From 8319755171c7313360e5ef408b35d017707aff1f Mon Sep 17 00:00:00 2001 From: mich-elle-luna <153109578+mich-elle-luna@users.noreply.github.com> Date: Mon, 18 Nov 2024 16:08:33 -0800 Subject: [PATCH 01/19] Create index.md --- content/develop/ai/index.md | 72 +++++++++++++++++++++++++++++++++++++ 1 file changed, 72 insertions(+) create mode 100644 content/develop/ai/index.md diff --git a/content/develop/ai/index.md b/content/develop/ai/index.md new file mode 100644 index 000000000..91691ead8 --- /dev/null +++ b/content/develop/ai/index.md @@ -0,0 +1,72 @@ +--- +Title: Redis for AI documentation +alwaysopen: false +categories: +- docs +- operate +- rs +- rc +description: An overivew of the Redis for AI documentation +linkTitle: Redis for AI +weight: 4 +--- +Redis stores and indexes vector embeddings that semantically represent unstructured data including text passages, images, videos, or audio. Store vectors and the associated metadata within hashes or JSON documents for indexing and search. + +| Vector | RAG | +| :-- | :-- | +| {{AI Redis icon.}}[Redis as a vector database quick start guide]({{< relref "/develop/get-started/vector-database" >}}) |{{AI Redis icon.}} [quick start guide]({{< relref "/develop/get-started/rag" >}}) | + + +## Overview + +1. [**Create a vector index**]({{< baseurl >}}/develop/interact/search-and-query/advanced-concepts/vectors#create-a-vector-index): Redis maintains a secondary index over your data with a defined schema (including vector fields and metadata). Redis supports [`FLAT`]({{< baseurl >}}/develop/interact/search-and-query/advanced-concepts/vectors#flat-index) and [`HNSW`]({{< baseurl >}}/develop/interact/search-and-query/advanced-concepts/vectors#hnsw-index) vector index types. +1. [**Store and update vectors**]({{< baseurl >}}/develop/interact/search-and-query/advanced-concepts/vectors#store-and-update-vectors): Redis stores vectors and metadata in hashes or JSON objects. +1. [**Search with vectors**]({{< baseurl >}}/develop/interact/search-and-query/advanced-concepts/vectors#search-with-vectors): Redis supports several advanced querying strategies with vector fields including k-nearest neighbor ([KNN]({{< baseurl >}}/develop/interact/search-and-query/advanced-concepts/vectors#knn-vector-search)), [vector range queries]({{< baseurl >}}/develop/interact/search-and-query/advanced-concepts/vectors#vector-range-queries), and [metadata filters]({{< baseurl >}}/develop/interact/search-and-query/advanced-concepts/vectors#filters). +1. [**Configure vector queries at runtime**]({{< baseurl >}}/develop/interact/search-and-query/advanced-concepts/vectors#runtime-query-params). + +## Resources + +Learn to perform vector search and use Redis integrations in your AI/ML projects. + +| Search | Cloud Model Integration | Python Vector Library | +| :-- | :-- | :-- | +| [Vector search guide]({{< relref "/develop/interact/search-and-query/query/vector-search/" >}}) | [Amazon Bedrock setup guide]({{< relref "/integrate/amazon-bedrock/set-up-redis/ " >}}) |[Redis vector python library documentation]({{< relref "/integrate/redisvl/overview/ " >}}) + +## Next steps + +Get started with the following Redis python notebooks. + +* [The place to start if you are brand new to Redis](https://colab.research.google.com/github/redis-developer/redis-ai-resources/blob/main/python-recipes/redis-intro/00_redis_intro.ipynb) + +**Hybrid and vector search notebooks** +* [Implementing hybrid search with Redis](https://colab.research.google.com/github/redis-developer/redis-ai-resources/blob/main/python-recipes/vector-search/02_hybrid_search.ipynb) +* [Vector search with Redis python client](https://colab.research.google.com/github/redis-developer/redis-ai-resources/blob/main/python-recipes/vector-search/00_redispy.ipynb) +* [Vector search with Redis Vector Library](https://colab.research.google.com/github/redis-developer/redis-ai-resources/blob/main/python-recipes/vector-search/01_redisvl.ipynb) + +**RAG notebooks** +* [RAG