ggml: update SCHED_DEBUG output to use ggml_op_desc()

* CUDA: batch out_prod inner loop with cublasSgemmStridedBatched

* CUDA: batch out_prod inner loop with cublasSgemmStridedBatched

* CUDA: add cublasSgemmStridedBatched mapping for HIP and MUSA backends

convert_hf_to_gguf.py

@@ -13684,6 +13684,27 @@ class DotsOCRVisionModel(MmprojModel):
         yield from super().modify_tensors(data_torch, name, bid)
 
 
+@ModelBase.register("Sarashina2VisionForCausalLM")
+class Sarashina2VLTextModel(LlamaModel):
+    model_arch = gguf.MODEL_ARCH.LLAMA
+
+    @classmethod
+    def filter_tensors(cls, item: tuple[str, Callable[[], Tensor]]) -> tuple[str, Callable[[], Tensor]] | None:
+        name, gen = item
+        if name.startswith("llm."):
+            name = name.replace("llm.", "", 1)
+        elif name.startswith("norm."):
+            return None
+        return super().filter_tensors((name, gen))
+
+
+@ModelBase.register("Sarashina2VisionForCausalLM")
+class Sarashina2VLVisionModel(Qwen2VLVisionModel):
+    def __init__(self, *args, **kwargs):
+        super().__init__(*args, **kwargs)
+        self.global_config['model_type'] = "qwen2_vl"
+
+
 ###### CONVERSION LOGIC ######
 
 
@@ -13940,7 +13961,7 @@ def get_model_architecture(hparams: dict[str, Any], model_type: ModelType) -> st
     # Step3-VL keeps text config under text_config but uses a custom top-level architecture.
     # For text conversion we route to a dedicated text-only class.
     # TODO: refactor this later to avoid adding exception here
-    if model_type == ModelType.TEXT and arch == "StepVLForConditionalGeneration":
+    if model_type == ModelType.TEXT and arch in ("StepVLForConditionalGeneration", "Sarashina2VisionForCausalLM"):
         return arch
 
     # if "architectures" is found in the sub-config, use that instead

ggml/src/ggml-backend.cpp

@@ -965,7 +965,7 @@ static void ggml_backend_sched_print_assignments(ggml_backend_sched_t sched, str
         }
         if (sched->debug > 1) {
             ggml_backend_t tensor_backend = ggml_backend_sched_get_tensor_backend(sched, node);
-            GGML_LOG_DEBUG("node #%3d (%10.10s): %20.20s (%5.5s) [%5.5s %8.8s] use=%d,c=%d:", i, ggml_op_name(node->op), node->name,
+            GGML_LOG_DEBUG("node #%3d (%10.10s): %20.20s (%5.5s) [%5.5s %8.8s] use=%d,c=%d:", i, ggml_op_desc(node), node->name,
                 fmt_size(ggml_nbytes(node)), tensor_backend ? ggml_backend_name(tensor_backend) : "NULL", GET_CAUSE(node),
                 graph->use_counts[ggml_hash_find(&graph->visited_hash_set, node)], node->flags & GGML_TENSOR_FLAG_COMPUTE ? 1 : 0);
             for (int j = 0; j < GGML_MAX_SRC; j++) {

ggml/src/ggml-cuda/out-prod.cu

@@ -54,15 +54,31 @@ void ggml_cuda_out_prod(ggml_backend_cuda_context & ctx, ggml_tensor * dst) {
     const int64_t dps2 = ne2 / ne02;
     const int64_t dps3 = ne3 / ne03;
 
