vlmm_metadata

.github/workflows/vllm.yml

@@ -0,0 +1,108 @@
+name: Daily Python Script Execution
+
+on:
+ pull_request:
+ schedule:
+ # Runs at 00:00 UTC every day
+ - cron: '0 0 * * *'
+
+jobs:
+ run-python-script:
+ runs-on: ubuntu-latest
+
+ steps:
+ - name: Checkout repository
+ uses: actions/checkout@v3
+
+ - name: Set up Python
+ uses: actions/setup-python@v4
+ with:
+ python-version: '3.10' # Ensure this matches the Python version you need
+
+ - name: Install dependencies
+ run: |
+ python -m pip install --upgrade pip
+ pip install requests huggingface-hub
+
+ - name: Execute Python script
+ env:
+ HF_TOKEN: ${{ secrets.HF_TOKEN }} # Make sure to set this secret in your repository settings
+ run: python -c '
+import os
+import ast
+import json
+import requests
+from huggingface_hub import HfApi
+
+
+def extract_models_sub_dict(parsed_code, sub_dict_name):
+ class MODELS_SUB_LIST_VISITOR(ast.NodeVisitor):
+ def __init__(self):
+ self.key = sub_dict_name
+ self.value = None
+
+ def visit_Assign(self, node):
+ for target in node.targets:
+ if isinstance(target, ast.Name) and target.id == self.key:
+ self.value = ast.literal_eval(node.value) 
+
+ visitor = MODELS_SUB_LIST_VISITOR()
+ visitor.visit(parsed_code)
+ return visitor.value
+
+
+def extract_models_dict(source_code):
+ parsed_code = ast.parse(source_code)
+
+ class MODELS_LIST_VISITOR(ast.NodeVisitor):
+ def __init__(self):
+ self.key = "_MODELS"
+ self.value = {}
+
+ def visit_Assign(self, node):
+ for target in node.targets:
+ if not isinstance(target, ast.Name):
+ return
+ if target.id == self.key:
+ for value in node.value.values:
+ dict = extract_models_sub_dict(parsed_code, value.id)
+ self.value.update(dict)
+
+ visitor = MODELS_LIST_VISITOR()
+ visitor.visit(parsed_code)
+ return visitor.value
+
+
+# Fetch the content of the file
+url = "https://raw.githubusercontent.com/vllm-project/vllm/refs/heads/main/vllm/model_executor/models/registry.py"
+response = requests.get(url)
+response.raise_for_status() # Raise an exception for bad status codes
+source_code = response.text
+
+if __name__ == '__main__':
+ # extract models dict that consists of sub dicts
+ # _MODELS = {
+ # **_TEXT_GENERATION_MODELS,
+ # **_EMBEDDING_MODELS,
+ # **_MULTIMODAL_MODELS,
+ # **_SPECULATIVE_DECODING_MODELS,
+ # }
+ # _TEXT_GENERATION_MODELS = {
+ # "AquilaModel": ("llama", "LlamaForCausalLM"),
+ # "AquilaForCausalLM": ("llama", "LlamaForCausalLM"), # AquilaChat2
+ # "ArcticForCausalLM": ("arctic", "ArcticForCausalLM"),
+ # ...
+ models_dict = extract_models_dict(source_code)
+ architectures = [item for tup in models_dict.values() for item in tup]
+ architectures_json_str = json.dumps(architectures, indent=4)
+ json_bytes = architectures_json_str.encode('utf-8')
+ print(architectures_json_str)
+
+ # api = HfApi(token=os.environ["HF_TOKEN"])
+ # api.upload_file(
+ # path_or_fileobj=json_bytes,
+ # path_in_repo="archtiectures.json",
+ # repo_id="mishig/test-vllm",
+ # repo_type="dataset",
+ # )'
+