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WIP: Refactor agent package - not compiling
- Renamed AppMessage to AgentMessage throughout - New agent-loop.ts with AgentLoopContext, AgentLoopConfig - Removed transport abstraction, Agent now takes streamFn directly - Extracted streamProxy to proxy.ts utility - Removed agent-loop from pi-ai (now in agent package) - Updated consumers (coding-agent, mom) for AgentMessage rename - Tests updated but some consumers still need migration Known issues: - AgentTool, AgentToolResult not exported from pi-ai - Attachment not exported from pi-agent-core - ProviderTransport removed but still referenced - messageTransformer -> convertToLlm migration incomplete - CustomMessages declaration merging not working properly
This commit is contained in:
Mario Zechner
parent
f7ef44dc38
commit
a055fd4481
32 changed files with 1312 additions and 2009 deletions
398
packages/agent/src/agent-loop.ts
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398
packages/agent/src/agent-loop.ts
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/**
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* Agent loop that works with AgentMessage throughout.
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* Transforms to Message[] only at the LLM call boundary.
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*/
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import {
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type AssistantMessage,
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type Context,
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EventStream,
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streamSimple,
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type ToolResultMessage,
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validateToolArguments,
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} from "@mariozechner/pi-ai";
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import type {
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AgentContext,
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AgentEvent,
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AgentLoopConfig,
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AgentMessage,
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AgentTool,
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AgentToolResult,
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StreamFn,
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} from "./types.js";
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/**
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* Start an agent loop with a new prompt message.
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* The prompt is added to the context and events are emitted for it.
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*/
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export function agentLoop(
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prompt: AgentMessage,
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context: AgentContext,
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config: AgentLoopConfig,
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signal?: AbortSignal,
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streamFn?: StreamFn,
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): EventStream<AgentEvent, AgentMessage[]> {
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const stream = createAgentStream();
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(async () => {
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const newMessages: AgentMessage[] = [prompt];
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const currentContext: AgentContext = {
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...context,
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messages: [...context.messages, prompt],
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};
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stream.push({ type: "agent_start" });
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stream.push({ type: "turn_start" });
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stream.push({ type: "message_start", message: prompt });
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stream.push({ type: "message_end", message: prompt });
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await runLoop(currentContext, newMessages, config, signal, stream, streamFn);
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})();
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return stream;
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}
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/**
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* Continue an agent loop from the current context without adding a new message.
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* Used for retries - context already has user message or tool results.
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*
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* **Important:** The last message in context must convert to a `user` or `toolResult` message
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* via `convertToLlm`. If it doesn't, the LLM provider will reject the request.
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* This cannot be validated here since `convertToLlm` is only called once per turn.
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*/
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export function agentLoopContinue(
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context: AgentContext,
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config: AgentLoopConfig,
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signal?: AbortSignal,
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streamFn?: StreamFn,
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): EventStream<AgentEvent, AgentMessage[]> {
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if (context.messages.length === 0) {
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throw new Error("Cannot continue: no messages in context");
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}
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if (context.messages[context.messages.length - 1].role === "assistant") {
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throw new Error("Cannot continue from message role: assistant");
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}
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const stream = createAgentStream();
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(async () => {
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const newMessages: AgentMessage[] = [];
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const currentContext: AgentContext = { ...context };
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stream.push({ type: "agent_start" });
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stream.push({ type: "turn_start" });
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await runLoop(currentContext, newMessages, config, signal, stream, streamFn);
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})();
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return stream;
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}
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function createAgentStream(): EventStream<AgentEvent, AgentMessage[]> {
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return new EventStream<AgentEvent, AgentMessage[]>(
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(event: AgentEvent) => event.type === "agent_end",
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(event: AgentEvent) => (event.type === "agent_end" ? event.messages : []),
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);
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}
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/**
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* Main loop logic shared by agentLoop and agentLoopContinue.