-    // TODO batched matrix multiplication
-    for (int64_t i3 = 0; i3 < ne3; ++i3) {
-        for (int64_t i2 = 0; i2 < ne2; ++i2) {
+    if (dps2 == 1 && ne2 > 1) {
+        // src0 has uniform stride s02 along dim 2; batch the inner loop with a strided GEMM
+        GGML_ASSERT(ne2 <= std::numeric_limits<int>::max());
+        const int batch_count = (int) ne2;
+        for (int64_t i3 = 0; i3 < ne3; ++i3) {
             CUBLAS_CHECK(
-                cublasSgemm(handle, CUBLAS_OP_N, src1_cublas_op,
+                cublasSgemmStridedBatched(handle, CUBLAS_OP_N, src1_cublas_op,
                         ne0, ne1, ne01,
-                        &alpha, src0_d + (i3/dps3)*s03 + (i2/dps2)*s02, lda,
-                                src1_d +  i3      *s13 +  i2      *s12, ldb,
-                        &beta,  dst_d  +  i3      *s3  +  i2      *s2,  ldc));
+                        &alpha, src0_d + (i3/dps3)*s03, lda, s02,
+                                src1_d +  i3     *s13, ldb, s12,
+                        &beta,  dst_d  +  i3     *s3,  ldc, s2,
+                        batch_count));
+        }
+    } else {
+        // Fallback: ne2 == 1 (no batching benefit) or dps2 > 1 (src0 broadcast along dim 2
+        // with non-uniform stride; would need cublasSgemmBatched with pointer arrays).
+        for (int64_t i3 = 0; i3 < ne3; ++i3) {
+            for (int64_t i2 = 0; i2 < ne2; ++i2) {
+                CUBLAS_CHECK(
+                    cublasSgemm(handle, CUBLAS_OP_N, src1_cublas_op,
+                            ne0, ne1, ne01,
+                            &alpha, src0_d + (i3/dps3)*s03 + (i2/dps2)*s02, lda,
+                                    src1_d +  i3      *s13 +  i2      *s12, ldb,
+                            &beta,  dst_d  +  i3      *s3  +  i2      *s2,  ldc));
+            }
         }
     }
 }

ggml/src/ggml-cuda/vendors/hip.h

@@ -48,6 +48,7 @@
 #define cublasSetMathMode(handle, mode) CUBLAS_STATUS_SUCCESS
 #define cublasSetStream hipblasSetStream
 #define cublasSgemm hipblasSgemm
+#define cublasSgemmStridedBatched hipblasSgemmStridedBatched
 #define cublasStatus_t hipblasStatus_t
 #define cublasOperation_t hipblasOperation_t
 #define cudaDevAttrCooperativeLaunch hipDeviceAttributeCooperativeLaunch

ggml/src/ggml-cuda/vendors/musa.h

@@ -32,6 +32,7 @@
 #define cublasSetMathMode mublasSetMathMode
 #define cublasSetStream mublasSetStream
 #define cublasSgemm mublasSgemm
+#define cublasSgemmStridedBatched mublasSgemmStridedBatched
 #define cublasStatus_t mublasStatus_t
 #define cublasOperation_t mublasOperation_t
 #define cublasGetStatusString mublasGetStatusString

ggml/src/ggml-metal/ggml-metal.cpp

@@ -87,17 +87,17 @@ static void ggml_backend_metal_buffer_shared_clear(ggml_backend_buffer_t buffer,
 }
 
 static ggml_backend_buffer_i ggml_backend_metal_buffer_shared_i = {
-    /* .free_buffer     = */ ggml_backend_metal_buffer_shared_free_buffer,
-    /* .get_base        = */ ggml_backend_metal_buffer_shared_get_base,
-    /* .init_tensor     = */ NULL,
-    /* .memset_tensor   = */ ggml_backend_metal_buffer_shared_memset_tensor,
-    /* .set_tensor      = */ ggml_backend_metal_buffer_shared_set_tensor,
-    /* .get_tensor      = */ ggml_backend_metal_buffer_shared_get_tensor,
-    /* .set_tensor_2d   = */ NULL,
-    /* .get_tensor_2d   = */ NULL,
-    /* .cpy_tensor      = */ ggml_backend_metal_buffer_shared_cpy_tensor,
-    /* .clear           = */ ggml_backend_metal_buffer_shared_clear,
-    /* .reset           = */ NULL,
+    /* .free_buffer   = */ ggml_backend_metal_buffer_shared_free_buffer,
+    /* .get_base      = */ ggml_backend_metal_buffer_shared_get_base,
+    /* .init_tensor   = */ NULL,
+    /* .memset_tensor = */ ggml_backend_metal_buffer_shared_memset_tensor,
+    /* .set_tensor    = */ ggml_backend_metal_buffer_shared_set_tensor,
+    /* .get_tensor    = */ ggml_backend_metal_buffer_shared_get_tensor,
+    /* .set_tensor_2d = */ NULL,
+    /* .get_tensor_2d = */ NULL,
+    /* .cpy_tensor    = */ ggml_backend_metal_buffer_shared_cpy_tensor,
+    /* .clear         = */ ggml_backend_metal_buffer_shared_clear,
+    /* .reset         = */ NULL,
 };
 
