mirror of
https://github.com/lordmathis/llamactl.git
synced 2025-11-06 09:04:27 +00:00
Add vLLM backend support to webui
This commit is contained in:
@@ -9,7 +9,7 @@ import {
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DialogHeader,
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DialogTitle,
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} from "@/components/ui/dialog";
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import { type CreateInstanceOptions } from "@/types/instance";
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import { BackendType, type BackendTypeValue, type CreateInstanceOptions } from "@/types/instance";
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import { backendsApi } from "@/lib/api";
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import { toast } from "sonner";
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@@ -25,6 +25,7 @@ const ParseCommandDialog: React.FC<ParseCommandDialogProps> = ({
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onParsed,
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}) => {
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const [command, setCommand] = useState('');
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const [backendType, setBackendType] = useState<BackendTypeValue>(BackendType.LLAMA_CPP);
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const [loading, setLoading] = useState(false);
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const [error, setError] = useState<string | null>(null);
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@@ -38,18 +39,31 @@ const ParseCommandDialog: React.FC<ParseCommandDialogProps> = ({
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setError(null);
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try {
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const options = await backendsApi.llamaCpp.parseCommand(command);
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let options: CreateInstanceOptions;
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// Parse based on selected backend type
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switch (backendType) {
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case BackendType.LLAMA_CPP:
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options = await backendsApi.llamaCpp.parseCommand(command);
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break;
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case BackendType.MLX_LM:
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options = await backendsApi.mlx.parseCommand(command);
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break;
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case BackendType.VLLM:
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options = await backendsApi.vllm.parseCommand(command);
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break;
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default:
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throw new Error(`Unsupported backend type: ${backendType}`);
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}
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onParsed(options);
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onOpenChange(false);
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// Reset form
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setCommand('');
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setError(null);
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// Show success toast
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toast.success('Command parsed successfully');
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} catch (err) {
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const errorMessage = err instanceof Error ? err.message : 'Failed to parse command';
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setError(errorMessage);
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// Show error toast
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toast.error('Failed to parse command', {
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description: errorMessage
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});
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@@ -60,31 +74,58 @@ const ParseCommandDialog: React.FC<ParseCommandDialogProps> = ({
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const handleOpenChange = (open: boolean) => {
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if (!open) {
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// Reset form when closing
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setCommand('');
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setBackendType(BackendType.LLAMA_CPP);
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setError(null);
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}
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onOpenChange(open);
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};
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const getPlaceholderForBackend = (backendType: BackendTypeValue): string => {
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switch (backendType) {
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case BackendType.LLAMA_CPP:
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return "llama-server --model /path/to/model.gguf --gpu-layers 32 --ctx-size 4096";
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case BackendType.MLX_LM:
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return "mlx_lm.server --model mlx-community/Mistral-7B-Instruct-v0.3-4bit --host 0.0.0.0 --port 8080";
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case BackendType.VLLM:
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return "vllm serve --model microsoft/DialoGPT-medium --tensor-parallel-size 2 --gpu-memory-utilization 0.9";
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default:
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return "Enter your command here...";
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}
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};
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return (
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<Dialog open={open} onOpenChange={handleOpenChange}>
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<DialogContent className="sm:max-w-[600px]">
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<DialogHeader>
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<DialogTitle>Parse Llama Server Command</DialogTitle>
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<DialogTitle>Parse Backend Command</DialogTitle>
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<DialogDescription>
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Paste your llama-server command to automatically populate the form fields
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Select your backend type and paste the command to automatically populate the form fields
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</DialogDescription>
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</DialogHeader>
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<div className="space-y-4">
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<div>
