What happened?
New warning not seen previously has begun to show recently on each embedding request:
WARN [ json_value] Wrong type supplied for parameter 'prompt'. Expected 'string', using default value. | tid="40148" timestamp=1717981910 prompt=["Test"]
Name and Version
Broken: 10ceba3
Still OK: b90dc56
I'll try to pinpoint the exact version.
What operating system are you seeing the problem on?
No response
Relevant log output
Log BAD (10ceba354a3b152ff425e9fa97f9caaef99a46b1):
(llm) D:\build\llama.cpp>bin\release\server --n-gpu-layers 13 --model D:\code\test_llm\models\embedding\nomic-embed-text-v1.5.f16.gguf --ctx-size 2048 --batch-size 2048 --ubatch-size 2048 --port 8081 --embeddings
INFO [ main] build info | tid="40148" timestamp=1717981849 build=3119 commit="10ceba35"
INFO [ main] system info | tid="40148" timestamp=1717981849 n_threads=16 n_threads_batch=-1 total_threads=32 system_info="AVX = 1 | AVX_VNNI = 0 | AVX2 = 1 | AVX512 = 0 | AVX512_VBMI = 0 | AVX512_VNNI = 0 | AVX512_BF16 = 0 | FMA = 1 | NEON = 0 | SVE = 0 | ARM_FMA = 0 | F16C = 1 | FP16_VA = 0 | WASM_SIMD = 0 | BLAS = 1 | SSE3 = 1 | SSSE3 = 1 | VSX = 0 | MATMUL_INT8 = 0 | LLAMAFILE = 1 | "
llama_model_loader: loaded meta data with 22 key-value pairs and 112 tensors from D:\code\test_llm\models\embedding\nomic-embed-text-v1.5.f16.gguf (version GGUF V3 (latest))
llama_model_loader: Dumping metadata keys/values. Note: KV overrides do not apply in this output.
llama_model_loader: - kv 0: general.architecture str = nomic-bert
llama_model_loader: - kv 1: general.name str = nomic-embed-text-v1.5
llama_model_loader: - kv 2: nomic-bert.block_count u32 = 12
llama_model_loader: - kv 3: nomic-bert.context_length u32 = 2048
llama_model_loader: - kv 4: nomic-bert.embedding_length u32 = 768
llama_model_loader: - kv 5: nomic-bert.feed_forward_length u32 = 3072
llama_model_loader: - kv 6: nomic-bert.attention.head_count u32 = 12
llama_model_loader: - kv 7: nomic-bert.attention.layer_norm_epsilon f32 = 0.000000
llama_model_loader: - kv 8: general.file_type u32 = 1
llama_model_loader: - kv 9: nomic-bert.attention.causal bool = false
llama_model_loader: - kv 10: nomic-bert.pooling_type u32 = 1
llama_model_loader: - kv 11: nomic-bert.rope.freq_base f32 = 1000.000000
llama_model_loader: - kv 12: tokenizer.ggml.token_type_count u32 = 2
llama_model_loader: - kv 13: tokenizer.ggml.bos_token_id u32 = 101
llama_model_loader: - kv 14: tokenizer.ggml.eos_token_id u32 = 102
llama_model_loader: - kv 15: tokenizer.ggml.model str = bert
llama_model_loader: - kv 16: tokenizer.ggml.tokens arr[str,30522] = ["[PAD]", "[unused0]", "[unused1]", "...
llama_model_loader: - kv 17: tokenizer.ggml.scores arr[f32,30522] = [-1000.000000, -1000.000000, -1000.00...
