feat(anthropic): Claude subscription-backed chat model via the Claude Agent SDK (Anthropic counterpart to `_ChatOpenAICodex`)

### Submission checklist - [x] This is a feature request, not a bug report or usage question. - [x] I added a clear and descriptive title that summarizes the feature request. - [x] I used the GitHub search to find a similar feature request and didn't find it. - [x] I checked the LangChain documentation and API reference to see if this feature already exists. - [x] This is not related to the langchain-community package. ### Package (Required) - [ ] langchain - [ ] langchain-openai - [x] langchain-anthropic - [ ] langchain-classic - [ ] langchain-core - [ ] langchain-model-profiles - [ ] langchain-tests - [ ] langchain-text-splitters - [ ] langchain-chroma - [ ] langchain-deepseek - [ ] langchain-exa - [ ] langchain-fireworks - [ ] langchain-groq - [ ] langchain-huggingface - [ ] langchain-mistralai - [ ] langchain-nomic - [ ] langchain-ollama - [ ] langchain-openrouter - [ ] langchain-perplexity - [ ] langchain-qdrant - [ ] langchain-xai - [ ] Other / not sure / general ### Feature Description `langchain-openai` ships `_ChatOpenAICodex` (#37569): a `ChatOpenAI` variant that authenticates with a ChatGPT subscription via OAuth instead of an API key, so Codex-eligible models can be used from LangChain under a consumer plan. I would like an equivalent for Anthropic in `langchain-anthropic`: a chat model that runs on a Claude Pro/Max subscription (Claude Code login) rather than an API key. Concretely, a `BaseChatModel` implementation backed by the official [Claude Agent SDK](https://github.com/anthropics/claude-agent-sdk-python) (`claude-agent-sdk`), which drives the bundled Claude Code CLI as a subprocess and reuses its `claude auth login` / `claude setup-token` session. Something like: ```python from langchain_anthropic.claude_agent import _ChatAnthropicClaudeAgent model = _ChatAnthropicClaudeAgent(model="claude-sonnet-4-5") model.invoke("hello") # sync model.stream("hello") # streaming await model.ainvoke("hello") # async ``` ### Use Case Develop…