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<Label htmlFor="backend-type">Backend Type</Label>
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<select
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id="backend-type"
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value={backendType}
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onChange={(e) => setBackendType(e.target.value as BackendTypeValue)}
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className="flex h-10 w-full rounded-md border border-input bg-background px-3 py-2 text-sm ring-offset-background file:border-0 file:bg-transparent file:text-sm file:font-medium placeholder:text-muted-foreground focus-visible:outline-none focus-visible:ring-2 focus-visible:ring-ring focus-visible:ring-offset-2 disabled:cursor-not-allowed disabled:opacity-50"
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>
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<option value={BackendType.LLAMA_CPP}>Llama Server</option>
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<option value={BackendType.MLX_LM}>MLX LM</option>
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<option value={BackendType.VLLM}>vLLM</option>
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</select>
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</div>
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<div>
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<Label htmlFor="command">Command</Label>
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<textarea
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id="command"
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value={command}
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onChange={(e) => setCommand(e.target.value)}
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placeholder="llama-server --model /path/to/model.gguf --gpu-layers 32 --ctx-size 4096"
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placeholder={getPlaceholderForBackend(backendType)}
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className="w-full h-32 p-3 mt-2 border border-input rounded-md font-mono text-sm resize-vertical focus:outline-none focus:ring-2 focus:ring-ring focus:ring-offset-2"
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/>
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</div>
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@@ -39,6 +39,7 @@ const ZodFormField: React.FC<ZodFormFieldProps> = ({ fieldKey, value, onChange }
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>
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<option value={BackendType.LLAMA_CPP}>Llama Server</option>
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<option value={BackendType.MLX_LM}>MLX LM</option>
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<option value={BackendType.VLLM}>vLLM</option>
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</select>
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{config.description && (
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<p className="text-sm text-muted-foreground">{config.description}</p>
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@@ -101,6 +101,14 @@ export const backendsApi = {
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body: JSON.stringify({ command }),
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}),
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},
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vllm: {
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// POST /backends/vllm/parse-command
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parseCommand: (command: string) =>
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apiCall<CreateInstanceOptions>('/backends/vllm/parse-command', {
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method: 'POST',
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body: JSON.stringify({ command }),
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}),
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},
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};
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// Instance API functions
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@@ -2,13 +2,17 @@ import {
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type CreateInstanceOptions,
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type LlamaCppBackendOptions,
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type MlxBackendOptions,
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type VllmBackendOptions,
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LlamaCppBackendOptionsSchema,
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MlxBackendOptionsSchema,
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VllmBackendOptionsSchema,
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getAllFieldKeys,
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getAllLlamaCppFieldKeys,
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getAllMlxFieldKeys,
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getAllVllmFieldKeys,
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getLlamaCppFieldType,
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getMlxFieldType
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getMlxFieldType,
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getVllmFieldType
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} from '@/schemas/instanceOptions'
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// Instance-level basic fields (not backend-specific)
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@@ -117,6 +121,31 @@ const basicMlxFieldsConfig: Record<string, {
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}
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}
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// vLLM backend-specific basic fields
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const basicVllmFieldsConfig: Record<string, {
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label: string
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description?: string
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placeholder?: string
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required?: boolean
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}> = {
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model: {
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label: 'Model',
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placeholder: 'microsoft/DialoGPT-medium',
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description: 'The name or path of the Hugging Face model to use',
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required: true
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},
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tensor_parallel_size: {
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label: 'Tensor Parallel Size',
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placeholder: '1',
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description: 'Number of GPUs to use for distributed serving'
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},
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gpu_memory_utilization: {
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label: 'GPU Memory Utilization',
