ref(pydantic-ai): Move pydantic-ai object reads behind an extraction layer - #7194
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…layer Introduce _extract.py as the module that concentrates reads of pydantic-ai object internals (private attributes, message part classes, version-dependent shapes) behind typed accessors returning plain data structures. Span modules and patches now consume those accessors, collapsing the duplicated message formatters and blob serializers into one implementation. Review-driven fixes folded in: response access in extract_response_model_name is now exception-safe (AgentRunResult.response can raise), token usage reporting goes through the shared record_token_usage helper, model-name resolution for the chat span name matches gen_ai.request.model resolution, and unknown model settings are skipped instead of raising KeyError.
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Codecov Results 📊✅ 111074 passed | ❌ 2 failed | ⏭️ 6759 skipped | Total: 117835 | Pass Rate: 94.26% | Execution Time: 400m 2s 📊 Comparison with Base Branch
➕ New Tests (1)View new tests
❌ Failed Teststest_binary_content_encoding_mixed_content[False-False]File: tests.integrations.litellm.test_litellm tests/integrations/litellm/test_litellm.py:3128: in test_binary_content_encoding_mixed_content
assert len(chat_spans) == 1
E assert 0 == 1
E + where 0 = len([])
✅ Patch coverage is 93.75%. Project has 2472 uncovered lines.
@@ Coverage Diff @@
## main #PR +/-##
==========================================
+ Coverage 90.23% 90.26% +0.03%
==========================================
Files 193 194 +1
Lines 25361 25379 +18
Branches 9302 9282 -20
==========================================
+ Hits 22883 22907 +24
- Misses 2478 2472 -6
- Partials 1432 1425 -7Generated by Codecov Action |
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