[Bug]: ValidationError using langchain_community.llms.VLLM

[santurini]

Your current environment

PyTorch version: 2.3.0+cu121
Is debug build: False
CUDA used to build PyTorch: 12.1
ROCM used to build PyTorch: N/A

OS: Ubuntu 22.04.3 LTS (x86_64)
GCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
Clang version: 14.0.0-1ubuntu1.1
CMake version: version 3.27.9
Libc version: glibc-2.35

Python version: 3.10.12 (main, Nov 20 2023, 15:14:05) [GCC 11.4.0] (64-bit runtime)
Python platform: Linux-6.1.85+-x86_64-with-glibc2.35
Is CUDA available: True
CUDA runtime version: 12.2.140
CUDA_MODULE_LOADING set to: LAZY
GPU models and configuration: GPU 0: Tesla T4
Nvidia driver version: 535.104.05
cuDNN version: Probably one of the following:
/usr/lib/x86_64-linux-gnu/libcudnn.so.8.9.6
/usr/lib/x86_64-linux-gnu/libcudnn_adv_infer.so.8.9.6
/usr/lib/x86_64-linux-gnu/libcudnn_adv_train.so.8.9.6
/usr/lib/x86_64-linux-gnu/libcudnn_cnn_infer.so.8.9.6
/usr/lib/x86_64-linux-gnu/libcudnn_cnn_train.so.8.9.6
/usr/lib/x86_64-linux-gnu/libcudnn_ops_infer.so.8.9.6
/usr/lib/x86_64-linux-gnu/libcudnn_ops_train.so.8.9.6
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:                        46 bits physical, 48 bits virtual
Byte Order:                           Little Endian
CPU(s):                               2
On-line CPU(s) list:                  0,1
Vendor ID:                            GenuineIntel
Model name:                           Intel(R) Xeon(R) CPU @ 2.30GHz
CPU family:                           6
Model:                                63
Thread(s) per core:                   2
Core(s) per socket:                   1
Socket(s):                            1
Stepping:                             0
BogoMIPS:                             4599.99
Flags:                                fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ss ht syscall nx pdpe1gb rdtscp lm constant_tsc rep_good nopl xtopology nonstop_tsc cpuid tsc_known_freq pni pclmulqdq ssse3 fma cx16 pcid sse4_1 sse4_2 x2apic movbe popcnt aes xsave avx f16c rdrand hypervisor lahf_lm abm invpcid_single ssbd ibrs ibpb stibp fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid xsaveopt arat md_clear arch_capabilities
Hypervisor vendor:                    KVM
Virtualization type:                  full
L1d cache:                            32 KiB (1 instance)
L1i cache:                            32 KiB (1 instance)
L2 cache:                             256 KiB (1 instance)
L3 cache:                             45 MiB (1 instance)
NUMA node(s):                         1
NUMA node0 CPU(s):                    0,1
Vulnerability Gather data sampling:   Not affected
Vulnerability Itlb multihit:          Not affected
Vulnerability L1tf:                   Mitigation; PTE Inversion
Vulnerability Mds:                    Vulnerable; SMT Host state unknown
Vulnerability Meltdown:               Vulnerable
Vulnerability Mmio stale data:        Vulnerable
Vulnerability Reg file data sampling: Not affected
Vulnerability Retbleed:               Vulnerable
Vulnerability Spec rstack overflow:   Not affected
Vulnerability Spec store bypass:      Vulnerable
Vulnerability Spectre v1:             Vulnerable: __user pointer sanitization and usercopy barriers only; no swapgs barriers
Vulnerability Spectre v2:             Vulnerable; IBPB: disabled; STIBP: disabled; PBRSB-eIBRS: Not affected; BHI: Vulnerable (Syscall hardening enabled)
Vulnerability Srbds:                  Not affected
Vulnerability Tsx async abort:        Not affected

Versions of relevant libraries:
[pip3] mypy-extensions==1.0.0
[pip3] numpy==1.25.2
[pip3] nvidia-nccl-cu12==2.20.5
[pip3] torch==2.3.0+cu121
[pip3] torchaudio==2.3.0+cu121
[pip3] torchsummary==1.5.1
[pip3] torchtext==0.18.0
[pip3] torchvision==0.18.0+cu121
[pip3] transformers==4.41.2
[pip3] triton==2.3.0
[conda] Could not collect
ROCM Version: Could not collect
Neuron SDK Version: N/A
vLLM Version: 0.5.0.post1
vLLM Build Flags:
CUDA Archs: Not Set; ROCm: Disabled; Neuron: Disabled
GPU Topology:
GPU0    CPU Affinity    NUMA Affinity   GPU NUMA ID
GPU0     X  0-1     N/A     N/A

Legend:

  X    = Self
  SYS  = Connection traversing PCIe as well as the SMP interconnect between NUMA nodes (e.g., QPI/UPI)
  NODE = Connection traversing PCIe as well as the interconnect between PCIe Host Bridges within a NUMA node
  PHB  = Connection traversing PCIe as well as a PCIe Host Bridge (typically the CPU)
  PXB  = Connection traversing multiple PCIe bridges (without traversing the PCIe Host Bridge)
  PIX  = Connection traversing at most a single PCIe bridge
  NV#  = Connection traversing a bonded set of # NVLinks

🐛 Describe the bug

When trying to initialize an LLM instance of vllm I keep getting the same error no matter what I do. I found out some recent changes specific to the Phi3 model in this commit #5595 but yesterday it was working fin. Below the code and error:

llm = VLLM(
    model="microsoft/Phi-3-mini-128k-instruct",
    trust_remote_code=True, 
    top_p=0.95,
    temperature=0.5,
    # rope_scaling = {"type":"yarn","factor":2.0}
    # I tried to add this parameter in every way possible but nothing changes
)

----> 1 llm = VLLM(
      2     model="microsoft/Phi-3-mini-128k-instruct",
      3     #trust_remote_code=True,
      4     top_p=0.95,
      5     temperature=0.5,

[/usr/local/lib/python3.10/dist-packages/pydantic/v1/main.py](https://localhost:8080/#) in __init__(__pydantic_self__, **data)
    339         values, fields_set, validation_error = validate_model(__pydantic_self__.__class__, data)
    340         if validation_error:
--> 341             raise validation_error
    342         try:
    343             object_setattr(__pydantic_self__, '__dict__', values)

ValidationError: 1 validation error for VLLM
__root__
  `rope_scaling`'s type field must be one of ['su', 'yarn'], got longrope (type=value_error)

[nevercast]

My first time ever using vLLM and it happens that I wanted to use it with phi-3, sure enough, same issue. Here is my repro too:

Python: 3.10 CUDA: 12.2

from vllm import SamplingParams, LLM

prompts = [
    "Hello, my name is",
    "The president of the United States is",
    "The capital of France is",
    "The future of AI is",
]
sampling_params = SamplingParams(temperature=0.8, top_p=0.95)

llm = LLM(model="microsoft/Phi-3-mini-128k-instruct")

outputs = llm.generate(prompts, sampling_params)

# Print the outputs.
for output in outputs:
    prompt = output.prompt
    generated_text = output.outputs[0].text
    print(f"Prompt: {prompt!r}, Generated text: {generated_text!r}")

Traceback (most recent call last):
  File "/home/nevercast/vllm/vllm_run.py", line 11, in <module>
    llm = LLM(model="microsoft/Phi-3-mini-128k-instruct")
  File "/home/nevercast/vllm/.venv/lib/python3.10/site-packages/vllm/entrypoints/llm.py", line 144, in __init__
    self.llm_engine = LLMEngine.from_engine_args(
  File "/home/nevercast/vllm/.venv/lib/python3.10/site-packages/vllm/engine/llm_engine.py", line 336, in from_engine_args
    engine_config = engine_args.create_engine_config()
  File "/home/nevercast/vllm/.venv/lib/python3.10/site-packages/vllm/engine/arg_utils.py", line 630, in create_engine_config
    model_config = ModelConfig(
  File "/home/nevercast/vllm/.venv/lib/python3.10/site-packages/vllm/config.py", line 137, in __init__
    self.hf_config = get_config(self.model, trust_remote_code, revision,
  File "/home/nevercast/vllm/.venv/lib/python3.10/site-packages/vllm/transformers_utils/config.py", line 48, in get_config
    raise e
  File "/home/nevercast/vllm/.venv/lib/python3.10/site-packages/vllm/transformers_utils/config.py", line 33, in get_config
    config = AutoConfig.from_pretrained(
  File "/home/nevercast/vllm/.venv/lib/python3.10/site-packages/transformers/models/auto/configuration_auto.py", line 989, in from_pretrained
    return config_class.from_dict(config_dict, **unused_kwargs)
  File "/home/nevercast/vllm/.venv/lib/python3.10/site-packages/transformers/configuration_utils.py", line 772, in from_dict
    config = cls(**config_dict)
  File "/home/nevercast/vllm/.venv/lib/python3.10/site-packages/transformers/models/phi3/configuration_phi3.py", line 158, in __init__
    self._rope_scaling_validation()
  File "/home/nevercast/vllm/.venv/lib/python3.10/site-packages/transformers/models/phi3/configuration_phi3.py", line 185, in _rope_scaling_validation
    raise ValueError(f"`rope_scaling`'s type field must be one of ['su', 'yarn'], got {rope_scaling_type}")
ValueError: `rope_scaling`'s type field must be one of ['su', 'yarn'], got longrope

[sanjay920]

upgrade to the latest vllm v0.5.1. worked for me!

[github-actions[bot]]

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