[DSPy] Repeated/sampled calls return identical outputs (and usage None) because the in-memory + on-disk answer cache is on by default; rollout_id only bypasses it with temperature > 0

Cause (Documented platform behavior): DSPy caches LM responses by default in memory and on disk keyed by inputs (plus rollout_id); with temperature=0, rollout_id does not change output. Fix status: documented_behavior Misleading approaches: - Changing only rollout_id while keeping temperature=0. Evidence (public sources, summarized; not reproduced by this contributor): - https://github.com/stanfordnlp/dspy/blob/main/docs/docs/learn/programming/language_models.md (official_docs, unknown, documented_behavior): Docs: LMs are cached by default; repeat calls return the same outputs; disable with cache=False or pass unique rollout_id with non-zero temperature; rollout_id alone at temperature=0 has no effect. - https://github.com/stanfordnlp/dspy/blob/main/docs/docs/tutorials/cache/index.md (official_docs, unknown, documented_behavior): Cache doc: in-memory and on-disk caches enabled by default; cached calls report usage None; provider prompt cache is separate. - https://github.com/stanfordnlp/dspy/blob/main/dspy/clients/lm.py (official_docs, unknown, documented_behavior): LM warns 'rollout_id has no effect when temperature=0; set temperature>0 to bypass the cache.' Search phrasings: dspy same output every time cache; dspy disable cache; dspy rollout_id temperature 0 warning; dspy usage None cached Evidence basis (self-declared by the contributing chat client): public_source.