LangChain 生成
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LangChain Builder
Build LangChain chains, agents, and tool integrations with scaffolding, validation, and template generation.
What it does
Scaffolds LangChain projects, generates chain and agent configurations, creates prompt templates, and validates chain configs for common errors. Produces ready-to-run Python files with proper imports and structure.
Commands
| Command | Description |
|---|---|
init <project> |
Scaffold a new LangChain project with requirements.txt and project structure |
chain <type> --name <n> |
Generate a chain template: llm, sequential, router |
agent <tools> |
Generate an agent config with specified tools (search, calculator, python_repl) |
prompt <description> |
Create a prompt template from a natural language description |
validate <file> |
Check a chain/agent Python file for common configuration errors |
Examples
python3 langchain_builder.py init my-rag-app
python3 langchain_builder.py chain llm --name summarizer
python3 langchain_builder.py agent search,calculator
python3 langchain_builder.py prompt "Summarize a document in 3 bullet points"
python3 langchain_builder.py validate my_chain.py
Chain types
- llm — Single LLMChain with prompt + model
- sequential — SequentialChain connecting multiple LLMChains
- router — RouterChain that selects sub-chains based on input classification
Generated files include
- Proper
langchainimports (community packages where needed) - Environment variable loading via
python-dotenv - Error handling and type hints
- Runnable patterns (LangChain Expression Language where applicable)
<!-- tomevault:4.0:skill_md:2026-05-23 -->Source: Danielhogben/hermes-skills — distributed by TomeVault.
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- AI 智能
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- 88 / 100 · 启发式扫描,不代表运行安全
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- @tomevault-io · 未声明 license
- 流狐 Token 估算
- 低消耗
- 流狐接入估算
- 即装即用
- 是否需要外部 API Key
- 未发现要求
- 检测到的系统要求
- 未声明
- 底层运行要求
- Python
- 检测到的文件与系统行为
-
- 只读
- 允许写入 / 修改
- 读取环境变量
- 检测到的网络行为
- 仅限本地
- 安装命令数
- 无(仅作为资料)
档案由构建时根据 SKILL.md 与安装命令自动衍生,可能与作者实际意图存在差异。
需要注意: 未限定 allowed-tools,默认拥有全部工具权限。
作者没有在当前 SKILL.md 中定义固定输出样例。 Scaffolds LangChain projects, generates chain and agent configurations, creates prompt templates, and validates chain configs for common errors. Produces ready-to-run Python files with proper imports and structure.
Command · Description init <project> · Scaffold a new LangChain project with requirements.txt and project structure chain <type> --name <n> · Generate a chain template: llm, sequential, router
Examples
llm — Single LLMChain with prompt + model sequential — SequentialChain connecting multiple LLMChains router — RouterChain that selects sub-chains based on input classification
Proper langchain imports (community packages where needed) Environment variable loading via python-dotenv Error handling and type hints
# LangChain Builder
Build LangChain chains, agents, and tool integrations with scaffolding, validation, and template generation.
## What it does
Scaffolds LangChain projects, generates chain and agent configurations, creates prompt templates, and validates chain configs for common errors. Produces ready-to-run Python files with proper imports and structure.
## Commands
| Command | Description |
|---------|-------------|
| `init <project>` | Scaffold a new LangChain project with requirements.txt and project structure |
| `chain <type> --name <n>` | Generate a chain template: `llm`, `sequential`, `router` |
| `agent <tools>` | Generate an agent config with specified tools (search, calculator, python_repl) |
| `prompt <description>` | Create a prompt template from a natural language description |
| `validate <file>` | Check a chain/agent Python file for common configuration errors |
## Examples
```bash
python3 langchain_builder.py init my-rag-app
python3 langchain_builder.py chain llm --name summarizer
python3 langchain_builder.py agent search,calculator
python3 langchain_builder.py prompt "Summarize a document in 3 bullet points"
python3 langchain_builder.py validate my_chain.py
```
## Chain types
- **llm** — Single LLMChain with prompt + model
- **sequential** — SequentialChain connecting multiple LLMChains
- **router** — RouterChain that selects sub-chains based on input classification
## Generated files include
- Proper `langchain` imports (community packages where needed)
- Environment variable loading via `python-dotenv`
- Error handling and type hints
- Runnable patterns (LangChain Expression Language where applicable)
---
… 作者原文负责流程事实;流狐只索引当前章节、要点、文件与命令。
章节 -> What it does → Commands → Examples → Chain types → Generated files include
要点 -> llm · sequential · router · Build LangChain chains, agents, and tool integrations with scaffolding, validation, and template generation. · --- > Source: [Danielhogben/hermes-skills](https://github.com/Danielhogben/hermes-skills) — distributed by [TomeVault](https://tomevault.io).
文件/命令 -> init <project> · chain <type> --name <n> · llm · sequential · router · agent <tools> · prompt <description> · validate <file>
内容 SHA-256 -> c94fce76139b
原文结构
适用与边界
原文中的明确线索
init <project>、chain <type> --name <n>、llm、sequential、router、agent <tools>、prompt <description>、validate <file>