Moss - Real-time Semantic Search for Conversational AI

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.

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.

Required tools

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

Integration guide

Installation

pip install moss langchain langchain-openai python-dotenv

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-...

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"])

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

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Why use Moss with LangChain?

Required tools

Integration guide

​Why use Moss with LangChain?

​Required tools

​Integration guide

Why use Moss with LangChain?

Required tools

Integration guide