reminix-langgraph 0.0.9

Reminix adapter for LangGraph - serve agents as REST APIs

reminix-langgraph

Reminix Runtime adapter for LangGraph. Serve any LangGraph agent as a REST API.

Ready to go live? Deploy to Reminix Cloud for zero-config hosting, or self-host on your own infrastructure.

Installation

pip install reminix-langgraph

This will also install reminix-runtime as a dependency.

Quick Start

from langgraph.prebuilt import create_react_agent
from langchain_openai import ChatOpenAI
from reminix_langgraph import serve_agent

llm = ChatOpenAI(model="gpt-4o")
graph = create_react_agent(llm, tools=[])
serve_agent(graph, name="my-agent", port=8080)

For more flexibility (e.g., serving multiple agents), use wrap_agent and serve separately:

from langgraph.prebuilt import create_react_agent
from langchain_openai import ChatOpenAI
from reminix_langgraph import wrap_agent
from reminix_runtime import serve

llm = ChatOpenAI(model="gpt-4o")
graph = create_react_agent(llm, tools=[])
agent = wrap_agent(graph, name="my-agent")
serve(agents=[agent], port=8080)

Your agent is now available at:

• POST /agents/my-agent/execute - Execute the agent

API Reference

serve_agent(graph, name, port, host)

Wrap a LangGraph graph and serve it immediately. Combines wrap_agent and serve for single-agent setups.

Parameter	Type	Default	Description
graph	CompiledGraph	required	A LangGraph compiled graph
name	str	"langgraph-agent"	Name for the agent (used in URL path)
port	int	8080	Port to serve on
host	str	"0.0.0.0"	Host to bind to

wrap_agent(graph, name)

Wrap a LangGraph compiled graph for use with Reminix Runtime. Use this with serve from reminix_runtime for multi-agent setups.

Parameter	Type	Default	Description
graph	CompiledGraph	required	A LangGraph compiled graph
name	str	"langgraph-agent"	Name for the agent (used in URL path)

Returns: LangGraphAgentAdapter - A Reminix adapter instance

How It Works

LangGraph uses a state-based approach. The adapter:

1. Converts incoming messages to LangChain message format
2. Invokes the graph with {"messages": [...]}
3. Extracts the last AI message from the response
4. Returns it in the Reminix response format

Endpoint Input/Output Formats

POST /agents/{name}/execute

Execute the graph. Input keys are passed directly to the graph.

Request:

{
  "messages": [
    {"role": "user", "content": "Hello!"}
  ]
}

Response:

{
  "output": "Hello! How can I help you today?"
}

Streaming

For streaming responses, set stream: true in the request:

{
  "messages": [{"role": "user", "content": "Hello!"}],
  "stream": true
}

The response will be sent as Server-Sent Events (SSE).

Runtime Documentation

For information about the server, endpoints, request/response formats, and more, see the reminix-runtime package.

Deployment

Ready to go live?

• Deploy to Reminix Cloud - Zero-config cloud hosting
• Self-host - Run on your own infrastructure

Links

• GitHub Repository
• LangGraph Documentation

License

Apache-2.0