 // private buffer
@@ -163,17 +163,17 @@ static void ggml_backend_metal_buffer_private_clear(ggml_backend_buffer_t buffer
 }
 
 static ggml_backend_buffer_i ggml_backend_metal_buffer_private_i = {
-    /* .free_buffer             = */ ggml_backend_metal_buffer_private_free_buffer,
-    /* .get_base                = */ ggml_backend_metal_buffer_private_get_base,
-    /* .init_tensor             = */ NULL,
-    /* .memset_tensor           = */ ggml_backend_metal_buffer_private_memset_tensor,
-    /* .set_tensor              = */ ggml_backend_metal_buffer_private_set_tensor,
-    /* .get_tensor              = */ ggml_backend_metal_buffer_private_get_tensor,
-    /* .set_tensor_2d           = */ NULL,
-    /* .get_tensor_2d           = */ NULL,
-    /* .cpy_tensor              = */ ggml_backend_metal_buffer_private_cpy_tensor,
-    /* .clear                   = */ ggml_backend_metal_buffer_private_clear,
-    /* .reset                   = */ NULL,
+    /* .free_buffer   = */ ggml_backend_metal_buffer_private_free_buffer,
+    /* .get_base      = */ ggml_backend_metal_buffer_private_get_base,
+    /* .init_tensor   = */ NULL,
+    /* .memset_tensor = */ ggml_backend_metal_buffer_private_memset_tensor,
+    /* .set_tensor    = */ ggml_backend_metal_buffer_private_set_tensor,
+    /* .get_tensor    = */ ggml_backend_metal_buffer_private_get_tensor,
+    /* .set_tensor_2d = */ NULL,
+    /* .get_tensor_2d = */ NULL,
+    /* .cpy_tensor    = */ ggml_backend_metal_buffer_private_cpy_tensor,
+    /* .clear         = */ ggml_backend_metal_buffer_private_clear,
+    /* .reset         = */ NULL,
 };
 
 static bool ggml_backend_buffer_is_metal(ggml_backend_buffer_t buffer) {

ggml/src/ggml-opencl/ggml-opencl.cpp

@@ -28,6 +28,7 @@
 #include <memory>
 #include <charconv>
 #include <mutex>
+#include <regex>
 
 #undef MIN
 #undef MAX
@@ -396,6 +397,8 @@ struct ggml_backend_opencl_context {
     bool has_vector_subgroup_broadcast;
     bool disable_fusion;
 
+    std::regex *opfilter = nullptr; // regex of ops to not claim
+
     bool adreno_has_large_buffer;
     bool adreno_use_large_buffer;
     ggml_cl_compiler_version adreno_cl_compiler_version;
@@ -3494,6 +3497,12 @@ static ggml_backend_opencl_context * ggml_cl2_init(ggml_backend_dev_t dev) {
 
     backend_ctx->disable_fusion = getenv("GGML_OPENCL_DISABLE_FUSION") != nullptr;
 
+    const char * str_opfilter = getenv("GGML_OPENCL_OPFILTER");
+    if (str_opfilter) {
+        backend_ctx->opfilter = new std::regex(str_opfilter, std::regex_constants::icase);
+        GGML_LOG_INFO("ggml_opencl: opfilter regex = \"%s\"\n", str_opfilter);
+    }
+
     dev_ctx->backend_ctx = backend_ctx.release();
     return dev_ctx->backend_ctx;
 }
@@ -4143,6 +4152,11 @@ static bool ggml_opencl_supports_op(ggml_backend_dev_t dev, const struct ggml_te
     ggml_backend_opencl_device_context * dev_ctx     = (ggml_backend_opencl_device_context *)dev->context;
     ggml_backend_opencl_context *        backend_ctx = dev_ctx->backend_ctx;
 
+    // reject ops that match the opfilter regex
+    if (backend_ctx->opfilter && std::regex_match(std::string(ggml_op_desc(op)), *backend_ctx->opfilter)) {
+        return false;
+    }
+
     switch (op->op) {
         case GGML_OP_NONE:
             return true;

src/llama-context.cpp

@@ -2451,7 +2451,30 @@ public:
         for (auto & [buft, mbuf] : mbufs_new) {
             auto & mbuf_cur = mbufs[buft];
 
