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This adds codemode and MCP support to pi. Codemode (packages/codemode) runs model-written JavaScript in a QuickJS wasm VM inside a worker. From there the script calls pi's tools as async functions, uses a per-session store, and can read the model catalog and run classifiers. The codemode tool in coding-agent is compatible with Codex's exec tool, and codemode.mode works like Codex's tool modes (on or only). Large results are written to a JSON temp file. MCP (packages/mcp) is a standalone client for stdio and streamable HTTP servers, with OAuth. The core only gets general mechanisms; codemode, tool_search and MCP are built-in extensions that use them. Other extensions can replace these built-ins. Tools declare an exposure: direct, model-only, codemode, deferred or hidden. prepareLoadout() lets an orchestrating tool change which tool declarations the model sees. ctx.executeTool() runs nested calls through validation and the tool_call/tool_result hooks. Those calls emit events with parentToolCallId and are recorded as bounded nestedCalls on the parent result, which compaction and HTML export use. Tools can also return structuredContent with an outputSchema, and can report errors with isError instead of throwing. MCP servers come from mcp.json (global, or per project after the project is trusted) or from pi.registerMcpServer(). They are managed with /mcp and pi mcp list|login|logout, and their runtimes load on first use. Closes #10040
172 lines
6.6 KiB
TypeScript
172 lines
6.6 KiB
TypeScript
/**
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* Adapters that give a pi-agent-core `Agent` MCP tools and a codemode tool, using
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* `@earendil-works/pi-mcp` and `@earendil-works/pi-codemode`. See main.ts for how they fit together.
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*/
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import {
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type Agent,
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type AgentTool,
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type AgentToolCallOutcome,
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type AgentToolResult,
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runToolCall,
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} from "@earendil-works/pi-agent-core";
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import type { ImageContent, JsonObject, JsonValue, TextContent } from "@earendil-works/pi-ai";
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import {
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type CodemodeJsonSchema,
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CodemodeSandbox,
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type CodemodeTool,
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renderDeclarations,
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} from "@earendil-works/pi-codemode";
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import { type McpClient, toLlmContent } from "@earendil-works/pi-mcp";
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import { Type } from "typebox";
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/** Provider tool names are limited to 64 characters of `[A-Za-z0-9_-]`. */
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function toToolName(prefix: string, name: string): string {
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return `${prefix}_${name}`.replace(/[^A-Za-z0-9_-]/g, "_").slice(0, 64);
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}
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function textOf(result: AgentToolResult<unknown>): string {
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return result.content
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.filter((block): block is TextContent => block.type === "text")
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.map((block) => block.text)
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.join("\n");
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}
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/**
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* One `AgentTool` per tool of a connected MCP server, named `<prefix>_<tool>`. Tools with an MCP
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* output schema declare it as `outputSchema` and return `structuredContent`, which codemode scripts
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* receive instead of the text.
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*/
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export async function createMcpTools(client: McpClient, prefix: string): Promise<AgentTool[]> {
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const tools = await client.listTools();
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return tools.map(
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(tool): AgentTool => ({
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name: toToolName(prefix, tool.name),
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label: tool.title ?? tool.name,
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description: tool.description ?? tool.title ?? `MCP tool ${tool.name}`,
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// Providers require an object schema, and some reject one without `properties`.
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parameters: Type.Unsafe({
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...tool.inputSchema,
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type: "object",
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properties: tool.inputSchema.properties ?? {},
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}),
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outputSchema: tool.outputSchema ? Type.Unsafe<Record<string, unknown>>(tool.outputSchema) : undefined,
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execute: async (_toolCallId, params, signal, onUpdate) => {
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const result = await client.callTool(tool.name, params as Record<string, unknown>, {
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signal,
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onProgress: (progress) => {
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const text = progress.message ?? `Progress ${progress.progress}`;
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onUpdate?.({ content: [{ type: "text", text }], details: undefined });
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},
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});
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const content = toLlmContent(result);
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if (result.isError && content.length === 0) {
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content.push({ type: "text", text: `MCP tool ${tool.name} failed` });
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}
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return {
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content,
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details: undefined,
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structuredContent: result.structuredContent as JsonValue | undefined,
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// MCP reports tool failures in the result instead of as a protocol error.
