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[GH-ISSUE #2162] [BUG]: Ollama Embeddings + Llama3.1 signal: aborted (core dumped) #1409

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opened 2026-02-22 18:24:40 -05:00 by yindo · 4 comments
yindo commented 2026-02-22 18:24:40 -05:00
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Originally created by @Milor123 on GitHub (Aug 22, 2024).
Original GitHub issue: https://github.com/Mintplex-Labs/anything-llm/issues/2162

How are you running AnythingLLM?

Docker (local)

What happened?

I load the ollama server in my local manjaro and then select it into AnythingLLM but when try do embed to the document, it simply dont work

Before I used LMStudio throught AnythingLLM for embeddings and works, but now i want use directly ollama

Is it a bug?

ollama serve             
2024/08/22 15:25:04 routes.go:1108: INFO server config env="map[CUDA_VISIBLE_DEVICES: GPU_DEVICE_ORDINAL: HIP_VISIBLE_DEVICES: HSA_OVERRIDE_GFX_VERSION: OLLAMA_DEBUG:false OLLAMA_FLASH_ATTENTION:false OLLAMA_HOST:http://127.0.0.1:11434 OLLAMA_INTEL_GPU:false OLLAMA_KEEP_ALIVE:5m0s OLLAMA_LLM_LIBRARY: OLLAMA_MAX_LOADED_MODELS:0 OLLAMA_MAX_QUEUE:512 OLLAMA_MODELS:/home/noe/.ollama/models OLLAMA_NOHISTORY:false OLLAMA_NOPRUNE:false OLLAMA_NUM_PARALLEL:0 OLLAMA_ORIGINS:[http://localhost https://localhost http://localhost:* https://localhost:* http://127.0.0.1 https://127.0.0.1 http://127.0.0.1:* https://127.0.0.1:* http://0.0.0.0 https://0.0.0.0 http://0.0.0.0:* https://0.0.0.0:* app://* file://* tauri://*] OLLAMA_RUNNERS_DIR: OLLAMA_SCHED_SPREAD:false OLLAMA_TMPDIR: ROCR_VISIBLE_DEVICES:]"
time=2024-08-22T15:25:04.033-05:00 level=INFO source=images.go:781 msg="total blobs: 72"
time=2024-08-22T15:25:04.034-05:00 level=INFO source=images.go:788 msg="total unused blobs removed: 0"
time=2024-08-22T15:25:04.035-05:00 level=INFO source=routes.go:1155 msg="Listening on 127.0.0.1:11434 (version 0.3.3)"
time=2024-08-22T15:25:04.035-05:00 level=INFO source=payload.go:30 msg="extracting embedded files" dir=/tmp/ollama3186541070/runners
time=2024-08-22T15:25:06.822-05:00 level=INFO source=payload.go:44 msg="Dynamic LLM libraries [cpu cpu_avx cpu_avx2 cuda_v12]"
time=2024-08-22T15:25:06.822-05:00 level=INFO source=gpu.go:205 msg="looking for compatible GPUs"
time=2024-08-22T15:25:06.979-05:00 level=INFO source=types.go:105 msg="inference compute" id=GPU-3fcffc7b-1af0-cc5c-ce0d-c8611e5f13d8 library=cuda compute=8.9 driver=12.4 name="NVIDIA GeForce RTX 4070" total="11.5 GiB" available="10.8 GiB"
[GIN] 2024/08/22 - 15:25:13 | 200 |       32.44µs |       127.0.0.1 | HEAD     "/"
[GIN] 2024/08/22 - 15:25:13 | 503 |     232.081µs |       127.0.0.1 | POST     "/api/embeddings"
[GIN] 2024/08/22 - 15:25:13 | 503 |     186.619µs |       127.0.0.1 | POST     "/api/embeddings"
[GIN] 2024/08/22 - 15:25:13 | 503 |     171.071µs |       127.0.0.1 | POST     "/api/embeddings"
[GIN] 2024/08/22 - 15:25:13 | 503 |   13.723882ms |       127.0.0.1 | POST     "/api/embeddings"
[GIN] 2024/08/22 - 15:25:13 | 503 |     219.933µs |       127.0.0.1 | POST     "/api/embeddings"
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[GIN] 2024/08/22 - 15:25:13 | 503 |      217.58µs |       127.0.0.1 | POST     "/api/embeddings"
[GIN] 2024/08/22 - 15:25:13 | 503 |     232.791µs |       127.0.0.1 | POST     "/api/embeddings"
[GIN] 2024/08/22 - 15:25:13 | 503 |     169.869µs |       127.0.0.1 | POST     "/api/embeddings"
[GIN] 2024/08/22 - 15:25:13 | 503 |     182.215µs |       127.0.0.1 | POST     "/api/embeddings"
[GIN] 2024/08/22 - 15:25:13 | 503 |     176.538µs |       127.0.0.1 | POST     "/api/embeddings"
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[GIN] 2024/08/22 - 15:25:13 | 503 |     171.953µs |       127.0.0.1 | POST     "/api/embeddings"
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[GIN] 2024/08/22 - 15:25:13 | 503 |     385.004µs |       127.0.0.1 | POST     "/api/embeddings"
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[GIN] 2024/08/22 - 15:25:13 | 503 |    24.49434ms |       127.0.0.1 | POST     "/api/embeddings"
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[GIN] 2024/08/22 - 15:25:13 | 503 |   28.565057ms |       127.0.0.1 | POST     "/api/embeddings"