-            if (!mbuf_cur.buf || mbuf_cur.org.size() != mbuf.org.size() || mbuf_cur.total_size != mbuf.total_size) {
+            bool need_alloc = false;
+
+            need_alloc = need_alloc || (!mbuf_cur.buf);
+            need_alloc = need_alloc || (mbuf_cur.org.size() != mbuf.org.size());
+            need_alloc = need_alloc || (mbuf_cur.total_size != mbuf.total_size);
+
+            if (!need_alloc) {
+                for (size_t i = 0; i < mbuf_cur.org.size(); ++i) {
+                    auto * org0 = mbuf_cur.org[i];
+                    auto * org1 = mbuf.org[i];
+
+                    if (!ggml_are_same_shape(org0, org1)) {
+                        need_alloc = true;
+                        break;
+                    }
+
+                    if (org0->view_src != org1->view_src || org0->view_offs != org1->view_offs) {
+                        need_alloc = true;
+                        break;
+                    }
+                }
+            }
+
+            if (need_alloc) {
                 mbuf_cur = std::move(mbuf);
 
                 mbuf_cur.buf.reset(ggml_backend_alloc_ctx_tensors_from_buft(mbuf_cur.ctx.get(), buft));
@@ -2515,6 +2538,31 @@ public:
             mbufs_new[buft].total_size += rinfo.size;
         }
 
+        for (auto & [buft, mbuf] : mbufs_new) {
+            ggml_init_params params = {
+                /*.mem_size   =*/ mbuf.n_tensors*ggml_tensor_overhead(),
+                /*.mem_buffer =*/ NULL,
+                /*.no_alloc   =*/ true,
+            };
+
+            mbuf.ctx.reset(ggml_init(params));
+
+            mbuf.org.reserve(mbuf.n_tensors);
+        }
+
+        for (const auto & rinfo : rinfos) {
+            auto * buft = ggml_backend_buffer_get_type(rinfo.tensor->buffer);
+
+            const int64_t n = rinfo.size/ggml_element_size(rinfo.tensor);
+
+            auto & mbuf = mbufs_new[buft];
+
+            mbuf.org.push_back(ggml_view_1d(mbuf.ctx.get(), rinfo.tensor, n, rinfo.offset));
+
+            auto & view = mbuf.org.back();
+            view->buffer = rinfo.tensor->buffer;
+        }
+
         for (auto & [buft, mbuf] : mbufs_new) {
             const auto & mbuf_cur = mbufs.at(buft);
 
@@ -2523,9 +2571,11 @@ public:
             }
 
             for (size_t i = 0; i < mbuf_cur.org.size(); ++i) {
-                ggml_backend_tensor_copy(mbuf_cur.cpy[i], mbuf_cur.org[i]);
+                ggml_backend_tensor_copy(mbuf_cur.cpy[i], mbuf.org[i]);
             }
         }
+
+        GGML_ASSERT(buf_size == 0);
     }
 
     void read(void * dst, size_t size) override {

src/llama-memory-recurrent.cpp

@@ -726,6 +726,10 @@ void llama_memory_recurrent::state_write(llama_io_write_i & io, llama_seq_id seq
         cell_ranges.emplace_back(cell_range_begin, size);
     }
 
+    if (flags % LLAMA_STATE_SEQ_FLAGS_ON_DEVICE && cell_ranges.size() > 1) {
+        GGML_ABORT("cannot save/load multiple ranges of cells to/from device memory\n");
+    }
+
     // DEBUG CHECK: Sum of cell counts in ranges should equal the total cell count
     uint32_t cell_count_check = 0;
     for (const auto & range : cell_ranges) {

tests/test-backend-ops.cpp

@@ -8385,6 +8385,12 @@ static std::vector<std::unique_ptr<test_case>> make_test_cases_eval() {
         }
     }
 
+    // ne2 sweep to cover the cublasSgemmStridedBatched path (dps2 == 1, ne2 > 1)
+    for (int64_t ne2 : {1, 8, 16, 32}) {
+        test_cases.emplace_back(new test_out_prod(GGML_TYPE_F32, GGML_TYPE_F32,
+                                                  256, 16, 16, {ne2, 1}, {1, 1}));
+    }
+
     // add_id
     for (ggml_type type_a : {GGML_TYPE_F32}) {
         for (ggml_type type_b : {GGML_TYPE_F32}) {

tools/server/webui/src/lib/components/app/navigation/SidebarNavigation/SidebarNavigationConversationItem.svelte

