What are the best strategies and practices to prevent or resolve errors like these?
When using the HP AI Studio Platform, I often encounter pip dependency conflicts inside a Jupyter Notebook — particularly when pulling the NVIDIA NeMo framework from the HP AI Studio Images Catalog to create a new workspace—and then running Jupyter notebooks in the HP AI Blueprint “Agentic RAG for AI Studio with TRT-LLM and LangGraph” (https://github.com/HPInc/AI-Blueprints/tree/main/generative-ai/agentic_rag_with_trt-llm_and_langgraph). A similar dependency issue also occurred when running the notebooks in the “Vacation Recommendation Agent” blueprint (https://github.com/HPInc/AI-Blueprints/tree/main/ngc-integration/vacation_recommendation_agent_with_bert). In both cases, pip reports conflicts such as:
ERROR: pip’s dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.
numba 0.57.1+1.g5fba9aa8f requires numpy<1.25,>=1.21, but you have numpy 1.26.4 which is incompatible.
nemo-toolkit 1.22.0 requires numpy<1.24,>=1.22, but you have numpy 1.26.4 which is incompatible.
nemo-toolkit 1.22.0 requires setuptools>=65.5.1, but you have setuptools 59.6.0 which is incompatible.
nemo-text-processing 0.2.2rc0 requires setuptools>=65.5.1, but you have setuptools 59.6.0 which is incompatible.
What are the best strategies and practices for preventing or resolving these pip dependency conflicts in this environment?
What are the best strategies and practices to prevent or resolve errors like these?
When using the HP AI Studio Platform, I often encounter pip dependency conflicts inside a Jupyter Notebook — particularly when pulling the NVIDIA NeMo framework from the HP AI Studio Images Catalog to create a new workspace—and then running Jupyter notebooks in the HP AI Blueprint “Agentic RAG for AI Studio with TRT-LLM and LangGraph” (https://github.com/HPInc/AI-Blueprints/tree/main/generative-ai/agentic_rag_with_trt-llm_and_langgraph). A similar dependency issue also occurred when running the notebooks in the “Vacation Recommendation Agent” blueprint (https://github.com/HPInc/AI-Blueprints/tree/main/ngc-integration/vacation_recommendation_agent_with_bert). In both cases, pip reports conflicts such as:
ERROR: pip’s dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.
numba 0.57.1+1.g5fba9aa8f requires numpy<1.25,>=1.21, but you have numpy 1.26.4 which is incompatible.
nemo-toolkit 1.22.0 requires numpy<1.24,>=1.22, but you have numpy 1.26.4 which is incompatible.
nemo-toolkit 1.22.0 requires setuptools>=65.5.1, but you have setuptools 59.6.0 which is incompatible.
nemo-text-processing 0.2.2rc0 requires setuptools>=65.5.1, but you have setuptools 59.6.0 which is incompatible.
What are the best strategies and practices for preventing or resolving these pip dependency conflicts in this environment?