500 when uploading large documents to memory bank

[aidando73]

System Info

PyTorch version: 2.5.1+cu124
Is debug build: False
CUDA used to build PyTorch: 12.4
ROCM used to build PyTorch: N/A

OS: Ubuntu 22.04.5 LTS (x86_64)
GCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
Clang version: Could not collect
CMake version: version 3.22.1
Libc version: glibc-2.35

Python version: 3.10.15 (main, Oct  3 2024, 07:27:34) [GCC 11.2.0] (64-bit runtime)
Python platform: Linux-6.8.0-49-generic-x86_64-with-glibc2.35
Is CUDA available: True
CUDA runtime version: 12.4.131
CUDA_MODULE_LOADING set to: LAZY
GPU models and configuration: GPU 0: NVIDIA A100-SXM4-40GB
Nvidia driver version: 550.127.05
cuDNN version: Could not collect
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True

CPU:
Architecture:                         x86_64
CPU op-mode(s):                       32-bit, 64-bit
Address sizes:                        48 bits physical, 48 bits virtual
Byte Order:                           Little Endian
CPU(s):                               30
On-line CPU(s) list:                  0-29
Vendor ID:                            AuthenticAMD
Model name:                           AMD EPYC 7J13 64-Core Processor
CPU family:                           25
Model:                                1
Thread(s) per core:                   1
Core(s) per socket:                   1
Socket(s):                            30
Stepping:                             1
BogoMIPS:                             4899.99
Flags:                                fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 syscall nx mmxext fxsr_opt pdpe1gb rdtscp lm rep_good nopl cpuid extd_apicid tsc_known_freq pni pclmulqdq ssse3 fma cx16 pcid sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand hypervisor lahf_lm cmp_legacy svm cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw perfctr_core ssbd ibrs ibpb stibp vmmcall fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 xsaves clzero xsaveerptr wbnoinvd arat npt nrip_save umip pku ospke vaes vpclmulqdq rdpid fsrm arch_capabilities
Virtualization:                       AMD-V
Hypervisor vendor:                    KVM
Virtualization type:                  full
L1d cache:                            1.9 MiB (30 instances)
L1i cache:                            1.9 MiB (30 instances)
L2 cache:                             15 MiB (30 instances)
L3 cache:                             480 MiB (30 instances)
NUMA node(s):                         1
NUMA node0 CPU(s):                    0-29
Vulnerability Gather data sampling:   Not affected
Vulnerability Itlb multihit:          Not affected
Vulnerability L1tf:                   Not affected
Vulnerability Mds:                    Not affected
Vulnerability Meltdown:               Not affected
Vulnerability Mmio stale data:        Not affected
Vulnerability Reg file data sampling: Not affected
Vulnerability Retbleed:               Not affected
Vulnerability Spec rstack overflow:   Vulnerable: Safe RET, no microcode
Vulnerability Spec store bypass:      Mitigation; Speculative Store Bypass disabled via prctl
Vulnerability Spectre v1:             Mitigation; usercopy/swapgs barriers and __user pointer sanitization
Vulnerability Spectre v2:             Mitigation; Retpolines; IBPB conditional; IBRS_FW; STIBP disabled; RSB filling; PBRSB-eIBRS Not affected; BHI Not affected
Vulnerability Srbds:                  Not affected
Vulnerability Tsx async abort:        Not affected

Versions of relevant libraries:
[pip3] numpy==2.1.3
[pip3] torch==2.5.1
[pip3] triton==3.1.0
[conda] numpy                     2.1.3                    pypi_0    pypi
[conda] torch                     2.5.1                    pypi_0    pypi
[conda] triton                    3.1.0                    pypi_0    pypi

Information

• The official example scripts
• My own modified scripts

🐛 Describe the bug

I've created a repro here: https://github.com/aidando73/llama-stack/blob/ae54376bbbf9350d8822f673261a71bb1037c939/repro.ipynb

tl;dr: when uploading multiple long documents (for me about 9) - runs into 500 error

Error logs

See repro: https://github.com/aidando73/llama-stack/blob/ae54376bbbf9350d8822f673261a71bb1037c939/repro.ipynb

Expected behavior

No 500 error. Uploads successfully.

[yanxi0830]

This is a general gap where processing & indexing large documents takes time, and we lack the primitives to perform this in background jobs. Hence, the error occurs due to timeout when indexing large documents into memory bank.

It is not a trivial thing to fix as we will first need to enable (1) ability for background jobs processing (e.g. Jobs API) to be able to index large documents in background, (2) ability to support large files (e.g. via remote data storage connectors).