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placeholder: '0.9',
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description: 'The fraction of GPU memory to be used for the model executor'
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}
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}
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function isBasicField(key: keyof CreateInstanceOptions): boolean {
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return key in basicFieldsConfig
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}
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@@ -134,6 +163,8 @@ export function getAdvancedFields(): (keyof CreateInstanceOptions)[] {
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export function getBasicBackendFields(backendType?: string): string[] {
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if (backendType === 'mlx_lm') {
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return Object.keys(basicMlxFieldsConfig)
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} else if (backendType === 'vllm') {
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return Object.keys(basicVllmFieldsConfig)
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} else if (backendType === 'llama_cpp') {
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return Object.keys(basicLlamaCppFieldsConfig)
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}
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@@ -144,6 +175,8 @@ export function getBasicBackendFields(backendType?: string): string[] {
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export function getAdvancedBackendFields(backendType?: string): string[] {
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if (backendType === 'mlx_lm') {
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return getAllMlxFieldKeys().filter(key => !(key in basicMlxFieldsConfig))
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} else if (backendType === 'vllm') {
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return getAllVllmFieldKeys().filter(key => !(key in basicVllmFieldsConfig))
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} else if (backendType === 'llama_cpp') {
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return getAllLlamaCppFieldKeys().filter(key => !(key in basicLlamaCppFieldsConfig))
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}
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@@ -159,7 +192,8 @@ export const basicBackendFieldsConfig: Record<string, {
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required?: boolean
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}> = {
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...basicLlamaCppFieldsConfig,
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...basicMlxFieldsConfig
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...basicMlxFieldsConfig,
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...basicVllmFieldsConfig
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}
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// Get field type for any backend option (union type)
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@@ -182,6 +216,15 @@ export function getBackendFieldType(key: string): 'text' | 'number' | 'boolean'
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// Schema might not be available
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}
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// Try vLLM schema
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try {
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if (VllmBackendOptionsSchema.shape && key in VllmBackendOptionsSchema.shape) {
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return getVllmFieldType(key as keyof VllmBackendOptions)
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}
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} catch {
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// Schema might not be available
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}
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// Default fallback
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return 'text'
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}
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4
webui/src/schemas/backends/index.ts
Normal file
4
webui/src/schemas/backends/index.ts
Normal file
@@ -0,0 +1,4 @@
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// Re-export all backend schemas from one place
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export * from './llamacpp'
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export * from './mlx'
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export * from './vllm'
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192
webui/src/schemas/backends/llamacpp.ts
Normal file
192
webui/src/schemas/backends/llamacpp.ts
Normal file
@@ -0,0 +1,192 @@
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import { z } from 'zod'
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// Define the LlamaCpp backend options schema
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export const LlamaCppBackendOptionsSchema = z.object({
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// Common params
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verbose_prompt: z.boolean().optional(),
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threads: z.number().optional(),
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threads_batch: z.number().optional(),
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cpu_mask: z.string().optional(),
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cpu_range: z.string().optional(),
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cpu_strict: z.number().optional(),
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prio: z.number().optional(),
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poll: z.number().optional(),
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cpu_mask_batch: z.string().optional(),
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cpu_range_batch: z.string().optional(),
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cpu_strict_batch: z.number().optional(),
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prio_batch: z.number().optional(),
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poll_batch: z.number().optional(),
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ctx_size: z.number().optional(),
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predict: z.number().optional(),
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batch_size: z.number().optional(),
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ubatch_size: z.number().optional(),
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keep: z.number().optional(),
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flash_attn: z.boolean().optional(),
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no_perf: z.boolean().optional(),
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escape: z.boolean().optional(),
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no_escape: z.boolean().optional(),
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rope_scaling: z.string().optional(),