[GIN] 2024/08/22 - 15:25:13 | 503 |    31.14689ms |       127.0.0.1 | POST     "/api/embeddings"
[GIN] 2024/08/22 - 15:25:13 | 503 |   31.337142ms |       127.0.0.1 | POST     "/api/embeddings"
[GIN] 2024/08/22 - 15:25:13 | 503 |     200.341µs |       127.0.0.1 | POST     "/api/embeddings"
[GIN] 2024/08/22 - 15:25:13 | 503 |   31.401956ms |       127.0.0.1 | POST     "/api/embeddings"
[GIN] 2024/08/22 - 15:25:13 | 503 |   31.236679ms |       127.0.0.1 | POST     "/api/embeddings"
[GIN] 2024/08/22 - 15:25:13 | 503 |   31.255518ms |       127.0.0.1 | POST     "/api/embeddings"
[GIN] 2024/08/22 - 15:25:13 | 503 |   28.462273ms |       127.0.0.1 | POST     "/api/embeddings"
[GIN] 2024/08/22 - 15:25:13 | 503 |   31.561612ms |       127.0.0.1 | POST     "/api/embeddings"
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[GIN] 2024/08/22 - 15:25:13 | 503 |   20.707547ms |       127.0.0.1 | POST     "/api/embeddings"
[GIN] 2024/08/22 - 15:25:13 | 503 |   30.431302ms |       127.0.0.1 | POST     "/api/embeddings"
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[GIN] 2024/08/22 - 15:25:13 | 503 |      245.71µs |       127.0.0.1 | POST     "/api/embeddings"
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[GIN] 2024/08/22 - 15:25:13 | 503 |   31.882082ms |       127.0.0.1 | POST     "/api/embeddings"
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[GIN] 2024/08/22 - 15:25:13 | 503 |     217.468µs |       127.0.0.1 | POST     "/api/embeddings"
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[GIN] 2024/08/22 - 15:25:13 | 503 |     169.801µs |       127.0.0.1 | POST     "/api/embeddings"
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[GIN] 2024/08/22 - 15:25:13 | 503 |     179.464µs |       127.0.0.1 | POST     "/api/embeddings"
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[GIN] 2024/08/22 - 15:25:13 | 503 |     197.867µs |       127.0.0.1 | POST     "/api/embeddings"
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[GIN] 2024/08/22 - 15:25:13 | 503 |     195.429µs |       127.0.0.1 | POST     "/api/embeddings"
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[GIN] 2024/08/22 - 15:25:13 | 503 |     266.539µs |       127.0.0.1 | POST     "/api/embeddings"
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[GIN] 2024/08/22 - 15:25:13 | 503 |     772.573µs |       127.0.0.1 | POST     "/api/embeddings"
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[GIN] 2024/08/22 - 15:25:13 | 503 |     160.314µs |       127.0.0.1 | POST     "/api/embeddings"
[GIN] 2024/08/22 - 15:25:13 | 503 |     245.545µs |       127.0.0.1 | POST     "/api/embeddings"
[GIN] 2024/08/22 - 15:25:13 | 503 |   42.302774ms |       127.0.0.1 | POST     "/api/embeddings"
[GIN] 2024/08/22 - 15:25:13 | 503 |   36.041904ms |       127.0.0.1 | POST     "/api/embeddings"
[GIN] 2024/08/22 - 15:25:13 | 503 |     37.1775ms |       127.0.0.1 | POST     "/api/embeddings"
[GIN] 2024/08/22 - 15:25:13 | 503 |   35.997161ms |       127.0.0.1 | POST     "/api/embeddings"
[GIN] 2024/08/22 - 15:25:13 | 503 |    42.25475ms |       127.0.0.1 | POST     "/api/embeddings"
[GIN] 2024/08/22 - 15:25:13 | 503 |   12.069205ms |       127.0.0.1 | POST     "/api/embeddings"
[GIN] 2024/08/22 - 15:25:13 | 503 |   37.422906ms |       127.0.0.1 | POST     "/api/embeddings"
[GIN] 2024/08/22 - 15:25:13 | 503 |   37.683513ms |       127.0.0.1 | POST     "/api/embeddings"
[GIN] 2024/08/22 - 15:25:13 | 503 |   39.870712ms |       127.0.0.1 | POST     "/api/embeddings"
[GIN] 2024/08/22 - 15:25:13 | 503 |   36.023897ms |       127.0.0.1 | POST     "/api/embeddings"
[GIN] 2024/08/22 - 15:25:13 | 503 |   39.945476ms |       127.0.0.1 | POST     "/api/embeddings"
time=2024-08-22T15:25:13.416-05:00 level=INFO source=sched.go:710 msg="new model will fit in available VRAM in single GPU, loading" model=/home/noe/.ollama/models/blobs/sha256-970aa74c0a90ef7482477cf803618e776e173c007bf957f635f1015bfcfef0e6 gpu=GPU-3fcffc7b-xxxxxxxxx parallel=4 available=11571036160 required="1.0 GiB"
time=2024-08-22T15:25:13.416-05:00 level=INFO source=memory.go:309 msg="offload to cuda" layers.requested=-1 layers.model=13 layers.offload=13 layers.split="" memory.available="[10.8 GiB]" memory.required.full="1.0 GiB" memory.required.partial="1.0 GiB" memory.required.kv="96.0 MiB" memory.required.allocations="[1.0 GiB]" memory.weights.total="312.1 MiB" memory.weights.repeating="267.4 MiB" memory.weights.nonrepeating="44.7 MiB" memory.graph.full="192.0 MiB" memory.graph.partial="192.0 MiB"
