195 lines
7.0 KiB
TypeScript
195 lines
7.0 KiB
TypeScript
/**
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* Command Code provider for pi.
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* Connects pi to Command Code's API (https://api.commandcode.ai/alpha/generate).
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*/
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import { existsSync, readFileSync } from "node:fs";
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import { homedir } from "node:os";
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import { join } from "node:path";
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import type { ExtensionAPI } from "@mariozechner/pi-coding-agent";
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const API_BASE = "https://api.commandcode.ai";
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// ---------------------------------------------------------------------------
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// Model definitions
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// ---------------------------------------------------------------------------
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const MODELS = [
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// Premium (Anthropic)
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{ id: "claude-opus-4-7", name: "Claude Opus 4.7 (CC)", reasoning: true, contextWindow: 200_000, maxTokens: 32_000 },
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{ id: "claude-opus-4-6", name: "Claude Opus 4.6 (CC)", reasoning: true, contextWindow: 200_000, maxTokens: 32_000 },
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{ id: "claude-sonnet-4-6", name: "Claude Sonnet 4.6 (CC)", reasoning: true, contextWindow: 200_000, maxTokens: 16_384 },
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{ id: "claude-haiku-4-5-20251001", name: "Claude Haiku 4.5 (CC)", reasoning: true, contextWindow: 200_000, maxTokens: 8_192 },
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// Premium (OpenAI)
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{ id: "gpt-5.5", name: "GPT-5.5 (CC)", reasoning: true, contextWindow: 256_000, maxTokens: 128_000 },
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{ id: "gpt-5.4", name: "GPT-5.4 (CC)", reasoning: true, contextWindow: 256_000, maxTokens: 128_000 },
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{ id: "gpt-5.3-codex", name: "GPT-5.3 Codex (CC)", reasoning: true, contextWindow: 256_000, maxTokens: 128_000 },
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{ id: "gpt-5.4-mini", name: "GPT-5.4 Mini (CC)", reasoning: false, contextWindow: 256_000, maxTokens: 128_000 },
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// Open-source
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{ id: "deepseek/deepseek-v4-pro", name: "DeepSeek V4 Pro (CC)", reasoning: true, contextWindow: 1_000_000, maxTokens: 384_000 },
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{ id: "deepseek/deepseek-v4-flash", name: "DeepSeek V4 Flash (CC)", reasoning: true, contextWindow: 1_000_000, maxTokens: 384_000 },
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{ id: "moonshotai/Kimi-K2.6", name: "Kimi K2.6 (CC)", reasoning: true, contextWindow: 262_144, maxTokens: 131_072 },
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{ id: "moonshotai/Kimi-K2.5", name: "Kimi K2.5 (CC)", reasoning: true, contextWindow: 262_144, maxTokens: 131_072 },
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{ id: "zai-org/GLM-5.1", name: "GLM-5.1 (CC)", reasoning: true, contextWindow: 200_000, maxTokens: 131_072 },
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{ id: "zai-org/GLM-5", name: "GLM-5 (CC)", reasoning: true, contextWindow: 200_000, maxTokens: 131_072 },
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{ id: "MiniMaxAI/MiniMax-M2.7", name: "MiniMax M2.7 (CC)", reasoning: true, contextWindow: 1_048_576, maxTokens: 131_072 },
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{ id: "MiniMaxAI/MiniMax-M2.5", name: "MiniMax M2.5 (CC)", reasoning: true, contextWindow: 1_048_576, maxTokens: 131_072 },
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{ id: "Qwen/Qwen3.6-Max-Preview", name: "Qwen 3.6 Max (CC)", reasoning: true, contextWindow: 1_000_000, maxTokens: 131_072 },
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{ id: "Qwen/Qwen3.6-Plus", name: "Qwen 3.6 Plus (CC)", reasoning: true, contextWindow: 1_000_000, maxTokens: 131_072 },
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];
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// ---------------------------------------------------------------------------
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// Typebox → JSON Schema conversion
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// ---------------------------------------------------------------------------
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function toJsonSchema(schema: any): any {
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if (!schema) return {};
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const s = schema as Record<string, any>;
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const kind = s.kind ?? s.type;
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if (s.enum) {
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return { type: typeof s.enum[0], enum: s.enum };
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}
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switch (kind) {
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case "string":
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case "String":
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return { type: "string" };
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case "number":
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case "Number":
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return { type: "number" };
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case "boolean":
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case "Boolean":
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return { type: "boolean" };
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case "object":
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case "Object": {
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const props: Record<string, any> = {};
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const inferredRequired: string[] = [];
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if (s.properties) {
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for (const [k, v] of Object.entries(s.properties)) {
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props[k] = toJsonSchema(v);
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if (!(v as any).optional && !s.optional?.includes?.(k))
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inferredRequired.push(k);
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}
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}
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const required = Array.isArray(s.required) ? s.required : inferredRequired;
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const out: any = { type: "object" };
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if (Object.keys(props).length) out.properties = props;
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if (required.length) out.required = required;
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return out;
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}
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case "array":
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case "Array":
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return { type: "array", items: toJsonSchema(s.items ?? s.element) };
