import { streamText, Message, createDataStream } from "ai";
import { Hono } from "hono";
import { stream } from "hono/streaming";
import { processPendingToolCalls } from "./util.js";
import { agentsById, openrouter } from "./agentRegistry.js";

const app = new Hono();

app.post("/api/chat/:agent_id", async (c) => {
  const input: { messages: Message[] } = await c.req.json();
  const agentId = c.req.param("agent_id");
  const agent = agentsById[agentId];
  if (!agent) {
    c.status(404);
    return c.json({ error: `No such agent: ${agentId}` });
  }

  const dataStream = createDataStream({
    execute: async (dataStreamWriter) => {
      // dataStreamWriter.writeData('initialized call');

      // Process any pending tool calls in the messages
      // This modifies the messages array in place
      await processPendingToolCalls(input.messages, dataStreamWriter);

      const result = streamText({
        model: openrouter(agent.modelName),
        maxSteps: 5,
        messages: [
          { role: "system", content: agent.systemMessage },
          ...Object.values(agentsById).map((agent) => ({
            role: "system" as const,
            content: `Agent ${JSON.stringify({
              id: agent.id,
              name: agent.name,
              description: agent.description,
              skills: agent.skills,
            })}`,
          })),
          ...input.messages,
        ],
        tools: agent.tools,
        onError: (error) => {
          console.error("Error in streamText:", error);
        },
      });

      result.mergeIntoDataStream(dataStreamWriter);
    },
    onError: (error) => {
      // Error messages are masked by default for security reasons.
      // If you want to expose the error message to the client, you can do so here:
      return error instanceof Error ? error.message : String(error);
    },
  });

  // Mark the response as a v1 data stream:
  c.header("X-Vercel-AI-Data-Stream", "v1");
  c.header("Content-Type", "text/plain; charset=utf-8");

  return stream(c, (stream) =>
    stream.pipe(dataStream.pipeThrough(new TextEncoderStream()))
  );
});

export default app;