time=2024-08-22T15:25:13.416-05:00 level=INFO source=server.go:384 msg="starting llama server" cmd="/tmp/ollama3186541070/runners/cuda_v12/ollama_llama_server --model /home/noe/.ollama/models/blobs/sha256-970aa74c0a90ef7482477cf803618e776e173c007bf957f635f1015bfcfef0e6 --ctx-size 32768 --batch-size 512 --embedding --log-disable --n-gpu-layers 13 --parallel 4 --port 35739"
time=2024-08-22T15:25:13.417-05:00 level=INFO source=sched.go:445 msg="loaded runners" count=1
time=2024-08-22T15:25:13.417-05:00 level=INFO source=server.go:584 msg="waiting for llama runner to start responding"
time=2024-08-22T15:25:13.417-05:00 level=INFO source=server.go:618 msg="waiting for server to become available" status="llm server error"
INFO [main] build info | build=3485 commit="6eeaeba12" tid="140352059068416" timestamp=1724358313
INFO [main] system info | n_threads=6 n_threads_batch=-1 system_info="AVX = 1 | AVX_VNNI = 0 | AVX2 = 0 | AVX512 = 0 | AVX512_VBMI = 0 | AVX512_VNNI = 0 | AVX512_BF16 = 0 | FMA = 0 | NEON = 0 | SVE = 0 | ARM_FMA = 0 | F16C = 0 | FP16_VA = 0 | WASM_SIMD = 0 | BLAS = 1 | SSE3 = 1 | SSSE3 = 1 | VSX = 0 | MATMUL_INT8 = 0 | LLAMAFILE = 1 | " tid="140352059068416" timestamp=1724358313 total_threads=20
INFO [main] HTTP server listening | hostname="127.0.0.1" n_threads_http="19" port="35739" tid="140352059068416" timestamp=1724358313
llama_model_loader: loaded meta data with 24 key-value pairs and 112 tensors from /home/noe/.ollama/models/blobs/sha256-970aa74c0a90ef7482477cf803618e776e173c007bf957f635f1015bfcfef0e6 (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: - kv  22:                tokenizer.ggml.cls_token_id u32              = 101
llama_model_loader: - kv  23:               tokenizer.ggml.mask_token_id u32              = 103
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: vocab_only       = 0
llm_load_print_meta: n_ctx_train      = 2048
llm_load_print_meta: n_embd           = 768
llm_load_print_meta: n_layer          = 12
llm_load_print_meta: n_head           = 12
llm_load_print_meta: n_head_kv        = 12
llm_load_print_meta: n_rot            = 64
llm_load_print_meta: n_swa            = 0
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]'
llm_load_print_meta: max token length = 21
ggml_cuda_init: GGML_CUDA_FORCE_MMQ:    no
ggml_cuda_init: GGML_CUDA_FORCE_CUBLAS: no
ggml_cuda_init: found 1 CUDA devices:
  Device 0: NVIDIA GeForce RTX 4070, compute capability 8.9, VMM: yes
llm_load_tensors: ggml ctx size =    0.10 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      = 32768
llama_new_context_with_model: n_batch    = 512
llama_new_context_with_model: n_ubatch   = 512
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 =  1152.00 MiB
llama_new_context_with_model: KV self size  = 1152.00 MiB, K (f16):  576.00 MiB, V (f16):  576.00 MiB
llama_new_context_with_model:        CPU  output buffer size =     0.00 MiB
[1724358313] warming up the model with an empty run
llama_new_context_with_model:      CUDA0 compute buffer size =    22.01 MiB
llama_new_context_with_model:  CUDA_Host compute buffer size =     2.51 MiB
llama_new_context_with_model: graph nodes  = 453
llama_new_context_with_model: graph splits = 2
/usr/include/c++/14.1.1/bits/stl_vector.h:1130: std::vector<_Tp, _Alloc>::reference std::vector<_Tp, _Alloc>::operator[](size_type) [with _Tp = long unsigned int; _Alloc = std::allocator<long unsigned int>; reference = long unsigned int&; size_type = long unsigned int]: Assertion '__n < this->size()' failed.
time=2024-08-22T15:25:13.868-05:00 level=INFO source=server.go:618 msg="waiting for server to become available" status="llm server not responding"
time=2024-08-22T15:25:14.569-05:00 level=ERROR source=sched.go:451 msg="error loading llama server" error="llama runner process has terminated: signal: aborted (core dumped)"
[GIN] 2024/08/22 - 15:25:14 | 500 |  1.334080519s |       127.0.0.1 | POST     "/api/embeddings"
time=2024-08-22T15:25:14.569-05:00 level=WARN source=server.go:503 msg="llama runner process no longer running" sys=134 string="signal: aborted (core dumped)"