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rope_scale: z.number().optional(),
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rope_freq_base: z.number().optional(),
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rope_freq_scale: z.number().optional(),
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yarn_orig_ctx: z.number().optional(),
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yarn_ext_factor: z.number().optional(),
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yarn_attn_factor: z.number().optional(),
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yarn_beta_slow: z.number().optional(),
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yarn_beta_fast: z.number().optional(),
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dump_kv_cache: z.boolean().optional(),
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no_kv_offload: z.boolean().optional(),
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cache_type_k: z.string().optional(),
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cache_type_v: z.string().optional(),
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defrag_thold: z.number().optional(),
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parallel: z.number().optional(),
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mlock: z.boolean().optional(),
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no_mmap: z.boolean().optional(),
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numa: z.string().optional(),
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device: z.string().optional(),
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override_tensor: z.array(z.string()).optional(),
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gpu_layers: z.number().optional(),
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split_mode: z.string().optional(),
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tensor_split: z.string().optional(),
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main_gpu: z.number().optional(),
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check_tensors: z.boolean().optional(),
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override_kv: z.array(z.string()).optional(),
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lora: z.array(z.string()).optional(),
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lora_scaled: z.array(z.string()).optional(),
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control_vector: z.array(z.string()).optional(),
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control_vector_scaled: z.array(z.string()).optional(),
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control_vector_layer_range: z.string().optional(),
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model: z.string().optional(),
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model_url: z.string().optional(),
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hf_repo: z.string().optional(),
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hf_repo_draft: z.string().optional(),
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hf_file: z.string().optional(),
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hf_repo_v: z.string().optional(),
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hf_file_v: z.string().optional(),
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hf_token: z.string().optional(),
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log_disable: z.boolean().optional(),
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log_file: z.string().optional(),
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log_colors: z.boolean().optional(),
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verbose: z.boolean().optional(),
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verbosity: z.number().optional(),
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log_prefix: z.boolean().optional(),
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log_timestamps: z.boolean().optional(),
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// Sampling params
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samplers: z.string().optional(),
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seed: z.number().optional(),
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sampling_seq: z.string().optional(),
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ignore_eos: z.boolean().optional(),
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temp: z.number().optional(),
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top_k: z.number().optional(),
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top_p: z.number().optional(),
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min_p: z.number().optional(),
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xtc_probability: z.number().optional(),
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xtc_threshold: z.number().optional(),
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typical: z.number().optional(),
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repeat_last_n: z.number().optional(),
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repeat_penalty: z.number().optional(),
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presence_penalty: z.number().optional(),
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frequency_penalty: z.number().optional(),
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dry_multiplier: z.number().optional(),
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dry_base: z.number().optional(),
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dry_allowed_length: z.number().optional(),
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dry_penalty_last_n: z.number().optional(),
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dry_sequence_breaker: z.array(z.string()).optional(),
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dynatemp_range: z.number().optional(),
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dynatemp_exp: z.number().optional(),
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mirostat: z.number().optional(),
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mirostat_lr: z.number().optional(),
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mirostat_ent: z.number().optional(),
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logit_bias: z.array(z.string()).optional(),
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grammar: z.string().optional(),
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grammar_file: z.string().optional(),
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json_schema: z.string().optional(),
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json_schema_file: z.string().optional(),
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// Example-specific params
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no_context_shift: z.boolean().optional(),
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special: z.boolean().optional(),
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no_warmup: z.boolean().optional(),
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spm_infill: z.boolean().optional(),
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pooling: z.string().optional(),
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cont_batching: z.boolean().optional(),
