training: restructure as vLLM plugin package

- Convert to installable package with entry points for vLLM auto-discovery
- Add checkpoint_sync.py: Python replacement for Rust checkpoint binary
  - Block-level diffing of safetensors files (4KB blocks)
  - vLLM→HF weight name conversion built-in
  - Scheduled 10min after training jobs (batched)
- API change: /train now takes raw token IDs (context_ids + continuation_ids)
  - No tokenizer on training side, client owns tokenization
- Remove superseded code: standalone scripts, Rust binary, tokenizer helpers

Install: pip install -e ./training
Then vLLM auto-loads via entry point.

Co-Authored-By: Proof of Concept <poc@bcachefs.org>

training/pyproject.toml

@@ -0,0 +1,28 @@
+[build-system]
+requires = ["setuptools>=61.0"]
+build-backend = "setuptools.build_meta"
+
+[project]
+name = "apollo-plugin"
+version = "0.1.0"
+description = "Apollo training plugin for vLLM"
+requires-python = ">=3.10"
+dependencies = [
+    "torch",
+    "aiohttp",
+    "safetensors",
+]
+
+[project.optional-dependencies]
+dev = ["pytest"]
+
+[project.entry-points."vllm.general_plugins"]
+apollo = "apollo_plugin:register"
+
+[project.scripts]
+apollo-worker = "apollo_plugin.worker:main"
+apollo-checkpoint = "apollo_plugin.checkpoint_sync:main"
+
+[tool.setuptools.packages.find]
+where = ["."]
+include = ["apollo_plugin*"]