client.OnFirstComplete(func() { firstFired++ })
-			err := call()
-			Expect(err).ToNot(HaveOccurred())
-			Expect(tracker.increments).To(Equal(1), "method must increment in-flight")
-			Expect(tracker.decrements).To(Equal(1), "method must decrement in-flight")
-			Expect(firstFired).To(Equal(1), "method must release the load-time reservation")
-		}
-
-		It("VAD", func() {
-			assertTracked(func() error {
-				_, err := client.VAD(context.Background(), &pb.VADRequest{})
-				return err
-			})
-		})
-
-		It("Diarize", func() {
-			assertTracked(func() error {
-				_, err := client.Diarize(context.Background(), &pb.DiarizeRequest{})
-				return err
-			})
-		})
-
-		It("VoiceVerify", func() {
-			assertTracked(func() error {
-				_, err := client.VoiceVerify(context.Background(), &pb.VoiceVerifyRequest{})
-				return err
-			})
-		})
-
-		It("VoiceAnalyze", func() {
-			assertTracked(func() error {
-				_, err := client.VoiceAnalyze(context.Background(), &pb.VoiceAnalyzeRequest{})
-				return err
-			})
-		})
-
-		It("VoiceEmbed", func() {
-			assertTracked(func() error {
-				_, err := client.VoiceEmbed(context.Background(), &pb.VoiceEmbedRequest{})
-				return err
-			})
-		})
-
-		It("FaceVerify", func() {
-			assertTracked(func() error {
-				_, err := client.FaceVerify(context.Background(), &pb.FaceVerifyRequest{})
-				return err
-			})
-		})
-
-		It("FaceAnalyze", func() {
-			assertTracked(func() error {
-				_, err := client.FaceAnalyze(context.Background(), &pb.FaceAnalyzeRequest{})
-				return err
-			})
-		})
-
-		It("TokenClassify", func() {
-			assertTracked(func() error {
-				_, err := client.TokenClassify(context.Background(), &pb.TokenClassifyRequest{})
-				return err
-			})
-		})
-
-		It("Score", func() {
-			assertTracked(func() error {
-				_, err := client.Score(context.Background(), &pb.ScoreRequest{})
-				return err
-			})
-		})
-
-		It("AudioEncode", func() {
-			assertTracked(func() error {
-				_, err := client.AudioEncode(context.Background(), &pb.AudioEncodeRequest{})
-				return err
-			})
-		})
-
-		It("AudioDecode", func() {
-			assertTracked(func() error {
-				_, err := client.AudioDecode(context.Background(), &pb.AudioDecodeRequest{})
-				return err
-			})
-		})
-
-		It("AudioTransform", func() {
-			assertTracked(func() error {
-				_, err := client.AudioTransform(context.Background(), &pb.AudioTransformRequest{})
-				return err
-			})
-		})
-	})
-
 	Describe("stale model reload (self-heal)", func() {
 		It("removes the replica when the backend reports the model is not loaded", func() {
 			backend.predictErr = fmt.Errorf("parakeet-cpp: model not loaded")

docs/content/features/openai-realtime.md

@@ -74,28 +74,6 @@ EXTERNAL_GRPC_BACKENDS=opus:/path/to/backend/go/opus/opus
 
 The opus backend is loaded automatically when a WebRTC session starts. It does not require any model configuration file — just the backend binary.
 
-#### WebRTC behind Docker host networking or NAT
-
-By default pion gathers a host ICE candidate for every local interface. Under
-Docker **host networking** that includes bridge addresses (`docker0`/`veth`,
-`172.x`) that a remote browser cannot route to: the call typically connects on a
-good candidate and then drops a few seconds later when ICE consent checks fail on
-the unreachable ones. Two settings let you advertise only the reachable address:
-
-```bash
-# Advertise these IPs as the host ICE candidates (e.g. the host's LAN IP)
-LOCALAI_WEBRTC_NAT_1TO1_IPS=192.168.1.10
-
-# ...or restrict ICE gathering to specific interfaces
-LOCALAI_WEBRTC_ICE_INTERFACES=eth0
-```
-
-{{% notice tip %}}
-For a browser on another LAN machine talking to LocalAI in a host-networked
-container, set `LOCALAI_WEBRTC_NAT_1TO1_IPS` to the host's LAN IP. This is the
-most reliable fix for WebRTC connections that establish and then drop.
-{{% /notice %}}
-
 ## Protocol
 
