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Author	SHA1	Message	Date
kurquhar	970b51ce7c	opencl: add depthwise conv2d (#30900) ... * opencl: add Adreno depthwise conv2d Assisted-by: OpenCode * opencl: use local program for depthwise conv2d Assisted-by: OpenCode * opencl: use singed type for args --------- Co-authored-by: Li He <lih@qti.qualcomm.com> b11827	2026-10-22 10:54:24 -07:00
tc-mb	a08ab75ae7	mtmd : add MiniCPM-OCR 1.0 support (#30979) ... Signed-off-by: tc-mb <tianchi_cai@icloud.com> b11826	2026-10-22 19:22:15 +02:00
Martin Kleinberger	19ab5a5e65	clef : include <algorithm> for std::find and std::copy (#30981) ... [no ci]	2026-10-22 18:14:47 +02:00
Gaurav Garg	36cbf415f1	Fix !30793 b11824	2026-10-22 19:30:57 +05:30
Georgi Gerganov	5c19a5a756	glm5 : optimize inputs (#30932) ... * glm5 : avoid sel_mask_2d input * cont : avoid new_pool_flat input b11823	2026-10-22 16:59:29 +03:00
Georgi Gerganov	d9ee007a06	model : fix qwen4exp layer inputs for DFlash drafters (#30927) ... qwen4exp published the hc-wide residual [n_embd, hc, n_tokens] as t_layer_inp, but the drafter reads layer inputs as [n_embd, n_tokens] rows: llama_context sizes each embd_layer_inp buffer as n_embd * n_batch and the DFlash encoder input is n_extract * n_embd wide. Evaluating a DFlash draft over a qwen4exp target therefore aborts on the first request in llama_context::extract_layer_inputs. Collapse the streams with a plain mean before exposing them, as deepseek4 already does for its hyper-connection residual, and build the mean only for the layers a drafter actually requested. Assisted-by: pi:llama.cpp/ggml-org/Qwen3.8-Flash-Next-GGUF (MacBook, M5 Max, 128GB) b11822	2026-10-22 16:49:38 +03:00
budiony	d81d0d8fb9	Multi-column on Intel XMX matrix engines refactored (#29864) ... * Multi-column on Intel XMX matrix engines refactored Multi-column (2 to 80 activation columns) mul_mat_vec_q for reordered K-quant and Q8_0 weights on the Intel XMX matrix engines (int8 DPAS, ESIMD), for the SYCL backend. It targets speculative decoding verification (2 to 8 tokens per step) and short prompt batches (9 to 80 tokens). Three types also use it for a single column (Q2_K, Q3_K, Q8_0). * Fixed regression bug real bug found: the first version produced NaN whenever the row count wasn't a multiple of 4 * Removed GGML_TYPE_Q8_0 activation * rewritten xmx_mul_mat 64-byte alignment and 16-byte pitch check on the activations * Implemented fused gate/up kernel One launch computes up * act(gate) for both FFN weights, reading the activations once and applying SWIGLU or GEGLU in the epilogue. It covers up to 16 columns and works for all six XMX types. * Removed the temporary XMX_NOGLU environment switch * Q2_K min-sum optimization Q2_K weight is d·scl·q − dmin·mc, where scl (the 4-bit scale) and mc (the 4-bit min code) apply to each half of a 32-weight group * Added dispatch check and GRF sweep tg128 on Q4_K_M goes from 26.67 to 28.23 tok/s on the B70 (+5.9%). Q6_K is unchanged. MUL_MAT passes 1727/1727 and MUL_MAT_VEC_FUSION 1361/1361. Perplexity at batch 1 is 5.2064 with XMX and 5.2058 without. * Renamed variables * Added 2 environment variables GGML_SYCL_XMX_MAX_COLS (default 80, any value 0 or higher) and GGML_SYCL_XMX_GLU_MAX_COLS (default 16, range 0 to 16): the largest batch for the fused gate/up kernel. It is clamped to 16 because that is the most the fused kernel is compiled for, so the variable can only lower it. * Update esimd.hpp 1. All five quant structs were repeating the same boilerplate, so I moved it into shared pieces. 2. A new helper xmx_term does one DPAS, converts it to float and scales it per row. The four branches are now one or two lines each, and the shared Cb += z * d8r is written once. The refactor passes all three op tests. MUL_MAT_VEC_FUSION is 1369/1369, MUL_MAT is 2281/2281 (the count includes your uncommitted f32 tests) and MUL_MAT_ID is 937/937. b11821	2026-10-22 21:39:01 +08:00
Bill Sideris	d77256999f	vulkan: replace std::aligned_alloc with posix_memalign for termux compatibility (#30828) ... std::aligned_alloc is unavailable on Android bionic below API 28 (Termux targets API 24); use posix_memalign like ggml.c does. b11820	2026-10-22 14:40:13 +02:00