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*/
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async function runLoop(
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currentContext: AgentContext,
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newMessages: AgentMessage[],
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config: AgentLoopConfig,
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signal: AbortSignal | undefined,
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stream: EventStream<AgentEvent, AgentMessage[]>,
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streamFn?: StreamFn,
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): Promise<void> {
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let hasMoreToolCalls = true;
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let firstTurn = true;
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let queuedMessages: AgentMessage[] = (await config.getQueuedMessages?.()) || [];
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let queuedAfterTools: AgentMessage[] | null = null;
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while (hasMoreToolCalls || queuedMessages.length > 0) {
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if (!firstTurn) {
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stream.push({ type: "turn_start" });
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} else {
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firstTurn = false;
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}
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// Process queued messages (inject before next assistant response)
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if (queuedMessages.length > 0) {
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for (const message of queuedMessages) {
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stream.push({ type: "message_start", message });
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stream.push({ type: "message_end", message });
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currentContext.messages.push(message);
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newMessages.push(message);
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}
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queuedMessages = [];
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}
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// Stream assistant response
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const message = await streamAssistantResponse(currentContext, config, signal, stream, streamFn);
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newMessages.push(message);
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if (message.stopReason === "error" || message.stopReason === "aborted") {
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stream.push({ type: "turn_end", message, toolResults: [] });
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stream.push({ type: "agent_end", messages: newMessages });
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stream.end(newMessages);
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return;
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}
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// Check for tool calls
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const toolCalls = message.content.filter((c) => c.type === "toolCall");
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hasMoreToolCalls = toolCalls.length > 0;
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const toolResults: ToolResultMessage[] = [];
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if (hasMoreToolCalls) {
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const toolExecution = await executeToolCalls(
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currentContext.tools,
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message,
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signal,
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stream,
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config.getQueuedMessages,
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);
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toolResults.push(...toolExecution.toolResults);
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queuedAfterTools = toolExecution.queuedMessages ?? null;
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for (const result of toolResults) {
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currentContext.messages.push(result);
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newMessages.push(result);
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}
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}
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stream.push({ type: "turn_end", message, toolResults });
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// Get queued messages after turn completes
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if (queuedAfterTools && queuedAfterTools.length > 0) {
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queuedMessages = queuedAfterTools;
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queuedAfterTools = null;
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} else {
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queuedMessages = (await config.getQueuedMessages?.()) || [];
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}
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}
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stream.push({ type: "agent_end", messages: newMessages });
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stream.end(newMessages);
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}
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/**
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* Stream an assistant response from the LLM.
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* This is where AgentMessage[] gets transformed to Message[] for the LLM.
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*/
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async function streamAssistantResponse(
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context: AgentContext,
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config: AgentLoopConfig,
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signal: AbortSignal | undefined,
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stream: EventStream<AgentEvent, AgentMessage[]>,
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streamFn?: StreamFn,
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): Promise<AssistantMessage> {
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// Apply context transform if configured (AgentMessage[] → AgentMessage[])
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let messages = context.messages;
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if (config.transformContext) {
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messages = await config.transformContext(messages, signal);
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}
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// Convert to LLM-compatible messages (AgentMessage[] → Message[])
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const llmMessages = await config.convertToLlm(messages);
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// Build LLM context
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const llmContext: Context = {
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systemPrompt: context.systemPrompt,
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messages: llmMessages,
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tools: context.tools,
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};
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const streamFunction = streamFn || streamSimple;
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// Resolve API key (important for expiring tokens)
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const resolvedApiKey =
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(config.getApiKey ? await config.getApiKey(config.model.provider) : undefined) || config.apiKey;
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const response = streamFunction(config.model, llmContext, {
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...config,
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apiKey: resolvedApiKey,
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signal,
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});
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let partialMessage: AssistantMessage | null = null;
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let addedPartial = false;
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for await (const event of response) {
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switch (event.type) {
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case "start":
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partialMessage = event.partial;
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context.messages.push(partialMessage);
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addedPartial = true;
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stream.push({ type: "message_start", message: { ...partialMessage } });
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break;
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case "text_start":
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case "text_delta":
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case "text_end":
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case "thinking_start":
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case "thinking_delta":
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case "thinking_end":
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case "toolcall_start":
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case "toolcall_delta":
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case "toolcall_end":
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if (partialMessage) {
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partialMessage = event.partial;
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context.messages[context.messages.length - 1] = partialMessage;
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stream.push({
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type: "message_update",
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assistantMessageEvent: event,
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message: { ...partialMessage },
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});
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}
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break;
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case "done":
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case "error": {
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const finalMessage = await response.result();
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if (addedPartial) {
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context.messages[context.messages.length - 1] = finalMessage;
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} else {
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context.messages.push(finalMessage);
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}
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if (!addedPartial) {
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stream.push({ type: "message_start", message: { ...finalMessage } });
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}
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stream.push({ type: "message_end", message: finalMessage });
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return finalMessage;
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}
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}
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}
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return await response.result();
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}
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/**
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* Execute tool calls from an assistant message.