Are there known steps to reproduce?

No response

Originally created by @Milor123 on GitHub (Aug 22, 2024). Original GitHub issue: https://github.com/Mintplex-Labs/anything-llm/issues/2162 ### How are you running AnythingLLM? Docker (local) ### What happened? I load the ollama server in my local manjaro and then select it into AnythingLLM but when try do embed to the document, it simply dont work Before I used LMStudio throught AnythingLLM for embeddings and works, but now i want use directly ollama Is it a bug? ``` ollama serve 2024/08/22 15:25:04 routes.go:1108: INFO server config env="map[CUDA_VISIBLE_DEVICES: GPU_DEVICE_ORDINAL: HIP_VISIBLE_DEVICES: HSA_OVERRIDE_GFX_VERSION: OLLAMA_DEBUG:false OLLAMA_FLASH_ATTENTION:false OLLAMA_HOST:http://127.0.0.1:11434 OLLAMA_INTEL_GPU:false OLLAMA_KEEP_ALIVE:5m0s OLLAMA_LLM_LIBRARY: OLLAMA_MAX_LOADED_MODELS:0 OLLAMA_MAX_QUEUE:512 OLLAMA_MODELS:/home/noe/.ollama/models OLLAMA_NOHISTORY:false OLLAMA_NOPRUNE:false OLLAMA_NUM_PARALLEL:0 OLLAMA_ORIGINS:[http://localhost https://localhost http://localhost:* https://localhost:* http://127.0.0.1 https://127.0.0.1 http://127.0.0.1:* https://127.0.0.1:* http://0.0.0.0 https://0.0.0.0 http://0.0.0.0:* https://0.0.0.0:* app://* file://* tauri://*] OLLAMA_RUNNERS_DIR: OLLAMA_SCHED_SPREAD:false OLLAMA_TMPDIR: ROCR_VISIBLE_DEVICES:]" time=2024-08-22T15:25:04.033-05:00 level=INFO source=images.go:781 msg="total blobs: 72" time=2024-08-22T15:25:04.034-05:00 level=INFO source=images.go:788 msg="total unused blobs removed: 0" time=2024-08-22T15:25:04.035-05:00 level=INFO source=routes.go:1155 msg="Listening on 127.0.0.1:11434 (version 0.3.3)" time=2024-08-22T15:25:04.035-05:00 level=INFO source=payload.go:30 msg="extracting embedded files" dir=/tmp/ollama3186541070/runners time=2024-08-22T15:25:06.822-05:00 level=INFO source=payload.go:44 msg="Dynamic LLM libraries [cpu cpu_avx cpu_avx2 cuda_v12]" time=2024-08-22T15:25:06.822-05:00 level=INFO source=gpu.go:205 msg="looking for compatible GPUs" time=2024-08-22T15:25:06.979-05:00 level=INFO source=types.go:105 msg="inference compute" id=GPU-3fcffc7b-1af0-cc5c-ce0d-c8611e5f13d8 library=cuda compute=8.9 driver=12.4 name="NVIDIA GeForce RTX 4070" total="11.5 GiB" available="10.8 GiB" [GIN] 2024/08/22 - 15:25:13 | 200 | 32.44µs | 127.0.0.1 | HEAD "/" [GIN] 2024/08/22 - 15:25:13 | 503 | 232.081µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 186.619µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 171.071µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 13.723882ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 219.933µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 199.771µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 213.309µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 227.527µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 211.258µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 225.055µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 229.13µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 178.276µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 849.472µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 170.986µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 916.538µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 854.474µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 1.095243ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 1.006658ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 247.414µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 194.574µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 249.072µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 238.848µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 164.84µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 3.694857ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 276.896µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 3.747013ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 259.072µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 237.146µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 3.528697ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 3.586678ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 266.401µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 3.740078ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 211.54µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 236.684µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 6.799308ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 3.968129ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 3.755543ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 176.878µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 173.822µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 167.796µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 199.566µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 164.596µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 159.905µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 141.408µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 231.027µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 130.111µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 247.495µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 180.971µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 7.299068ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 200.39µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 149.669µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 160.194µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 236.388µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 207.066µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 176.434µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 211.252µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 220.449µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 233.839µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 267.125µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 212.15µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 332.471µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 276.712µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 300.101µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 230.727µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 298.74µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 579.756µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 552.945µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 555.217µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 595.846µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 432.694µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 704.552µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 428.777µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 371.814µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 424.178µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 474.134µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 455.021µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 6.978056ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 446.336µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 427.611µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 6.915662ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 534.876µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 581.657µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 627.622µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 581.675µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 406.084µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 555.829µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 421.024µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 425.359µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 844.23µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 546.511µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 495.034µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 541.877µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 578.038µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 474.625µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 