martin-cimmino	0693dbfb91	nemotron : support non-standard GQA, BPE tokenizer and domyn-small pre-type (#23343) ... * nemotron : support non-standard GQA, BPE tokenizer and domyn-small pre-type * gguf-py : write Metaspace prepend_scheme as GGUF metadata * vocab : parse metaspace prepend_scheme into enum, rename key * vocab : use metaspace prepend_scheme in detokenize, add TODOs for other tokenizers * vocab : use constant for metaspace escaped space --------- Co-authored-by: Martin Cimmino <martin.cimmino@domyn.com> b11819	2026-10-22 13:34:47 +02:00
Tim Wang	a5d22276be	server : support typed content input for RERANK endpoint (#29625) ... * server : support typed content input for rerank endpoint Assisted-by: Opencode/Qwen3.8 27B * server : address rerank multimodal review findings - reject multimodal rerank input when the model has no rerank chat template (images were silently dropped) - translate handle_media download/base64 failures to 400 instead of 500 - reject negative top_n with 400 instead of letting resize throw - fix comment typos, redundant comments, indentation and trailing whitespace - README: document that TEI input accepts the same shape as Jina; drop stray blank line Assisted-by: opencode * Trimmed README --------- Co-authored-by: timothywang21 <timothywang21@users.noreply.github.com> b11818	2026-10-22 13:27:24 +02:00
Georgi Gerganov	5f5acfe250	ci : disable slow WebGPU tests (#30963)	2026-10-22 13:56:20 +03:00
Georgi Gerganov	1f4c2eeaa5	ci : be able to reconfigure HTTP port for server pytest workers (#30972)	2026-10-22 13:56:03 +03:00
Michael Taylor	7170cad4d0	sycl: fix CONV_2D wrong results for non-contiguous input (#30363) ... * sycl: fix CONV_2D wrong results for non-contiguous input The kernel indexes the `input` as a contiguous [W, H, C, N] tensor, but supports_op claimed the op for any layout. A non-contiguous (e.g. `CWHN` permuted) input was read with the wrong element offsets, silently producing wrong results. Gate the CONV_2D op on `input` and `kernel` contiguity, matching the CUDA backend contract, and assert input contiguity in the op. `test-backend-ops -b SYCL0 -o CONV_2D`: goes from 16 failures to 0, none. ```text 2006/2006 tests passed Backend SYCL0: OK Backend 2/2: CPU Skipping 2/2 backends passed OK ``` Assisted-by: pi (unsloth/Qwen3.8-27B-GGUF:Q4_K_M via llama.cpp) * sycl : CONV_2D cwhn=1 support Make the SYCL backend compute `GGML_OP_CONV_2D` correctly for `cwhn=1` (CWHN channel-order) inputs and kernels, so the previously failing test- backend-ops CONV_2D cases pass on SYCL instead of being skipped or miscomputed. - Implement CWHN layout support in `ggml/src/ggml-sycl/conv2d.cpp` (`ggml_sycl_op_conv2d`). - Update SYCL `supports_op` for `GGML_OP_CONV_2D` in `ggml/src/ggml-sycl/ggml-sycl.cpp` to accept both layouts. Assisted-by: pi (Greatjedi/Qwen3.8-27B-Intel-Arc-Tuned-GGUF via llama.cpp) * sycl docs : update ops for SYCL b11815	2026-10-22 16:19:58 +08:00
tkran2	d88040c704	vocab : add clean_spaces GGUF key (#30940) b11814	2026-10-22 09:58:08 +02:00
tkran2	e197cef455	vocab : use Tekken pre-tokenizer for pixtral rather than the Llama 3 one (#30960) b11813	2026-10-22 09:06:47 +02:00
Gabe Goodhart	bf039c8496	models : Record layer inputs for all granite models (#30957) ... Branch: GraniteSpeculatorSupport AI-usage: full (Claude + Sonnet 5.5) Signed-off-by: Gabe Goodhart <ghart@us.ibm.com> b11812	2026-10-22 10:02:41 +03:00
Charles Xu	dfeea52005	kleidiai : add Q8_0 SVE dotprod GEMV and SVE i8mm GEMM kernels (#30808) b11811	2026-10-22 09:56:21 +03:00
Titaniumtown	e3797b184d	sycl: merge the fp16 and fp32 dequant switches (#30740) b11810	2026-10-22 08:30:21 +03:00
Chanho Lee	0b1281aeef	webgpu : add Q2_0 support (#30914) ... * webgpu : add Q2_0 row dequantization * webgpu : add Q2_0 matrix multiplication b11809	2026-10-22 08:30:04 +03:00
Hrishith Thadicherla	4912ac24f1	dflash : load optional FC input scale (#30945) ... Assisted-by: Codex b11808	2026-10-22 08:24:12 +03:00