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isError: result.isError === true,
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};
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},
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}),
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);
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}
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/**
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* Run a tool call on behalf of another tool through the agent's pipeline: argument validation and
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* the agent's `beforeToolCall`/`afterToolCall` hooks apply as for calls the model makes. Calling
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* `tool.execute()` directly also works when the agent has no hooks.
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*/
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export function createNestedToolRunner(
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agent: Agent,
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): (name: string, args: unknown, signal: AbortSignal) => Promise<AgentToolCallOutcome> {
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let nextId = 1;
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return (name, args, signal) => {
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const assistantMessage = agent.state.messages.findLast((message) => message.role === "assistant");
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if (assistantMessage?.role !== "assistant") throw new Error("Nested tool calls need an assistant message");
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const tools = agent.state.tools;
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return runToolCall(
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{ type: "toolCall", id: `nested-${nextId++}`, name, arguments: (args ?? {}) as JsonObject },
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{
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tools,
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assistantMessage,
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context: { messages: agent.state.messages, tools },
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beforeToolCall: agent.beforeToolCall,
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afterToolCall: agent.afterToolCall,
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signal,
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},
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);
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};
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}
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export const CODEMODE_TOOL_NAME = "codemode";
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const codemodeParameters = Type.Object({
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code: Type.String({ description: "JavaScript source. Top-level await and return work." }),
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});
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/**
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* A tool that runs model-written JavaScript in the codemode sandbox, where `tools.<name>(args)`
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* calls `tools`. Nested results stay out of the model context; only the script's output and
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* return value come back.
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*/
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export function createCodemodeTool(
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tools: readonly AgentTool[],
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runTool: (name: string, args: unknown, signal: AbortSignal) => Promise<AgentToolCallOutcome>,
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): AgentTool<typeof codemodeParameters> {
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const callable = tools.filter((tool) => tool.name !== CODEMODE_TOOL_NAME);
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const sandboxTools: CodemodeTool[] = callable.map((tool) => ({
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name: tool.name,
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description: tool.description,
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// TypeBox schemas are JSON Schema.
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inputSchema: tool.parameters as CodemodeJsonSchema,
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// What the script receives: the structured result if the tool declares one, else its text.
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outputSchema: (tool.outputSchema as CodemodeJsonSchema | undefined) ?? { type: "string" },
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execute: async (args, { signal }) => {
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const outcome = await runTool(tool.name, args, signal);
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if (tool.outputSchema && outcome.result.structuredContent !== undefined) {
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return outcome.result.structuredContent;
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}
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const text = textOf(outcome.result);
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if (outcome.isError) throw new Error(text || `Tool ${tool.name} failed`);
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return text;
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},
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}));
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return {
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name: CODEMODE_TOOL_NAME,
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label: "Codemode",
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description: [
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"Run JavaScript that calls other tools, to chain calls, run them in parallel, or filter large results.",
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"The code is the body of an async function. There is no Node, file system, network, or timers.",
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"Call tools as `await tools.<name>(args)`. Output with `text(value)` or `console.log()`, or `return` a value.",
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"Only the output and the return value reach you, not the results of the tool calls.",
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"",
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"```ts",
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renderDeclarations({ tools: sandboxTools }),
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"```",
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].join("\n"),
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parameters: codemodeParameters,
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execute: async (_toolCallId, params, signal) => {
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const sandbox = new CodemodeSandbox({ tools: sandboxTools, timeoutMs: 120_000 });
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try {
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const result = await sandbox.execute(params.code, { signal });
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// Items from text(), console.*, and image(), in order. They have pi-ai's content shapes.
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const content: (TextContent | ImageContent)[] = [...result.output];
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if (result.ok && result.value !== undefined) {
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const value = typeof result.value === "string" ? result.value : JSON.stringify(result.value);
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content.push({ type: "text", text: value });
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}
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if (!result.ok) {
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content.push({ type: "text", text: `Script failed: ${result.error.stack ?? result.error.message}` });
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}
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return { content, details: { calls: result.calls }, isError: !result.ok };
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} finally {
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await sandbox.close();
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}
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},
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};
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}
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