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@@ -49,7 +49,7 @@ Install `redisvl` into your Python (>=3.8) environment using `pip`:
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```bash
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pip install redisvl
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```
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> For more detailed instructions, visit the [installation guide](https://docs.redisvl.com/en/latest/overview/installation.html).
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> For more detailed instructions, visit the [installation guide](https://docs.redisvl.com/en/stable/overview/installation.html).
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## Setting up Redis
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## 🗃️ Redis Index Management
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1. [Design a schema for your use case](https://docs.redisvl.com/en/latest/user_guide/getting_started_01.html#define-an-indexschema) that models your dataset with built-in Redis and indexable fields (*e.g. text, tags, numerics, geo, and vectors*). [Load a schema](https://docs.redisvl.com/en/latest/user_guide/getting_started_01.html#example-schema-creation) from a YAML file:
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1. [Design a schema for your use case](https://docs.redisvl.com/en/stable/user_guide/getting_started_01.html#define-an-indexschema) that models your dataset with built-in Redis and indexable fields (*e.g. text, tags, numerics, geo, and vectors*). [Load a schema](https://docs.redisvl.com/en/stable/user_guide/getting_started_01.html#example-schema-creation) from a YAML file:
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```yaml
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index:
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name: user-idx
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})
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```
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2. [Create a SearchIndex](https://docs.redisvl.com/en/latest/user_guide/getting_started_01.html#create-a-searchindex) class with an input schema and client connection in order to perform admin and search operations on your index in Redis:
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2. [Create a SearchIndex](https://docs.redisvl.com/en/stable/user_guide/getting_started_01.html#create-a-searchindex) class with an input schema and client connection in order to perform admin and search operations on your index in Redis:
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```python
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from redis import Redis
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from redisvl.index import SearchIndex
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# Create the index in Redis
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index.create()
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```
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> Async compliant search index class also available: [AsyncSearchIndex](https://docs.redisvl.com/en/latest/api/searchindex.html#redisvl.index.AsyncSearchIndex).
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> Async compliant search index class also available: [AsyncSearchIndex](https://docs.redisvl.com/en/stable/api/searchindex.html#redisvl.index.AsyncSearchIndex).
from redisvl.utils.vectorize import CohereTextVectorizer
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)
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```
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> Learn more about using [vectorizers]((https://docs.redisvl.com/en/latest/user_guide/vectorizers_04.html))in your embedding workflows.
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> Learn more about using [vectorizers]((https://docs.redisvl.com/en/stable/user_guide/vectorizers_04.html))in your embedding workflows.
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### Rerankers
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[Integrate with popular reranking providers](https://docs.redisvl.com/en/latest/user_guide/rerankers_06.html) to improve the relevancy of the initial search results from Redis
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[Integrate with popular reranking providers](https://docs.redisvl.com/en/stable/user_guide/rerankers_06.html) to improve the relevancy of the initial search results from Redis
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@@ -230,7 +230,7 @@ We're excited to announce the support for **RedisVL Extensions**. These modules
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*Have an idea for another extension? Open a PR or reach out to us at [email protected]. We're always open to feedback.*
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### LLM Semantic Caching
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Increase application throughput and reduce the cost of using LLM models in production by leveraging previously generated knowledge with the [`SemanticCache`](https://docs.redisvl.com/en/latest/api/cache.html#semanticcache).
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Increase application throughput and reduce the cost of using LLM models in production by leveraging previously generated knowledge with the [`SemanticCache`](https://docs.redisvl.com/en/stable/api/cache.html#semanticcache).
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```python
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from redisvl.extensions.llmcache import SemanticCache
> Learn more about [semantic caching]((https://docs.redisvl.com/en/latest/user_guide/llmcache_03.html))for LLMs.
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> Learn more about [semantic caching]((https://docs.redisvl.com/en/stable/user_guide/llmcache_03.html))for LLMs.
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### LLM Session Management
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Improve personalization and accuracy of LLM responses by providing user chat history as context. Manage access to the session data using recency or relevancy, *powered by vector search* with the [`SemanticSessionManager`](https://docs.redisvl.com/en/latest/api/session_manager.html).
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Improve personalization and accuracy of LLM responses by providing user chat history as context. Manage access to the session data using recency or relevancy, *powered by vector search* with the [`SemanticSessionManager`](https://docs.redisvl.com/en/stable/api/session_manager.html).
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```python
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from redisvl.extensions.session_manager import SemanticSessionManager
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