import "dotenv/config";
import { Agent, createCtx, type Tool } from "@sisu-ai/core";
import { registerTools } from "@sisu-ai/mw-register-tools";
import { inputToMessage, conversationBuffer } from "@sisu-ai/mw-conversation-buffer";
import { errorBoundary } from "@sisu-ai/mw-error-boundary";
import { toolCalling } from "@sisu-ai/mw-tool-calling";
import { openAIAdapter } from "@sisu-ai/adapter-openai";
import { traceViewer } from "@sisu-ai/mw-trace-viewer";
import { z } from "zod";

const weather: Tool<{ city: string }> = {
  name: "getWeather",
  description: "Get weather for a city",
  schema: z.object({ city: z.string() }),
  handler: async ({ city }) => ({ city, tempC: 21, summary: "Sunny" }),
};

const ctx = createCtx({
  model: openAIAdapter({ model: "gpt-4o-mini" }),
  input: "What is the weather in Stockholm?",
  systemPrompt: "You are a helpful assistant.",
});

const app = new Agent()
  .use(errorBoundary())
  .use(traceViewer())
  .use(registerTools([weather]))
  .use(inputToMessage)
  .use(conversationBuffer({ window: 8 }))
  .use(toolCalling);

await app.handler()(ctx);

const app = new Agent()
  .use(errorBoundary())
  .use(traceViewer())
  .use(registerTools([...]))
  .use(toolCalling);

(ctx, next) => {
  ctx.messages.push(...)  // Modify state
  await next()            // Pass to next middleware
  console.log(ctx.result) // React to changes
}

const tool: Tool = {
  name: "searchDocs",
  schema: z.object({ query: z.string() }),
  handler: async ({ query }) => { /* ... */ },
};

import { sequence, branch, parallel, graph } from '@sisu-ai/mw-control-flow';

.use(sequence([
  classifyIntent,
  branch({
    'search': searchPipeline,
    'chat': conversationPipeline
  })
]))

const model = openAIAdapter({ model: "gpt-4o-mini" });
// const model = anthropicAdapter({ model: 'claude-sonnet-4' });
// const model = ollamaAdapter({ model: 'llama3.1' });

const model = openAIAdapter({
  model: "gpt-4o-mini",
  baseUrl: "http://localhost:1234/v1",
});