/LangChain V1.0.3 最新版本文档

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# LangChain V1.0.3 最新版本文档

## 1.LangChain

### Core components

Agents: https://docs.langchain.com/oss/python/langchain/agents

Models: https://docs.langchain.com/oss/python/langchain/models

Messages: https://docs.langchain.com/oss/python/langchain/messages

Tools: https://docs.langchain.com/oss/python/langchain/tools

Short-term memory: https://docs.langchain.com/oss/python/langchain/short-term-memory

Streaming: https://docs.langchain.com/oss/python/langchain/streaming

Middleware: https://docs.langchain.com/oss/python/langchain/middleware

Structured output: https://docs.langchain.com/oss/python/langchain/structured-output


### Advanced usage

Guardrails: https://docs.langchain.com/oss/python/langchain/guardrails

Runtime: https://docs.langchain.com/oss/python/langchain/runtime

Context engineering in agents: https://docs.langchain.com/oss/python/langchain/context-engineering

Model Context Protocol (MCP): https://docs.langchain.com/oss/python/langchain/mcp

Human-in-the-loop: https://docs.langchain.com/oss/python/langchain/human-in-the-loop

Multi-agent: https://docs.langchain.com/oss/python/langchain/multi-agent

Retrieval: https://docs.langchain.com/oss/python/langchain/retrieval

Long-term memory: https://docs.langchain.com/oss/python/langchain/long-term-memory

### LangChain Reference

https://reference.langchain.com/python/langchain/

## 2.LangGraph

- Quickstart： https://docs.langchain.com/oss/python/langgraph/quickstart

- Run a local server： https://docs.langchain.com/oss/python/langgraph/local-server

- Thinking in LangGraph： https://docs.langchain.com/oss/python/langgraph/thinking-in-langgraph

- Workflows and agents： https://docs.langchain.com/oss/python/langgraph/workflows-agents

### Capabilities

Persistence：https://docs.langchain.com/oss/python/langgraph/persistence

Durable execution： https://docs.langchain.com/oss/python/langgraph/durable-execution

Streaming：https://docs.langchain.com/oss/python/langgraph/streaming

Interrupts： https://docs.langchain.com/oss/python/langgraph/interrupts

Use time-travel：https://docs.langchain.com/oss/python/langgraph/use-time-travel

Memory： https://docs.langchain.com/oss/python/langgraph/add-memory

Subgraphs： https://docs.langchain.com/oss/python/langgraph/use-subgraphs

## 3.Deep Agents

- Quickstart：https://docs.langchain.com/oss/python/deepagents/quickstart

- Customize Deep Agents：https://docs.langchain.com/oss/python/deepagents/customization

- Agent harness capabilities：https://docs.langchain.com/oss/python/deepagents/harness

- Backends：https://docs.langchain.com/oss/python/deepagents/backends

- Subagents：https://docs.langchain.com/oss/python/deepagents/subagents

- Human-in-the-loop： https://docs.langchain.com/oss/python/deepagents/human-in-the-loop

- Long-term memory： https://docs.langchain.com/oss/python/deepagents/long-term-memory

- Deep Agents Middleware：https://docs.langchain.com/oss/python/deepagents/middleware


## 4. LangChain Reference

### 🧭 一级目录

* **LangChain**
  [https://reference.langchain.com/python/langchain/](https://reference.langchain.com/python/langchain/)

---

### 📂 二级目录

#### langchain

* Agents — [https://reference.langchain.com/python/langchain/agents/](https://reference.langchain.com/python/langchain/agents/)
* Middleware — [https://reference.langchain.com/python/langchain/middleware/](https://reference.langchain.com/python/langchain/middleware/)
* Models — [https://reference.langchain.com/python/langchain/models/](https://reference.langchain.com/python/langchain/models/)
* Messages — [https://reference.langchain.com/python/langchain/messages/](https://reference.langchain.com/python/langchain/messages/)
* Tools — [https://reference.langchain.com/python/langchain/tools/](https://reference.langchain.com/python/langchain/tools/)
* Embeddings — [https://reference.langchain.com/python/langchain/embeddings/](https://reference.langchain.com/python/langchain/embeddings/)