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case "union":
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case "Union": {
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const variants = s.variants ?? s.anyOf ?? [];
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for (const v of variants) {
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const schema = toJsonSchema(v);
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if (schema && Object.keys(schema).length) return schema;
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}
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return {};
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}
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case "optional":
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case "Optional":
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return toJsonSchema(s.wrapped ?? s.inner);
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default:
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return {};
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}
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}
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function toolsToJson(tools: any[]): any[] {
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if (!tools) return [];
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return tools.map((t) => {
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const schema = t.parameters ? toJsonSchema(t.parameters) : {};
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return {
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type: "function",
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name: t.name,
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description: t.description,
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input_schema: schema,
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};
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});
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}
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function messagesToCC(msgs: any[]): any[] {
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const out: any[] = [];
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for (const m of msgs) {
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if (m.role === "user") {
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out.push({
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role: "user",
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content: typeof m.content === "string" ? m.content : m.content,
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});
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} else if (m.role === "assistant") {
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const parts: any[] = [];
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for (const c of m.content) {
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if (c.type === "text") {
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parts.push({ type: "text", text: c.text });
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} else if (c.type === "thinking") {
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parts.push({ type: "reasoning", text: c.thinking });
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} else if (c.type === "toolCall") {
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parts.push({
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type: "tool-call",
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toolCallId: c.id,
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toolName: c.name,
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input: c.arguments,
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});
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}
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}
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out.push({ role: "assistant", content: parts });
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} else if (m.role === "toolResult") {
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const text = (m.content ?? [])
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.filter((c: any) => c.type === "text")
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.map((c: any) => c.text ?? "")
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.join("\n");
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out.push({
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role: "tool",
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content: [
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{
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type: "tool-result",
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toolCallId: m.toolCallId,
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toolName: m.toolName,
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output: m.isError
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? { type: "error-text", value: text }
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: { type: "text", value: text },
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},
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],
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});
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}
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}
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return out;
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}
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function getEnvironmentInfo(): string {
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return `${process.platform}-${process.arch}, Node.js ${process.version}`;
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}
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function uuid(): string {
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return crypto.randomUUID();
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}
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// ---------------------------------------------------------------------------
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// Extension entry point
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// ---------------------------------------------------------------------------
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export default function (pi: ExtensionAPI) {
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pi.registerProvider("commandcode", {
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name: "Command Code",
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baseUrl: API_BASE,
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api: "commandcode-custom" as any,
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headers: {
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"x-command-code-version": "0.24.1",
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"x-cli-environment": "production",
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},
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models: MODELS.map((m) => ({
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id: m.id,
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name: m.name,
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reasoning: m.reasoning,
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input: ["text"] as ("text" | "image")[],
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cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0 },
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contextWindow: m.contextWindow,
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maxTokens: m.maxTokens,
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})),
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});
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}
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