feat: add notebook-focused dev shell

devshells/README.md

@@ -34,37 +34,35 @@ nix develop .#python-uv
 - Ruff (linter/formatter)
 - Pyright (type checker)
 
-### `ml-ai`
+### `ai-notebook`
-Machine Learning and AI development with HuggingFace model management.
+Notebook-focused ML/AI environment with HuggingFace tooling and JupyterLab.
 
 ```bash
-nix develop .#ml-ai
+nix develop .#ai-notebook
 ```
 
 **Includes:**
-- Python 3.12 with huggingface-hub
+- Python 3.12 with JupyterLab, NumPy/Pandas/SciPy stack
-- `huggingface-cli` for downloading models
+- HuggingFace `transformers`, `datasets`, `accelerate`, `tokenizers`
-- UV for package management
+- Vision tooling: OpenCV, scikit-image, Pillow, albumentations, Altair/Plotly
-- Git LFS for large files
+- Optional CPU PyTorch (Linux hosts) plus torchvision/torchaudio
-- Ruff and Pyright
+- UV, Ruff, Pyright, Git LFS
 
-**Model cache:** `~/.cache/huggingface` (persistent across projects)
+**HuggingFace caches:**
+- Models: `~/.cache/huggingface/hub`
+- Transformers: `~/.cache/huggingface/transformers`
 
 **Example usage:**
 ```bash
-# Download a TTS model
+# Launch JupyterLab with AI helpers
-huggingface-cli download facebook/mms-tts-eng
+jupyter lab
 
-# Download a small LLM
+# Download a model or dataset
 huggingface-cli download meta-llama/Llama-3.2-1B
+python -c "from datasets import load_dataset; load_dataset('ag_news')"
 
-# Download specific files only
+# Fine-tune with Accelerate
-huggingface-cli download openai/whisper-large-v3 --include "*.json" "*.safetensors"
+python -m accelerate.commands.launch train.py
-
-# Use in your project
-uv init my-ml-project
-cd my-ml-project
-uv add transformers torch
 ```
 
 ### `go`
@@ -114,7 +112,7 @@ Use the full path to your dotfiles:
 
 ```bash
 cd ~/my-project
-nix develop ~/Development/dotfiles#ml-ai
+nix develop ~/Development/dotfiles#ai-notebook
 ```
 
 ### Option 2: Flake Registry Alias (Recommended)
@@ -130,7 +128,7 @@ nix registry list | grep dotfiles
 **Then from anywhere:**
 ```bash
 cd ~/any-project
-nix develop dotfiles#ml-ai
+nix develop dotfiles#ai-notebook
 ```
 
 Benefits: Shorter commands, cleaner paths, easy to remember!
@@ -145,14 +143,14 @@ nix registry add dotfiles ~/Development/dotfiles
 
 # In each project:
 cd ~/my-ml-project
-echo "use flake dotfiles#ml-ai" > .envrc
+echo "use flake dotfiles#ai-notebook" > .envrc
 direnv allow
 ```
 
 **Alternative: Without registry (using full path):**
 ```bash
 cd ~/my-ml-project
-echo "use flake ~/Development/dotfiles#ml-ai" > .envrc
+echo "use flake ~/Development/dotfiles#ai-notebook" > .envrc
 direnv allow
 ```
 
@@ -172,7 +170,7 @@ Create a `flake.nix` in your project that imports the shell:
     let
       system = "aarch64-darwin";
     in {
-      devShells.${system}.default = dotfiles.devShells.${system}.ml-ai;
+      devShells.${system}.default = dotfiles.devShells.${system}.ai-notebook;
     };
 }
 ```
@@ -187,9 +185,9 @@ nix develop
 
 | Method | Command | Pros |
 |--------|---------|------|
-| Direct path | `nix develop ~/Development/dotfiles#ml-ai` | Simple, no setup |
+| Direct path | `nix develop ~/Development/dotfiles#ai-notebook` | Simple, no setup |
-| Registry | `nix develop dotfiles#ml-ai` | Clean, short commands |
+| Registry | `nix develop dotfiles#ai-notebook` | Clean, short commands |
-| direnv + registry | `echo "use flake dotfiles#ml-ai" > .envrc` | Auto-loads, clean |
+| direnv + registry | `echo "use flake dotfiles#ai-notebook" > .envrc` | Auto-loads, clean |
 | Project flake | `nix develop` | Shareable, version-controlled |
 
