dify - 💡(How to fix) Fix Legacy model_type values break custom model credential management [1 pull requests]

AI disclosure: This issue was drafted and analyzed with Codex using GPT-5.4. I have reviewed the analysis, and I am responsible for the content.

Summary

Custom model credential management breaks for workspaces that still have legacy model_type values in provider-related tables. Requests with canonical query values such as model_type=llm can return Credential with id ... not found, which prevents users from loading, updating, switching, or deleting OpenAI-compatible custom model credentials.

Root cause

The EnumText(ModelType) migration removed legacy query normalization from several read paths while keeping only result deserialization compatibility.

ModelType.value_of("text-generation") still deserializes legacy rows to ModelType.LLM, but SQL bind parameters are emitted as canonical values such as llm. Rows that still store legacy values such as text-generation or embeddings are therefore skipped by read queries.

The regression affects mixed datasets in tables including:

• provider_models
• tenant_default_models
• provider_model_settings
• provider_model_credentials
• load_balancing_model_configs

Reproduction

1. Persist a custom model credential row with provider_model_credentials.model_type = 'text-generation'.
2. Open the custom model credential endpoint with model_type=llm.
3. Observe Credential with id ... not found.

Impact

• Users cannot load, update, switch, or delete affected custom model credentials.
• Available credential lists can appear empty.
• Default model and load balancing lookups can also miss legacy rows.

Proposed fix

Use a shared read-path helper that matches both canonical and legacy model_type values during queries, while keeping new writes on canonical enum values.