fix: spelling errors and add spellcheck CI workflow

.github/workflows/spellcheck.yml

@@ -0,0 +1,37 @@
+name: Spellcheck Documentation
+
+on:
+  push:
+    branches:
+      - main
+    paths:
+      - '**.md'
+  pull_request:
+    paths:
+      - '**.md'
+
+jobs:
+  spellcheck:
+    runs-on: ubuntu-latest
+    name: Spellcheck Markdown Files
+    # Non-blocking: spellcheck is advisory, not a merge barrier
+    continue-on-error: true
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@v4
+
+      - name: Install aspell
+        run: |
+          sudo apt-get update
+          sudo apt-get install -y aspell aspell-en
+
+      - name: Set up Python
+        uses: actions/setup-python@v5
+        with:
+          python-version: '3.x'
+
+      - name: Install pyspelling
+        run: pip install pyspelling
+
+      - name: Run spellcheck
+        run: python -m pyspelling --config .spellcheck.yml

.spellcheck.yml

@@ -0,0 +1,14 @@
+matrix:
+- name: Markdown
+  sources:
+  - '**/*.md'
+  expect_match: false
+  aspell:
+    lang: en_US
+  dictionary:
+    wordlists:
+    - .wordlist.txt
+  pipeline:
+  - pyspelling.filters.markdown:
+      markdown_extensions:
+      - markdown.extensions.extra:

.wordlist.txt

@@ -0,0 +1,94 @@
+ianvs
+Ianvs
+kubeedge
+KubeEdge
+Kubeedge
+sedna
+Sedna
+YAML
+yaml
+yml
+LLM
+LLMs
+vLLM
+vllm
+TTFT
+ITL
+GPQA
+MMLU
+API
+APIs
+HuggingFace
+huggingface
+PyTorch
+pytorch
+TensorFlow
+tensorflow
+numpy
+NumPy
+sklearn
+ONNX
+K8s
+CNCF
+PCB
+AOI
+AoI
+FPN
+RFNET
+RFNet
+ERFNet
+GPU
+GPUs
+VRAM
+CPU
+CPUs
+fp16
+fp32
+FLOPS
+OBS
+csv
+JSON
+json
+JSONL
+jsonl
+url
+CLI
+ci
+cd
+dockerfile
+Dockerfile
+conda
+Conda
+pyspelling
+aspell
+hunspell
+config
+configs
+env
+testenv
+benchmarkingjob
+testcase
+testcases
+leaderboard
+repo
+repos
+plugin
+plugins
+frontend
+backend
+hyperparameters
+hyperparameter
+dataclass
+dataloader
+warmup
+rollback
+rollbacks
+checkpoint
+checkpoints
+autoregressive
+RTT
+RTTs
+pre
+untitled
+localhost
+hostname

docs/guides/how-to-build-simulation-env.md

@@ -12,11 +12,11 @@ The models in `simulation controller` are as follows:
 
