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@hanzochat/agents

Fork of danny-avila/agents (MIT), maintained for Hanzo Chat. Tracks upstream so fixes can be pulled forward.

TypeScript utilities for building agent workflows. The package provides graph orchestration, streaming event handling, tool execution, provider adapters, and message formatting for single-agent and multi-agent runs.

Features

  • LangGraph-based single-agent and multi-agent workflows
  • Streaming content aggregation and run-step event handlers
  • Tool calling, tool search, subagent handoffs, and programmatic tool execution
  • Provider adapters for Anthropic, Bedrock, Vertex AI, OpenAI-compatible providers, Google, Mistral, DeepSeek, and xAI
  • Message formatting, context pruning, summarization, and cache-control helpers

Installation

npm install @hanzochat/agents

Basic Usage

import { HumanMessage } from '@langchain/core/messages';
import { Providers, Run } from '@hanzochat/agents';

const run = await Run.create({
  runId: crypto.randomUUID(),
  graphConfig: {
    type: 'standard',
    instructions: 'You are a helpful assistant.',
    llmConfig: {
      provider: Providers.OPENAI,
      model: 'gpt-4o-mini',
      apiKey: process.env.OPENAI_API_KEY,
    },
  },
  returnContent: true,
});

const content = await run.processStream(
  { messages: [new HumanMessage('Hello')] },
  {
    runId: crypto.randomUUID(),
    streamMode: 'values',
    version: 'v2',
  }
);

Programmatic Sessions

For scripts, CI, and programmatic integrations, use the session facade. It keeps a JSONL session tree by default, so runs can be resumed, cloned, forked, branched in place, compacted, and inspected later.

import { Providers, createAgentSession } from '@hanzochat/agents';

const session = await createAgentSession({
  checkpointing: true,
  graphConfig: {
    type: 'standard',
    instructions: 'You are a concise coding assistant.',
    llmConfig: {
      provider: Providers.OPENAI,
      model: 'gpt-4o-mini',
      apiKey: process.env.OPENAI_API_KEY,
    },
  },
});

const result = await session.run('Summarize this repository.');
console.log(result.text);
console.log(session.sessionPath); // durable .jsonl session file

When checkpointing is enabled, the session injects a shared LangGraph checkpointer into compileOptions, records checkpoint IDs in JSONL, and uses checkpoint state for later turns on the same thread_id. When HITL is enabled (humanInTheLoop: { enabled: true }), sessions also get a MemorySaver by default so resumeInterrupt() can reuse the same saver instead of relying on a per-run fallback. JSONL still owns portable replay, clone, fork, and audit records.

Sessions expose tree operations inspired by Pi-style workflows:

const store = session.getSessionStore();
const forkPoint = store?.getForkPoints()[0];

if (forkPoint) {
  const forked = await session.fork(forkPoint.id, { position: 'before' });
  await forked.run('Try a different approach from here.');
}

const cloned = await session.clone();
await cloned.compact({ instructions: 'Keep only implementation decisions.' });

session.stream() projects the SDK's existing graph events, and session.compact() uses the same summarization node, hooks, and provider logic as normal runs. JSONL is the durable journal; the graph remains the execution engine.

OpenAI-compatible streaming helpers are available as experimental subpaths:

import { composeEventHandlers } from '@hanzochat/agents';
import { createOpenAIHandlers } from '@hanzochat/agents/openai';
import { createResponsesEventHandlers } from '@hanzochat/agents/responses';

const customHandlers = composeEventHandlers(
  createOpenAIHandlers(openAIConfig),
  createResponsesEventHandlers(responsesConfig),
  hostHandlers
);

Development

npm ci
npm run build
npm test
npx tsc --noEmit
npx eslint src/

Documentation

License

MIT — see LICENSE. Copyright (c) 2024 LibreChat; fork maintained by Hanzo AI.

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Description
Hanzo Chat agent runtime (fork of danny-avila/agents, MIT)
Readme MIT
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