Refactor CLI Config Manager and Add Provider Model Routes

- Removed deprecated constants and functions from cli-config-manager.ts.
- Introduced new provider model presets in litellm-provider-models.ts for better organization and management of model information.
- Created provider-routes.ts to handle API endpoints for retrieving provider information and models.
- Added integration tests for provider routes to ensure correct functionality and response structure.
- Implemented unit tests for settings persistence functions, covering various scenarios and edge cases.
- Enhanced error handling and validation in the new routes and settings functions.
This commit is contained in:
catlog22
2026-01-25 17:27:58 +08:00
parent 7c16cc6427
commit 985085c624
13 changed files with 1252 additions and 300 deletions

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/**
* Provider Model Presets
*
* Predefined model information for each supported LLM provider.
* Used for UI dropdowns and validation.
*/
import type { ProviderType } from '../types/litellm-api-config.js';
/**
* Model information metadata
*/
export interface ModelInfo {
/** Model identifier (used in API calls) */
id: string;
/** Human-readable display name */
name: string;
/** Context window size in tokens */
contextWindow: number;
/** Whether this model supports prompt caching */
supportsCaching: boolean;
}
/**
* Embedding model information metadata
*/
export interface EmbeddingModelInfo {
/** Model identifier (used in API calls) */
id: string;
/** Human-readable display name */
name: string;
/** Embedding dimensions */
dimensions: number;
/** Maximum input tokens */
maxTokens: number;
/** Provider identifier */
provider: string;
}
/**
* Predefined models for each API format
* Used for UI selection and validation
* Note: Most providers use OpenAI-compatible format
*/
export const PROVIDER_MODELS: Record<ProviderType, ModelInfo[]> = {
// OpenAI-compatible format (used by OpenAI, DeepSeek, Ollama, etc.)
openai: [
{
id: 'gpt-4o',
name: 'GPT-4o',
contextWindow: 128000,
supportsCaching: true
},
{
id: 'gpt-4o-mini',
name: 'GPT-4o Mini',
contextWindow: 128000,
supportsCaching: true
},
{
id: 'o1',
name: 'O1',
contextWindow: 200000,
supportsCaching: true
},
{
id: 'deepseek-chat',
name: 'DeepSeek Chat',
contextWindow: 64000,
supportsCaching: false
},
{
id: 'deepseek-coder',
name: 'DeepSeek Coder',
contextWindow: 64000,
supportsCaching: false
},
{
id: 'llama3.2',
name: 'Llama 3.2',
contextWindow: 128000,
supportsCaching: false
},
{
id: 'qwen2.5-coder',
name: 'Qwen 2.5 Coder',
contextWindow: 32000,
supportsCaching: false
}
],
// Anthropic format
anthropic: [
{
id: 'claude-sonnet-4-20250514',
name: 'Claude Sonnet 4',
contextWindow: 200000,
supportsCaching: true
},
{
id: 'claude-3-5-sonnet-20241022',
name: 'Claude 3.5 Sonnet',
contextWindow: 200000,
supportsCaching: true
},
{
id: 'claude-3-5-haiku-20241022',
name: 'Claude 3.5 Haiku',
contextWindow: 200000,
supportsCaching: true
},
{
id: 'claude-3-opus-20240229',
name: 'Claude 3 Opus',
contextWindow: 200000,
supportsCaching: false
}
],
// Custom format
custom: [
{
id: 'custom-model',
name: 'Custom Model',
contextWindow: 128000,
supportsCaching: false
}
]
};
/**
* Get models for a specific provider
* @param providerType - Provider type to get models for
* @returns Array of model information
*/
export function getModelsForProvider(providerType: ProviderType): ModelInfo[] {
return PROVIDER_MODELS[providerType] || [];
}
/**
* Predefined embedding models for each API format
* Used for UI selection and validation
*/
export const EMBEDDING_MODELS: Record<ProviderType, EmbeddingModelInfo[]> = {
// OpenAI embedding models
openai: [
{
id: 'text-embedding-3-small',
name: 'Text Embedding 3 Small',
dimensions: 1536,
maxTokens: 8191,
provider: 'openai'
},
{
id: 'text-embedding-3-large',
name: 'Text Embedding 3 Large',
dimensions: 3072,
maxTokens: 8191,
provider: 'openai'
},
{
id: 'text-embedding-ada-002',
name: 'Ada 002',
dimensions: 1536,
maxTokens: 8191,
provider: 'openai'
}
],
// Anthropic doesn't have embedding models
anthropic: [],
// Custom embedding models
custom: [
{
id: 'custom-embedding',
name: 'Custom Embedding',
dimensions: 1536,
maxTokens: 8192,
provider: 'custom'
}
]
};
/**
* Get embedding models for a specific provider
* @param providerType - Provider type to get embedding models for
* @returns Array of embedding model information
*/
export function getEmbeddingModelsForProvider(providerType: ProviderType): EmbeddingModelInfo[] {
return EMBEDDING_MODELS[providerType] || [];
}
/**
* Get model information by ID within a provider
* @param providerType - Provider type
* @param modelId - Model identifier
* @returns Model information or undefined if not found
*/
export function getModelInfo(providerType: ProviderType, modelId: string): ModelInfo | undefined {
const models = PROVIDER_MODELS[providerType] || [];
return models.find(m => m.id === modelId);
}
/**
* Validate if a model ID is supported by a provider
* @param providerType - Provider type
* @param modelId - Model identifier to validate
* @returns true if model is valid for provider
*/
export function isValidModel(providerType: ProviderType, modelId: string): boolean {
return getModelInfo(providerType, modelId) !== undefined;
}