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no_cont_batching: z.boolean().optional(),
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mmproj: z.string().optional(),
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mmproj_url: z.string().optional(),
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no_mmproj: z.boolean().optional(),
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no_mmproj_offload: z.boolean().optional(),
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alias: z.string().optional(),
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host: z.string().optional(),
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port: z.number().optional(),
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path: z.string().optional(),
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no_webui: z.boolean().optional(),
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embedding: z.boolean().optional(),
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reranking: z.boolean().optional(),
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api_key: z.string().optional(),
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api_key_file: z.string().optional(),
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ssl_key_file: z.string().optional(),
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ssl_cert_file: z.string().optional(),
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chat_template_kwargs: z.string().optional(),
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timeout: z.number().optional(),
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threads_http: z.number().optional(),
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cache_reuse: z.number().optional(),
|
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metrics: z.boolean().optional(),
|
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slots: z.boolean().optional(),
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props: z.boolean().optional(),
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no_slots: z.boolean().optional(),
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slot_save_path: z.string().optional(),
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jinja: z.boolean().optional(),
|
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reasoning_format: z.string().optional(),
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reasoning_budget: z.number().optional(),
|
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chat_template: z.string().optional(),
|
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chat_template_file: z.string().optional(),
|
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no_prefill_assistant: z.boolean().optional(),
|
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slot_prompt_similarity: z.number().optional(),
|
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lora_init_without_apply: z.boolean().optional(),
|
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draft_max: z.number().optional(),
|
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draft_min: z.number().optional(),
|
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draft_p_min: z.number().optional(),
|
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ctx_size_draft: z.number().optional(),
|
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device_draft: z.string().optional(),
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gpu_layers_draft: z.number().optional(),
|
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model_draft: z.string().optional(),
|
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cache_type_k_draft: z.string().optional(),
|
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cache_type_v_draft: z.string().optional(),
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|
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// Audio/TTS params
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model_vocoder: z.string().optional(),
|
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tts_use_guide_tokens: z.boolean().optional(),
|
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|
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// Default model params
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embd_bge_small_en_default: z.boolean().optional(),
|
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embd_e5_small_en_default: z.boolean().optional(),
|
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embd_gte_small_default: z.boolean().optional(),
|
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fim_qwen_1_5b_default: z.boolean().optional(),
|
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fim_qwen_3b_default: z.boolean().optional(),
|
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fim_qwen_7b_default: z.boolean().optional(),
|
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fim_qwen_7b_spec: z.boolean().optional(),
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fim_qwen_14b_spec: z.boolean().optional(),
|
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})
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// Infer the TypeScript type from the schema
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export type LlamaCppBackendOptions = z.infer<typeof LlamaCppBackendOptionsSchema>
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// Helper to get all LlamaCpp backend option field keys
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export function getAllLlamaCppFieldKeys(): (keyof LlamaCppBackendOptions)[] {
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return Object.keys(LlamaCppBackendOptionsSchema.shape) as (keyof LlamaCppBackendOptions)[]
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}
|
||||
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||||
// Get field type for LlamaCpp backend options
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||||
export function getLlamaCppFieldType(key: keyof LlamaCppBackendOptions): 'text' | 'number' | 'boolean' | 'array' {
|
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const fieldSchema = LlamaCppBackendOptionsSchema.shape[key]
|
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if (!fieldSchema) return 'text'
|
||||
|
||||
// Handle ZodOptional wrapper
|
||||
const innerSchema = fieldSchema instanceof z.ZodOptional ? fieldSchema.unwrap() : fieldSchema
|
||||
|
||||
if (innerSchema instanceof z.ZodBoolean) return 'boolean'
|
||||
if (innerSchema instanceof z.ZodNumber) return 'number'
|
||||
if (innerSchema instanceof z.ZodArray) return 'array'
|
||||
return 'text' // ZodString and others default to text
|
||||
}
|
||||
51
webui/src/schemas/backends/mlx.ts
Normal file
51
webui/src/schemas/backends/mlx.ts
Normal file
@@ -0,0 +1,51 @@
|
||||
import { z } from 'zod'
|
||||
|
||||
// Define the MLX backend options schema
|
||||
export const MlxBackendOptionsSchema = z.object({
|
||||
// Basic connection options
|
||||
model: z.string().optional(),
|
||||
host: z.string().optional(),
|
||||
port: z.number().optional(),
|
||||
|
||||
// Model and adapter options
|
||||
adapter_path: z.string().optional(),
|
||||
draft_model: z.string().optional(),
|
||||
num_draft_tokens: z.number().optional(),
|
||||
trust_remote_code: z.boolean().optional(),
|
||||
|
||||
// Logging and templates
|
||||
