Feature Request: Support default LLM settings for models to avoid repeated configuration in LLM nodes

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### 1. Is this request related to a challenge you're experiencing? Tell me about your story.

Yes.

When building complex workflows in Dify Workflow/Chatflow, I often need to create multiple LLM nodes. However, each LLM node requires manually configuring the same model parameters repeatedly.

For example, when using DeepSeek models, I need to configure settings such as:

- Thinking mode (enable/disable)
- Temperature
- Max tokens
- Other model-specific parameters

Currently, these configurations are stored independently in each LLM node. If a workflow contains many LLM nodes, I have to repeat the same configuration dozens of times.

This causes several problems:

1. It significantly reduces workflow development efficiency.
2. It is easy to create inconsistent configurations between nodes using the same model.
3. When I need to change a global model behavior (for example, disabling thinking mode), I have to manually update every LLM node.

For large workflows and agent applications, this configuration method becomes difficult to maintain.

### 2. Additional context or comments

I suggest adding a default model configuration mechanism at the Model Provider or Model level.

For example:

Settings → Model Providers → DeepSeek → Default Parameters

Users can define default parameters for each model:

Model: deepseek-chat

Default parameters:
- Thinking mode: OFF
- Temperature: 0.7
- Max tokens: 4096

When a user creates a new LLM node and selects this model, Dify automatically applies these default settings.

The priority could be:

Node custom settings
>
Model default settings
>
Provider default settings

This allows users to maintain global consistency while still allowing individual nodes to override settings when needed.

This feature would greatly improve workflow maintainability and development efficiency, especially for complex Chatflow and Agent applications.

### 3. Can you help us with this feature?

- [ ] I am interested in contributing to this feature.

The issue names no files, tests, or code entry points. Start by tracing how model-provider settings and LLM node parameters are represented, then determine where model and provider defaults would be stored and applied. Done means new nodes inherit defaults while node-specific settings override them.

Written by the indexing model from the issue text.