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*/
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async function executeToolCalls(
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tools: AgentTool<any>[] | undefined,
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assistantMessage: AssistantMessage,
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signal: AbortSignal | undefined,
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stream: EventStream<AgentEvent, AgentMessage[]>,
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getQueuedMessages?: AgentLoopConfig["getQueuedMessages"],
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): Promise<{ toolResults: ToolResultMessage[]; queuedMessages?: AgentMessage[] }> {
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const toolCalls = assistantMessage.content.filter((c) => c.type === "toolCall");
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const results: ToolResultMessage[] = [];
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let queuedMessages: AgentMessage[] | undefined;
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for (let index = 0; index < toolCalls.length; index++) {
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const toolCall = toolCalls[index];
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const tool = tools?.find((t) => t.name === toolCall.name);
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stream.push({
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type: "tool_execution_start",
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toolCallId: toolCall.id,
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toolName: toolCall.name,
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args: toolCall.arguments,
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});
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let result: AgentToolResult<any>;
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let isError = false;
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try {
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if (!tool) throw new Error(`Tool ${toolCall.name} not found`);
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const validatedArgs = validateToolArguments(tool, toolCall);
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result = await tool.execute(toolCall.id, validatedArgs, signal, (partialResult) => {
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stream.push({
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type: "tool_execution_update",
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toolCallId: toolCall.id,
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toolName: toolCall.name,
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args: toolCall.arguments,
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partialResult,
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});
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});
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} catch (e) {
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result = {
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content: [{ type: "text", text: e instanceof Error ? e.message : String(e) }],
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details: {},
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};
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isError = true;
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}
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stream.push({
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type: "tool_execution_end",
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toolCallId: toolCall.id,
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toolName: toolCall.name,
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result,
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isError,
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});
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const toolResultMessage: ToolResultMessage = {
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role: "toolResult",
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toolCallId: toolCall.id,
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toolName: toolCall.name,
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content: result.content,
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details: result.details,
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isError,
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timestamp: Date.now(),
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};
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results.push(toolResultMessage);
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stream.push({ type: "message_start", message: toolResultMessage });
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stream.push({ type: "message_end", message: toolResultMessage });
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// Check for queued messages - skip remaining tools if user interrupted
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if (getQueuedMessages) {
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const queued = await getQueuedMessages();
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if (queued.length > 0) {
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queuedMessages = queued;
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const remainingCalls = toolCalls.slice(index + 1);
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for (const skipped of remainingCalls) {
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results.push(skipToolCall(skipped, stream));
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}
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break;
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}
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}
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}
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return { toolResults: results, queuedMessages };
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}
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function skipToolCall(
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toolCall: Extract<AssistantMessage["content"][number], { type: "toolCall" }>,
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stream: EventStream<AgentEvent, AgentMessage[]>,
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): ToolResultMessage {
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const result: AgentToolResult<any> = {
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content: [{ type: "text", text: "Skipped due to queued user message." }],
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details: {},
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};
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stream.push({
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type: "tool_execution_start",
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toolCallId: toolCall.id,
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toolName: toolCall.name,
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args: toolCall.arguments,
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});
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stream.push({
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type: "tool_execution_end",
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toolCallId: toolCall.id,
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toolName: toolCall.name,
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result,
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isError: true,
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});
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const toolResultMessage: ToolResultMessage = {
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role: "toolResult",
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toolCallId: toolCall.id,
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toolName: toolCall.name,
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content: result.content,
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details: {},
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isError: true,
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timestamp: Date.now(),
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};
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stream.push({ type: "message_start", message: toolResultMessage });
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stream.push({ type: "message_end", message: toolResultMessage });
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return toolResultMessage;
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}
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