log_level: z.enum(['DEBUG', 'INFO', 'WARNING', 'ERROR', 'CRITICAL']).optional(),
|
||||
chat_template: z.string().optional(),
|
||||
use_default_chat_template: z.boolean().optional(),
|
||||
chat_template_args: z.string().optional(), // JSON string
|
||||
|
||||
// Sampling defaults
|
||||
temp: z.number().optional(), // Note: MLX uses "temp" not "temperature"
|
||||
top_p: z.number().optional(),
|
||||
top_k: z.number().optional(),
|
||||
min_p: z.number().optional(),
|
||||
max_tokens: z.number().optional(),
|
||||
})
|
||||
|
||||
// Infer the TypeScript type from the schema
|
||||
export type MlxBackendOptions = z.infer<typeof MlxBackendOptionsSchema>
|
||||
|
||||
// Helper to get all MLX backend option field keys
|
||||
export function getAllMlxFieldKeys(): (keyof MlxBackendOptions)[] {
|
||||
return Object.keys(MlxBackendOptionsSchema.shape) as (keyof MlxBackendOptions)[]
|
||||
}
|
||||
|
||||
// Get field type for MLX backend options
|
||||
export function getMlxFieldType(key: keyof MlxBackendOptions): 'text' | 'number' | 'boolean' | 'array' {
|
||||
const fieldSchema = MlxBackendOptionsSchema.shape[key]
|
||||
if (!fieldSchema) return 'text'
|
||||
|
||||
// Handle ZodOptional wrapper
|
||||
const innerSchema = fieldSchema instanceof z.ZodOptional ? fieldSchema.unwrap() : fieldSchema
|
||||
|
||||
if (innerSchema instanceof z.ZodBoolean) return 'boolean'
|
||||
if (innerSchema instanceof z.ZodNumber) return 'number'
|
||||
if (innerSchema instanceof z.ZodArray) return 'array'
|
||||
if (innerSchema instanceof z.ZodEnum) return 'text' // Enum treated as text/select
|
||||
return 'text' // ZodString and others default to text
|
||||
}
|
||||
150
webui/src/schemas/backends/vllm.ts
Normal file
150
webui/src/schemas/backends/vllm.ts
Normal file
@@ -0,0 +1,150 @@
|
||||
import { z } from 'zod'
|
||||
|
||||
// Define the vLLM backend options schema
|
||||
export const VllmBackendOptionsSchema = z.object({
|
||||
// Basic connection options (auto-assigned by llamactl)
|
||||
host: z.string().optional(),
|
||||
port: z.number().optional(),
|
||||
|
||||
// Model and engine configuration
|
||||
model: z.string().optional(),
|
||||
tokenizer: z.string().optional(),
|
||||
skip_tokenizer_init: z.boolean().optional(),
|
||||
revision: z.string().optional(),
|
||||
code_revision: z.string().optional(),
|
||||
tokenizer_revision: z.string().optional(),
|
||||
tokenizer_mode: z.string().optional(),
|
||||
trust_remote_code: z.boolean().optional(),
|
||||
download_dir: z.string().optional(),
|
||||
load_format: z.string().optional(),
|
||||
config_format: z.string().optional(),
|
||||
dtype: z.string().optional(),
|
||||
kv_cache_dtype: z.string().optional(),
|
||||
quantization_param_path: z.string().optional(),
|
||||
seed: z.number().optional(),
|
||||
max_model_len: z.number().optional(),
|
||||
guided_decoding_backend: z.string().optional(),
|
||||
distributed_executor_backend: z.string().optional(),
|
||||
worker_use_ray: z.boolean().optional(),
|
||||
ray_workers_use_nsight: z.boolean().optional(),
|
||||
|
||||
// Performance and serving configuration
|
||||
block_size: z.number().optional(),
|
||||
enable_prefix_caching: z.boolean().optional(),
|
||||
disable_sliding_window: z.boolean().optional(),
|
||||
use_v2_block_manager: z.boolean().optional(),
|
||||
num_lookahead_slots: z.number().optional(),
|
||||
swap_space: z.number().optional(),
|
||||
cpu_offload_gb: z.number().optional(),
|
||||
gpu_memory_utilization: z.number().optional(),
|
||||
num_gpu_blocks_override: z.number().optional(),
|
||||
max_num_batched_tokens: z.number().optional(),
|
||||
max_num_seqs: z.number().optional(),
|
||||
max_logprobs: z.number().optional(),
|
||||
disable_log_stats: z.boolean().optional(),
|
||||
quantization: z.string().optional(),
|
||||
rope_scaling: z.string().optional(),
|
||||
rope_theta: z.number().optional(),
|
||||
enforce_eager: z.boolean().optional(),
|
||||
max_context_len_to_capture: z.number().optional(),
|
||||
max_seq_len_to_capture: z.number().optional(),
|
||||
disable_custom_all_reduce: z.boolean().optional(),
|
||||
tokenizer_pool_size: z.number().optional(),
|
||||
tokenizer_pool_type: z.string().optional(),
|
||||
tokenizer_pool_extra_config: z.string().optional(),
|
||||
enable_lora_bias: z.boolean().optional(),
|
||||
lora_extra_vocab_size: z.number().optional(),
|
||||
lora_rank: z.number().optional(),
|
||||
prompt_lookback_distance: z.number().optional(),
|
||||
preemption_mode: z.string().optional(),
|
||||
|
||||
// Distributed and parallel processing
|
||||
tensor_parallel_size: z.number().optional(),
|
||||
pipeline_parallel_size: z.number().optional(),
|
||||
max_parallel_loading_workers: z.number().optional(),
|
||||
disable_async_output_proc: z.boolean().optional(),
|
||||
worker_class: z.string().optional(),
|
||||
enabled_lora_modules: z.string().optional(),
|
||||
max_lora_rank: z.number().optional(),
|
||||
fully_sharded_loras: z.boolean().optional(),
|
||||
lora_modules: z.string().optional(),
|
||||
prompt_adapters: z.string().optional(),
|
||||
max_prompt_adapter_token: z.number().optional(),
|
||||
device: z.string().optional(),
|
||||
scheduler_delay: z.number().optional(),
|
||||
enable_chunked_prefill: z.boolean().optional(),
|
||||
speculative_model: z.string().optional(),
|
||||
speculative_model_quantization: z.string().optional(),
|
||||
speculative_revision: z.string().optional(),
|
||||
speculative_max_model_len: z.number().optional(),
|
||||
speculative_disable_by_batch_size: z.number().optional(),
|
||||
ngpt_speculative_length: z.number().optional(),
|
||||
speculative_disable_mqa: z.boolean().optional(),
|
||||
model_loader_extra_config: z.string().optional(),
|
||||
ignore_patterns: z.string().optional(),
|
||||
preloaded_lora_modules: z.string().optional(),
|
||||
|
||||
// OpenAI server specific options
|
||||
uds: z.string().optional(),
|
||||
uvicorn_log_level: z.string().optional(),
|
||||
response_role: z.string().optional(),
|
||||
ssl_keyfile: z.string().optional(),
|
||||
ssl_certfile: z.string().optional(),
|
||||
ssl_ca_certs: z.string().optional(),
|
||||
ssl_cert_reqs: z.number().optional(),
|
||||
root_path: z.string().optional(),
|
||||
middleware: z.array(z.string()).optional(),
|
||||
return_tokens_as_token_ids: z.boolean().optional(),
|
||||
disable_frontend_multiprocessing: z.boolean().optional(),
|
||||
enable_auto_tool_choice: z.boolean().optional(),
|
||||
tool_call_parser: z.string().optional(),
|
||||
tool_server: z.string().optional(),
|
||||
chat_template: z.string().optional(),
|
||||
chat_template_content_format: z.string().optional(),
|
||||
allow_credentials: z.boolean().optional(),
|
||||
allowed_origins: z.array(z.string()).optional(),
|
||||
allowed_methods: z.array(z.string()).optional(),
|
||||
allowed_headers: z.array(z.string()).optional(),
|
||||
api_key: z.array(z.string()).optional(),
|
||||
enable_log_outputs: z.boolean().optional(),
|
||||
enable_token_usage: z.boolean().optional(),
|
||||
enable_async_engine_debug: z.boolean().optional(),
|
||||
engine_use_ray: z.boolean().optional(),
|
||||
disable_log_requests: z.boolean().optional(),
|
||||
max_log_len: z.number().optional(),
|
||||
|
||||
// Additional engine configuration
|
||||
task: z.string().optional(),
|
||||
multi_modal_config: z.string().optional(),
|
||||
limit_mm_per_prompt: z.string().optional(),
|
||||
enable_sleep_mode: z.boolean().optional(),