 The API follows the OpenAI Realtime API protocol for handling sessions, audio buffers, and conversation items.

docs/content/getting-started/try-it-out.md

@@ -20,29 +20,7 @@ With the CLI you can list the models with `local-ai models list` and install the
 You can also [run models manually]({{%relref "getting-started/models" %}}) by copying files into the `models` directory.
  {{% /notice %}}
 
-You can test chat models from the CLI without keeping a separate `curl` command around:
-
-```bash
-# Terminal 1
-local-ai run
-
-# Terminal 2
-local-ai chat --model gpt-4
-```
-
-`local-ai chat` connects to a running LocalAI server, opens an interactive chat prompt, and exits when you type `/exit`, `/quit`, or `/bye`. Use `/models` to list installed models, `/model <name>` to switch models, and `/clear` to reset the current conversation. If the server exposes exactly one model, LocalAI uses that model automatically:
-
-```bash
-# Terminal 1
-local-ai run llama-3.2-1b-instruct:q4_k_m
-
-# Terminal 2
-local-ai chat
-```
-
-When more than one model is configured, pass `--model` with the installed model name to avoid ambiguity. Use `--endpoint` to connect to a non-default server, for example `local-ai chat --endpoint http://127.0.0.1:8081 --model gpt-4`.
-
-You can also test out the API endpoints using `curl`, few examples are listed below. The models we are referring here (`gpt-4`, `gpt-4-vision-preview`, `tts-1`, `whisper-1`) are examples - replace them with the model names you have installed.
+You can test out the API endpoints using `curl`, few examples are listed below. The models we are referring here (`gpt-4`, `gpt-4-vision-preview`, `tts-1`, `whisper-1`) are examples - replace them with the model names you have installed.
 
 ### Text Generation
 

docs/content/reference/cli-reference.md

@@ -118,21 +118,6 @@ For more information on VRAM management, see [VRAM and Memory Management]({{%rel
 
 See [Authentication & Authorization]({{%relref "features/authentication" %}}) for full documentation.
 
-## Chat Flags
-
-Use `local-ai chat` to open an interactive terminal chat session against a running LocalAI server.
-
-| Parameter | Default | Description | Environment Variable |
-|-----------|---------|-------------|----------------------|
-| `--endpoint` | `http://127.0.0.1:8080` | LocalAI server endpoint. The `/v1` path is added automatically when omitted. | `$LOCALAI_CHAT_ENDPOINT` |
-| `--model` | | Model name to use. If omitted, LocalAI uses the only model returned by the server when exactly one is available. | |
-| `--api-key` | | API key to use when the LocalAI server requires authentication. | `$LOCALAI_API_KEY`, `$API_KEY` |
-
-- Inside the chat prompt:
-  - Use `/models` to list installed models.
-  - Use `/model <name>` to switch to a different model and clear the conversation.
-  - Use `/clear` to reset the current conversation.
-
 ## P2P Flags
 
 | Parameter | Default | Description | Environment Variable |
@@ -196,3 +181,4 @@ export LOCALAI_F16=true
 
 - See [Advanced Usage]({{%relref "advanced/advanced-usage" %}}) for configuration examples
 - See [VRAM and Memory Management]({{%relref "advanced/vram-management" %}}) for memory management options
+

pkg/reasoning/reasoning.go

@@ -89,35 +89,6 @@ func ExtractReasoningWithConfig(content, thinkingStartToken string, config Confi
 	return reasoning, cleanedContent
 }
 
