mirror of
https://github.com/getcompanion-ai/co-mono.git
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a74c5da112
- Set up npm workspaces for three packages: pi-tui, pi-agent, and pi (pods) - Implemented dual TypeScript configuration: - Root tsconfig.json with path mappings for development and type checking - Package-specific tsconfig.build.json for clean production builds - Configured lockstep versioning with sync script for inter-package dependencies - Added comprehensive documentation for development and publishing workflows - All packages at version 0.5.0 ready for npm publishing
111 lines
2.6 KiB
TypeScript
111 lines
2.6 KiB
TypeScript
import { readFileSync } from "fs";
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import { dirname, join } from "path";
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import { fileURLToPath } from "url";
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import type { GPU } from "./types.js";
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const __filename = fileURLToPath(import.meta.url);
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const __dirname = dirname(__filename);
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interface ModelConfig {
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gpuCount: number;
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gpuTypes?: string[];
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args: string[];
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env?: Record<string, string>;
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notes?: string;
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}
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interface ModelInfo {
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name: string;
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configs: ModelConfig[];
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notes?: string;
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}
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interface ModelsData {
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models: Record<string, ModelInfo>;
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}
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// Load models configuration - resolve relative to this file
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const modelsJsonPath = join(__dirname, "models.json");
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const modelsData: ModelsData = JSON.parse(readFileSync(modelsJsonPath, "utf-8"));
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/**
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* Get the best configuration for a model based on available GPUs
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*/
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export const getModelConfig = (
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modelId: string,
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gpus: GPU[],
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requestedGpuCount: number,
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): { args: string[]; env?: Record<string, string>; notes?: string } | null => {
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const modelInfo = modelsData.models[modelId];
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if (!modelInfo) {
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// Unknown model, no default config
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return null;
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}
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// Extract GPU type from the first GPU name (e.g., "NVIDIA H200" -> "H200")
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const gpuType = gpus[0]?.name?.replace("NVIDIA", "")?.trim()?.split(" ")[0] || "";
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// Find best matching config
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let bestConfig: ModelConfig | null = null;
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for (const config of modelInfo.configs) {
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// Check GPU count
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if (config.gpuCount !== requestedGpuCount) {
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continue;
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}
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// Check GPU type if specified
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if (config.gpuTypes && config.gpuTypes.length > 0) {
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const typeMatches = config.gpuTypes.some((type) => gpuType.includes(type) || type.includes(gpuType));
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if (!typeMatches) {
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continue;
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}
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}
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// This config matches
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bestConfig = config;
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break;
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}
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// If no exact match, try to find a config with just the right GPU count
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if (!bestConfig) {
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for (const config of modelInfo.configs) {
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if (config.gpuCount === requestedGpuCount) {
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bestConfig = config;
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break;
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}
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}
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}
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if (!bestConfig) {
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// No suitable config found
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return null;
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}
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return {
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args: [...bestConfig.args],
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env: bestConfig.env ? { ...bestConfig.env } : undefined,
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notes: bestConfig.notes || modelInfo.notes,
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};
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};
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/**
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* Check if a model is known
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*/
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export const isKnownModel = (modelId: string): boolean => {
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return modelId in modelsData.models;
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};
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/**
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* Get all known models
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*/
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export const getKnownModels = (): string[] => {
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return Object.keys(modelsData.models);
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};
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/**
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* Get model display name
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*/
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export const getModelName = (modelId: string): string => {
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return modelsData.models[modelId]?.name || modelId;
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};
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