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)
Source: Danielhogben/hermes-skills — distributed by TomeVault.