llama_model_loader: - kv 18: tokenizer.ggml.token_type arr[i32,30522] = [3, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
llama_model_loader: - kv 19: tokenizer.ggml.unknown_token_id u32 = 100
llama_model_loader: - kv 20: tokenizer.ggml.seperator_token_id u32 = 102
llama_model_loader: - kv 21: tokenizer.ggml.padding_token_id u32 = 0
llama_model_loader: - type f32: 51 tensors
llama_model_loader: - type f16: 61 tensors
llm_load_vocab: special tokens cache size = 5
llm_load_vocab: token to piece cache size = 0.2032 MB
llm_load_print_meta: format = GGUF V3 (latest)
llm_load_print_meta: arch = nomic-bert
llm_load_print_meta: vocab type = WPM
llm_load_print_meta: n_vocab = 30522
llm_load_print_meta: n_merges = 0
llm_load_print_meta: n_ctx_train = 2048
llm_load_print_meta: n_embd = 768
llm_load_print_meta: n_head = 12
llm_load_print_meta: n_head_kv = 12
llm_load_print_meta: n_layer = 12
llm_load_print_meta: n_rot = 64
llm_load_print_meta: n_embd_head_k = 64
llm_load_print_meta: n_embd_head_v = 64
llm_load_print_meta: n_gqa = 1
llm_load_print_meta: n_embd_k_gqa = 768
llm_load_print_meta: n_embd_v_gqa = 768
llm_load_print_meta: f_norm_eps = 1.0e-12
llm_load_print_meta: f_norm_rms_eps = 0.0e+00
llm_load_print_meta: f_clamp_kqv = 0.0e+00
llm_load_print_meta: f_max_alibi_bias = 0.0e+00
llm_load_print_meta: f_logit_scale = 0.0e+00
llm_load_print_meta: n_ff = 3072
llm_load_print_meta: n_expert = 0
llm_load_print_meta: n_expert_used = 0
llm_load_print_meta: causal attn = 0
llm_load_print_meta: pooling type = 1
llm_load_print_meta: rope type = 2
llm_load_print_meta: rope scaling = linear
llm_load_print_meta: freq_base_train = 1000.0
llm_load_print_meta: freq_scale_train = 1
llm_load_print_meta: n_ctx_orig_yarn = 2048
llm_load_print_meta: rope_finetuned = unknown
llm_load_print_meta: ssm_d_conv = 0
llm_load_print_meta: ssm_d_inner = 0
llm_load_print_meta: ssm_d_state = 0
llm_load_print_meta: ssm_dt_rank = 0
llm_load_print_meta: model type = 137M
llm_load_print_meta: model ftype = F16
llm_load_print_meta: model params = 136.73 M
llm_load_print_meta: model size = 260.86 MiB (16.00 BPW)
llm_load_print_meta: general.name = nomic-embed-text-v1.5
llm_load_print_meta: BOS token = 101 '[CLS]'
llm_load_print_meta: EOS token = 102 '[SEP]'
llm_load_print_meta: UNK token = 100 '[UNK]'
llm_load_print_meta: SEP token = 102 '[SEP]'
llm_load_print_meta: PAD token = 0 '[PAD]'
llm_load_print_meta: CLS token = 101 '[CLS]'
llm_load_print_meta: MASK token = 103 '[MASK]'
llm_load_print_meta: LF token = 0 '[PAD]'
ggml_cuda_init: GGML_CUDA_FORCE_MMQ: no
ggml_cuda_init: CUDA_USE_TENSOR_CORES: yes
ggml_cuda_init: found 1 CUDA devices:
Device 0: NVIDIA GeForce RTX 2080 Ti, compute capability 7.5, VMM: yes
llm_load_tensors: ggml ctx size = 0.11 MiB
llm_load_tensors: offloading 12 repeating layers to GPU
llm_load_tensors: offloading non-repeating layers to GPU
llm_load_tensors: offloaded 13/13 layers to GPU
llm_load_tensors: CPU buffer size = 44.72 MiB
llm_load_tensors: CUDA0 buffer size = 216.15 MiB
.......................................................
