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Integrate Moss semantic search into LangChain using a custom retriever and agent tool. This setup lets you use Moss in standard LangChain RAG pipelines and agentic workflows with sub-10ms retrieval latency.
Note: For complete examples including RAG chains and ReAct agents, see the LangChain cookbook.

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Why use Moss with LangChain?

LangChain’s retriever interface is the standard way to plug external knowledge into LLM chains. Moss delivers sub-10ms semantic search that slots directly into this interface, giving your chains and agents fast, accurate retrieval without the latency overhead of traditional vector databases.

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Required tools

  • Moss account with project credentials
  • OpenAI API key (for LLM and agent usage)
  • Python 3.11+

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Integration guide

1

Installation

pip install moss langchain langchain-openai python-dotenv
2

Environment setup

Create a .env file in your project root.
.env
# Moss Credentials
MOSS_PROJECT_ID=your_project_id
MOSS_PROJECT_KEY=your_project_key
MOSS_INDEX_NAME=your_index_name

# OpenAI
OPENAI_API_KEY=sk-...
3

Use as a retriever

The cookbook provides a MossRetriever class that implements LangChain’s BaseRetriever interface. It loads the Moss index once and returns Document objects with metadata and relevance scores.
from moss_langchain import MossRetriever

retriever = MossRetriever(
    project_id="your-project-id",
    project_key="your-project-key",
    index_name="your-index-name",
    top_k=3,
    alpha=0.5,
)

# Use in async contexts (recommended)
docs = await retriever.ainvoke("What is the return policy?")
for doc in docs:
    print(doc.page_content, doc.metadata["score"])
4

Use as an agent tool

The cookbook also provides a get_moss_tool() function that wraps the retriever as a LangChain Tool, so agents can search the knowledge base autonomously.
from moss_langchain import MossRetriever, get_moss_tool

retriever = MossRetriever(
    project_id="your-project-id",
    project_key="your-project-key",
    index_name="your-index-name",
)

tool = get_moss_tool(retriever)
# tool.name == "moss_search"
# Use with create_openai_functions_agent or any LangChain agent