Default the Anthropic batch model from the connection

[kaxil]

AnthropicBatchOperator made you repeat params["model"] in every request of
requests=[{"custom_id", "params"}], even though the Anthropic connection already carries a
default_model (extra['model']) that the hook's create_message / count_tokens use.
Batches were the one path that ignored it.

Now a request that omits model inherits one. Resolution order:

1. the request's own params["model"] (unchanged; a batch can still mix models)
2. the operator's new model argument
3. the connection's default_model (extra['model'], else the provider default)

Design notes

• This aligns the batch path with the rest of the hook: create_message / count_tokens
  already resolve model or self.default_model. The connection is the natural home for "which
  model", and batches now honor it.
• params stays a verbatim passthrough of the Anthropic messages.create payload.
  create_batch fills a missing model via _apply_default_model
  without mutating the caller's request dicts, and leaves an explicit per-request model
  untouched, so mixed-model batches keep working.
• Defaulting runs after the first-party guard and deliberately skips the Bedrock-prefix
  _resolve_model step: the Message Batches API is first-party + AWS only, so the Bedrock
  branch is unreachable here.

Usage

# Set the model once for the whole batch instead of on every request:
AnthropicBatchOperator(
    task_id="summarize",
    model="claude-opus-4-8",  # or omit and set extra['model'] on the connection
    requests=[
        {"custom_id": "t1", "params": {"max_tokens": 1024, "messages": [...]}},
        {"custom_id": "t2", "params": {"max_tokens": 1024, "messages": [...]}},
    ],
)

A request that sets its own model overrides both, so you can still mix models within one batch.