llama_new_context_with_model: n_ctx = 2048
llama_new_context_with_model: n_batch = 2048
llama_new_context_with_model: n_ubatch = 2048
llama_new_context_with_model: flash_attn = 0
llama_new_context_with_model: freq_base = 1000.0
llama_new_context_with_model: freq_scale = 1
llama_kv_cache_init: CUDA0 KV buffer size = 72.00 MiB
llama_new_context_with_model: KV self size = 72.00 MiB, K (f16): 36.00 MiB, V (f16): 36.00 MiB
llama_new_context_with_model: CPU output buffer size = 0.00 MiB
llama_new_context_with_model: CUDA0 compute buffer size = 260.01 MiB
llama_new_context_with_model: CUDA_Host compute buffer size = 38.02 MiB
llama_new_context_with_model: graph nodes = 453
llama_new_context_with_model: graph splits = 2
INFO [ init] initializing slots | tid="40148" timestamp=1717981850 n_slots=1
INFO [ init] new slot | tid="40148" timestamp=1717981850 id_slot=0 n_ctx_slot=2048
INFO [ main] model loaded | tid="40148" timestamp=1717981850
INFO [ main] chat template | tid="40148" timestamp=1717981850 chat_example="<|im_start|>system\nYou are a helpful assistant<|im_end|>\n<|im_start|>user\nHello<|im_end|>\n<|im_start|>assistant\nHi there<|im_end|>\n<|im_start|>user\nHow are you?<|im_end|>\n<|im_start|>assistant\n" built_in=true
INFO [ main] HTTP server listening | tid="40148" timestamp=1717981850 hostname="127.0.0.1" port="8081" n_threads_http="31"
INFO [ update_slots] all slots are idle | tid="40148" timestamp=1717981850
WARN [ json_value] Wrong type supplied for parameter 'prompt'. Expected 'string', using default value. | tid="40148" timestamp=1717981910 prompt=["Test"]
INFO [ launch_slot_with_task] slot is processing task | tid="40148" timestamp=1717981910 id_slot=0 id_task=0
INFO [ update_slots] kv cache rm [p0, end) | tid="40148" timestamp=1717981910 id_slot=0 id_task=0 p0=0
INFO [ update_slots] slot released | tid="40148" timestamp=1717981910 id_slot=0 id_task=0 n_ctx=2048 n_past=3 n_system_tokens=0 n_cache_tokens=0 truncated=false
INFO [ update_slots] all slots are idle | tid="40148" timestamp=1717981910
INFO [ log_server_request] request | tid="39808" timestamp=1717981910 remote_addr="127.0.0.1" remote_port=50789 status=200 method="POST" path="/embeddings" params={}
WARN [ json_value] Wrong type supplied for parameter 'prompt'. Expected 'string', using default value. | tid="40148" timestamp=1717981910 prompt=["Test"]
INFO [ launch_slot_with_task] slot is processing task | tid="40148" timestamp=1717981910 id_slot=0 id_task=2
INFO [ update_slots] kv cache rm [p0, end) | tid="40148" timestamp=1717981910 id_slot=0 id_task=2 p0=0
INFO [ update_slots] slot released | tid="40148" timestamp=1717981910 id_slot=0 id_task=2 n_ctx=2048 n_past=3 n_system_tokens=0 n_cache_tokens=0 truncated=false
INFO [ update_slots] all slots are idle | tid="40148" timestamp=1717981910
INFO [ log_server_request] request | tid="39808" timestamp=1717981910 remote_addr="127.0.0.1" remote_port=50789 status=200 method="POST" path="/embeddings" params={}
WARN [ json_value] Wrong type supplied for parameter 'prompt'. Expected 'string', using default value. | tid="40148" timestamp=1717981910 prompt=["Test"]
INFO [ launch_slot_with_task] slot is processing task | tid="40148" timestamp=1717981910 id_slot=0 id_task=4
INFO [ update_slots] kv cache rm [p0, end) | tid="40148" timestamp=1717981910 id_slot=0 id_task=4 p0=0
WARN [ json_value] Wrong type supplied for parameter 'prompt'. Expected 'string', using default value. | tid="40148" timestamp=1717981910 prompt=["Test"]
WARN [ json_value] Wrong type supplied for parameter 'prompt'. Expected 'string', using default value. | tid="40148" timestamp=1717981910 prompt=["Test"]
INFO [ log_server_request] request | tid="38504" timestamp=1717981910 remote_addr="127.0.0.1" remote_port=50799 status=200 method="POST" path="/embeddings" params={}
WARN [ json_value] Wrong type supplied for parameter 'prompt'. Expected 'string', using default value. | tid="40148" timestamp=1717981910 prompt=["Test"]
INFO [ update_slots] slot released | tid="40148" timestamp=1717981910 id_slot=0 id_task=4 n_ctx=2048 n_past=3 n_system_tokens=0 n_cache_tokens=0 truncated=false
INFO [ update_slots] all slots are idle | tid="40148" timestamp=1717981910
WARN [ json_value] Wrong type supplied for parameter 'prompt'. Expected 'string', using default value. | tid="40148" timestamp=1717981910 prompt=["Test"]
INFO [ launch_slot_with_task] slot is processing task | tid="40148" timestamp=1717981910 id_slot=0 id_task=6
===
Log GOOD (b90dc566c1c615289b05b50d61680f23744a21e7):
(llm) D:\build\llama.cpp>d:\opt\llama.cpp\bin\server --n-gpu-layers 13 --model D:\code\test_llm\models\embedding\nomic-embed-text-v1.5.f16.gguf --ctx-size 2048 --batch-size 2048 --ubatch-size 2048 --por
t 8081 --embeddings
INFO [ main] build info | tid="33428" timestamp=1717982359 build=3088 commit="b90dc566"
INFO [ main] system info | tid="33428" timestamp=1717982359 n_threads=16 n_threads_batch=-1 total_threads=32 system_info="AVX = 1 | AVX_VNNI = 0 | AVX2 = 1 | AVX512 = 0 | AVX512_VBMI = 0 | AVX512_VNNI = 0 | AVX512_BF16 = 0 | FMA = 1 | NEON = 0 | SVE = 0 | ARM_FMA = 0 | F16C = 1 | FP16_VA = 0 | WASM_SIMD = 0 | BLAS = 1 | SSE3 = 1 | SSSE3 = 1 | VSX = 0 | MATMUL_INT8 = 0 | LLAMAFILE = 1 | "
llama_model_loader: loaded meta data with 22 key-value pairs and 112 tensors from D:\code\test_llm\models\embedding\nomic-embed-text-v1.5.f16.gguf (version GGUF V3 (latest))
llama_model_loader: Dumping metadata keys/values. Note: KV overrides do not apply in this output.
