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Update redis vector store #12386

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Apr 11, 2024
Merged

Update redis vector store #12386

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c90a144
add basic index schema and update environment
tylerhutcherson Mar 21, 2024
15015c0
refactor redis interface
tylerhutcherson Mar 28, 2024
3d6d155
initial lock file
tylerhutcherson Mar 28, 2024
ed11137
update version
tylerhutcherson Mar 28, 2024
7b26ae4
formatting and linting updates
tylerhutcherson Mar 29, 2024
79c6a73
fix
tylerhutcherson Mar 29, 2024
d671247
more formatting tweaks
tylerhutcherson Mar 29, 2024
b66edc3
update doc string
tylerhutcherson Apr 8, 2024
91217f4
fixup ingestion examples cont
tylerhutcherson Apr 9, 2024
56e8a68
update author
tylerhutcherson Apr 9, 2024
1bfe4fd
update flag for old kwargs
tylerhutcherson Apr 9, 2024
cec41be
handle index creation on class instantiation
tylerhutcherson Apr 10, 2024
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2 changes: 1 addition & 1 deletion docs/docs/community/integrations/vector_stores.md
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Expand Up @@ -32,7 +32,7 @@ as the storage backend for `VectorStoreIndex`.
- Pinecone (`PineconeVectorStore`). [Installation/Quickstart](https://docs.pinecone.io/docs/quickstart).
- Qdrant (`QdrantVectorStore`) [Installation](https://qdrant.tech/documentation/install/) [Python Client](https://qdrant.tech/documentation/install/#python-client)
- LanceDB (`LanceDBVectorStore`) [Installation/Quickstart](https://lancedb.github.io/lancedb/basic/)
- Redis (`RedisVectorStore`). [Installation](https://redis.io/docs/getting-started/installation/).
- Redis (`RedisVectorStore`). [Installation](https://redis.io/docs/latest/operate/oss_and_stack/install/install-stack/).
- Supabase (`SupabaseVectorStore`). [Quickstart](https://supabase.github.io/vecs/api/).
- TiDB (`TiDBVectorStore`). [Quickstart](../../examples/vector_stores/TiDBVector.ipynb). [Installation](https://tidb.cloud/ai). [Python Client](https://github.com/pingcap/tidb-vector-python).
- TimeScale (`TimescaleVectorStore`). [Installation](https://github.com/timescale/python-vector).
Expand Down
174 changes: 142 additions & 32 deletions docs/docs/examples/ingestion/ingestion_gdrive.ipynb
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Expand Up @@ -100,10 +100,107 @@
" IngestionPipeline,\n",
" IngestionCache,\n",
")\n",
"from llama_index.core.ingestion.cache import RedisCache\n",
"from llama_index.storage.kvstore.redis import RedisKVStore as RedisCache\n",
"from llama_index.storage.docstore.redis import RedisDocumentStore\n",
"from llama_index.core.node_parser import SentenceSplitter\n",
"from llama_index.vector_stores.redis import RedisVectorStore"
"from llama_index.vector_stores.redis import RedisVectorStore\n",
"\n",
"from redisvl.schema import IndexSchema"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "baf744be",
"metadata": {},
"outputs": [
{
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"text/plain": [
"model.safetensors: 0%| | 0.00/133M [00:00<?, ?B/s]"
]
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]
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},
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"text/plain": [
"vocab.txt: 0%| | 0.00/232k [00:00<?, ?B/s]"
]
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},
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},
"text/plain": [
"special_tokens_map.json: 0%| | 0.00/125 [00:00<?, ?B/s]"
]
},
"metadata": {},
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},
{
"data": {
"application/vnd.jupyter.widget-view+json": {