|
||||
enable_chunking_request: z.boolean().optional(),
|
||||
compilation_config: z.string().optional(),
|
||||
disable_sliding_window_mask: z.boolean().optional(),
|
||||
enable_trtllm_engine_latency: z.boolean().optional(),
|
||||
override_pooling_config: z.string().optional(),
|
||||
override_neuron_config: z.string().optional(),
|
||||
override_kv_cache_align_size: z.number().optional(),
|
||||
})
|
||||
|
||||
// Infer the TypeScript type from the schema
|
||||
export type VllmBackendOptions = z.infer<typeof VllmBackendOptionsSchema>
|
||||
|
||||
// Helper to get all vLLM backend option field keys
|
||||
export function getAllVllmFieldKeys(): (keyof VllmBackendOptions)[] {
|
||||
return Object.keys(VllmBackendOptionsSchema.shape) as (keyof VllmBackendOptions)[]
|
||||
}
|
||||
|
||||
// Get field type for vLLM backend options
|
||||
export function getVllmFieldType(key: keyof VllmBackendOptions): 'text' | 'number' | 'boolean' | 'array' {
|
||||
const fieldSchema = VllmBackendOptionsSchema.shape[key]
|
||||
if (!fieldSchema) return 'text'
|
||||
|
||||
// Handle ZodOptional wrapper
|
||||
const innerSchema = fieldSchema instanceof z.ZodOptional ? fieldSchema.unwrap() : fieldSchema
|
||||
|
||||
if (innerSchema instanceof z.ZodBoolean) return 'boolean'
|
||||
if (innerSchema instanceof z.ZodNumber) return 'number'
|
||||
if (innerSchema instanceof z.ZodArray) return 'array'
|
||||
return 'text' // ZodString and others default to text
|
||||
}
|
||||
@@ -1,206 +1,27 @@
|
||||
import { BackendType } from '@/types/instance'
|
||||
import { z } from 'zod'
|
||||
|
||||
// Define the LlamaCpp backend options schema
|
||||
export const LlamaCppBackendOptionsSchema = z.object({
|
||||
// Common params
|
||||
verbose_prompt: z.boolean().optional(),
|
||||
threads: z.number().optional(),
|
||||
threads_batch: z.number().optional(),
|
||||
cpu_mask: z.string().optional(),
|
||||
cpu_range: z.string().optional(),
|
||||
cpu_strict: z.number().optional(),
|
||||
prio: z.number().optional(),
|
||||
poll: z.number().optional(),
|
||||
cpu_mask_batch: z.string().optional(),
|
||||
cpu_range_batch: z.string().optional(),
|
||||
cpu_strict_batch: z.number().optional(),
|
||||
prio_batch: z.number().optional(),
|
||||
poll_batch: z.number().optional(),
|
||||
ctx_size: z.number().optional(),
|
||||
predict: z.number().optional(),
|
||||
batch_size: z.number().optional(),
|
||||
ubatch_size: z.number().optional(),
|
||||
keep: z.number().optional(),
|
||||
flash_attn: z.boolean().optional(),
|
||||
no_perf: z.boolean().optional(),
|
||||
escape: z.boolean().optional(),
|
||||
no_escape: z.boolean().optional(),
|
||||
rope_scaling: z.string().optional(),
|
||||
rope_scale: z.number().optional(),
|
||||
rope_freq_base: z.number().optional(),
|
||||
rope_freq_scale: z.number().optional(),
|
||||
yarn_orig_ctx: z.number().optional(),
|
||||
yarn_ext_factor: z.number().optional(),
|
||||
yarn_attn_factor: z.number().optional(),
|
||||
yarn_beta_slow: z.number().optional(),
|
||||
yarn_beta_fast: z.number().optional(),
|
||||
dump_kv_cache: z.boolean().optional(),
|
||||
no_kv_offload: z.boolean().optional(),
|
||||
cache_type_k: z.string().optional(),
|
||||
cache_type_v: z.string().optional(),
|
||||
defrag_thold: z.number().optional(),
|
||||
parallel: z.number().optional(),
|
||||
mlock: z.boolean().optional(),
|
||||
no_mmap: z.boolean().optional(),
|
||||
numa: z.string().optional(),
|
||||
device: z.string().optional(),
|
||||
override_tensor: z.array(z.string()).optional(),
|
||||
gpu_layers: z.number().optional(),
|
||||
split_mode: z.string().optional(),
|
||||
tensor_split: z.string().optional(),
|
||||
main_gpu: z.number().optional(),
|
||||
check_tensors: z.boolean().optional(),
|
||||
override_kv: z.array(z.string()).optional(),
|
||||
lora: z.array(z.string()).optional(),
|
||||
lora_scaled: z.array(z.string()).optional(),
|
||||
control_vector: z.array(z.string()).optional(),
|
||||
control_vector_scaled: z.array(z.string()).optional(),
|
||||
control_vector_layer_range: z.string().optional(),
|
||||
model: z.string().optional(),
|
||||
model_url: z.string().optional(),
|
||||
hf_repo: z.string().optional(),
|
||||
hf_repo_draft: z.string().optional(),
|
||||
hf_file: z.string().optional(),
|
||||
hf_repo_v: z.string().optional(),
|
||||
hf_file_v: z.string().optional(),
|
||||
hf_token: z.string().optional(),
|
||||
log_disable: z.boolean().optional(),
|
||||
log_file: z.string().optional(),
|
||||
log_colors: z.boolean().optional(),
|
||||
verbose: z.boolean().optional(),
|
||||
verbosity: z.number().optional(),
|
||||
log_prefix: z.boolean().optional(),
|
||||
log_timestamps: z.boolean().optional(),
|
||||
|
||||
// Sampling params
|
||||
samplers: z.string().optional(),
|
||||
seed: z.number().optional(),
|
||||
sampling_seq: z.string().optional(),
|
||||
ignore_eos: z.boolean().optional(),
|
||||
temp: z.number().optional(),
|
||||
top_k: z.number().optional(),
|
||||
top_p: z.number().optional(),
|
||||
min_p: z.number().optional(),
|
||||
xtc_probability: z.number().optional(),
|
||||
xtc_threshold: z.number().optional(),
|
||||
typical: z.number().optional(),
|
||||
repeat_last_n: z.number().optional(),
|
||||
repeat_penalty: z.number().optional(),
|
||||
presence_penalty: z.number().optional(),
|
||||
frequency_penalty: z.number().optional(),
|
||||
dry_multiplier: z.number().optional(),
|
||||
dry_base: z.number().optional(),
|
||||
dry_allowed_length: z.number().optional(),
|
||||
dry_penalty_last_n: z.number().optional(),
|
||||
dry_sequence_breaker: z.array(z.string()).optional(),
|
||||
dynatemp_range: z.number().optional(),
|
||||
dynatemp_exp: z.number().optional(),
|
||||
mirostat: z.number().optional(),
|
||||
mirostat_lr: z.number().optional(),
|
||||
mirostat_ent: z.number().optional(),
|
||||
logit_bias: z.array(z.string()).optional(),
|
||||
grammar: z.string().optional(),
|
||||
grammar_file: z.string().optional(),
|
||||
json_schema: z.string().optional(),
|
||||
json_schema_file: z.string().optional(),
|
||||
|
||||
// Example-specific params
|
||||
no_context_shift: z.boolean().optional(),
|
||||
special: z.boolean().optional(),
|
||||
no_warmup: z.boolean().optional(),
|
||||
spm_infill: z.boolean().optional(),
|
||||
pooling: z.string().optional(),
|
||||
cont_batching: z.boolean().optional(),
|
||||
no_cont_batching: z.boolean().optional(),
|
||||
mmproj: z.string().optional(),
|
||||
mmproj_url: z.string().optional(),
|
||||
no_mmproj: z.boolean().optional(),
|
||||
no_mmproj_offload: z.boolean().optional(),
|
||||
alias: z.string().optional(),
|
||||
host: z.string().optional(),
|
||||
port: z.number().optional(),
|
||||
path: z.string().optional(),
|
||||
no_webui: z.boolean().optional(),
|
||||
embedding: z.boolean().optional(),
|
||||
reranking: z.boolean().optional(),
|
||||
api_key: z.string().optional(),
|
||||
api_key_file: z.string().optional(),
|
||||
ssl_key_file: z.string().optional(),
|
||||
ssl_cert_file: z.string().optional(),
|
||||
chat_template_kwargs: z.string().optional(),
|
||||
timeout: z.number().optional(),
|
||||
threads_http: z.number().optional(),
|
||||
cache_reuse: z.number().optional(),
|
||||
metrics: z.boolean().optional(),
|
||||
slots: z.boolean().optional(),
|
||||
props: z.boolean().optional(),
|
||||
no_slots: z.boolean().optional(),
|
||||
slot_save_path: z.string().optional(),
|
||||
jinja: z.boolean().optional(),
