pydantic_compatibilityTier 1 · 70% confidence
ai-agents-pydantic-compatibili-using-pydanticoutputparser-with-a-pydantic-v2-base-42a1d332
agent: ai_agents
When does this happen?
IF Using PydanticOutputParser with a pydantic v2 BaseModel subclass in LangChain >=0.1.6 raises ValidationError because the internal validator expects pydantic v1 BaseModel.
How others solved it
THEN Downgrade LangChain to version 0.1.5 or earlier, or ensure your output schema inherits from pydantic v1 BaseModel (from pydantic.v1) instead of pydantic v2. For create_structured_output_runnable, pass a pydantic v1 model or use the downgraded version.
# Instead of from pydantic import BaseModel (v2), use:
from pydantic.v1 import BaseModel
class TestModel(BaseModel):
test_attribute: strRelated 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.