NVIDIA / NVIDIA/GenerativeAIExamples
chain-server container keeps crashing (rag-app-text-chatbot.yaml)
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Description
I'm trying to deploy a basic RAG chatbot using the rag-app-text-chatbot.yaml file, but I'm running into issues with the chain-server container crashing shortly after startup. I believe I've properly followed the directions on https://nvidia.github.io/GenerativeAIExamples/latest/local-gpu.html. I'm using the v0.6.0 tag on the github repository. If I run docker logs on the chain-server container, here's the output I see:
===
INFO: Started server process [1]
INFO: Waiting for application startup.
/usr/local/lib/python3.10/dist-packages/langchain/embeddings/__init__.py:29: LangChainDeprecationWarning: Importing embeddings from langchain is deprecated. Importing from langchain will no longer be supported as of langchain==0.2.0. Please import from langchain-community instead:
`from langchain_community.embeddings import HuggingFaceEmbeddings`.
To install langchain-community run `pip install -U langchain-community`.
warnings.warn(
/usr/local/lib/python3.10/dist-packages/langchain/vectorstores/__init__.py:35: LangChainDeprecationWarning: Importing vector stores from langchain is deprecated. Importing from langchain will no longer be supported as of langchain==0.2.0. Please import from langchain-community instead:
`from langchain_community.vectorstores import FAISS`.
To install langchain-community run `pip install -U langchain-community`.
warnings.warn(
INFO:faiss.loader:Loading faiss with AVX2 support.
INFO:faiss.loader:Successfully loaded faiss with AVX2 support.
/usr/local/lib/python3.10/dist-packages/tritonclient/grpc/service_pb2_grpc.py:21: RuntimeWarning: The grpc package installed is at version 1.60.0, but the generated code in grpc_service_pb2_grpc.py depends on grpcio>=1.64.0. Please upgrade your grpc module to grpcio>=1.64.0 or downgrade your generated code using grpcio-tools<=1.60.0. This warning will become an error in 1.65.0, scheduled for release on June 25, 2024.
warnings.warn(
[nltk_data] Downloading package averaged_perceptron_tagger to
[nltk_data] /root/nltk_data...
[nltk_data] Package averaged_perceptron_tagger is already up-to-
[nltk_data] date!
INFO:RetrievalAugmentedGeneration.common.utils:Using huggingface as model engine and WhereIsAI/UAE-Large-V1 and model for embeddings
INFO:sentence_transformers.SentenceTransformer:Load pretrained SentenceTransformer: WhereIsAI/UAE-Large-V1
/usr/local/lib/python3.10/dist-packages/huggingface_hub/file_download.py:1132: FutureWarning: `resume_download` is deprecated and will be removed in version 1.0.0. Downloads always resume when possible. If you want to force a new download, use `force_download=True`.
warnings.warn(
INFO:RetrievalAugmentedGeneration.common.utils:Using triton-trt-llm as model engine for llm. Model name: ensemble
ERROR: Traceback (most recent call last):
File "/usr/local/lib/python3.10/dist-packages/starlette/routing.py", line 734, in lifespan
async with self.lifespan_context(app) as maybe_state:
File "/usr/local/lib/python3.10/dist-packages/starlette/routing.py", line 610, in __aenter__
await self._router.startup()
File "/usr/local/lib/python3.10/dist-packages/starlette/routing.py", line 713, in startup
handler()
File "/opt/RetrievalAugmentedGeneration/common/server.py", line 158, in import_example
spec.loader.exec_module(module)
File "<frozen importlib._bootstrap_external>", line 883, in exec_module
File "<frozen importlib._bootstrap>", line 241, in _call_with_frames_removed
File "/opt/RetrievalAugmentedGeneration/example/chains.py", line 56, in <module>
set_service_context()
File "/opt/RetrievalAugmentedGeneration/common/utils.py", line 131, in wrapper
return func(*args_hashable, **kwargs_hashable)
File "/opt/RetrievalAugmentedGeneration/common/utils.py", line 138, in set_service_context
llm = LangChainLLM(get_llm(**kwargs))
File "/opt/RetrievalAugmentedGeneration/common/utils.py", line 131, in wrapper
return func(*args_hashable, **kwargs_hashable)
File "/opt/RetrievalAugmentedGeneration/common/utils.py", line 270, in get_llm
trtllm = TensorRTLLM( # type: ignore
File "/usr/local/lib/python3.10/dist-packages/langchain_core/load/serializable.py", line 120, in __init__
super().__init__(**kwargs)
File "/usr/local/lib/python3.10/dist-packages/pydantic/v1/main.py", line 341, in __init__
raise validation_error
pydantic.v1.error_wrappers.ValidationError: 1 validation error for TensorRTLLM
__root__
Channel.unary_unary() got an unexpected keyword argument '_registered_method' (type=type_error)
ERROR: Application startup failed. Exiting.
Exception ignored in: <function InferenceServerClient.__del__ at 0x7561548a9750>
Traceback (most recent call last):
File "/usr/local/lib/python3.10/dist-packages/tritonclient/grpc/_client.py", line 257, in __del__
self.close()
File "/usr/local/lib/python3.10/dist-packages/tritonclient/grpc/_client.py", line 264, in close
self.stop_stream()
File "/usr/local/lib/python3.10/dist-packages/tritonclient/grpc/_client.py", line 1811, in stop_stream
if self._stream is not None:
AttributeError: 'InferenceServerClient' object has no attribute '_stream'
===
Here's some docker ps output:
$ docker ps -a --format "table {{.ID}}\t{{.Names}}\t{{.Status}}"
CONTAINER ID NAMES STATUS
f025cd96cc5c milvus-standalone Up 13 minutes
ca017bfe8648 milvus-etcd Up 13 minutes (healthy)
b44caa6c6e9a milvus-minio Up 13 minutes (healthy)
4b812c48035b rag-playground Up 13 minutes
a686d2b3938f chain-server Exited (3) 13 minutes ago
7fe575e94855 llm-inference-server Up 13 minutes
80f535f5a462 notebook-server Up 13 minutes
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Piste de recherche
Commencez par rag-app-text-chatbot.yaml et le traceback de démarrage, puis lisez common/server.py, example/chains.py et common/utils.py autour de l’import signalé et de la configuration de LLM. Utilisez docker logs pour chain-server afin de reproduire l’échec et d’inspecter les versions des dépendances impliquées. C’est terminé lorsque l’application chain-server termine son démarrage et reste en fonctionnement avec cette configuration.
Rédigé par le modèle d'indexation à partir du texte de l'issue.
Évaluation
- Stack technique
- docker, grpc, python
- Domaine
- ai, backend, infrastructure
- Type d'issue
- Bug
- Difficulté
- 4/5
- Temps estimé
- 3-5 jours
- Activité
- À l'abandon
- Clarté
- À clarifier
- Accessibilité débutants
- 38/100