Initial monorepo setup with npm workspaces and dual TypeScript configuration

- 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

packages/pods/src/model-configs.ts

@@ -0,0 +1,111 @@
+import { readFileSync } from "fs";
+import { dirname, join } from "path";
+import { fileURLToPath } from "url";
+import type { GPU } from "./types.js";
+
+const __filename = fileURLToPath(import.meta.url);
+const __dirname = dirname(__filename);
+
+interface ModelConfig {
+	gpuCount: number;
+	gpuTypes?: string[];
+	args: string[];
+	env?: Record<string, string>;
+	notes?: string;
+}
+
+interface ModelInfo {
+	name: string;
+	configs: ModelConfig[];
+	notes?: string;
+}
+
+interface ModelsData {
+	models: Record<string, ModelInfo>;
+}
+
+// Load models configuration - resolve relative to this file
+const modelsJsonPath = join(__dirname, "models.json");
+const modelsData: ModelsData = JSON.parse(readFileSync(modelsJsonPath, "utf-8"));
+
+/**
+ * Get the best configuration for a model based on available GPUs
+ */
+export const getModelConfig = (
+	modelId: string,
+	gpus: GPU[],
+	requestedGpuCount: number,
+): { args: string[]; env?: Record<string, string>; notes?: string } | null => {
+	const modelInfo = modelsData.models[modelId];
+	if (!modelInfo) {
+		// Unknown model, no default config
+		return null;
+	}
+
+	// Extract GPU type from the first GPU name (e.g., "NVIDIA H200" -> "H200")
+	const gpuType = gpus[0]?.name?.replace("NVIDIA", "")?.trim()?.split(" ")[0] || "";
+
+	// Find best matching config
+	let bestConfig: ModelConfig | null = null;
+
+	for (const config of modelInfo.configs) {
+		// Check GPU count
+		if (config.gpuCount !== requestedGpuCount) {
+			continue;
+		}
+
+		// Check GPU type if specified
+		if (config.gpuTypes && config.gpuTypes.length > 0) {
+			const typeMatches = config.gpuTypes.some((type) => gpuType.includes(type) || type.includes(gpuType));
+			if (!typeMatches) {
+				continue;
+			}
+		}
+
+		// This config matches
+		bestConfig = config;
+		break;
+	}
+
+	// If no exact match, try to find a config with just the right GPU count
+	if (!bestConfig) {
+		for (const config of modelInfo.configs) {
+			if (config.gpuCount === requestedGpuCount) {
+				bestConfig = config;
+				break;
+			}
+		}
+	}
+
+	if (!bestConfig) {
+		// No suitable config found
+		return null;
+	}
+
+	return {
+		args: [...bestConfig.args],
+		env: bestConfig.env ? { ...bestConfig.env } : undefined,
+		notes: bestConfig.notes || modelInfo.notes,
+	};
+};
+
+/**
+ * Check if a model is known
+ */
+export const isKnownModel = (modelId: string): boolean => {
+	return modelId in modelsData.models;
+};
+
+/**
+ * Get all known models
+ */
+export const getKnownModels = (): string[] => {
+	return Object.keys(modelsData.models);
+};
+
+/**
+ * Get model display name
+ */
+export const getModelName = (modelId: string): string => {
+	return modelsData.models[modelId]?.name || modelId;
+};