fix: handle mixed-type lists in _flatten across instrumentors; isolate dspy extraction errors

[Harsh23Kashyap]

Description

Resolves #3727

_flatten has the same defect in nine instrumentors: for a list that mixes mappings with other types it takes the mapping branch and then recurses into every item, so a mixed-type content list (a normal shape for vision and tool messages) breaks attribute extraction. The visible impact differs by package:

• instructor: AttributeError raised into user code from the patched call, before the wrapped function runs.
• dspy: the same AttributeError into user code from LM spans.
• llama-index: no crash, but the flattening failure is caught and logged, so the event loses every attribute.
• autogen-agentchat, guardrails: the mixed-list path is not reachable from their current call sites; fixed for consistency so future call sites inherit the safe behavior.
• langchain: also not currently reachable - message content is pre-flattened by _extract_message_kwargs before it reaches _flatten, and other structured payloads (document metadata, prompts) are JSON-serialized first. Fixed for consistency.
• google-genai, portkey, groq: these copies of _flatten are unused today; fixed for consistency.

The dspy instrumentor had a second problem: no extractor had error isolation, so a circular reference in the inputs surfaced as ValueError: Circular reference detected from safe_json_dumps in user code. litellm got the same class of fix in #3578.

Changes:

• _flatten recurses only into mapping items of a list; non-mapping parts pass through indexed. Output for all-mapping and all-scalar lists is unchanged. Same edit in all nine copies; every _flatten in the tree is now a safe copy.
• dspy generator extractors get _suppress_extractor_errors, the same shape as litellm's: a failing extractor drops its attributes with a logged warning while the span and the wrapped call proceed. _get_input_value and _module_prediction_output_attributes fall back to a safe value on failure.

Verification:

• One new regression test per package; each fails on main and passes with the fix.
• instructor: end-to-end through _PatchWrapper with a fake create function. On main the mixed content list crashes with AttributeError: 'str' object has no attribute 'items'; with the fix the call completes and both content parts land on the span. Ran twice identical both ways.
• llama-index: end-to-end through _finish_tracing with a fabricated event carrying the mixed list. On main the event keeps none of its attributes; with the fix the model name and both content parts survive. Ran twice identical both ways.
• langchain: end-to-end through _update_span with a real HumanMessage carrying a mixed content list - no crash on either side, because langchain-core and _extract_message_kwargs normalize and pre-flatten content before _flatten runs. That run is what established the not-reachable status above.
• dspy: the repro scripts from the issue run twice identical before (AttributeError / ValueError into user code) and after (the call reaches the LM).
• Package suites: autogen-agentchat 7 passed, google-genai 122 passed, groq 12 passed, llama-index test_callback.py 14 passed and 4 xfailed, langchain 231 passed and 2 skipped. instructor, guardrails, portkey, and langchain each show a small set of pre-existing failures in this environment; the failure sets are identical on unmodified main.
• ruff check and ruff format clean on the changed files.

Checklist:

• Properly respects suppress tracing context (the suppression check at wrapper entry is untouched; the guards only affect attribute extraction)

[github-actions]

CLA Assistant Lite bot All contributors have signed the CLA ✍️ ✅

[Harsh23Kashyap]

I have read the CLA Document and I hereby sign the CLA