llama_model_loader: - kv 0: general.architecture str = nomic-bert
llama_model_loader: - kv 1: general.name str = nomic-embed-text-v1.5
llama_model_loader: - kv 2: nomic-bert.block_count u32 = 12
llama_model_loader: - kv 3: nomic-bert.context_length u32 = 2048
llama_model_loader: - kv 4: nomic-bert.embedding_length u32 = 768
llama_model_loader: - kv 5: nomic-bert.feed_forward_length u32 = 3072
llama_model_loader: - kv 6: nomic-bert.attention.head_count u32 = 12
llama_model_loader: - kv 7: nomic-bert.attention.layer_norm_epsilon f32 = 0.000000
llama_model_loader: - kv 8: general.file_type u32 = 1
llama_model_loader: - kv 9: nomic-bert.attention.causal bool = false
llama_model_loader: - kv 10: nomic-bert.pooling_type u32 = 1
llama_model_loader: - kv 11: nomic-bert.rope.freq_base f32 = 1000.000000
llama_model_loader: - kv 12: tokenizer.ggml.token_type_count u32 = 2
llama_model_loader: - kv 13: tokenizer.ggml.bos_token_id u32 = 101
llama_model_loader: - kv 14: tokenizer.ggml.eos_token_id u32 = 102
llama_model_loader: - kv 15: tokenizer.ggml.model str = bert
llama_model_loader: - kv 16: tokenizer.ggml.tokens arr[str,30522] = ["[PAD]", "[unused0]", "[unused1]", "...
llama_model_loader: - kv 17: tokenizer.ggml.scores arr[f32,30522] = [-1000.000000, -1000.000000, -1000.00...
llama_model_loader: - kv 18: tokenizer.ggml.token_type arr[i32,30522] = [3, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
llama_model_loader: - kv 19: tokenizer.ggml.unknown_token_id u32 = 100
llama_model_loader: - kv 20: tokenizer.ggml.seperator_token_id u32 = 102
llama_model_loader: - kv 21: tokenizer.ggml.padding_token_id u32 = 0
llama_model_loader: - type f32: 51 tensors
llama_model_loader: - type f16: 61 tensors
llm_load_vocab: special tokens cache size = 5
llm_load_vocab: token to piece cache size = 0.2032 MB
llm_load_print_meta: format = GGUF V3 (latest)
llm_load_print_meta: arch = nomic-bert
llm_load_print_meta: vocab type = WPM
llm_load_print_meta: n_vocab = 30522
llm_load_print_meta: n_merges = 0
llm_load_print_meta: n_ctx_train = 2048
llm_load_print_meta: n_embd = 768
llm_load_print_meta: n_head = 12
llm_load_print_meta: n_head_kv = 12
llm_load_print_meta: n_layer = 12
llm_load_print_meta: n_rot = 64
llm_load_print_meta: n_embd_head_k = 64
llm_load_print_meta: n_embd_head_v = 64
llm_load_print_meta: n_gqa = 1
llm_load_print_meta: n_embd_k_gqa = 768
llm_load_print_meta: n_embd_v_gqa = 768
llm_load_print_meta: f_norm_eps = 1.0e-12
llm_load_print_meta: f_norm_rms_eps = 0.0e+00
llm_load_print_meta: f_clamp_kqv = 0.0e+00
llm_load_print_meta: f_max_alibi_bias = 0.0e+00
llm_load_print_meta: f_logit_scale = 0.0e+00
llm_load_print_meta: n_ff = 3072
llm_load_print_meta: n_expert = 0
llm_load_print_meta: n_expert_used = 0
llm_load_print_meta: causal attn = 0
llm_load_print_meta: pooling type = 1
llm_load_print_meta: rope type = 2
llm_load_print_meta: rope scaling = linear
llm_load_print_meta: freq_base_train = 1000.0
llm_load_print_meta: freq_scale_train = 1
llm_load_print_meta: n_yarn_orig_ctx = 2048
llm_load_print_meta: rope_finetuned = unknown
llm_load_print_meta: ssm_d_conv = 0
llm_load_print_meta: ssm_d_inner = 0
llm_load_print_meta: ssm_d_state = 0
llm_load_print_meta: ssm_dt_rank = 0
llm_load_print_meta: model type = 137M
