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# Astra DB
> [DataStax Astra DB](https://docs.datastax.com/en/astra/home/astra.html) is a serverless
> vector-capable database built on `Apache Cassandra®`and made conveniently available
> through an easy-to-use JSON API.
See a [tutorial provided by DataStax](https://docs.datastax.com/en/astra/astra-db-vector/tutorials/chatbot.html).
## Installation and Setup
Install the following Python package:
```bash
pip install "langchain-astradb>=0.1.0"
```
Get the [connection secrets](https://docs.datastax.com/en/astra/astra-db-vector/get-started/quickstart.html).
Set up the following environment variables:
```python
ASTRA_DB_APPLICATION_TOKEN="TOKEN"
ASTRA_DB_API_ENDPOINT="API_ENDPOINT"
```
## Vector Store
```python
from langchain_astradb import AstraDBVectorStore
vector_store = AstraDBVectorStore(
embedding=my_embedding,
collection_name="my_store",
api_endpoint=ASTRA_DB_API_ENDPOINT,
token=ASTRA_DB_APPLICATION_TOKEN,
)
```
Learn more in the [example notebook](/docs/integrations/vectorstores/astradb).
See the [example provided by DataStax](https://docs.datastax.com/en/astra/astra-db-vector/integrations/langchain.html).
## Chat message history
```python
from langchain_astradb import AstraDBChatMessageHistory
message_history = AstraDBChatMessageHistory(
session_id="test-session",
api_endpoint=ASTRA_DB_API_ENDPOINT,
token=ASTRA_DB_APPLICATION_TOKEN,
)
```
See the [usage example](/docs/integrations/memory/astradb_chat_message_history#example).
## LLM Cache
```python
from langchain.globals import set_llm_cache
from langchain_astradb import AstraDBCache
set_llm_cache(AstraDBCache(
api_endpoint=ASTRA_DB_API_ENDPOINT,
token=ASTRA_DB_APPLICATION_TOKEN,
))
```
Learn more in the [example notebook](/docs/integrations/llm_caching#astra-db-caches) (scroll to the Astra DB section).
## Semantic LLM Cache
```python
from langchain.globals import set_llm_cache
from langchain_astradb import AstraDBSemanticCache
set_llm_cache(AstraDBSemanticCache(
embedding=my_embedding,
api_endpoint=ASTRA_DB_API_ENDPOINT,
token=ASTRA_DB_APPLICATION_TOKEN,
))
```
Learn more in the [example notebook](/docs/integrations/llm_caching#astra-db-caches) (scroll to the appropriate section).
Learn more in the [example notebook](/docs/integrations/memory/astradb_chat_message_history).
## Document loader
```python
from langchain_astradb import AstraDBLoader
loader = AstraDBLoader(
collection_name="my_collection",
api_endpoint=ASTRA_DB_API_ENDPOINT,
token=ASTRA_DB_APPLICATION_TOKEN,
)
```
Learn more in the [example notebook](/docs/integrations/document_loaders/astradb).
## Self-querying retriever
```python
from langchain_astradb import AstraDBVectorStore
from langchain.retrievers.self_query.base import SelfQueryRetriever
vector_store = AstraDBVectorStore(
embedding=my_embedding,
collection_name="my_store",
api_endpoint=ASTRA_DB_API_ENDPOINT,
token=ASTRA_DB_APPLICATION_TOKEN,
)
retriever = SelfQueryRetriever.from_llm(
my_llm,
vector_store,
document_content_description,
metadata_field_info
)
```
Learn more in the [example notebook](/docs/integrations/retrievers/self_query/astradb).
## Store
```python
from langchain_astradb import AstraDBStore
store = AstraDBStore(
collection_name="my_kv_store",
api_endpoint=ASTRA_DB_API_ENDPOINT,
token=ASTRA_DB_APPLICATION_TOKEN,
)
```
Learn more in the [example notebook](/docs/integrations/stores/astradb#astradbstore).
## Byte Store
```python
from langchain_astradb import AstraDBByteStore
store = AstraDBByteStore(
collection_name="my_kv_store",
api_endpoint=ASTRA_DB_API_ENDPOINT,
token=ASTRA_DB_APPLICATION_TOKEN,
)
```
Learn more in the [example notebook](/docs/integrations/stores/astradb#astradbbytestore).
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