@@ -13,6 +13,7 @@
 	import { FORK_TREE_DEPTH_PADDING } from '$lib/constants';
 	import { getAllLoadingChats } from '$lib/stores/chat.svelte';
 	import { conversationsStore } from '$lib/stores/conversations.svelte';
+	import { TruncatedText } from '$lib/components/app';
 	import { onMount } from 'svelte';
 
 	interface Props {
@@ -148,9 +149,7 @@
 			</Tooltip.Root>
 		{/if}
 
-		<span class="truncate text-sm font-medium">
-			{conversation.name}
-		</span>
+		<TruncatedText text={conversation.name} class="text-sm font-medium" showTooltip={false} />
 	</div>
 
 	{#if renderActionsDropdown}

tools/server/webui/src/lib/components/app/settings/SettingsChat/SettingsChatFields.svelte

@@ -104,13 +104,15 @@
 				</p>
 			{/if}
 		{:else if field.type === SettingsFieldType.TEXTAREA}
-			<Label for={field.key} class="block flex items-center gap-1.5 text-sm font-medium">
-				{field.label}
+			{#if field.label}
+				<Label for={field.key} class="block flex items-center gap-1.5 text-sm font-medium">
+					{field.label}
 
-				{#if field.isExperimental}
-					<FlaskConical class="h-3.5 w-3.5 text-muted-foreground" />
-				{/if}
-			</Label>
+					{#if field.isExperimental}
+						<FlaskConical class="h-3.5 w-3.5 text-muted-foreground" />
+					{/if}
+				</Label>
+			{/if}
 
 			<Textarea
 				id={field.key}

tools/server/webui/src/lib/constants/index.ts

@@ -35,6 +35,7 @@ export * from './settings-keys';
 export * from './settings-sections';
 export * from './supported-file-types';
 export * from './table-html-restorer';
+export * from './title-generation';
 export * from './tools';
 export * from './tooltip-config';
 export * from './ui';

tools/server/webui/src/lib/constants/settings-config.ts

@@ -1,5 +1,6 @@
 import { ColorMode } from '$lib/enums/ui';
 import { Monitor, Moon, Sun } from '@lucide/svelte';
+import { TITLE } from './title-generation';
 
 export const SETTING_CONFIG_DEFAULT: Record<string, string | number | boolean | undefined> = {
 	// Note: in order not to introduce breaking changes, please keep the same data type (number, string, etc) if you want to change the default value.
@@ -16,6 +17,8 @@ export const SETTING_CONFIG_DEFAULT: Record<string, string | number | boolean |
 	showMessageStats: true,
 	askForTitleConfirmation: false,
 	titleGenerationUseFirstLine: false,
+	titleGenerationUseLLM: false,
+	titleGenerationPrompt: TITLE.DEFAULT_PROMPT,
 	pasteLongTextToFileLen: 2500,
 	copyTextAttachmentsAsPlainText: false,
 	pdfAsImage: false,
@@ -121,6 +124,10 @@ export const SETTING_CONFIG_INFO: Record<string, string> = {
 		'Ask for confirmation before automatically changing conversation title when editing the first message.',
 	titleGenerationUseFirstLine:
 		'Use only the first non-empty line of the prompt to generate the conversation title.',
+	titleGenerationUseLLM:
+		'Use the LLM to automatically generate conversation titles based on the first message exchange.',
+	titleGenerationPrompt:
+		'Optional template for the title generation prompt. Use {{USER}} for the user message and {{ASSISTANT}} for the assistant message.',
 	pdfAsImage:
 		'Parse PDF as image instead of text. Automatically falls back to text processing for non-vision models.',
 	disableAutoScroll:

tools/server/webui/src/lib/constants/settings-keys.ts

@@ -16,6 +16,8 @@ export const SETTINGS_KEYS = {
 	PDF_AS_IMAGE: 'pdfAsImage',
 	ASK_FOR_TITLE_CONFIRMATION: 'askForTitleConfirmation',
 	TITLE_GENERATION_USE_FIRST_LINE: 'titleGenerationUseFirstLine',
+	TITLE_GENERATION_USE_LLM: 'titleGenerationUseLLM',
+	TITLE_GENERATION_PROMPT: 'titleGenerationPrompt',
 	// Display
 	SHOW_MESSAGE_STATS: 'showMessageStats',
 	SHOW_THOUGHT_IN_PROGRESS: 'showThoughtInProgress',