llm_load_print_meta: model ftype = F16
llm_load_print_meta: model params = 136.73 M
llm_load_print_meta: model size = 260.86 MiB (16.00 BPW)
llm_load_print_meta: general.name = nomic-embed-text-v1.5
llm_load_print_meta: BOS token = 101 '[CLS]'
llm_load_print_meta: EOS token = 102 '[SEP]'
llm_load_print_meta: UNK token = 100 '[UNK]'
llm_load_print_meta: SEP token = 102 '[SEP]'
llm_load_print_meta: PAD token = 0 '[PAD]'
llm_load_print_meta: CLS token = 101 '[CLS]'
llm_load_print_meta: MASK token = 103 '[MASK]'
llm_load_print_meta: LF token = 0 '[PAD]'
ggml_cuda_init: GGML_CUDA_FORCE_MMQ: no
ggml_cuda_init: CUDA_USE_TENSOR_CORES: yes
ggml_cuda_init: found 1 CUDA devices:
Device 0: NVIDIA GeForce RTX 2080 Ti, compute capability 7.5, VMM: yes
llm_load_tensors: ggml ctx size = 0.11 MiB
llm_load_tensors: offloading 12 repeating layers to GPU
llm_load_tensors: offloading non-repeating layers to GPU
llm_load_tensors: offloaded 13/13 layers to GPU
llm_load_tensors: CPU buffer size = 44.72 MiB
llm_load_tensors: CUDA0 buffer size = 216.15 MiB
.......................................................
llama_new_context_with_model: n_ctx = 2048
llama_new_context_with_model: n_batch = 2048
llama_new_context_with_model: n_ubatch = 2048
llama_new_context_with_model: flash_attn = 0
llama_new_context_with_model: freq_base = 1000.0
llama_new_context_with_model: freq_scale = 1
llama_kv_cache_init: CUDA0 KV buffer size = 72.00 MiB
llama_new_context_with_model: KV self size = 72.00 MiB, K (f16): 36.00 MiB, V (f16): 36.00 MiB
llama_new_context_with_model: CPU output buffer size = 0.00 MiB
llama_new_context_with_model: CUDA0 compute buffer size = 260.01 MiB
llama_new_context_with_model: CUDA_Host compute buffer size = 38.02 MiB
llama_new_context_with_model: graph nodes = 453
llama_new_context_with_model: graph splits = 2
INFO [ init] initializing slots | tid="33428" timestamp=1717982360 n_slots=1
INFO [ init] new slot | tid="33428" timestamp=1717982360 id_slot=0 n_ctx_slot=2048
INFO [ main] model loaded | tid="33428" timestamp=1717982360
INFO [ main] chat template | tid="33428" timestamp=1717982360 chat_example="<|im_start|>system\nYou are a helpful assistant<|im_end|>\n<|im_start|>user\nHello<|im_end|>\n<|im_start|>assistant\nHi there<|im_end|>\n<|im_start|>user\nHow are you?<|im_end|>\n<|im_start|>assistant\n" built_in=true
INFO [ main] HTTP server listening | tid="33428" timestamp=1717982360 hostname="127.0.0.1" port="8081" n_threads_http="31"
INFO [ update_slots] all slots are idle | tid="33428" timestamp=1717982360
INFO [ launch_slot_with_task] slot is processing task | tid="33428" timestamp=1717982369 id_slot=0 id_task=0
INFO [ update_slots] kv cache rm [p0, end) | tid="33428" timestamp=1717982369 id_slot=0 id_task=0 p0=0
INFO [ update_slots] slot released | tid="33428" timestamp=1717982369 id_slot=0 id_task=0 n_ctx=2048 n_past=3 n_system_tokens=0 n_cache_tokens=0 truncated=false
INFO [ update_slots] all slots are idle | tid="33428" timestamp=1717982369
INFO [ log_server_request] request | tid="36500" timestamp=1717982369 remote_addr="127.0.0.1" remote_port=50918 status=200 method="POST" path="/embeddings" params={}
INFO [ launch_slot_with_task] slot is processing task | tid="33428" timestamp=1717982369 id_slot=0 id_task=2