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},
"text/plain": [
"1_Pooling/config.json: 0%| | 0.00/190 [00:00<?, ?B/s]"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"embed_model = HuggingFaceEmbedding(model_name=\"BAAI/bge-small-en-v1.5\")"
]
},
{
Expand All @@ -113,15 +210,32 @@
"metadata": {},
"outputs": [],
"source": [
"vector_store = RedisVectorStore(\n",
" index_name=\"redis_vector_store\",\n",
" index_prefix=\"vectore_store\",\n",
" redis_url=\"redis://localhost:6379\",\n",
"custom_schema = IndexSchema.from_dict(\n",
" {\n",
" \"index\": {\"name\": \"gdrive\", \"prefix\": \"doc\"},\n",
" # customize fields that are indexed\n",
" \"fields\": [\n",
" # required fields for llamaindex\n",
" {\"type\": \"tag\", \"name\": \"id\"},\n",
" {\"type\": \"tag\", \"name\": \"doc_id\"},\n",
" {\"type\": \"text\", \"name\": \"text\"},\n",
" # custom vector field for bge-small-en-v1.5 embeddings\n",
" {\n",
" \"type\": \"vector\",\n",
" \"name\": \"vector\",\n",
" \"attrs\": {\n",
" \"dims\": 384,\n",
" \"algorithm\": \"hnsw\",\n",
" \"distance_metric\": \"cosine\",\n",
" },\n",
" },\n",
" ],\n",
" }\n",
")\n",
"\n",
"cache = IngestionCache(\n",
" cache=RedisCache.from_host_and_port(\"localhost\", 6379),\n",
" collection=\"redis_cache\",\n",
"vector_store = RedisVectorStore(\n",
" schema=custom_schema,\n",
" redis_url=\"redis://localhost:6379\",\n",
")"
]
},
Expand All @@ -133,19 +247,31 @@
"outputs": [],
"source": [
"# Optional: clear vector store if exists\n",
"if vector_store._index_exists():\n",
"if vector_store.index_exists():\n",
" vector_store.delete_index()"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "e6d98845",
"metadata": {},
"outputs": [],
"source": [
"# Set up the ingestion cache layer\n",
"cache = IngestionCache(\n",
" cache=RedisCache.from_host_and_port(\"localhost\", 6379),\n",
" collection=\"redis_cache\",\n",
")"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "3be817bd-81a1-436f-8f92-3eb48531c915",
"metadata": {},
"outputs": [],
"source": [
"embed_model = HuggingFaceEmbedding(model_name=\"BAAI/bge-small-en-v1.5\")\n",
"\n",
"pipeline = IngestionPipeline(\n",
" transformations=[\n",
" SentenceSplitter(),\n",
Expand Down Expand Up @@ -239,15 +365,7 @@
"execution_count": null,
"id": "c77f74b2-9bbe-46d6-b35f-23ea757b315b",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Ingested 6 Nodes\n"
]
}
],
"outputs": [],
"source": [
"nodes = pipeline.run(documents=docs)\n",
"print(f\"Ingested {len(nodes)} Nodes\")"
Expand Down Expand Up @@ -326,15 +444,7 @@
"execution_count": null,
"id": "d490fbb8-82ec-4284-a19d-1a8ca69da2a4",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Ingested 1 Nodes\n"
]
}
],
"outputs": [],
"source": [
"docs = load_data(folder_id=\"1RFhr3-KmOZCR5rtp4dlOMNl3LKe1kOA5\")\n",
"nodes = pipeline.run(documents=docs)\n",
Expand Down Expand Up @@ -398,9 +508,9 @@
],
"metadata": {
"kernelspec": {
"display_name": "llama_index_v2",
"display_name": "llama-index-vector-stores-redis-MBNLFpFJ-py3.9",
"language": "python",
"name": "llama_index_v2"
"name": "python3"
},
"language_info": {
"codemirror_mode": {
Expand Down
78 changes: 41 additions & 37 deletions docs/docs/examples/ingestion/redis_ingestion_pipeline.ipynb
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Expand Up @@ -29,27 +29,6 @@
"%pip install llama-index-embeddings-huggingface"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Requirement already satisfied: redis in /home/loganm/.cache/pypoetry/virtualenvs/llama-index-4a-wkI5X-py3.11/lib/python3.11/site-packages (5.0.1)\n",
"Requirement already satisfied: async-timeout>=4.0.2 in /home/loganm/.cache/pypoetry/virtualenvs/llama-index-4a-wkI5X-py3.11/lib/python3.11/site-packages (from redis) (4.0.3)\n",