Aleksander Grygier	84746c5c94	ui: Add "Show tool call in progress" setting (#30681) ... * feat(ui): add Show tool call in progress display setting Add the showToolCallInProgress key and its checkbox to Settings > Display, right next to its "always show" counterpart. Upstream dropped a setting of this exact name in 43b5e63589, folding it into alwaysShowToolCallContent because the old name promised expansion that outlives the call; this brings back the narrower, in-progress-only meaning. The entry is registry-driven, so SETTING_CONFIG_DEFAULT, the dialog field and the ui_settings admin baseline pick it up without extra wiring. It ships enabled, mirroring Show thought in progress, and the always-show help text is reworded so the two toggles read as a pair rather than contradicting each other. Assisted by: llama-ui (ggml-org/Qwen3.8-Flash-Next:Q8_0) * feat(ui): expand tool call blocks while they are in progress Drive the default expansion of TOOL_CALL_STREAMING and TOOL_CALL_PENDING from showToolCallInProgress and leave TOOL_CALL, the terminal state, to alwaysShowToolCallContent. A finished call now folds back on its own once its result lands, which is exactly how the reasoning block behaves when the thought completes. Manual toggling keeps precedence over both defaults in either direction: isExpanded() only consults the settings while expandedStates holds no entry for the section. Client tests pin the truth table for the two toggles, including the automatic fold-back and both manual overrides. Assisted by: llama-ui (ggml-org/Qwen3.8-Flash-Next:Q8_0) * fix(ui): keep running tool calls expanded A call the agentic loop reports as running now outranks its section type. exec_shell_command persists an empty result before reading any output, so a live call is already TOOL_CALL and folded back, which hid the streaming output the setting is meant to show. Move the expansion default to isSectionExpandedByDefault so the running-id rule is covered by a truth table, and test the pending -> finished transition instead of only the finished state: a block that only ever got mounted finished cannot prove it folds back on its own. Assisted by: llama-ui (ggml-org/Qwen3.8-Flash-Next:Q8_0) * feat(ui): stream the exec command from the first character The exec parser read its args strictly, so while the model was still typing the call the block title stayed empty and the body claimed "Running...". Parse the args partially (the read_file / edit_file / write_file pattern), keep a terminal cursor while the args JSON is incomplete, and stand the conversation cwd in for the x-tool-cwd that only arrives with the result message, so the prompt is there from the first character. The body stays empty while the args stream, shows "Executing command..." once the call is executing, and the wrapper drops its padding for empty phases so the title sits flush with the frame. Assisted by: Delta (zai-org/GLM-5.3) * fix(ui): stream file tool bodies even before a path arrives write_file and edit_file refused to render until their args carried a path, so a call that streams its body first (or a same-named tool with other arg names) showed an empty block. Meta now carries optional fileName/filePath, path alias reading moves to shared helpers, and the blocks fall back to the raw args JSON when no known content key is present. Assisted by: Delta (zai-org/GLM-5.3) * fix(ui): keep an empty write_file body instead of the raw args A call carrying {"content":""} fell through to the raw-args fallback, so a finished write of an empty file showed the args JSON. The parser now leaves content undefined when the key is missing and the block tests !== undefined, so an empty write renders as an empty code block with its byte count. Assisted by: DeepSeek-V4.1-Flash (deepseek-ai)	2026-10-22 08:14:47 +03:00
Hoang Vien Duy	0682a576a7	lora : support prism.hadamard folded weights (#30910) ... * lora : support prism.hadamard folded weights * tests : remove LoRA test from test-llama-archs b11806	2026-10-22 08:12:17 +03:00
Aleksander Grygier	a6b83d426f	ui : key draft sidecar badges by model instead of repo (#30919) ... Two quants of one repo pulled each other's draft: the badge read every --model-draft arg of the repo, so each row showed both drafts. Assisted-by: DeepSeek-V4.1-Flash-1017	2026-10-22 08:11:45 +03:00