522.661µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 520.669µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 668.893µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 599.629µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 587.88µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 813.16µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 633.832µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 569.865µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 789.642µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 501.801µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 469.879µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 565.033µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 1.024699ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 544.76µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 1.151473ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 909.758µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 677.901µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 206.814µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 286.762µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 312.692µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 325.146µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 241.476µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 265.096µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 265.77µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 308.064µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 321.142µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 332.857µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 300.215µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 230.829µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 335.699µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 268.857µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 214.154µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 204.519µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 197.85µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 199.457µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 299.216µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 267.377µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 198.15µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 233.162µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 234.037µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 252.773µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 245.126µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 225.391µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 181.234µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 181.706µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 195.99µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 188.685µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 202.874µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 228.291µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 210.382µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 218.928µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 209.646µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 212.272µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 181.069µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 219.942µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 179.113µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 236.735µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 182.367µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 205.562µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 164.875µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 220.13µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 220.573µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 234.729µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 216.119µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 203.035µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 217.58µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 232.791µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 169.869µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 182.215µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 176.538µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 208.075µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 166.009µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 233.014µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 171.953µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 204.257µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 165.314µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 176.891µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 210.601µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 171.129µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 213.576µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 213.402µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 152.724µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 216.995µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 217.639µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 169.53µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 166.87µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 213.741µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 175.349µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 171.546µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 197.731µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 205.267µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 209.412µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 159.132µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 165.63µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 208.603µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 208.655µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 202.262µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 180.173µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 177.18µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 153.052µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 180.579µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 173.093µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 208.201µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 215.704µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 18.9113ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 22.305846ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 23.102686ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 21.496641ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 25.085636ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 21.232382ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 22.383644ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 21.188606ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 23.656834ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 25.800886ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 22.314917ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 24.949141ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 23.243484ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 24.77953ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 20.57704ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 24.508476ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 25.748224ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 24.708748ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 23.26364ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 19.156852ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 21.517595ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 25.623471ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 21.75499ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 22.330042ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 23.050285ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 26.750592ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 21.82057ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 