Install & Compatibility
Where this runs
tested against v0.2.5 · pip install
no network on importno background threads
Install × environment matrix
Each cell = how many times install + import succeeded across repeated harness runs. Partial = flaky.
glibc = Debian/Ubuntu slim · musl = Alpine Linux
muslpy 3.10–3.910 runs
build_error
glibcpy 3.10–3.910 runs
installs and imports cleanly · install 10.0s · import 2.691s · 182MB
183MB installed
● package 183MB
Code
Verified usage
Verified import paths — ran on the pinned version, not inferred.
RedisVectorStore
✓ from langchain_redis import RedisVectorStore
✗ from langchain_redis.vectorstores import RedisVectorStore
Incorrect import path removed in v0.1.0
Initializes a RedisVectorStore, adds documents, and performs similarity search. Requires a running Redis instance and OpenAI API key set as OPENAI_API_KEY.
import os
from langchain_redis import RedisVectorStore, RedisConfig
from langchain_core.documents import Document
from langchain_openai import OpenAIEmbeddings
redis_url = os.environ.get('REDIS_URL', 'redis://localhost:6379')
embeddings = OpenAIEmbeddings(model="text-embedding-ada-002")
config = RedisConfig(redis_url=redis_url)
vector_store = RedisVectorStore(config, embeddings)
docs = [
Document(page_content="LangChain is a framework for LLM apps", metadata={"category": "ai"}),
Document(page_content="Redis is an in-memory data store", metadata={"category": "database"})
]
vector_store.add_documents(docs)
results = vector_store.similarity_search("LLM framework", k=1)
print(results[0].page_content)
Debug
Known issues
breakingUpgraded from Pydantic v1 to v2 in v0.1.0. Custom schemas using Pydantic v1 model validators may break.fixUpdate custom schemas to Pydantic v2 syntax (e.g., model_validator instead of root_validator).
affects: <0.1.0 -> >=0.1.0
breakingImport paths restructured in v0.2.0. Top-level imports like `from langchain_redis import RedisVectorStore` now required; deep imports (e.g., `from langchain_redis.vectorstores import RedisVectorStore`) removed.fixUse top-level imports from `langchain_redis`.
affects: <0.2.0 -> >=0.2.0
deprecatedRedisConfig.index_schema initialization changed in v0.1.0. Setting index_schema directly is deprecated; use `add_texts` or `create_index` with schema instead.fixPass schema via `add_texts` method or use `RedisVectorStore.from_texts`.
affects: >=0.1.0
gotchaRedisVectorStore.add_texts ignores the `ids` parameter if provided. This is a known bug fixed in v0.2.2.fixUpgrade to v0.2.2 or later, or use `add_documents` with Document objects that have explicit IDs.
affects: >=0.2.0, <0.2.2
Errors
Common errors & fixes
ModuleNotFoundError: No module named 'langchain_redis'
Package not installed or import name mismatch (old import path `langchain_redis` vs `langchain.redis`).
fixRun `pip install langchain-redis` and use `from langchain_redis import RedisVectorStore`.
redis.exceptions.ResponseError: Unknown index name
The specified Redis index does not exist or was not created before querying.
fixEnsure the index is created by calling `vector_store.create_index()` or using `add_texts` first. Verify index name spelling.
pydantic.errors.PydanticInvalidForJsonSchema
Using Pydantic v1 custom schema with langchain-redis v0.1.0+ which requires Pydantic v2.
fixMigrate custom schemas to Pydantic v2 syntax. See Pydantic migration guide.
Upgrade
Version history
0.2.5latest on PyPI · released Nov 25, 2025
Audit
Dependencies
langchain-corerequiredCore dependency for all integrations
redisrequiredRedis client library
redisvlrequiredRedis vector library for vector store and semantic cache
numpyrequiredRequired for vector operations