-// ExtractReasoningComplete extracts reasoning from a COMPLETE (non-streaming)
-// model response. It behaves like ExtractReasoningWithConfig except that it only
-// honors a prefilled thinking start token when the response actually contains
-// the matching closing tag.
-//
-// Rationale: when a chat template injects the start token into the prompt (so
-// DetectThinkingStartToken returns e.g. "<think>"), the model's output begins
-// inside a reasoning block and carries only the closing tag. The defensive
-// fallback prepends the start token so the extractor can pair it with that
-// close tag. But on a COMPLETE response with no closing tag, the model answered
-// directly with no reasoning at all — prepending the start token would
-// manufacture an unclosed block that swallows the entire answer into reasoning,
-// leaving content empty (breaking short/direct answers such as session names or
-// JSON summaries). Genuine reasoning tags already present in the content still
-// extract, because dropping the synthetic prefill does not affect them.
-//
-// Streaming callers must keep using ExtractReasoningWithConfig: mid-stream an
-// as-yet-unclosed block is legitimate and its tokens should surface as
-// reasoning deltas as they arrive.
-func ExtractReasoningComplete(content, thinkingStartToken string, config Config) (reasoning string, cleanedContent string) {
-	startToken := thinkingStartToken
-	if startToken != "" {
-		if end := ClosingTokenForStart(startToken, &config); end == "" || !strings.Contains(content, end) {
-			startToken = ""
-		}
-	}
-	return ExtractReasoningWithConfig(content, startToken, config)
-}
-
 // PrependThinkingTokenIfNeeded prepends the thinking start token to content if it was
 // detected in the prompt. This allows the standard extraction logic to work correctly
 // for models where the thinking token is already in the prompt.
@@ -160,48 +131,6 @@ func PrependThinkingTokenIfNeeded(content string, startToken string) string {
 	return startToken + content
 }
 
-// defaultReasoningTagPairs are the built-in start/end reasoning tag pairs,
-// matching llama.cpp's chat-parser.cpp. Kept at package scope so that
-// ExtractReasoning and ClosingTokenForStart share a single source of truth.
-var defaultReasoningTagPairs = []TagPair{
-	{Start: "<|START_THINKING|>", End: "<|END_THINKING|>"},            // Command-R models
-	{Start: "<|inner_prefix|>", End: "<|inner_suffix|>"},              // Apertus models
-	{Start: "<seed:think>", End: "</seed:think>"},                     // Seed models
-	{Start: "<think>", End: "</think>"},                               // DeepSeek, Granite, ExaOne models
-	{Start: "<|think|>", End: "<|end|><|begin|>assistant<|content|>"}, // Solar Open models (complex end)
-	{Start: "<|channel>thought", End: "<channel|>"},                   // Gemma 4 models
-	{Start: "<thinking>", End: "</thinking>"},                         // General thinking tag
-	{Start: "[THINK]", End: "[/THINK]"},                               // Magistral models
-}
-
-// ClosingTokenForStart returns the closing reasoning tag that pairs with the
-// given start token, searching custom config TagPairs first then the built-in
-// defaults. Returns "" when startToken is empty or unrecognized.
-//
-// Used by the non-streaming autoparser fallback to decide whether a complete
-// response that began with a prefilled thinking token actually closed its
-// reasoning block: only then is synthesizing the start token (so the standard
-// extractor can pair it with the model's close tag) safe. A complete response
-// with no closing tag is a direct answer, not unclosed reasoning.
-func ClosingTokenForStart(startToken string, config *Config) string {
-	if startToken == "" {
-		return ""
-	}
-	if config != nil {
-		for _, pair := range config.TagPairs {
-			if pair.Start == startToken {
-				return pair.End
-			}
-		}
-	}
-	for _, pair := range defaultReasoningTagPairs {
-		if pair.Start == startToken {
-			return pair.End
-		}
-	}
-	return ""
-}
-
 // ExtractReasoning extracts reasoning content from thinking tags and returns
 // both the extracted reasoning and the cleaned content (with tags removed).
 // It handles <thinking>...</thinking> and <think>...</think> tags.
@@ -216,7 +145,22 @@ func ExtractReasoning(content string, config *Config) (reasoning string, cleaned
 	var cleanedParts []string
 	remaining := content
 
