Token导航 LogoToken导航TokenDH.com
研究检索敏感数据github未标认证来源可访问许可证需确认审计通过

langchain-dependenciesLangChain dependencies 搜索

Agent Skill

langchain-dependencies 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

23,249

周安装

812

GitHub Stars

7

下载量

8,960
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:langchain-dependencies(LangChain dependencies 搜索)
来源仓库:https://github.com/jackjin1997/clawforge
仓库路径:skills/langchain-dependencies
安装命令:
npx skills add https://github.com/jackjin1997/clawforge --skill 'LangChain Dependencies'
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/jackjin1997/clawforge --skill 'LangChain Dependencies'

简介

用于查找、检索和筛选相关信息。langchain-dependencies 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

  • 适合根据关键词或任务线索快速定位候选结果。
  • 可结合来源仓库和原始文档继续核验用法。
  • 安装前建议确认权限范围和维护状态。
  • 需注意是否会触发联网或文件读写操作。

SKILL.md

Key principles:

  • LangChain 1.0 is the current LTS release. Always start new projects on 1.0+. LangChain 0.3 is legacy maintenance-only — do not use it for new work.
  • langchain-core is the shared foundation: always install it explicitly alongside any other package.
  • langchain-community (Python only) does NOT follow semantic versioning; pin it conservatively.
  • LangGraph vs Deep Agents: choose one orchestration approach based on your use case — they are alternatives, not a required stack (see Framework Choice below).
  • Provider integrations (model, vector store, tools) are installed separately so you only pull in what you use.

Environment Requirements

RequirementPythonTypeScript / Node
Runtime minimumPython 3.10+Node.js 20+
LangChain1.0+ (LTS)1.0+ (LTS)
LangSmith SDK>= 0.3.0>= 0.3.0

Framework Choice

FrameworkWhen to useCore extra package
LangGraphNeed fine-grained graph control, custom workflows, loops, or branchinglanggraph / @langchain/langgraph
Deep AgentsWant batteries-included planning, memory, file context, and skills out of the boxdeepagents (depends on LangGraph; installs it as a transitive dep)

Both sit on top of langchain + langchain-core + langsmith.


Core Packages

Python — always required

PackageRoleMin version
langchainAgents, chains, retrieval1.0
langchain-coreBase types & interfaces (peer dep)1.0
langsmithTracing, evaluation, datasets0.3.0

Python — orchestration (pick one)

PackageUse whenMin version
langgraphBuilding custom graphs directly1.0
deepagentsUsing the Deep Agents frameworklatest

Python — model providers (pick the one(s) you use)

PackageProvider
langchain-openaiOpenAI (GPT-4o, o3, …)
langchain-anthropicAnthropic (Claude)
langchain-google-genaiGoogle (Gemini)
langchain-mistralaiMistral
langchain-groqGroq (fast inference)
langchain-cohereCohere
langchain-fireworksFireworks AI
langchain-togetherTogether AI
langchain-huggingfaceHugging Face Hub
langchain-ollamaOllama (local models)
langchain-awsAWS Bedrock
langchain-azure-aiAzure AI Foundry

Python — common tool & retrieval packages

These packages have tighter compatibility requirements — use the latest available version unless you have a specific reason not to.

PackageAddsNotes
langchain-tavilyTavily web search (TavilySearch)Dedicated integration package; prefer latest
langchain-text-splittersText chunking utilitiesSemver, keep current
langchain-community1000+ integrations (fallback)NOT semver — pin to minor series
faiss-cpuFAISS vector store (local)Via langchain-community; use latest
langchain-chromaChroma vector storeDedicated integration package; prefer latest
langchain-pineconePinecone vector storeDedicated integration package; prefer latest
langchain-qdrantQdrant vector storeDedicated integration package; prefer latest
langchain-weaviateWeaviate vector storeDedicated integration package; prefer latest
langsmith[pytest]pytest plugin for LangSmithRequires langsmith >= 0.3.4
langchain-community stability note: This package is NOT on semantic versioning. Minor releases can contain breaking changes. Prefer dedicated integration packages (e.g. langchain-chroma, langchain-tavily) when they exist — they are independently versioned and more stable.

