3badf6649c
- Implemented backend model configuration mapping to training state. - Added auto-apply logic for default configurations when models are selected. - Introduced utilities for type conversion and validation within training configuration.
86 lines
2.3 KiB
TypeScript
86 lines
2.3 KiB
TypeScript
import { authFetch } from "@/features/auth";
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interface VisionCheckResponse {
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model_name: string;
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is_vision: boolean;
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}
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interface BackendTrainingDefaults {
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max_seq_length?: number;
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num_epochs?: number;
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learning_rate?: number | string;
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batch_size?: number;
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gradient_accumulation_steps?: number;
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warmup_steps?: number;
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max_steps?: number;
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save_steps?: number;
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eval_steps?: number;
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weight_decay?: number;
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random_seed?: number;
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packing?: boolean;
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train_on_completions?: boolean;
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gradient_checkpointing?: "none" | "true" | "unsloth";
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}
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interface BackendLoraDefaults {
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lora_r?: number;
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lora_alpha?: number;
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lora_dropout?: number;
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target_modules?: string[];
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use_rslora?: boolean;
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use_loftq?: boolean;
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finetune_vision_layers?: boolean;
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finetune_language_layers?: boolean;
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finetune_attention_modules?: boolean;
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finetune_mlp_modules?: boolean;
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}
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interface BackendLoggingDefaults {
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enable_wandb?: boolean;
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wandb_project?: string;
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enable_tensorboard?: boolean;
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tensorboard_dir?: string;
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log_frequency?: number;
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}
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export interface BackendModelConfig {
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training?: BackendTrainingDefaults;
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lora?: BackendLoraDefaults;
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logging?: BackendLoggingDefaults;
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}
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export interface ModelConfigResponse {
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id: string;
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model_name?: string | null;
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config?: BackendModelConfig | null;
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is_vision: boolean;
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is_lora: boolean;
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base_model?: string | null;
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}
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/**
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* Check whether a model is a vision model by asking the backend.
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* Calls GET /api/models/check-vision/{model_name}.
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*/
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export async function checkVisionModel(modelName: string): Promise<boolean> {
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const encoded = encodeURIComponent(modelName);
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const response = await authFetch(`/api/models/check-vision/${encoded}`);
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if (!response.ok) {
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// If the check fails (e.g. network error), default to non-vision
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return false;
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}
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const data = (await response.json()) as VisionCheckResponse;
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return data.is_vision;
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}
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export async function getModelConfig(
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modelName: string,
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signal?: AbortSignal,
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): Promise<ModelConfigResponse> {
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const encoded = encodeURIComponent(modelName);
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const response = await authFetch(`/api/models/config/${encoded}`, { signal });
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if (!response.ok) {
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throw new Error(`Failed to fetch model config (${response.status})`);
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}
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return (await response.json()) as ModelConfigResponse;
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}
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