tools/server/webui/src/lib/constants/settings-sections.ts

@@ -95,6 +95,17 @@ export const SETTINGS_CHAT_SECTIONS: SettingsSection[] = [
 				key: SETTINGS_KEYS.TITLE_GENERATION_USE_FIRST_LINE,
 				label: 'Use first non-empty line for conversation title',
 				type: SettingsFieldType.CHECKBOX
+			},
+			{
+				key: SETTINGS_KEYS.TITLE_GENERATION_USE_LLM,
+				label: 'Use LLM to generate conversation title',
+				type: SettingsFieldType.CHECKBOX,
+				isExperimental: true
+			},
+			{
+				key: SETTINGS_KEYS.TITLE_GENERATION_PROMPT,
+				type: SettingsFieldType.TEXTAREA,
+				isExperimental: true
 			}
 		]
 	},

tools/server/webui/src/lib/constants/title-generation.ts

@@ -0,0 +1,9 @@
+/* Title generation constants */
+export const TITLE = {
+	MIN_LENGTH: 3,
+	FALLBACK: 'New Chat',
+	DEFAULT_PROMPT:
+		'Based on the following interaction, generate a short, concise title (maximum 6-8 words) that captures the main topic. Return ONLY the title text, nothing else. Do not use quotes.\n\nUser: {{USER}}\n\nAssistant: {{ASSISTANT}}\n\nTitle:',
+	PREFIX_PATTERN: /^(Title:|Subject:|Topic:)\s*/i,
+	QUOTE_PATTERN: /^["]|["]$/g
+} as const;

tools/server/webui/src/lib/services/chat.service.ts

@@ -14,11 +14,59 @@ import {
 	ReasoningFormat,
 	UrlProtocol
 } from '$lib/enums';
-import type { ApiChatMessageContentPart, ApiChatCompletionToolCall } from '$lib/types/api';
+import type {
+	ApiChatMessageContentPart,
+	ApiChatMessageData,
+	ApiChatCompletionToolCall
+} from '$lib/types/api';
 import type { DatabaseMessageExtraMcpPrompt, DatabaseMessageExtraMcpResource } from '$lib/types';
 import { modelsStore } from '$lib/stores/models.svelte';
 
 export class ChatService {
+	/**
+	 *
+	 *
+	 * Title Generation
+	 *
+	 *
+	 */
+
+	/**
+	 * Sends a streaming chat completion request for generating a chat title.
+	 * Delegates to `sendMessage` for fetch, SSE parsing, and error handling.
+	 *
+	 * @param message - The single message to send (a user message containing the title generation prompt)
+	 * @param model - Optional model name to use (required in ROUTER mode)
+	 * @param signal - Optional AbortSignal to cancel the request
+	 * @returns {Promise<string>} The aggregated title text, or empty string if request failed
+	 * @static
+	 */
+	static async generateTitle(
+		message: ApiChatMessageData,
+		model?: string | null,
+		signal?: AbortSignal
+	): Promise<string> {
+		let titleResponse = '';
+		try {
+			await ChatService.sendMessage(
+				[message],
+				{
+					model: model || undefined,
+					stream: true,
+					custom: { chat_template_kwargs: { enable_thinking: false } },
+					onChunk: (chunk: string) => {
+						titleResponse += chunk;
+					}
+				},
+				undefined,
+				signal
+			);
+		} catch {
+			return '';
+		}
+		return titleResponse;
+	}
+
 	/**
 	 *
 	 *
@@ -122,7 +170,11 @@ export class ChatService {
 						return true;
 					});
 					// If only text remains and it's a single part, simplify to string
-					if (msg.content.length === 1 && msg.content[0].type === ContentPartType.TEXT) {
+					if (
+						msg.content.length === 1 &&
+						msg.content[0].type === ContentPartType.TEXT &&
+						typeof msg.content[0].text === 'string'
+					) {
 						msg.content = msg.content[0].text;
 					}
 				}

