langchain-milvus
An integration package connecting Milvus and LangChain
Decision gist · record as of 2026-08-14
Yes. The package is actively maintained, has no security vulnerabilities, low install friction, and MIT licensing. Install it if you are building LangChain applications that need vector storage and retrieval—it is the direct integration point between LangChain and Milvus.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.10 or later; langchain-core and pymilvus must be installed and configured.
- Low install friction with a pure-Python wheel.
- Active maintenance: last commit 2026-07-25, release 28 days old.
License · maintenance · safety
MIT (permissive) — MIT license is permissive; you may use, modify, and distribute this package freely in commercial and private projects with minimal restrictions.
last release 2026-07-17 (28 days) · last repo commit 2026-07-25 · 58 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 675,671 downloads/mo, #5,384 on PyPI
Alternatives
Verify before relying
pip install langchain-milvus
from langchain_milvus import Milvus
from langchain_core.embeddings import Embeddings
vector_store = Milvus(embedding_function=your_embeddings, collection_name="my_collection")- Whether milvus-lite runs without additional system dependencies on all supported platforms.
- Performance characteristics and scaling limits for the vector search operations.
- Specific async API coverage and whether all retrieval methods support async.
What it is and what it does
langchain-milvus bridges LangChain and Milvus, a vector database built for similarity search and AI workloads. It lets you store embeddings from any LangChain embedding model in Milvus and retrieve them via vector similarity, hybrid search (combining vector and keyword matching), and diversity-filtered results. The package wraps Milvus operations as a LangChain VectorStore, so you can use it directly in retrieval chains and RAG pipelines without learning Milvus internals.
The integration supports multiple vector fields per collection, sparse embeddings, Milvus built-in functions like BM25, and full async operations. It is actively maintained, has no known vulnerabilities, and depends on three runtime packages: langchain-core (the LangChain abstraction layer), milvus-lite (an embedded Milvus instance), and pymilvus (the Python client for Milvus).
Use it for
- Build RAG (Retrieval Augmented Generation) pipelines that fetch relevant documents from Milvus before passing them to an LLM.
- Implement semantic search over embeddings stored in Milvus, returning results ranked by vector similarity.
- Combine vector search with full-text search (hybrid search) to balance semantic and keyword relevance.
- Store and retrieve sparse vector embeddings for specialized AI models that produce sparse representations.
- Filter search results for diversity using maximal marginal relevance to avoid redundant or near-duplicate results.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
The package is actively maintained, has no security vulnerabilities, low install friction, and MIT licensing. Install it if you are building LangChain applications that need vector storage and retrieval—it is the direct integration point between LangChain and Milvus.
Install
langchain-milvus on PyPI
Before you install
Low install friction with a pure-Python wheel. Active maintenance: last commit 2026-07-25, release 28 days old. Depends on langchain-core, milvus-lite, and pymilvus.
Requires Python 3.10 or later; langchain-core and pymilvus must be installed and configured.
License in practice
MIT license is permissive; you may use, modify, and distribute this package freely in commercial and private projects with minimal restrictions.
Quickstart
pip install langchain-milvus
from langchain_milvus import Milvus
from langchain_core.embeddings import Embeddings
vector_store = Milvus(embedding_function=your_embeddings, collection_name="my_collection")Verify before relying
- Whether milvus-lite runs without additional system dependencies on all supported platforms.
- Performance characteristics and scaling limits for the vector search operations.
- Specific async API coverage and whether all retrieval methods support async.
Package facts
| License | MIT permissive |
| Python support | Supports the current Python release <4.0,>=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 3 packageslangchain-coremilvus-litepymilvus |
| Maintenance | Actively maintained 28 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 675,671 / month, #5,384 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | License :: OSI Approved :: MIT LicenseProgramming Language :: Python :: 3Programming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13 |
Evidence: langchain_milvus-0.4.0-py3-none-any.whl
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See also langchain-chroma · milvus-lite · pymilvus.model · llama-index-vector-stores-milvus · langchain-qdrant · langchain-weaviate · langchain-plaid · langchain-redis · langchain-pinecone · langchain-graph-retriever