---

#### langchain-core

* [https://reference.langchain.com/python/langchain_core/](https://reference.langchain.com/python/langchain_core/)

  * Caches — [https://reference.langchain.com/python/langchain_core/caches/](https://reference.langchain.com/python/langchain_core/caches/)
  * Callbacks — [https://reference.langchain.com/python/langchain_core/callbacks/](https://reference.langchain.com/python/langchain_core/callbacks/)
  * Documents — [https://reference.langchain.com/python/langchain_core/documents/](https://reference.langchain.com/python/langchain_core/documents/)
  * Document loaders — [https://reference.langchain.com/python/langchain_core/document_loaders/](https://reference.langchain.com/python/langchain_core/document_loaders/)
  * Embeddings — [https://reference.langchain.com/python/langchain_core/embeddings/](https://reference.langchain.com/python/langchain_core/embeddings/)
  * Exceptions — [https://reference.langchain.com/python/langchain_core/exceptions/](https://reference.langchain.com/python/langchain_core/exceptions/)
  * Language models — [https://reference.langchain.com/python/langchain_core/language_models/](https://reference.langchain.com/python/langchain_core/language_models/)
  * Serialization (load) — [https://reference.langchain.com/python/langchain_core/load/](https://reference.langchain.com/python/langchain_core/load/)
  * Output parsers — [https://reference.langchain.com/python/langchain_core/output_parsers/](https://reference.langchain.com/python/langchain_core/output_parsers/)
  * Prompts — [https://reference.langchain.com/python/langchain_core/prompts/](https://reference.langchain.com/python/langchain_core/prompts/)
  * Rate limiters — [https://reference.langchain.com/python/langchain_core/rate_limiters/](https://reference.langchain.com/python/langchain_core/rate_limiters/)
  * Retrievers — [https://reference.langchain.com/python/langchain_core/retrievers/](https://reference.langchain.com/python/langchain_core/retrievers/)
  * Runnables — [https://reference.langchain.com/python/langchain_core/runnables/](https://reference.langchain.com/python/langchain_core/runnables/)
  * Utilities — [https://reference.langchain.com/python/langchain_core/utils/](https://reference.langchain.com/python/langchain_core/utils/)
  * Vector stores — [https://reference.langchain.com/python/langchain_core/vectorstores/](https://reference.langchain.com/python/langchain_core/vectorstores/)

---

#### langchain-text-splitters

* [https://reference.langchain.com/python/langchain_text_splitters/](https://reference.langchain.com/python/langchain_text_splitters/)

#### langchain-mcp-adapters

* [https://reference.langchain.com/python/langchain_mcp_adapters/](https://reference.langchain.com/python/langchain_mcp_adapters/)

#### langchain-model-profiles

* [https://reference.langchain.com/python/langchain_model_profiles/](https://reference.langchain.com/python/langchain_model_profiles/)

---

#### langchain-tests

* [https://reference.langchain.com/python/langchain_tests/](https://reference.langchain.com/python/langchain_tests/)

  * Unit tests — [https://reference.langchain.com/python/langchain_tests/unit_tests/](https://reference.langchain.com/python/langchain_tests/unit_tests/)
  * Integration tests — [https://reference.langchain.com/python/langchain_tests/integration_tests/](https://reference.langchain.com/python/langchain_tests/integration_tests/)

---

#### langchain-classic

* [https://reference.langchain.com/python/langchain_classic/](https://reference.langchain.com/python/langchain_classic/)