"\n",
"\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m A new release of pip is available: \u001b[0m\u001b[31;49m23.2.1\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m23.3.1\u001b[0m\n",
"\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m To update, run: \u001b[0m\u001b[32;49mpip install --upgrade pip\u001b[0m\n"
]
}
],
"source": [
"!pip install redis"
]
},
{
"cell_type": "code",
"execution_count": null,
Expand All @@ -75,7 +54,8 @@
"source": [
"import os\n",
"\n",
"os.environ[\"OPENAI_API_KEY\"] = \"sk-...\""
"os.environ[\"OPENAI_API_KEY\"] = \"sk-...\"\n",
"os.environ[\"TOKENIZERS_PARALLELISM\"] = \"false\""
]
},
{
Expand All @@ -102,16 +82,7 @@
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/loganm/.cache/pypoetry/virtualenvs/llama-index-4a-wkI5X-py3.11/lib/python3.11/site-packages/deeplake/util/check_latest_version.py:32: UserWarning: A newer version of deeplake (3.8.9) is available. It's recommended that you update to the latest version using `pip install -U deeplake`.\n",
" warnings.warn(\n"
]
}
],
"outputs": [],
"source": [
"from llama_index.core import SimpleDirectoryReader\n",
"\n",
Expand Down Expand Up @@ -144,13 +115,46 @@
" IngestionPipeline,\n",
" IngestionCache,\n",
")\n",
"from llama_index.core.ingestion.cache import RedisCache\n",
"from llama_index.storage.kvstore.redis import RedisKVStore as RedisCache\n",
"from llama_index.storage.docstore.redis import RedisDocumentStore\n",
"from llama_index.core.node_parser import SentenceSplitter\n",
"from llama_index.vector_stores.redis import RedisVectorStore\n",
"\n",
"from redisvl.schema import IndexSchema\n",
"\n",
"\n",
"embed_model = HuggingFaceEmbedding(model_name=\"BAAI/bge-small-en-v1.5\")\n",
"\n",
"custom_schema = IndexSchema.from_dict(\n",
" {\n",
" \"index\": {\"name\": \"redis_vector_store\", \"prefix\": \"doc\"},\n",
" # customize fields that are indexed\n",
" \"fields\": [\n",
" # required fields for llamaindex\n",
" {\"type\": \"tag\", \"name\": \"id\"},\n",
" {\"type\": \"tag\", \"name\": \"doc_id\"},\n",
" {\"type\": \"text\", \"name\": \"text\"},\n",
" # custom vector field for bge-small-en-v1.5 embeddings\n",
" {\n",
" \"type\": \"vector\",\n",
" \"name\": \"vector\",\n",
" \"attrs\": {\n",
" \"dims\": 384,\n",
" \"algorithm\": \"hnsw\",\n",
" \"distance_metric\": \"cosine\",\n",
" },\n",
" },\n",
" ],\n",
" }\n",
")"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"pipeline = IngestionPipeline(\n",
" transformations=[\n",
" SentenceSplitter(),\n",
Expand All @@ -160,8 +164,7 @@
" \"localhost\", 6379, namespace=\"document_store\"\n",
" ),\n",
" vector_store=RedisVectorStore(\n",
" index_name=\"redis_vector_store\",\n",
" index_prefix=\"vectore_store\",\n",
" schema=custom_schema,\n",
" redis_url=\"redis://localhost:6379\",\n",
" ),\n",
" cache=IngestionCache(\n",
Expand Down Expand Up @@ -221,7 +224,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
"I see two documents: \"test2.txt\" and \"test1.txt\".\n"
"I see two documents.\n"
]
}
],
Expand Down Expand Up @@ -261,6 +264,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
"13:32:07 redisvl.index.index INFO Index already exists, not overwriting.\n",
"Ingested 2 Nodes\n"
]
}
Expand All @@ -284,7 +288,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
"I see three documents: test3.txt, test1.txt, and test2.txt.\n",
"You see three documents: test3.txt, test1.txt, and test2.txt.\n",
"This is a test file: three!\n",
"This is a NEW test file: one!\n",
"This is a test file: two!\n"
Expand Down
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