 - The `Simulation System Administrator` is used to
   1. parse the system config(simulation)
-  2. check the host enviroment, e.g. check if the host has installed docker, kind, and whether memory > 4GB
-  3. build the simulation enviroment
-  4. create and deploy the moudles needed in simulation enviroment
-  5. close and delete the simulation enviroment
-- The `Simulation Job Administrator` is the core module for manage the simulation job, and provides the following funcitons:
+  2. check the host environment, e.g. check if the host has installed docker, kind, and whether memory > 4GB
+  3. build the simulation environment
+  4. create and deploy the modules needed in simulation environment
+  5. close and delete the simulation environment
+- The `Simulation Job Administrator` is the core module for manage the simulation job, and provides the following functions:
   1. build the docker images of algorithms to be tested
   2. generate the YAML file of `simulation job`
   3. deploy and delete the `simulation job` in K8s
@@ -113,7 +113,7 @@ See GM status: kubectl -n sedna get deploy
 See LC status: kubectl -n sedna get ds lc
 See Pod status: kubectl -n sedna get pod
 [I1029 01:16:56.974] Mini Sedna is created successfully
-[2022-10-29 01:17:12,880] simulation_system_admin.py(170) [INFO] - Congratulation! The simulation enviroment build successful!
+[2022-10-29 01:17:12,880] simulation_system_admin.py(170) [INFO] - Congratulations! The simulation environment build successful!
 ```
 
 In the end. You get an all-in-one environment of sedna.

docs/guides/how-to-contribute-algorithms.md

@@ -1,4 +1,4 @@
-# How to contributrbute an algorithm to Ianvs
+# How to contribute an algorithm to Ianvs
 
 Ianvs serves as testing tools for test objects, e.g., algorithms. Ianvs does NOT include code directly on the test object. Algorithms serve as typical test objects in Ianvs and detailed algorithms are thus NOT included in this Ianvs python file. As for the details of example test objects, e.g., algorithms, please refer to third party packages in the Ianvs example. For example, for AI workflow and interface please refer to sedna and for module implementation please refer to third party packages like FPN_TensorFlow and Sedna IBT algorithm.
 

docs/proposals/simulation/simulation.md

@@ -104,19 +104,19 @@ Provide ianvs with the feature of industrial distributed system simulation.
 
 ![img](images/simulation_framework.jpg)
 
-In the framwork of ianvs, the `simulation controller` is the core module of system simulation. The `simulation controller` has been supplemented, which build and deploy local edge-cloud simulation environment with K8s.
+In the framework of ianvs, the `simulation controller` is the core module of system simulation. The `simulation controller` has been supplemented, which build and deploy local edge-cloud simulation environment with K8s.
 
 ![img](images/simulation_controller.jpg)
 
 The models in `simulation controller` are as follows:
 
 - The `Simulation System Administrator` is used to
   1. parse the system config(simulation)
-  2. check the host enviroment, e.g. check if the host has installed docker, kind, and whether memory > 4GB
-  3. build the simulation enviroment
-  4. create and deploy the moudles needed in simulation enviroment
-  5. close and delete the simulation enviroment
-- The `Simulation Job Administrator` is the core module for manage the simulation job, and provides the following funcitons:
+  2. check the host environment, e.g. check if the host has installed docker, kind, and whether memory > 4GB
+  3. build the simulation environment
+  4. create and deploy the modules needed in simulation environment
+  5. close and delete the simulation environment
+- The `Simulation Job Administrator` is the core module for manage the simulation job, and provides the following functions:
   1. build the docker images of algorithms to be tested
   2. generate the YAML file of `simulation job`
   3. deploy and delete the `simulation job` in K8s
@@ -137,19 +137,19 @@ In the flowchart diagram above, the expected flow is as follows:
   - check environment: e.g. check if the host has installed docker, kind, and whether the memory > 4GB
   - parse simulation config
 
-4. `Simulation System Administrator` build the environment and create needed moudles.
+4. `Simulation System Administrator` build the environment and create needed modules.
   - build the environment: deploying a cluster including K8s and GM (global manager) locally through [all-in-one scripts of sedna](https://github.com/kubeedge/sedna/blob/527c574a60d0ae87b0436f9a8b38cf84fb6dab21/docs/setup/all-in-one.md)
   - create and deploy the `simulation job controller`
 
 5. `Simulation Job Administrator` generate and deploy simulation jobs.
   - build the docker images of algorithms to be tested
   - generate the YAML of simulation job base on `testenv.yaml` and `algorithm.yaml`
   - deploy simulation job: access k8s API-server via `python-k8sclient` to deploy simulation jobs
-6. `Simulation Job Administrator` list-watch the configmap of results: ianvs-simualtion-job-result
+6. `Simulation Job Administrator` list-watch the configmap of results: ianvs-simulation-job-result
 7. `Simulation Job Controller` run the simulation jobs
   - list-watch the simulation jobs in K8s
   - run the simulation jobs
-8. `Simulation Job Controller` save results of simulation job to configmap: ianvs-simualtion-job-result
+8. `Simulation Job Controller` save results of simulation job to configmap: ianvs-simulation-job-result
 9. `Simulation Job Administrator` generates the test_results after watched the configmap of results.
 ## Roadmap
 

examples/cloud-edge-collaborative-inference-for-llm/testalgorithms/query-routing/test_queryrouting.yaml

@@ -29,7 +29,7 @@ algorithm:
             #  2> "vllm": vLLM backend;
             #  3> "api": OpenAI API backend;
             #  4> "EagleSpecDec": EAGLE Speculative Decoding framework;
-            #  5> "LadeSepcDec": Lookahead Decoding framework;
+            #  5> "LadeSpecDec": Lookahead Decoding framework;
             values:
               - "huggingface"
               - "vllm"