  * Agents — [https://reference.langchain.com/python/langchain_classic/agents/](https://reference.langchain.com/python/langchain_classic/agents/)
  * Callbacks — [https://reference.langchain.com/python/langchain_classic/callbacks/](https://reference.langchain.com/python/langchain_classic/callbacks/)
  * Chains — [https://reference.langchain.com/python/langchain_classic/chains/](https://reference.langchain.com/python/langchain_classic/chains/)
  * Chat models — [https://reference.langchain.com/python/langchain_classic/chat_models/](https://reference.langchain.com/python/langchain_classic/chat_models/)
  * Embeddings — [https://reference.langchain.com/python/langchain_classic/embeddings/](https://reference.langchain.com/python/langchain_classic/embeddings/)
  * Evaluation — [https://reference.langchain.com/python/langchain_classic/evaluation/](https://reference.langchain.com/python/langchain_classic/evaluation/)
  * Globals — [https://reference.langchain.com/python/langchain_classic/globals/](https://reference.langchain.com/python/langchain_classic/globals/)
  * Hub — [https://reference.langchain.com/python/langchain_classic/hub/](https://reference.langchain.com/python/langchain_classic/hub/)
  * Memory — [https://reference.langchain.com/python/langchain_classic/memory/](https://reference.langchain.com/python/langchain_classic/memory/)
  * Output parsers — [https://reference.langchain.com/python/langchain_classic/output_parsers/](https://reference.langchain.com/python/langchain_classic/output_parsers/)
  * Retrievers — [https://reference.langchain.com/python/langchain_classic/retrievers/](https://reference.langchain.com/python/langchain_classic/retrievers/)
  * Runnables — [https://reference.langchain.com/python/langchain_classic/runnables/](https://reference.langchain.com/python/langchain_classic/runnables/)
  * LangSmith — [https://reference.langchain.com/python/langchain_classic/smith/](https://reference.langchain.com/python/langchain_classic/smith/)
  * Storage — [https://reference.langchain.com/python/langchain_classic/storage/](https://reference.langchain.com/python/langchain_classic/storage/)


### LangGraph Reference

以下是你贴出的 **LangGraph** 目录结构中所有子页面的 URL 整理列表（完整可直接访问）：

---

### 🌐 LangGraph Reference

**主目录：**
[https://reference.langchain.com/python/langgraph/](https://reference.langchain.com/python/langgraph/)

---

### 📂 二级目录（LangGraph 模块）

| 模块名            | 对应 URL                                                                                                                         |
| -------------- | ------------------------------------------------------------------------------------------------------------------------------ |
| Graphs         | [https://reference.langchain.com/python/langgraph/graphs/](https://reference.langchain.com/python/langgraph/graphs/)           |
| Functional API | [https://reference.langchain.com/python/langgraph/func/](https://reference.langchain.com/python/langgraph/func/)               |
| Pregel         | [https://reference.langchain.com/python/langgraph/pregel/](https://reference.langchain.com/python/langgraph/pregel/)           |
| Checkpointing  | [https://reference.langchain.com/python/langgraph/checkpoints/](https://reference.langchain.com/python/langgraph/checkpoints/) |
| Storage        | [https://reference.langchain.com/python/langgraph/store/](https://reference.langchain.com/python/langgraph/store/)             |
| Caching        | [https://reference.langchain.com/python/langgraph/cache/](https://reference.langchain.com/python/langgraph/cache/)             |
| Types          | [https://reference.langchain.com/python/langgraph/types/](https://reference.langchain.com/python/langgraph/types/)             |
| Runtime        | [https://reference.langchain.com/python/langgraph/runtime/](https://reference.langchain.com/python/langgraph/runtime/)         |
| Config         | [https://reference.langchain.com/python/langgraph/config/](https://reference.langchain.com/python/langgraph/config/)           |
| Errors         | [https://reference.langchain.com/python/langgraph/errors/](https://reference.langchain.com/python/langgraph/errors/)           |
| Constants      | [https://reference.langchain.com/python/langgraph/constants/](https://reference.langchain.com/python/langgraph/constants/)     |
| Channels       | [https://reference.langchain.com/python/langgraph/channels/](https://reference.langchain.com/python/langgraph/channels/)       |

## 5.DeepAgent Reference

DeepAgent Reference： https://reference.langchain.com/python/deepagents/?_gl=1*1i0c74*_gcl_au*NjA4NjYyNTA2LjE3NTc4MTY4ODg.*_ga*NDM4Njk4NTEwLjE3NTc4MTY4ODg.*_ga_47WX3HKKY2*czE3NjIzNDc0MDMkbzI1JGcxJHQxNzYyMzQ3OTg5JGo1OSRsMCRoMA..#deepagents.create_deep_agent