kurquhar	c7fc509417	opencl: add F32-to-I32 ARGMAX (#30897) ... * opencl: add F32-to-I32 ARGMAX Assisted-by: OpenCode * opencl: init to 0 to be consistent with cpu --------- Co-authored-by: Li He <lih@qti.qualcomm.com> b11804	2026-10-21 18:02:50 -07:00
alexey-rsi	a37cc46104	models : add Flint model (FlintForCausalLM) (#30928) ... * Add Flint model (FlintForCausalLM). Assisted by Codex * cleanup * one more --------- Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@huggingface.co> b11803	2026-10-21 23:26:22 +02:00
Tarek Dakhran	99fb997184	jinja : fix namespace attributes shadowed by dict methods (#30941) b11802	2026-10-21 23:06:56 +02:00
Maphist0	7775ffb7e4	model: Add support for SenseNova U1 model (#28919) ... * model : add SenseNova U1 understanding support Add support for the dense SenseNova U1 understanding branch, including the U1.5-8B-MoT model. - Add HF-to-GGUF conversion for NEOChatModel, excluding MoT generation tensors and concatenating temporal and spatial Q/K normalization weights. - Register the sensenova_u1 GGUF architecture and custom spatial RoPE metadata. - Implement temporal/spatial Q/K normalization with 4-axis RoPE. - Keep U1-specific text position handling in the model implementation. - Add synthetic architecture coverage for sensenova_u1. Only the dense understanding branch is supported; generation branches are intentionally rejected during conversion. * conversion : treat one-expert SenseNova U1 configs as dense * mtmd : add SenseNova U1 vision support Add conversion support for the SenseNova U1 vision encoder and implement its CPU mtmd projector graph. The graph applies patch embedding, GELU, adjacent-pair 2D RoPE, spatial downsampling, and dense projection for dynamic-resolution image inputs. * mtmd : fix SenseNova U1 vision token layout * model : clean up SenseNova U1 RoPE metadata Replace the hard-coded spatial RoPE key with shared GGUF and LLM_KV definitions used by conversion, model loading, and architecture tests. Clarify why SenseNova U1 retains its custom text-position input: U1 uses [t, 0, 0, 0], while the generic M-RoPE input uses [t, t, t, 0]. * mtmd : simplify SenseNova U1 projector integration Map the SenseNova U1 dense projection to the standard mm.0 weight and bias tensors and reuse the shared projector fields in the loader and graph. Read vision parameters from the checkpoint configuration and remove the U1-specific tensor names and model fields while preserving its strided projection, bias, and row-major token layout. * mtmd : fix SenseNova U1 image positions and attention * fix spacing * mtmd : restore generic test input chunks * mtmd : restore SenseNova U1 integration after upstream merge * Update conversion/sensenova_u1.py Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@huggingface.co> * Update src/models/sensenova-u1.cpp Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@huggingface.co> * model : remove SenseNova U1 BF16 activation casts Use standard backend precision handling for QKV, FFN, and output projections instead of casting inputs based on the output tensor type. Assisted-by: Codex * Update src/models/sensenova-u1.cpp Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@huggingface.co> --------- Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@huggingface.co> b11801	2026-10-21 21:54:16 +02:00
Aman Gupta	d454a204ef	llama: create new fused op for QSA mask (#30640) ... * llama: create new fused op for QSA scoring * enroll glm5.3-next too * tests : initialize the remaining tensors in test_kpool_mask The harness sentinels were left uninitialized, so leftover memory could read as NaN and fail the NaN check. * ggml: generalize the k-pool mask op into ggml_top_k_mask The k-pool mask op only covered the pooled QSA selection of qwen4exp and glm5-next, while the DSA models and the DeepSeek V4 CSA build the same top-k mask by hand with fill, set_rows and add. ggml_top_k_mask(mask, top_k, score, blocks, extra) keeps the mask cells of the live picks and the extra cells, and sets the rest to -inf. Every row tensor is 4D in the layout of top_k, and the mask is broadcast to those rows, so a selection can also be made per head. score, blocks and extra are optional: without score every pick is live, without blocks a pick is a cell, and extra holds the cells a row keeps without a pick. llm_graph_context::build_fused_top_k_mask views the row tensors in the layout of kq_mask and registers the fused node. The k-pool models, the DSA attention of build_attn and the DeepSeek V4 CSA mask use it when the probe enables the op, and keep their current path on backends without it. --------- Co-authored-by: Pascal <admin@serveurperso.com> b11800	2026-10-22 01:02:22 +08:00
