feat: add teacher config/sft loss for hosted training SFT

[eligotts]

Summary

Implements APR-157 SFT distillation support through the existing prime train config path.

• Adds top-level loss = "rl" | "sft" with [teacher] and [teacher.sampling] config models.
• Validates that SFT requires a teacher, RL rejects teacher config, and teacher.save = true is not supported.
• Defaults omitted SFT rollouts_per_example to 1 while preserving explicit overrides.
• Forwards the public platform payload shape as loss and teacher.
• Updates the confirmation summary so Training, Teacher, and Run Config render as separate sections.
• Keeps the generated template TOML-safe when SFT teacher config and checkpoint_id are uncommented together.

Config Shape

model = "openai/gpt-oss-20b"
loss = "sft"

[teacher]
model = "openai/gpt-oss-120b"
save = false

[teacher.sampling]
max_tokens = 2048
reasoning_effort = "medium"

[[env]]
id = "primeintellect/wordle"

API Payload

{
  "loss": "sft",
  "teacher": {
    "model": "openai/gpt-oss-120b",
    "save": false,
    "sampling": {
      "max_tokens": 2048,
      "reasoning_effort": "medium"
    }
  }
}

Tests

• uv run pytest packages/prime/tests/test_rl_config.py packages/prime/tests/test_train_cli.py -q

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