 ## Adding New Shells

devshells/ai-notebook.nix

@@ -0,0 +1,54 @@
+{ pkgs, lib, python ? pkgs.python312, ... }:
+
+let
+  pythonWithAI = python.withPackages (ps:
+    let
+      basePackages = with ps; [
+        accelerate
+        albumentations
+        altair
+        datasets
+        evaluate
+        huggingface-hub
+        ipykernel
+        jupyterlab
+        matplotlib
+        numpy
+        opencv4
+        pandas
+        pillow
+        plotly
+        scipy
+        scikit-image
+        scikit-learn
+        seaborn
+        sentencepiece
+        tokenizers
+        transformers
+      ];
+      linuxOnlyPackages = lib.optionals pkgs.stdenv.isLinux
+        (with ps; [ torch torchaudio torchvision ]);
+    in basePackages ++ linuxOnlyPackages);
+in pkgs.mkShell {
+  name = "ai-notebook";
+  packages = with pkgs; [ pythonWithAI uv git-lfs ruff pyright ];
+
+  shellHook = ''
+    export UV_PYTHON="${pythonWithAI}/bin/python3"
+    export UV_LINK_MODE=copy
+
+    export PYTHONNOUSERSITE=1
+    export HF_HOME="''${XDG_CACHE_HOME:-$HOME/.cache}/huggingface"
+    export HF_HUB_CACHE="$HF_HOME/hub"
+    export TRANSFORMERS_CACHE="$HF_HOME/transformers"
+    export JUPYTER_CONFIG_DIR="''${XDG_CONFIG_HOME:-$HOME/.config}/jupyter"
+
+    mkdir -p "$HF_HOME" "$JUPYTER_CONFIG_DIR"
+
+    echo "AI notebook shell ready"
+    echo "Python: ${python.version}"
+    echo "HuggingFace cache: $HF_HOME"
+    echo "Launch JupyterLab: jupyter lab"
+    echo "Launch classic notebook: jupyter notebook"
+  '';
+}

devshells/jupyter-notebook.nix

@@ -0,0 +1,31 @@
+{ pkgs, python ? pkgs.python312, ... }:
+
+let
+  # Python environment with notebook tooling and core data-science libs
+  pythonWithNotebook = python.withPackages (ps:
+    with ps; [
+      altair
+      ipykernel
+      jupyterlab
+      matplotlib
+      numpy
+      pandas
+      polars
+      plotly
+      scipy
+      scikit-learn
+      seaborn
+    ]);
+in pkgs.mkShell {
+  name = "jupyter-notebook";
+  packages = [ pythonWithNotebook pkgs.ruff pkgs.pyright pkgs.git ];
+  shellHook = ''
+    export PYTHONNOUSERSITE=1
+    export JUPYTER_CONFIG_DIR="''${XDG_CONFIG_HOME:-$HOME/.config}/jupyter"
+    mkdir -p "$JUPYTER_CONFIG_DIR"
+    echo "Jupyter notebook shell ready"
+    echo "Python: ${python.version}"
+    echo "Launch notebook: jupyter lab"
+    echo "Launch classic: jupyter notebook"
+  '';
+}

devshells/ml-ai.nix

@@ -1,35 +0,0 @@
-{ pkgs, python ? pkgs.python312, ... }:
-
-let
-  # Create a Python environment with huggingface-cli
-  pythonWithHF = python.withPackages (ps: [ ps.huggingface-hub ]);
-in pkgs.mkShell {
-  name = "ml-ai";
-  packages = with pkgs; [ pythonWithHF uv git-lfs ruff pyright ];
-  shellHook = ''
-    # Set up UV
-    export UV_PYTHON="${pythonWithHF}/bin/python3"
-    export UV_LINK_MODE=copy
-
-    # Set up HuggingFace cache (persistent across projects)
-    export HF_HOME="''${XDG_CACHE_HOME:-$HOME/.cache}/huggingface"
-    export HF_HUB_CACHE="$HF_HOME/hub"
-    mkdir -p "$HF_HOME"
-
-    # Optional: Set offline mode (uncomment to use only cached models)
-    # export HF_HUB_OFFLINE=1
-
-    echo "ML/AI shell ready"
-    echo "Python: ${python.version}"
-    echo "HuggingFace cache: $HF_HOME"
-    echo ""
-    echo "Download models with:"
-    echo "  huggingface-cli download <model-id>"
-    echo ""
-    echo "Example TTS:"
-    echo "  huggingface-cli download facebook/mms-tts-eng"
-    echo ""
-    echo "Example LLM:"
-    echo "  huggingface-cli download meta-llama/Llama-3.2-1B"
-  '';
-}