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Quickstart Guide

Get up and running with langchain-openapi in five minutes.

1. Load an OpenAPI Specification

OpenAPIToolkit provides convenient class methods to load specs from URLs, local files, or raw dictionaries.

from langchain_openapi_tools import OpenAPIToolkit

# Load from URL
toolkit = OpenAPIToolkit.from_url("https://api.crossref.org/swagger-docs")

# Load from local YAML/JSON file
# toolkit = OpenAPIToolkit.from_file("openapi.yaml")

# Load from dictionary
# toolkit = OpenAPIToolkit.from_dict(spec_dict)

2. Inspect Generated Tools

Call .get_tools() to obtain native LangChain StructuredTool instances.

tools = toolkit.get_tools()

for tool in tools[:3]:
    print(f"Name: {tool.name}")
    print(f"Description: {tool.description}")
    print("---")

3. Invoke a Tool Directly

You can invoke tools synchronously (tool.invoke) or asynchronously (tool.ainvoke):

import asyncio


async def main():
    tool = toolkit.get_tool("search_works")
    result = await tool.ainvoke({"query": "LangGraph"})
    print(result)


asyncio.run(main())

4. Bind Tools to a LangChain Agent

Bind generated tools to an agent or LLM framework:

from langchain_openapi_tools import OpenAPIToolkit

toolkit = OpenAPIToolkit.from_url("https://api.crossref.org/swagger-docs")
tools = toolkit.get_tools()

# Bind to LLM
# llm_with_tools = llm.bind_tools(tools)