[Redis]: Vector database added. (#2032)
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docs/components/vectordbs/dbs/redis.mdx
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44
docs/components/vectordbs/dbs/redis.mdx
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[Redis](https://redis.io/) is a scalable, real-time database that can store, search, and analyze vector data.
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### Installation
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```bash
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pip install redis redisvl
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```
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Redis Stack using Docker:
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```bash
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docker run -d --name redis-stack -p 6379:6379 -p 8001:8001 redis/redis-stack:latest
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```
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### Usage
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```python
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import os
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from mem0 import Memory
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os.environ["OPENAI_API_KEY"] = "sk-xx"
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config = {
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"vector_store": {
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"provider": "redis",
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"config": {
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"collection_name": "mem0",
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"embedding_model_dims": 1536,
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"redis_url": "redis://localhost:6379"
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}
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}
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}
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m = Memory.from_config(config)
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m.add("Likes to play cricket on weekends", user_id="alice", metadata={"category": "hobbies"})
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```
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### Config
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Let's see the available parameters for the `redis` config:
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| Parameter | Description | Default Value |
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| --- | --- | --- |
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| `collection_name` | The name of the collection to store the vectors | `mem0` |
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| `embedding_model_dims` | Dimensions of the embedding model | `1536` |
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| `redis_url` | The URL of the Redis server | `None` |
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@@ -14,6 +14,7 @@ See the list of supported vector databases below.
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<Card title="Pgvector" href="/components/vectordbs/dbs/pgvector"></Card>
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<Card title="Milvus" href="/components/vectordbs/dbs/milvus"></Card>
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<Card title="Azure AI Search" href="/components/vectordbs/dbs/azure_ai_search"></Card>
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<Card title="Redis" href="/components/vectordbs/dbs/redis"></Card>
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</CardGroup>
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## Usage
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@@ -111,7 +111,8 @@
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"components/vectordbs/dbs/chroma",
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"components/vectordbs/dbs/pgvector",
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"components/vectordbs/dbs/milvus",
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"components/vectordbs/dbs/azure_ai_search"
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"components/vectordbs/dbs/azure_ai_search",
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"components/vectordbs/dbs/redis"
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]
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}
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]
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