21.794778ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 25.521953ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 23.804377ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 26.547227ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 21.625929ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 22.545571ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 20.888936ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 24.522503ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 22.651255ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 23.095626ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 24.756847ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 21.443849ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 28.218702ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 25.857678ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 28.354817ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 21.963151ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 25.117247ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 22.184904ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 23.07197ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 28.327314ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 18.10239ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 21.8295ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 25.226168ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 19.917403ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 21.057507ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 20.669005ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 26.032747ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 21.630772ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 22.062773ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 24.043763ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 26.080899ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 21.343513ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 23.113863ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 21.836671ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 20.461561ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 26.172256ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 26.194522ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 23.815302ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 19.746944ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 26.067087ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 29.298104ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 29.30706ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 300.956µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 21.042364ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 24.134477ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 21.231037ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 26.623927ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 26.377362ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 22.056568ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 25.385664ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 21.464208ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 24.822687ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 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15:25:13 | 503 | 26.75758ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 22.001204ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 24.448124ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 21.135615ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 28.121459ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 23.74114ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 24.765756ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 27.166317ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 26.829606ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 385.004µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 26.120552ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 25.889844ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 28.068053ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 22.841933ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 24.771296ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 25.304885ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 520.271µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 31.420826ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 23.913917ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 25.106522ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 18.8548ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 33.332824ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 27.277235ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 27.752491ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 23.177107ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 23.212146ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 30.769227ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 25.818194ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 25.172084ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 31.21901ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 401.468µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 19.617116ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 24.967254ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 31.285273ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 30.150679ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 26.409568ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 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15:25:13 | 503 | 24.697581ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 31.057635ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 24.49434ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 30.110261ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 28.565057ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 31.14689ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 31.337142ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 200.341µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 31.401956ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 31.236679ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 31.255518ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 28.462273ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 31.561612ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 25.014052ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 31.576917ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 20.707547ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 30.431302ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 30.209439ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 30.052942ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 31.683243ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 27.676568ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 28.903692ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 23.983884ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 24.653972ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 30.591521ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 31.851894ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 245.71µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 32.146493ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 31.61795ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 20.037354ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 31.318829ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 32.16847ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 33.620269ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 26.044672ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 31.882082ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 33.858552ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 27.782695ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 28.193991ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 217.468µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 31.062778ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 