tools/server/webui/src/lib/stores/chat.svelte.ts

@@ -36,7 +36,8 @@ import {
 import {
 	MAX_INACTIVE_CONVERSATION_STATES,
 	INACTIVE_CONVERSATION_STATE_MAX_AGE_MS,
-	SYSTEM_MESSAGE_PLACEHOLDER
+	SYSTEM_MESSAGE_PLACEHOLDER,
+	TITLE
 } from '$lib/constants';
 import type {
 	ChatMessageTimings,
@@ -44,7 +45,12 @@ import type {
 	ChatStreamCallbacks,
 	ErrorDialogState
 } from '$lib/types/chat';
-import type { ApiProcessingState, DatabaseMessage, DatabaseMessageExtra } from '$lib/types';
+import type {
+	ApiChatMessageData,
+	ApiProcessingState,
+	DatabaseMessage,
+	DatabaseMessageExtra
+} from '$lib/types';
 import { ErrorDialogType, MessageRole, MessageType } from '$lib/enums';
 
 interface ConversationStateEntry {
@@ -572,7 +578,11 @@ class ChatStore {
 			conversationsStore.addMessageToActive(assistantMessage);
 			await this.streamChatCompletion(
 				conversationsStore.activeMessages.slice(0, -1),
-				assistantMessage
+				assistantMessage,
+				undefined,
+				undefined,
+				undefined,
+				config().titleGenerationUseLLM && isNewConversation ? content : undefined
 			);
 		} catch (error) {
 			if (isAbortError(error)) {
@@ -601,7 +611,8 @@ class ChatStore {
 		assistantMessage: DatabaseMessage,
 		onComplete?: (content: string) => Promise<void>,
 		onError?: (error: Error) => void,
-		modelOverride?: string | null
+		modelOverride?: string | null,
+		firstUserMessageContent?: string
 	): Promise<void> {
 		let effectiveModel = modelOverride;
 
@@ -894,6 +905,12 @@ class ChatStore {
 					if (onComplete) await onComplete(content);
 					if (isRouterMode()) modelsStore.fetchRouterModels().catch(console.error);
 
+					// Generate LLM based title for new conversations (avoids stale reference
+					// issue when user switches conversations while streaming)
+					if (firstUserMessageContent) {
+						await this.generateTitleWithLLM(firstUserMessageContent, streamedContent, convId);
+					}
+
 					// Check if there's a pending message queued during streaming
 					const pending = this.consumePendingMessage(convId);
 					if (pending) {
@@ -921,6 +938,49 @@ class ChatStore {
 		this.setProcessingState(convId, null);
 		this.clearPendingMessage(convId);
 	}
+
+	private async generateTitleWithLLM(
+		userContent: string,
+		assistantContent: string,
+		convId: string
+	): Promise<void> {
+		const effectiveModel = isRouterMode() && selectedModelName() ? selectedModelName() : undefined;
+		const configValue = config();
+		const titlePromptTemplate =
+			typeof configValue.titleGenerationPrompt === 'string' &&
+			configValue.titleGenerationPrompt.trim()
+				? configValue.titleGenerationPrompt
+				: TITLE.DEFAULT_PROMPT;
+
+		const titlePrompt = titlePromptTemplate
+			.replace('{{USER}}', String(userContent || ''))
+			.replace('{{ASSISTANT}}', String(assistantContent || ''));
+
+		const titleMessage: ApiChatMessageData = {
+			role: MessageRole.USER,
+			content: titlePrompt
+		};
+
+		const titleResponse = await ChatService.generateTitle(titleMessage, effectiveModel);
+
+		if (!titleResponse) {
+			return;
+		}
+
+		let cleanTitle = titleResponse.trim();
+		cleanTitle = cleanTitle
+			.replace(TITLE.PREFIX_PATTERN, '')
+			.replace(TITLE.QUOTE_PATTERN, '')
+			.trim();
+		if (!cleanTitle || cleanTitle.length < TITLE.MIN_LENGTH) {
+			const firstLine = userContent.split('\n').find((l) => l.trim().length > 0);
+			cleanTitle = firstLine ? firstLine.trim() : TITLE.FALLBACK;
+		}
+		if (cleanTitle && cleanTitle.length >= TITLE.MIN_LENGTH) {
+			await conversationsStore.updateConversationName(convId, cleanTitle);
+		}
+	}
+
 	private async savePartialResponseIfNeeded(convId?: string): Promise<void> {
 		const conversationId = convId || conversationsStore.activeConversation?.id;
 		if (!conversationId) return;