What this error means
langchain-anthropic: base64 file blocks with non-PDF text mime types fail with media_type validation error is a Anthropic API failure pattern reported for developers trying to fix anthropic document block translation in langchain that rejects csv/text base64 content with invalid media_type validation errors. Based on the imported evidence, treat this as a tool-specific troubleshooting page rather than a generic API error.
Why this happens
Open issue #37576 on langchain-ai/langchain (created May 20, 2026). When sending base64-encoded text files (CSV, etc.) through ChatAnthropic, the SDK hard-codes mime_type='application/pdf' for all document blocks. Any non-PDF text mime type triggers a media_type validation error. This breaks multimodal workflows where users need to upload documents with various text-based mime types. Directly related to core-level bug #36939.
Common causes
- Open issue #37576 on langchain-ai/langchain (created May 20, 2026). When sending base64-encoded text files (CSV, etc.) through ChatAnthropic, the SDK hard-codes mime_type='application/pdf' for all document blocks. Any non-PDF text mime type triggers a media_type validation error. This breaks multimodal workflows where users need to upload documents with various text-based mime types. Directly related to core-level bug #36939.
Quick fixes
- Confirm the exact error signature matches
langchain-anthropic: base64 file blocks with non-PDF text mime types fail with media_type validation error. - Check the Anthropic API account, local tool state, and provider configuration involved in the failing workflow.
- Compare the failing environment with a known working setup, then change one configuration value at a time.
Platform/tool-specific checks
- Verify the command, editor, extension, or API client that produced the error.
- Compare local settings with CI, deployment, or editor-level settings when the error appears in only one environment.
- Avoid deleting credentials, local model data, or project settings until the failing scope is clear.
Step-by-step troubleshooting
- Capture the exact error message and the command, editor action, or request that triggered it.
- Check whether the failure is account/auth, quota/rate, model/provider, local runtime, or deployment configuration.
- Review the source evidence below and compare it with your environment.
- Apply one change at a time and rerun the smallest failing action.
- Keep the working fix documented for the team or deployment environment.
How to prevent it
- Keep provider/tool configuration documented.
- Record non-secret diagnostics such as tool version, provider name, model name, and command path.
- Add a lightweight check before CI or production workflows depend on the tool.