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added redis method to delete entries by keys (#6222)

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In addition to my last pr (return keys of added entries), we also need a
method to delete the entries by keys.

@dev2049
pull/6623/head^2
Christoph Kahl 1 year ago committed by GitHub
parent c28990d871
commit 9d42621fa4
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2 changed files with 110 additions and 71 deletions
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139
docs/extras/modules/data_connection/vectorstores/integrations/redis.ipynb
Unescape Escape View File

@ -70,7 +70,7 @@
},
{
"cell_type": "code",
"execution_count": 4,
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
@ -84,9 +84,16 @@
"embeddings = OpenAIEmbeddings()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"If you're not interested in the keys of your entries you can also create your redis instance from the documents."
]
},
{
"cell_type": "code",
"execution_count": 5,
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
@ -95,45 +102,42 @@
")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"If you're interested in the keys of your entries you have to split your docs in texts and metadatas"
]
},
{
"cell_type": "code",
"execution_count": 6,
"execution_count": null,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"'link'"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"outputs": [],
"source": [
"texts = [d.page_content for d in docs]\n",
"metadatas = [d.metadata for d in docs]\n",
"\n",
"rds, keys = Redis.from_texts_return_keys(texts,\n",
" embeddings,\n",
" redis_url=\"redis://localhost:6379\",\n",
" index_name=\"link\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"rds.index_name"
]
},
{
"cell_type": "code",
"execution_count": 7,
"execution_count": null,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Tonight. I call on the Senate to: Pass the Freedom to Vote Act. Pass the John Lewis Voting Rights Act. And while you’re at it, pass the Disclose Act so Americans can know who is funding our elections. \n",
"\n",
"Tonight, I’d like to honor someone who has dedicated his life to serve this country: Justice Stephen Breyer—an Army veteran, Constitutional scholar, and retiring Justice of the United States Supreme Court. Justice Breyer, thank you for your service. \n",
"\n",
"One of the most serious constitutional responsibilities a President has is nominating someone to serve on the United States Supreme Court. \n",
"\n",
"And I did that 4 days ago, when I nominated Circuit Court of Appeals Judge Ketanji Brown Jackson. One of our nation’s top legal minds, who will continue Justice Breyer’s legacy of excellence.\n"
]
}
],
"outputs": [],
"source": [
"query = \"What did the president say about Ketanji Brown Jackson\"\n",
"results = rds.similarity_search(query)\n",
@ -142,34 +146,18 @@
},
{
"cell_type": "code",
"execution_count": 8,
"execution_count": null,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"['doc:link:d7d02e3faf1b40bbbe29a683ff75b280']\n"
]
}
],
"outputs": [],
"source": [
"print(rds.add_texts([\"Ankush went to Princeton\"]))"
]
},
{
"cell_type": "code",
"execution_count": 9,
"execution_count": null,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Ankush went to Princeton\n"
]
}
],
"outputs": [],
"source": [
"query = \"Princeton\"\n",
"results = rds.similarity_search(query)\n",
@ -178,23 +166,9 @@
},
{
"cell_type": "code",
"execution_count": 10,
"execution_count": null,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Tonight. I call on the Senate to: Pass the Freedom to Vote Act. Pass the John Lewis Voting Rights Act. And while you’re at it, pass the Disclose Act so Americans can know who is funding our elections. \n",
"\n",
"Tonight, I’d like to honor someone who has dedicated his life to serve this country: Justice Stephen Breyer—an Army veteran, Constitutional scholar, and retiring Justice of the United States Supreme Court. Justice Breyer, thank you for your service. \n",
"\n",
"One of the most serious constitutional responsibilities a President has is nominating someone to serve on the United States Supreme Court. \n",
"\n",
"And I did that 4 days ago, when I nominated Circuit Court of Appeals Judge Ketanji Brown Jackson. One of our nation’s top legal minds, who will continue Justice Breyer’s legacy of excellence.\n"
]
}
],
"outputs": [],
"source": [
"# Load from existing index\n",
"rds = Redis.from_existing_index(\n",
@ -219,7 +193,7 @@
},
{
"cell_type": "code",
"execution_count": 11,
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
@ -228,7 +202,7 @@
},
{
"cell_type": "code",
"execution_count": 12,
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
@ -244,7 +218,7 @@
},
{
"cell_type": "code",
"execution_count": 13,
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
@ -260,6 +234,31 @@
"# Here we can see it doesn't return any results because there are no relevant documents\n",
"retriever.get_relevant_documents(\"where did ankush go to college?\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Delete keys"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"To delete your entries you have to address them by their keys."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"scrolled": true
},
"outputs": [],
"source": [
"Redis.delete(keys, redis_url=\"redis://localhost:6379\")"
]
}
],
"metadata": {

42
langchain/vectorstores/redis.py
Unescape Escape View File

@ -375,13 +375,14 @@ class Redis(VectorStore):
1. Embeds documents.
2. Creates a new index for the embeddings in Redis.
3. Adds the documents to the newly created Redis index.
4. Returns the keys of the newly created documents.
This is intended to be a quick way to get started.
Example:
.. code-block:: python
from langchain.vectorstores import Redis
from langchain.embeddings import OpenAIEmbeddings
embeddings = OpenAIEmbeddings()
redisearch = RediSearch.from_texts(
redisearch, keys = RediSearch.from_texts_return_keys(
texts,
embeddings,
redis_url="redis://username:password@localhost:6379"
@ -458,6 +459,45 @@ class Redis(VectorStore):
)
return instance
@staticmethod
def delete(
keys: List[str],
**kwargs: Any,
) -> bool:
"""
Delete a Redis entry.
Args:
keys (List[str]): Keys of entries to delete.
Returns:
bool: Whether or not the deletions were successful.
"""
redis_url = get_from_dict_or_env(kwargs, "redis_url", "REDIS_URL")
try:
import redis
except ImportError:
raise ValueError(
"Could not import redis python package. "
"Please install it with `pip install redis`."
)
try:
# We need to first remove redis_url from kwargs,
# otherwise passing it to Redis will result in an error.
if "redis_url" in kwargs:
kwargs.pop("redis_url")
client = redis.from_url(url=redis_url, **kwargs)
except ValueError as e:
raise ValueError(f"Your redis connected error: {e}")
# Check if index exists
try:
client.delete(*keys)
logger.info("Entries deleted")
return True
except: # noqa: E722
# Keys not exist
return False
@staticmethod
def drop_index(
index_name: str,

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