169.801µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 27.470409ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 30.706313ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 179.464µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 34.05986ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 26.52143ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 27.821835ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 29.000317ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 31.508945ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 197.867µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 31.532931ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 31.915089ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 195.429µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 25.338462ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 31.88627ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 31.04357ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 32.035747ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 28.429727ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 34.406783ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 28.388884ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 32.664757ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 34.645163ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 34.483707ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 36.598172ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 26.501952ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 34.793292ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 34.818806ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 30.032659ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 31.657136ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 31.460382ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 30.233716ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 31.246556ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 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15:25:13 | 503 | 142.742µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 37.090245ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 276.816µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 160.314µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 245.545µs | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 42.302774ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 36.041904ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 37.1775ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 35.997161ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 42.25475ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 12.069205ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 37.422906ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 37.683513ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 39.870712ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 36.023897ms | 127.0.0.1 | POST "/api/embeddings" [GIN] 2024/08/22 - 15:25:13 | 503 | 39.945476ms | 127.0.0.1 | POST "/api/embeddings" time=2024-08-22T15:25:13.416-05:00 level=INFO source=sched.go:710 msg="new model will fit in available VRAM in single GPU, loading" model=/home/noe/.ollama/models/blobs/sha256-970aa74c0a90ef7482477cf803618e776e173c007bf957f635f1015bfcfef0e6 gpu=GPU-3fcffc7b-xxxxxxxxx parallel=4 available=11571036160 required="1.0 GiB" time=2024-08-22T15:25:13.416-05:00 level=INFO source=memory.go:309 msg="offload to cuda" layers.requested=-1 layers.model=13 layers.offload=13 layers.split="" memory.available="[10.8 GiB]" memory.required.full="1.0 GiB" memory.required.partial="1.0 GiB" memory.required.kv="96.0 MiB" memory.required.allocations="[1.0 GiB]" memory.weights.total="312.1 MiB" memory.weights.repeating="267.4 MiB" memory.weights.nonrepeating="44.7 MiB" memory.graph.full="192.0 MiB" memory.graph.partial="192.0 MiB" time=2024-08-22T15:25:13.416-05:00 level=INFO source=server.go:384 msg="starting llama server" cmd="/tmp/ollama3186541070/runners/cuda_v12/ollama_llama_server --model /home/noe/.ollama/models/blobs/sha256-970aa74c0a90ef7482477cf803618e776e173c007bf957f635f1015bfcfef0e6 --ctx-size 32768 --batch-size 512 --embedding --log-disable --n-gpu-layers 13 --parallel 4 --port 35739" time=2024-08-22T15:25:13.417-05:00 level=INFO source=sched.go:445 msg="loaded runners" count=1 time=2024-08-22T15:25:13.417-05:00 level=INFO source=server.go:584 msg="waiting for llama runner to start responding" time=2024-08-22T15:25:13.417-05:00 level=INFO source=server.go:618 msg="waiting for server to become available" status="llm server error" INFO [main] build info | build=3485 commit="6eeaeba12" tid="140352059068416" timestamp=1724358313 INFO [main] system info | n_threads=6 n_threads_batch=-1 system_info="AVX = 1 | AVX_VNNI = 0 | AVX2 = 0 | AVX512 = 0 | AVX512_VBMI = 0 | AVX512_VNNI = 0 | AVX512_BF16 = 0 | FMA = 0 | NEON = 0 | SVE = 0 | ARM_FMA = 0 | F16C = 0 | FP16_VA = 0 | WASM_SIMD = 0 | BLAS = 1 | SSE3 = 1 | SSSE3 = 1 | VSX = 0 | MATMUL_INT8 = 0 | LLAMAFILE = 1 | " tid="140352059068416" timestamp=1724358313 total_threads=20 INFO [main] HTTP server listening | hostname="127.0.0.1" n_threads_http="19" port="35739" tid="140352059068416" timestamp=1724358313 llama_model_loader: loaded meta data with 24 key-value pairs and 112 tensors from /home/noe/.ollama/models/blobs/sha256-970aa74c0a90ef7482477cf803618e776e173c007bf957f635f1015bfcfef0e6 (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: - kv 22: tokenizer.ggml.cls_token_id u32 = 101 llama_model_loader: - kv 23: tokenizer.ggml.mask_token_id u32 = 103 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: vocab_only = 0 llm_load_print_meta: n_ctx_train = 2048 llm_load_print_meta: n_embd = 768 llm_load_print_meta: n_layer = 12 llm_load_print_meta: n_head = 12 llm_load_print_meta: n_head_kv = 12 llm_load_print_meta: n_rot = 64 llm_load_print_meta: n_swa = 0 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]' llm_load_print_meta: max token length = 21 ggml_cuda_init: GGML_CUDA_FORCE_MMQ: no ggml_cuda_init: GGML_CUDA_FORCE_CUBLAS: no ggml_cuda_init: found 1 CUDA devices: Device 0: NVIDIA GeForce RTX 4070, compute capability 8.9, VMM: yes llm_load_tensors: ggml ctx size = 0.10 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 = 32768 llama_new_context_with_model: n_batch = 512 llama_new_context_with_model: n_ubatch = 512 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 = 1152.00 MiB llama_new_context_with_model: KV self size = 1152.00 MiB, K (f16): 576.00 MiB, V (f16): 576.00 MiB llama_new_context_with_model: CPU output buffer size = 0.00 MiB [1724358313] warming up the model with an empty run llama_new_context_with_model: CUDA0 compute buffer size = 22.01 MiB llama_new_context_with_model: CUDA_Host compute buffer size = 2.51 MiB llama_new_context_with_model: graph nodes = 453 llama_new_context_with_model: graph splits = 2 /usr/include/c++/14.1.1/bits/stl_vector.h:1130: std::vector<_Tp, _Alloc>::reference std::vector<_Tp, _Alloc>::operator[](size_type) [with _Tp = long unsigned int; _Alloc = std::allocator<long unsigned int>; reference = long unsigned int&; size_type = long unsigned int]: Assertion '__n < this->size()' failed. time=2024-08-22T15:25:13.868-05:00 level=INFO source=server.go:618 msg="waiting for server to become available" status="llm server not responding" time=2024-08-22T15:25:14.569-05:00 level=ERROR source=sched.go:451 msg="error loading llama server" error="llama runner process has terminated: signal: aborted (core dumped)" [GIN] 2024/08/22 - 15:25:14 | 500 | 1.334080519s | 127.0.0.1 | POST "/api/embeddings" time=2024-08-22T15:25:14.569-05:00 level=WARN source=server.go:503 msg="llama runner process no longer running" sys=134 string="signal: aborted (core dumped)" ``` ### Are there known steps to reproduce? _No response_
yindo added the possible bug label 2026-02-22 18:24:40 -05:00
yindo closed this issue 2026-02-22 18:24:40 -05:00
yindo commented 2026-02-22 18:24:40 -05:00
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@timothycarambat commented on GitHub (Aug 22, 2024):

