CascadeAgent

import { CascadeAgent, type AgentConfig } from '@cascadeflow/core';

const config: AgentConfig = {
  models: [
    { name: 'gpt-4o-mini', provider: 'openai', cost: 0.00015 },
    { name: 'gpt-4o', provider: 'openai', cost: 0.0025 },
  ],
  quality: {
    threshold: 0.7,
    requireMinimumTokens: 3,
  },
};

const agent = new CascadeAgent(config);

const result = await agent.run('Explain speculative execution', {
  maxTokens: 500,
  temperature: 0.2,
  systemPrompt: 'Answer for a software engineer.',
});

const result = await agent.run([
  { role: 'system', content: 'Answer concisely.' },
  { role: 'user', content: 'What is model cascading?' },
]);

const result = await agent.run('What is the weather in Zurich?', {
  tools: [weatherTool.toOpenAIFormat()],
  toolExecutor: new ToolExecutor([weatherTool]),
  maxSteps: 5,
});

const batch = await agent.runBatch(
  ['Summarize A', 'Summarize B'],
  { maxParallel: 2, stopOnError: false },
  { maxTokens: 200 },
);

console.log(batch.successCount, batch.failureCount);

import { StreamEventType } from '@cascadeflow/core';

for await (const event of agent.stream('Write a short explanation')) {
  if (event.type === StreamEventType.CHUNK) {
    process.stdout.write(event.content);
  }
}

console.log(agent.getModels());
console.log(agent.getModelCount());
console.log(agent.getRouterStats());

agent.resetRouterStats();