__init__

__init__ is an agent for coding agents from xt765/LangChain-Chinese-Comment. It costs 0 tokens per session (719 once invoked), scanned A, original, MIT.

The main entry point for LangChain’s agent framework, which lets a language model choose tools and the order in which to use them.

In plain words
What is it for?
Use it to create agents, run their step-by-step tool-use loops, load agents, or access built-in agent types.
Why use it?
It gathers the common agent classes, builders, executors, parsers, and loading helpers in one place.

Agent

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add agents/xt765/langchain-chinese-comment/__init__
Clone the repo
git clone --depth 1 https://github.com/xt765/LangChain-Chinese-Comment

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for __init__

README.md
[![agentmods](https://agentmods.dev/badge/agents/xt765/langchain-chinese-comment/__init__.svg)](https://agentmods.dev/agents/xt765/langchain-chinese-comment/__init__)
Your own site
<a href="https://agentmods.dev/agents/xt765/langchain-chinese-comment/__init__"><img src="https://agentmods.dev/badge/agents/xt765/langchain-chinese-comment/__init__.svg" alt="Measured on agentmods" height="20"></a>
Per session 0 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 719 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00000 $0.00719
Opus 5 $0.00000 $0.00360
Sonnet 5 $0.00000 $0.00144
Haiku 4.5 $0.00000 $0.00072

Measured 3d ago against content hash 61a212339db1, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

__init__ scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

code_comment/libs/langchain/langchain_classic/agents/__init__.md · 53 lines

What it actually says

libs\langchain\langchain_classic\agents_init_.py

此文档提供了 libs\langchain\langchain_classic\agents\__init__.py 文件的详细中文注释。该模块是 LangChain 代理系统的核心入口。

功能描述

代理 (Agent) 是一种使用大语言模型(LLM)来选择一系列动作执行的类。在链(Chains)中,动作序列是硬编码的;而在代理中,语言模型被用作推理引擎,来决定采取哪些动作以及以何种顺序执行。

代理会选择并使用 工具 (Tools)工具包 (Toolkits) 来执行动作。

主要组件

该模块聚合并导出了代理框架的核心类和函数:

1. 核心抽象与执行器

  • BaseSingleActionAgent, BaseMultiActionAgent: 代理的基础抽象类。
  • Agent: 传统的基于 LLMChain 的代理基类。
  • AgentExecutor: 代理执行器,负责驱动代理的思考-行动-观察循环。
  • AgentExecutorIterator: 允许迭代执行代理步骤的工具。
  • AgentOutputParser: 将 LLM 输出解析为代理动作或结束状态的解析器。

2. 预置代理类型与创建函数

  • AgentType: 代理类型的枚举。
  • create_react_agent: 创建 ReAct 风格的代理。
  • create_openai_functions_agent, create_openai_tools_agent: 利用 OpenAI 特定能力的代理。
  • create_structured_chat_agent: 适用于聊天模型的结构化代理。
  • create_xml_agent: 专门生成 XML 格式的代理。
  • create_tool_calling_agent: 通用的工具调用代理。
  • create_self_ask_with_search_agent: 自我提问搜索代理。

3. 加载与初始化

  • initialize_agent: (已弃用) 快速初始化代理的函数。
  • load_agent: 从配置文件或仓库加载代理。

动态导入与弃用处理

该模块使用了动态导入机制来处理已迁移到 langchain_communitylangchain_experimental 的组件。

1. 迁移至 langchain_community

以下组件通过 DEPRECATED_LOOKUP 动态映射到社区包:

  • load_tools, load_huggingface_tool, get_all_tool_names
  • create_json_agent, create_openapi_agent, create_pbi_agent, create_pbi_chat_agent, create_spark_sql_agent, create_sql_agent

2. 迁移至 langchain_experimental

以下代理创建函数已迁移到实验性包,直接调用会抛出 ImportError

  • create_csv_agent, create_pandas_dataframe_agent, create_spark_dataframe_agent, create_xorbits_agent

迁移建议

对于新的代理开发,建议参考 LangGraph 文档。LangGraph 提供了比传统 AgentExecutor 更灵活、功能更强大的框架,支持循环逻辑、状态持久化和复杂的人机交互模式。

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 3d ago First seen · 53 lines · 0 tokens per session scan A 61a212339db1

Subscribe to this mod's changes

__init__ is an agent published in the GitHub repository xt765/LangChain-Chinese-Comment (20 stars, last pushed 1mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 719 tokens. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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