TypeScript — always required

PackageRoleMin version
@langchain/coreBase types & interfaces (peer dep)1.0
langchainAgents, chains, retrieval1.0
langsmithTracing, evaluation, datasets0.3.0

TypeScript — orchestration (pick one)

PackageUse whenMin version
@langchain/langgraphBuilding custom graphs directly1.0
deepagentsUsing the Deep Agents frameworklatest

TypeScript — model providers (pick the one(s) you use)

PackageProvider
@langchain/openaiOpenAI (GPT-4o, o3, …)
@langchain/anthropicAnthropic (Claude)
@langchain/google-genaiGoogle (Gemini)
@langchain/mistralaiMistral
@langchain/groqGroq (fast inference)
@langchain/cohereCohere
@langchain/awsAWS Bedrock
@langchain/azure-openaiAzure OpenAI
@langchain/ollamaOllama (local models)

TypeScript — common tool & retrieval packages

PackageAddsNotes
@langchain/tavilyTavily web search (TavilySearch)Dedicated integration package; prefer latest
@langchain/communityBroad set of community integrationsUse sparingly; prefer dedicated packages
@langchain/pineconePinecone vector storeDedicated integration package; prefer latest
@langchain/qdrantQdrant vector storeDedicated integration package; prefer latest
@langchain/weaviateWeaviate vector storeDedicated integration package; prefer latest
@langchain/core must be installed explicitly in yarn workspaces and monorepos — it is a peer dependency and will not always be hoisted automatically.

Minimal Project Templates

Add your model provider, e.g.:

langchain-openai

langchain-anthropic

langchain-google-genai

</python>
</ex-langgraph-python>

<ex-langgraph-typescript>
<typescript>
Minimal package.json dependencies for a LangGraph project (provider-agnostic).

{ "dependencies": { "@langchain/core": "^1.0.0", "langchain": "^1.0.0", "@langchain/langgraph": "^1.0.0", "langsmith": "^0.3.0" } }


# Add your model provider, e.g.:

# langchain-anthropic

# langchain-openai

</python> </ex-deepagents-python>

<ex-deepagents-typescript> <typescript> Minimal package.json dependencies for a Deep Agents project (provider-agnostic).

{
  "dependencies": {
    "deepagents": "latest",
    "@langchain/core": "^1.0.0",
    "langchain": "^1.0.0",
    "langsmith": "^0.3.0"
  }
}

Web search

langchain-tavily # use latest; partner package, semver

Vector store — pick one:

langchain-chroma # use latest; partner package, semver

langchain-pinecone # use latest; partner package, semver

langchain-qdrant # use latest; partner package, semver

Text processing

langchain-text-splitters # use latest; semver

Your model provider:

langchain-openai / langchain-anthropic / etc.

</python>
</ex-with-tools-python>

<ex-with-tools-typescript>
<typescript>
Adding Tavily search and a vector store to a LangGraph project.

{ "dependencies": { "@langchain/core": "^1.0.0", "langchain": "^1.0.0", "@langchain/langgraph": "^1.0.0", "langsmith": "^0.3.0", "@langchain/tavily": "latest", "@langchain/pinecone": "latest" } }


---

## Versioning Policy & Upgrade Strategy

| Package group | Versioning | Safe upgrade strategy |
| --- | --- | --- |
| `langchain`, `langchain-core` | Strict semver (1.0 LTS) | Allow minor: `>=1.0,<2.0` |
| `langgraph` / `@langchain/langgraph` | Strict semver (v1 LTS) | Allow minor: `>=1.0,<2.0` |
| `langsmith` | Strict semver | Allow minor: `>=0.3.0` |
| Dedicated integration packages (e.g. `langchain-tavily`, `langchain-chroma`) | Independently versioned | Allow minor updates; use latest |
| `langchain-community` | **NOT semver** | Pin exact minor: `>=0.4.0,<0.5.0` |
| `deepagents` | Follow project releases | Pin to tested version in production |

**Breaking changes only happen in major versions** (1.x → 2.x) for all semver-compliant packages. Deprecated features remain functional across the entire 1.x series with warnings.

