chore: update dev environment and sync workflow

- Add nil LSP package to devenv.nix
- Add datasets and rich.progress imports to feature_retrieval.py
- Update pyproject.toml ty environment config
- Expand .stignore with cache directories
- Update uv.lock dependency lock
- Update AGENTS.md, adding the content of development environment11

.justfile

@@ -15,7 +15,8 @@ download:
 
 sync-pkgs:
     # micromamba env create -f ./environment.yml
-    export UV_PROJECT_ENVIRONMENT="/workspace/envs/mini-nav/" && uv sync --inexact
+    # export UV_PROJECT_ENVIRONMENT="/workspace/envs/mini-nav/" && uv sync --inexact
+    uv sync --inexact
 
 sync-data:
     python -m habitat_sim.utils.datasets_download --uids habitat_test_scenes --data-path data/
@@ -33,9 +34,10 @@ ssh:
 docker:
     docker exec -it docker-ial-pangyg bash
 
-marimo:
-    export UV_PROJECT_ENVIRONMENT="/workspace/envs/mini-nav/" \
-    && uv run marimo edit ./notebooks/verification.py --host 0.0.0.0 --port 2718
+marimo +notebook:
+    # export UV_PROJECT_ENVIRONMENT="/workspace/envs/mini-nav/" \
+    # && uv run marimo edit {{ notebook }} --host 0.0.0.0 --port 2718
+    uv run marimo edit {{ notebook }} --host 0.0.0.0 --port 2718 --no-token
 
 add +packages:
     uv add {{ packages }} --no-sync

.stignore

@@ -1,6 +1,8 @@
 .git
 .jj
 .venv
+.devenv
+.direnv
 .pytest_cache
 .ruff_cache
 .opencode

AGENTS.md

@@ -25,6 +25,8 @@
 
 ## 工程说明
 使用UV管理整个工程，pytest用于测试，justfile用于快捷命令，jujutsu用于版本管理。
+本地开发环境欠缺，无法验证需要调用GPU相关的测试，因此请勿在本地跑验证。
+请在远程开发环境中进行相关验证（相关脚本暂时为编写完毕）。
 
 ### 目录说明
 

devenv.nix

@@ -15,11 +15,12 @@
       nvidiaVersion = "580.126.09";
     };
 in {
-  packages = [
+  packages = with pkgs; [
+      nil
   ];
 
   enterShell = ''
-    export UV_PROJECT_ENVIRONMENT=$HOME/.local/share/mamba/envs/mini-nav/
+    export UV_PROJECT_ENVIRONMENT=$MAMBA_ROOT_PREFIX/envs/mini-nav
 
     eval "$(micromamba shell hook --shell bash)"
     micromamba activate mini-nav

mini-nav/feature_retrieval.py

@@ -3,10 +3,11 @@ from typing import Dict, List, Optional, cast
 
 import torch
 from database import db_manager
+from datasets import load_dataset
 from PIL import Image
 from PIL.PngImagePlugin import PngImageFile
-from torch import nn
 from rich.progress import track
+from torch import nn
 from transformers import (
     AutoImageProcessor,
     AutoModel,
@@ -15,8 +16,6 @@ from transformers import (
 )
 from utils.feature_extractor import extract_batch_features
 
-from datasets import load_dataset
-
 
 def pil_image_to_bytes(image: Image.Image, format: str = "PNG") -> bytes:
     """Convert a PIL Image to bytes in the specified format.

pyproject.toml

@@ -14,7 +14,7 @@ dependencies = [
     "habitat-lab>=0.3.320250127",
     "httpx[socks]>=0.28.1",
     "lancedb>=0.30.1",
-    "marimo[mcp]>=0.21.1",
+    "marimo[mcp]>=0.22.0",
     "matplotlib>=3.10.8",
     "polars[database,numpy,pandas,pydantic]>=1.37.1",
     "pyarrow>=23.0.0",
@@ -38,7 +38,7 @@ dev = [
 ]
 
 [tool.ty.environment]
-python = "/workspace/envs/mini-nav"
+python = "$UV_PROJECT_ENVIRONMENT"
 root = ["./mini-nav", "./notebooks"]
 
 [tool.basedpyright]