-	// Merge custom tag pairs (highest priority) with the built-in defaults.
+	// Define default tag pairs to look for (matching llama.cpp's chat-parser.cpp)
+	defaultTagPairs := []struct {
+		start string
+		end   string
+	}{
+		{"<|START_THINKING|>", "<|END_THINKING|>"},            // Command-R models
+		{"<|inner_prefix|>", "<|inner_suffix|>"},              // Apertus models
+		{"<seed:think>", "</seed:think>"},                     // Seed models
+		{"<think>", "</think>"},                               // DeepSeek, Granite, ExaOne models
+		{"<|think|>", "<|end|><|begin|>assistant<|content|>"}, // Solar Open models (complex end)
+		{"<|channel>thought", "<channel|>"},                    // Gemma 4 models
+		{"<thinking>", "</thinking>"},                         // General thinking tag
+		{"[THINK]", "[/THINK]"},                               // Magistral models
+	}
+
+	// Merge custom tag pairs with default tag pairs (custom pairs first for priority)
 	var tagPairs []struct {
 		start string
 		end   string
@@ -231,11 +175,9 @@ func ExtractReasoning(content string, config *Config) (reasoning string, cleaned
 			}
 		}
 	}
-	for _, pair := range defaultReasoningTagPairs {
-		tagPairs = append(tagPairs, struct {
-			start string
-			end   string
-		}{pair.Start, pair.End})
+	// Add default tag pairs
+	for _, pair := range defaultTagPairs {
+		tagPairs = append(tagPairs, pair)
 	}
 
 	// Track the last position we've processed

pkg/reasoning/reasoning_test.go

@@ -1175,55 +1175,6 @@ var _ = Describe("Custom Tokens and Tag Pairs Integration", func() {
 	})
 })
 
-var _ = Describe("ClosingTokenForStart", func() {
-	It("returns the default closing tag for a known start token", func() {
-		Expect(ClosingTokenForStart("<think>", nil)).To(Equal("</think>"))
-		Expect(ClosingTokenForStart("<thinking>", nil)).To(Equal("</thinking>"))
-		Expect(ClosingTokenForStart("[THINK]", nil)).To(Equal("[/THINK]"))
-	})
-
-	It("returns empty for an empty or unknown start token", func() {
-		Expect(ClosingTokenForStart("", nil)).To(BeEmpty())
-		Expect(ClosingTokenForStart("<nope>", nil)).To(BeEmpty())
-	})
-
-	It("prefers custom config tag pairs over the defaults", func() {
-		cfg := &Config{TagPairs: []TagPair{{Start: "<think>", End: "<<END>>"}}}
-		Expect(ClosingTokenForStart("<think>", cfg)).To(Equal("<<END>>"))
-	})
-})
-
-var _ = Describe("ExtractReasoningComplete", func() {
-	const startToken = "<think>"
-
-	It("keeps a tag-less answer as content when a start token is prefilled but no close tag is present", func() {
-		// The bug guard: prompt-prefilled <think>, model answered directly with
-		// no reasoning. The synthetic prefill must not swallow it as reasoning.
-		reasoning, content := ExtractReasoningComplete("hello", startToken, Config{})
-		Expect(reasoning).To(BeEmpty())
-		Expect(content).To(Equal("hello"))
-	})
-
-	It("extracts reasoning when the model emits only the closing tag (legitimate prefill)", func() {
-		reasoning, content := ExtractReasoningComplete("the rationale\n</think>\n\nthe answer", startToken, Config{})
-		Expect(reasoning).To(ContainSubstring("the rationale"))
-		Expect(content).To(ContainSubstring("the answer"))
-		Expect(content).ToNot(ContainSubstring("</think>"))
-	})
-
-	It("extracts a fully-tagged block regardless of the prefill token", func() {
-		reasoning, content := ExtractReasoningComplete("<think>r</think>answer", startToken, Config{})
-		Expect(reasoning).To(Equal("r"))
-		Expect(content).To(Equal("answer"))
-	})
-
-	It("behaves like ExtractReasoningWithConfig when no start token is prefilled", func() {
-		reasoning, content := ExtractReasoningComplete("<think>r</think>answer", "", Config{})
-		Expect(reasoning).To(Equal("r"))
-		Expect(content).To(Equal("answer"))
-	})
-})
-
 // Helper function to create bool pointers for test configs
 func boolPtr(b bool) *bool {
 	return &b