**Prefer dedicated integration packages over langchain-community.** When a dedicated package exists (e.g. `langchain-chroma` instead of `langchain-community`'s Chroma integration), use it — dedicated packages are independently versioned and better tested.

**Community tool packages (Tavily, vector stores, etc.) should be kept at latest** unless your project requires a locked environment. These packages frequently release compatibility fixes alongside LangChain/LangGraph updates.

---

## Environment Variables

LangSmith (always recommended for observability)

LANGSMITH_API_KEY=<your-key> LANGSMITH_PROJECT=<project-name> # optional, defaults to "default"

Model provider — set the one(s) you use

OPENAI_API_KEY=<your-key> ANTHROPIC_API_KEY=<your-key> GOOGLE_API_KEY=<your-key> MISTRAL_API_KEY=<your-key> GROQ_API_KEY=<your-key> COHERE_API_KEY=<your-key> FIREWORKS_API_KEY=<your-key> TOGETHER_API_KEY=<your-key> HUGGINGFACEHUB_API_TOKEN=<your-key>

Common tool/retrieval services

TAVILY_API_KEY=<your-key> # for Tavily search PINECONE_API_KEY=<your-key> # for Pinecone


---

## Common Mistakes

# CORRECT: LangChain 1.0 LTS

langchain>=1.0,<2.0

</fix-legacy-version>

<fix-community-unpinned> langchain-community can break on minor version bumps — it does not follow semver.


# WRONG: allows minor-version updates that may be breaking

langchain-community>=0.4

# CORRECT: pin to exact minor series

langchain-community>=0.4.0,<0.5.0

Also consider switching to the equivalent dedicated integration package if one exists (e.g. langchain-chroma instead of the community Chroma integration). </fix-community-unpinned>

<fix-community-tool-outdated> Community tool packages like langchain-tavily and vector store integrations release compatibility fixes alongside LangChain updates. Using an old pinned version can cause import errors or broken tool schemas.


# RISKY: old pin may be incompatible with LangChain 1.0

langchain-tavily==0.0.1

# BETTER: allow latest within the current major

langchain-tavily>=0.1

</fix-community-tool-outdated>

<fix-community-import-deprecated> Many tools that used to live in langchain-community now have dedicated packages with updated import paths. Always prefer the dedicated package import.

# WRONG — deprecated community import path
from langchain_community.tools.tavily_search import TavilySearchResults
from langchain_community.tools import WikipediaQueryRun
from langchain_community.vectorstores import Chroma
from langchain_community.vectorstores import Pinecone

# CORRECT — use dedicated package imports
from langchain_tavily import TavilySearch                  # pip: langchain-tavily (TavilySearchResults is deprecated)
from langchain_community.tools import WikipediaQueryRun  # no dedicated pkg yet
from langchain_chroma import Chroma                       # pip: langchain-chroma
from langchain_pinecone import PineconeVectorStore        # pip: langchain-pinecone

To find the current canonical import for any integration, search the integrations directory: https://python.langchain.com/docs/integrations/tools/

Each entry shows the correct package and import path. If a dedicated package exists, use it — the community path may still work but is considered legacy.

// CORRECT: always list @langchain/core explicitly {"dependencies": {"@langchain/core": "^1.0.0", "@langchain/langgraph": "^1.0.0"}}

</typescript>
</fix-core-not-installed>

<fix-python-version>
<python>
Python 3.9 and below are not supported by LangChain 1.0.

Verify before installing

import sys assert sys.version_info >= (3, 10), "Python 3.10+ required for LangChain 1.0"

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

37.27%
按下载量换算3,339

Claude

30.75%
按下载量换算2,755

Cursor

19.75%
按下载量换算1,770

Gemini CLI

10.1%
按下载量换算905

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

继续浏览同类 Skills