92es	0756e83fc1	sycl: q8 fast dequant (#30775) b11799	2026-10-21 10:01:03 -07:00
alexey-rsi	9febe63d5a	jinja: support hexadecimal string escapes (#30929) b11798	2026-10-21 18:04:36 +02:00
kurquhar	9b56ccf00d	ggml-opencl : add IM2COL_3D support (#30895) ... * ggml-opencl : add IM2COL_3D support Assisted-by: OpenCode * opencl: use same type for kernel and host * opencl: fix for older adreno --------- Co-authored-by: Li He <lih@qti.qualcomm.com> b11797	2026-10-21 07:59:55 -07:00
Xuan-Son Nguyen	0a1ef309cd	mtmd: add state object for mtmd_gen (#30902) b11796	2026-10-21 12:59:54 +02:00
David Garcia	261700b896	server : forward llama.cpp sampling params on /v1/messages (#30856) ... * server : forward llama.cpp sampling params on /v1/messages * server : pass the request through on /v1/messages instead of copying listed keys * NIT: Change comment from multiline to single line * server : accept llama.cpp params under extra_params on /v1/messages * server : remove test case for trivial functionality * server : show extra_params in the /v1/messages README example b11795	2026-10-21 12:58:52 +02:00
Alessandro de Oliveira Faria (A.K.A.CABELO)	f849095365	vendor: update BoringSSL to 0.20261020.0 (#30889) ... [no ci]	2026-10-21 11:15:54 +02:00
Evgen Mykhailenko	824eaecf48	llama : optimize vocabulary loading (#30679) ... * llama : optimize vocabulary loading * Update src/unicode.h Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> * CR : added reserve in gguf_kv_to_str * CR : trailing space fix --------- Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> b11793	2026-10-21 12:03:27 +03:00
Aman Gupta	eb182d85c0	llama : place d2t by its set_rows use so it can stay on the GPU (#30912) b11792	2026-10-21 16:32:29 +08:00
Niklas Wenzel	ea9e3446b5	metal : fix memory leaks and cleanup logic in GPU capture path (#30890) b11791	2026-10-21 09:54:33 +02:00
Max Krasnyansky	0efe8e4c6b	hexagon: neon-vectorized and threaded repack (tiling) (#30901) ... * add vectorized q4_0 repack * apply to more types * hex-repack: neon-vectorize the rest of the types q1/q2/f16/... * hex-repack: add simple chunking / threading --------- Co-authored-by: hubezhou <hubezhou@qti.qualcomm.com> b11790	2026-10-21 10:48:39 +03:00
lhez	b531e4c749	opencl: add dp4a GEMM variants to vector load activation (#30753) ... * opencl: add dp4a GEMM variants with vector activation loads * opencl: rename kernels and env vars b11789	2026-10-21 10:48:13 +03:00
Neo Zhang	74b115ca6e	sycl : fix fa crash for Query head dimension mismatch (neq0 != HSK / D=2048/4096) (#30286) b11788	2026-10-21 10:46:43 +03:00
Titaniumtown	96caa80059	sycl: collapse duplicate need_check launch bodies in mmq (#30739) b11787	2026-10-21 10:46:00 +03:00
bosh	479a52779f	ggml-cpu : compute f32 gelu_quick and geglu_quick without the fp16 table (#30737) ... * ggml-cpu : compute f32 gelu_quick and geglu_quick without the fp16 table * ggml-cpu : keep the GGML_GELU_QUICK_FP16 table path * ggml-cpu : add the VXE gelu_quick path * tests : add test-gelu-quick for the f32 CPU kernels * tests : drop inf/nan inputs from test-gelu-quick b11786	2026-10-21 09:34:37 +02:00
Georgi Gerganov	8baabd53b7	llama : scale moe down projection per expert token (#30861) ... * llama : scale moe down projection per expert token Replace the global amax rescaling for the MoE down projection with a per-expert-token factor computed by a POOL_1D max reduction along the intermediate dimension. Undo the scale on the output with the same exact power-of-two factor. Handle POOL_1D in the Meta split-state logic so a split along axis 0 becomes a replicated per-device partial result, enabling tensor parallelism. Assisted-by: pi:llama.cpp/ggml-org/DeepSeek-V4-Flash-Vision-Exp-GGUF (Mac Studio, M2 Ultra, 192GB) * cont : simplify comments Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> * llama : refactor amax src1 scaling result Return the rescaled activation and the optional scale tensor through a small struct instead of an output pointer. Assisted-by: pi:llama.cpp/ggml-org/DeepSeek-V4-Flash-Vision-Exp-GGUF (Mac Studio, M2 Ultra, 192GB) * cont : add TODO + clean-up b11785	2026-10-21 09:01:00 +03:00
