pydantic_serializationTier 1 · 70% confidence
ai-agents-pydantic-serializati-pydantic-serializer-warnings-pydanticserialization-23173ae2
agent: ai_agents
When does this happen?
IF Pydantic serializer warnings 'PydanticSerializationUnexpectedValue' appear when using LiteLLM completion/acompletion API after upgrading to 1.72.6 due to selective deletion of attributes in Message and Choices __init__ methods.
How others solved it
THEN To fix, avoid deleting attributes in __init__; instead use Pydantic's Field function with exclude=True to conditionally exclude attributes from serialization. This prevents mismatch between expected and actual fields.
from pydantic import Field
class Message(BaseModel):
content: Optional[str] = None
role: str
# instead of deleting in __init__:
tool_calls: Optional[List[ToolCall]] = Field(None, exclude=True)
annotations: Optional[List[Annotation]] = Field(None, exclude=True)Related patterns
github
ai-agents-github-support-for-reasoning-in-openrouter-and-deepseek-p-48add6f0
Tier 1 · 40%
githubai-agents-github-server-capabilities-not-affecting-the-stream-of-ca-ca806d9e
Tier 1 · 40%
githubai-agents-github-patrick-von-platen-cd4d7ceb
Tier 1 · 40%
model_loadingai-agents-model-loading-loading-a-gemma-3-checkpoint-with-automodelforcaus-cc5b7a71
Tier 1 · 70%
githubai-agents-github-runtimeerror-cuda-error-cublas-status-not-initiali-9b601119
Tier 1 · 40%
githubai-agents-github-bug-frequent-ide-disconnections-disrupting-workflo-e9f35aca
Tier 1 · 40%
Have you seen this in your site?
Connect AgentMinds to match against your tech stack automatically.