INFO [ update_slots] kv cache rm [p0, end) | tid="33428" timestamp=1717982369 id_slot=0 id_task=2 p0=0
INFO [ update_slots] slot released | tid="33428" timestamp=1717982370 id_slot=0 id_task=2 n_ctx=2048 n_past=3 n_system_tokens=0 n_cache_tokens=0 truncated=false
INFO [ update_slots] all slots are idle | tid="33428" timestamp=1717982370
INFO [ launch_slot_with_task] slot is processing task | tid="33428" timestamp=1717982370 id_slot=0 id_task=4
INFO [ update_slots] kv cache rm [p0, end) | tid="33428" timestamp=1717982370 id_slot=0 id_task=4 p0=0
INFO [ log_server_request] request | tid="17636" timestamp=1717982370 remote_addr="127.0.0.1" remote_port=50919 status=200 method="POST" path="/embeddings" params={}
INFO [ update_slots] slot released | tid="33428" timestamp=1717982370 id_slot=0 id_task=4 n_ctx=2048 n_past=3 n_system_tokens=0 n_cache_tokens=0 truncated=false
INFO [ update_slots] all slots are idle | tid="33428" timestamp=1717982370
INFO [ log_server_request] request | tid="18084" timestamp=1717982370 remote_addr="127.0.0.1" remote_port=50920 status=200 method="POST" path="/embeddings" params={}
INFO [ launch_slot_with_task] slot is processing task | tid="33428" timestamp=1717982370 id_slot=0 id_task=6
INFO [ update_slots] kv cache rm [p0, end) | tid="33428" timestamp=1717982370 id_slot=0 id_task=6 p0=0
INFO [ update_slots] slot released | tid="33428" timestamp=1717982370 id_slot=0 id_task=6 n_ctx=2048 n_past=3 n_system_tokens=0 n_cache_tokens=0 truncated=false
INFO [ update_slots] all slots are idle | tid="33428" timestamp=1717982370
INFO [ launch_slot_with_task] slot is processing task | tid="33428" timestamp=1717982370 id_slot=0 id_task=8
INFO [ log_server_request] request | tid="29004" timestamp=1717982370 remote_addr="127.0.0.1" remote_port=50927 status=200 method="POST" path="/embeddings" params={}
INFO [ update_slots] kv cache rm [p0, end) | tid="33428" timestamp=1717982370 id_slot=0 id_task=8 p0=0
INFO [ update_slots] slot released | tid="33428" timestamp=1717982370 id_slot=0 id_task=8 n_ctx=2048 n_past=3 n_system_tokens=0 n_cache_tokens=0 truncated=false
INFO [ update_slots] all slots are idle | tid="33428" timestamp=1717982370
INFO [ log_server_request] request | tid="26856" timestamp=1717982370 remote_addr="127.0.0.1" remote_port=50928 status=200 method="POST" path="/embeddings" params={}
INFO [ launch_slot_with_task] slot is processing task | tid="33428" timestamp=1717982370 id_slot=0 id_task=9
INFO [ update_slots] kv cache rm [p0, end) | tid="33428" timestamp=1717982370 id_slot=0 id_task=9 p0=0
INFO [ update_slots] slot released | tid="33428" timestamp=1717982370 id_slot=0 id_task=9 n_ctx=2048 n_past=3 n_system_tokens=0 n_cache_tokens=0 truncated=false
INFO [ update_slots] all slots are idle | tid="33428" timestamp=1717982370
INFO [ log_server_request] request | tid="36484" timestamp=1717982370 remote_addr="127.0.0.1" remote_port=50929 status=200 method="POST" path="/embeddings" params={}
What happened?
New warning not seen previously has begun to show recently on each embedding request:
Name and Version
Broken: 10ceba3
Still OK: b90dc56
I'll try to pinpoint the exact version.
What operating system are you seeing the problem on?
No response
Relevant log output