This is from Ollama, not AnythingLLM. Post your bug report in their repo, nothing from this is from AnythingLLM's logs
https://github.com/ollama/ollama

@timothycarambat commented on GitHub (Aug 22, 2024): This is from Ollama, not AnythingLLM. Post your bug report in their repo, nothing from this is from AnythingLLM's logs https://github.com/ollama/ollama
yindo commented 2026-02-22 18:24:40 -05:00
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@timothycarambat commented on GitHub (Aug 22, 2024):

https://github.com/ollama/ollama/issues/6434
https://github.com/ollama/ollama/issues/6448

@timothycarambat commented on GitHub (Aug 22, 2024): https://github.com/ollama/ollama/issues/6434 https://github.com/ollama/ollama/issues/6448
yindo commented 2026-02-22 18:24:41 -05:00
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@Milor123 commented on GitHub (Aug 22, 2024):

@timothycarambat Thank u very much bro !

@Milor123 commented on GitHub (Aug 22, 2024): @timothycarambat Thank u very much bro !
yindo commented 2026-02-22 18:24:41 -05:00
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@Milor123 commented on GitHub (Aug 23, 2024):

@timothycarambat Was a Ollama problem related with glibc or CUDA12, i am not sure but the found solution using docker with the ollama

here is the solution https://github.com/ollama/ollama/issues/6448#issuecomment-2305970013
Thank u very much !!!

@Milor123 commented on GitHub (Aug 23, 2024): @timothycarambat Was a Ollama problem related with glibc or CUDA12, i am not sure but the found solution using docker with the ollama here is the solution https://github.com/ollama/ollama/issues/6448#issuecomment-2305970013 Thank u very much !!!
yindo changed title from [BUG]: Ollama Embeddings + Llama3.1 signal: aborted (core dumped) to [GH-ISSUE #2162] [BUG]: Ollama Embeddings + Llama3.1 signal: aborted (core dumped) 2026-06-05 14:40:37 -04:00
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Reference: Mintplex-Labs/anything-llm#1409
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