Anant Shrivastava	493253fe5a	Sycl iq3 crash fix (#30604) b11784	2026-10-21 01:04:13 -04:00
Ben Ashbaugh	339f3242c7	opencl: fix rope program build error with newer Clang (#30893) ... Newer versions of Clang diagnose an incompatible pointer type error when assigning a pointer to float to a pointer to half. b11783	2026-10-20 17:19:08 -07:00
Unbug Lee	9a3b91c680	server : fix usage.completion_tokens undercount with n > 1 (#29486) ... Assisted-by: Copilot b11782	2026-10-21 01:19:54 +02:00
Xuan-Son Nguyen	5c0b49a23b	server : add POST /tts endpoint for TTS models (#26603) ... * mtmd: add audio out stream api * add /tts endpoint * add docs * wire up mtmd_helper_model_can_chat * upload speaker_ref via form-data * expose seed to api * fix header for pcm * wip * fix penalty_last_n * fix server_output_limits * fix pocket-tts stream * wip * add server_schema for tts * add server routing * server: coerce seed and stream from multipart form fields Form fields arrive as strings, so -F seed=42 and -F stream=true were rejected by the schema. seed joins the integer fields, parsed as a long long so a full uint32 seed fits, and stream is read as a boolean when it comes as a string. --------- Co-authored-by: Pascal <admin@serveurperso.com> b11781	2026-10-21 01:19:42 +02:00
Xuan-Son Nguyen	1242be66f6	server: add realtime transcription API (#30636) ... * server: add realtime transcription API * drop transcription_sessions * proxy ws * add docs * server: let the API key middleware guard the websocket httplib runs the pre-routing handler before the websocket upgrade, so the API key middleware answers 401 at handshake like any other route. This covers the router proxy, whose children run keyless, and accepts the same key forms as HTTP (Bearer, raw key, X-Api-Key). * server: keep realtime slots out of the prompt loop A realtime slot waiting for audio is GENERATING with nothing to decode, so it fell through the prompt loop and took slot_batched. A request on a higher slot then failed can_batch_with on the task type and starved for the whole session. Realtime slots have no prompt: the loop sets them up once and always leaves them. * server: start the realtime session once its slot is live The audio stream was created in the prompt loop, which skips a slot that cannot batch with the one generating, and session.created went out before the task was posted: early appends failed and the reader quit, leaving the socket open and the slot held until the HTTP timeout. The slot now sets up its stream at launch and signals it with the begin result, session.created waits for it, and a reader that stops closes the socket so the session ends with it. * server: name the committed item in input_audio_buffer.committed Per the Realtime spec, item_id is the item made from the committed audio and previous_item_id the one committed before it, null for the first. committed now comes before the transcript that completes that item, and both go out with the item switch under one lock, so a delta cannot land between them. * server: use the GA transcription session shape The session object follows the GA Realtime schema: type transcription, with the input format, transcription model, turn detection and noise reduction under audio.input. The rate stays the model sample rate, which is what the client must send for now. --------- Co-authored-by: Pascal <admin@serveurperso.com> b11780	2026-10-21 00:04:15 +02:00
Tarek Dakhran	84e66d0321	refactor : move LFM2 shortconv and FFN blocks into a shared LFM base (#30874) ... * llama : move LFM2 shortconv and FFN blocks into a shared LFM base * Update src/models/lfm-base.cpp Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> --------- Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> b11779	2026-10-20 23:17:13 +02:00
Takamichi Ohara	52ffa02745	model : support Nemotron-3(.5)-Embed (#30877) b11778	2026-10-20 22:48:45 +02:00