|
||||
reasoning_format: z.string().optional(),
|
||||
reasoning_budget: z.number().optional(),
|
||||
chat_template: z.string().optional(),
|
||||
chat_template_file: z.string().optional(),
|
||||
no_prefill_assistant: z.boolean().optional(),
|
||||
slot_prompt_similarity: z.number().optional(),
|
||||
lora_init_without_apply: z.boolean().optional(),
|
||||
draft_max: z.number().optional(),
|
||||
draft_min: z.number().optional(),
|
||||
draft_p_min: z.number().optional(),
|
||||
ctx_size_draft: z.number().optional(),
|
||||
device_draft: z.string().optional(),
|
||||
gpu_layers_draft: z.number().optional(),
|
||||
model_draft: z.string().optional(),
|
||||
cache_type_k_draft: z.string().optional(),
|
||||
cache_type_v_draft: z.string().optional(),
|
||||
|
||||
// Audio/TTS params
|
||||
model_vocoder: z.string().optional(),
|
||||
tts_use_guide_tokens: z.boolean().optional(),
|
||||
|
||||
// Default model params
|
||||
embd_bge_small_en_default: z.boolean().optional(),
|
||||
embd_e5_small_en_default: z.boolean().optional(),
|
||||
embd_gte_small_default: z.boolean().optional(),
|
||||
fim_qwen_1_5b_default: z.boolean().optional(),
|
||||
fim_qwen_3b_default: z.boolean().optional(),
|
||||
fim_qwen_7b_default: z.boolean().optional(),
|
||||
fim_qwen_7b_spec: z.boolean().optional(),
|
||||
fim_qwen_14b_spec: z.boolean().optional(),
|
||||
})
|
||||
|
||||
// Define the MLX backend options schema
|
||||
export const MlxBackendOptionsSchema = z.object({
|
||||
// Basic connection options
|
||||
model: z.string().optional(),
|
||||
host: z.string().optional(),
|
||||
port: z.number().optional(),
|
||||
|
||||
// Model and adapter options
|
||||
adapter_path: z.string().optional(),
|
||||
draft_model: z.string().optional(),
|
||||
num_draft_tokens: z.number().optional(),
|
||||
trust_remote_code: z.boolean().optional(),
|
||||
|
||||
// Logging and templates
|
||||
log_level: z.enum(['DEBUG', 'INFO', 'WARNING', 'ERROR', 'CRITICAL']).optional(),
|
||||
chat_template: z.string().optional(),
|
||||
use_default_chat_template: z.boolean().optional(),
|
||||
chat_template_args: z.string().optional(), // JSON string
|
||||
|
||||
// Sampling defaults
|
||||
temp: z.number().optional(), // Note: MLX uses "temp" not "temperature"
|
||||
top_p: z.number().optional(),
|
||||
top_k: z.number().optional(),
|
||||
min_p: z.number().optional(),
|
||||
max_tokens: z.number().optional(),
|
||||
})
|
||||
// Import backend schemas from separate files
|
||||
import {
|
||||
LlamaCppBackendOptionsSchema,
|
||||
type LlamaCppBackendOptions,
|
||||
getAllLlamaCppFieldKeys,
|
||||
getLlamaCppFieldType,
|
||||
MlxBackendOptionsSchema,
|
||||
type MlxBackendOptions,
|
||||
getAllMlxFieldKeys,
|
||||
getMlxFieldType,
|
||||
VllmBackendOptionsSchema,
|
||||
type VllmBackendOptions,
|
||||
getAllVllmFieldKeys,
|
||||
getVllmFieldType
|
||||
} from './backends'
|
||||
|
||||
// Backend options union
|
||||
export const BackendOptionsSchema = z.union([
|
||||
LlamaCppBackendOptionsSchema,
|
||||
MlxBackendOptionsSchema,
|
||||
VllmBackendOptionsSchema,
|
||||
])
|
||||
|
||||
// Define the main create instance options schema
|
||||
@@ -213,13 +34,27 @@ export const CreateInstanceOptionsSchema = z.object({
|
||||
on_demand_start: z.boolean().optional(),
|
||||
|
||||
// Backend configuration
|
||||
backend_type: z.enum([BackendType.LLAMA_CPP, BackendType.MLX_LM]).optional(),
|
||||
backend_type: z.enum([BackendType.LLAMA_CPP, BackendType.MLX_LM, BackendType.VLLM]).optional(),
|
||||
backend_options: BackendOptionsSchema.optional(),
|
||||
})
|
||||
|
||||
// Re-export types and schemas from backend files
|
||||
export {
|
||||
LlamaCppBackendOptionsSchema,
|
||||
MlxBackendOptionsSchema,
|
||||
VllmBackendOptionsSchema,
|
||||
type LlamaCppBackendOptions,
|
||||
type MlxBackendOptions,
|
||||
type VllmBackendOptions,
|
||||
getAllLlamaCppFieldKeys,
|
||||
getAllMlxFieldKeys,
|
||||
getAllVllmFieldKeys,
|
||||
getLlamaCppFieldType,
|
||||
getMlxFieldType,
|
||||
getVllmFieldType
|
||||
}
|
||||
|
||||
// Infer the TypeScript types from the schemas
|
||||
export type LlamaCppBackendOptions = z.infer<typeof LlamaCppBackendOptionsSchema>
|
||||
export type MlxBackendOptions = z.infer<typeof MlxBackendOptionsSchema>
|
||||
export type BackendOptions = z.infer<typeof BackendOptionsSchema>
|
||||
export type CreateInstanceOptions = z.infer<typeof CreateInstanceOptionsSchema>
|
||||
|
||||
@@ -228,16 +63,6 @@ export function getAllFieldKeys(): (keyof CreateInstanceOptions)[] {
|
||||
return Object.keys(CreateInstanceOptionsSchema.shape) as (keyof CreateInstanceOptions)[]
|
||||
}
|
||||
|
||||
// Helper to get all LlamaCpp backend option field keys
|
||||
export function getAllLlamaCppFieldKeys(): (keyof LlamaCppBackendOptions)[] {
|
||||
return Object.keys(LlamaCppBackendOptionsSchema.shape) as (keyof LlamaCppBackendOptions)[]
|
||||
}
|
||||
|
||||
// Helper to get all MLX backend option field keys
|
||||
export function getAllMlxFieldKeys(): (keyof MlxBackendOptions)[] {
|
||||
return Object.keys(MlxBackendOptionsSchema.shape) as (keyof MlxBackendOptions)[]
|
||||
}
|
||||
|
||||
// Get field type from Zod schema
|
||||
export function getFieldType(key: keyof CreateInstanceOptions): 'text' | 'number' | 'boolean' | 'array' | 'object' {
|
||||
const fieldSchema = CreateInstanceOptionsSchema.shape[key]
|
||||
@@ -252,32 +77,3 @@ export function getFieldType(key: keyof CreateInstanceOptions): 'text' | 'number
|
||||
if (innerSchema instanceof z.ZodObject) return 'object'
|
||||
return 'text' // ZodString and others default to text
|
||||
}
|
||||
|
||||
// Get field type for LlamaCpp backend options
|
||||
export function getLlamaCppFieldType(key: keyof LlamaCppBackendOptions): 'text' | 'number' | 'boolean' | 'array' {
|
||||
const fieldSchema = LlamaCppBackendOptionsSchema.shape[key]
|
||||
if (!fieldSchema) return 'text'
|
||||
|
||||
// Handle ZodOptional wrapper
|
||||
const innerSchema = fieldSchema instanceof z.ZodOptional ? fieldSchema.unwrap() : fieldSchema
|
||||
|
||||
if (innerSchema instanceof z.ZodBoolean) return 'boolean'
|
||||
if (innerSchema instanceof z.ZodNumber) return 'number'
|
||||
if (innerSchema instanceof z.ZodArray) return 'array'
|
||||
return 'text' // ZodString and others default to text
|
||||
}
|
||||
|
||||
// Get field type for MLX backend options
|
||||
export function getMlxFieldType(key: keyof MlxBackendOptions): 'text' | 'number' | 'boolean' | 'array' {
|
||||
const fieldSchema = MlxBackendOptionsSchema.shape[key]
|
||||
if (!fieldSchema) return 'text'
|
||||
|
||||
// Handle ZodOptional wrapper
|
||||
const innerSchema = fieldSchema instanceof z.ZodOptional ? fieldSchema.unwrap() : fieldSchema
|
||||
|
||||
if (innerSchema instanceof z.ZodBoolean) return 'boolean'
|
||||
if (innerSchema instanceof z.ZodNumber) return 'number'
|
||||
if (innerSchema instanceof z.ZodArray) return 'array'
|
||||
if (innerSchema instanceof z.ZodEnum) return 'text' // Enum treated as text/select
|
||||
return 'text' // ZodString and others default to text
|
||||
}
|
||||
@@ -5,6 +5,7 @@ export { type CreateInstanceOptions } from '@/schemas/instanceOptions'
|
||||
export const BackendType = {
|
||||
LLAMA_CPP: 'llama_cpp',
|
||||
MLX_LM: 'mlx_lm',
|
||||
VLLM: 'vllm',
|
||||
// MLX_VLM: 'mlx_vlm', // Future expansion
|
||||
} as const
|
||||
|
||||
|
||||
Reference in New Issue
Block a user