from scratch with the Redis Vector Library](https://colab.research.google.com/github/redis-developer/redis-ai-resources/blob/main/python-recipes/RAG/01_redisvl.ipynb) +* [RAG using Redis and LangChain](https://colab.research.google.com/github/redis-developer/redis-ai-resources/blob/main/python-recipes/RAG/02_langchain.ipynb) +* [RAG using Redis and LlamaIndex](https://colab.research.google.com/github/redis-developer/redis-ai-resources/blob/main/python-recipes/RAG/03_llamaindex.ipynb) +* [Advanced RAG with redisvl](https://colab.research.google.com/github/redis-developer/redis-ai-resources/blob/main/python-recipes/RAG/04_advanced_redisvl.ipynb) +* [RAG using Redis and Nvidia](https://colab.research.google.com/github/redis-developer/redis-ai-resources/blob/main/python-recipes/RAG/05_nvidia_ai_rag_redis.ipynb) +* [Utilize RAGAS framework to evaluate RAG performance](https://colab.research.google.com/github/redis-developer/redis-ai-resources/blob/main/python-recipes/RAG/06_ragas_evaluation.ipynb) +* [Notebook for additional tips and techniques to improve RAG quality](https://colab.research.google.com/github/redis-developer/redis-ai-resources/blob/main/python-recipes/RAG/04_advanced_redisvl.ipynb) + +**LLM session management notebooks** +* [LLM session manager with semantic similarity](https://colab.research.google.com/github/redis-developer/redis-ai-resources/blob/main/python-recipes/llm-session-manager/00_llm_session_manager.ipynb) +* [Handle multiple simultaneous chats with one instance](https://colab.research.google.com/github/redis-developer/redis-ai-resources/blob/main/python-recipes/llm-session-manager/01_multiple_sessions.ipynb) + +**Semantic caching notebooks** +* [Build a semantic cache using the Doc2Cache framework and Llama3.1](https://colab.research.google.com/github/redis-developer/redis-ai-resources/blob/main/python-recipes/semantic-cache/doc2cache_llama3_1.ipynb) +* [Build a semantic cache with Redis and Google Gemini](https://colab.research.google.com/github/redis-developer/redis-ai-resources/blob/main/python-recipes/semantic-cache/semantic_caching_gemini.ipynb) + +**Agent notebooks** +* [Notebook to get started with lang-graph and agents](https://colab.research.google.com/github/redis-developer/redis-ai-resources/blob/main/python-recipes/agents/00_langgraph_redis_agentic_rag.ipynb) +* [Notebook to get started with lang-graph and agents](https://colab.research.google.com/github/redis-developer/redis-ai-resources/blob/main/python-recipes/agents/01_crewai_langgraph_redis.ipynb) + +**Recommendation systems notebooks** +* [Intro content filtering example with redisvl](https://colab.research.google.com/github/redis-developer/redis-ai-resources/blob/main/python-recipes/recommendation-systems/content_filtering.ipynb) +* [Intro collaborative filtering example with redisvl](https://colab.research.google.com/github/redis-developer/redis-ai-resources/blob/main/python-recipes/recommendation-systems/collaborative_filtering.ipynb) + + + From 8cd24a910c176b19b28226a0bab8ba43b9d81bb0 Mon Sep 17 00:00:00 2001 From: mich-elle-luna <153109578+mich-elle-luna@users.noreply.github.com> Date: Mon, 18 Nov 2024 16:09:50 -0800 Subject: 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a/content/develop/ai/index.md +++ b/content/develop/ai/index.md @@ -8,13 +8,13 @@ categories: - rc description: An overivew of the Redis for AI documentation linkTitle: Redis for AI -weight: 4 +weight: 40 --- Redis stores and indexes vector embeddings that semantically represent unstructured data including text passages, images, videos, or audio. Store vectors and the associated metadata within hashes or JSON documents for indexing and search. | Vector | RAG | | :-- | :-- | -| {{AI Redis icon.}}[Redis as a vector database quick start guide]({{< relref "/develop/get-started/vector-database" >}}) |{{AI Redis icon.}} [quick start guide]({{< relref "/develop/get-started/rag" >}}) | +| {{AI Redis icon.}}[Redis as a vector database quick start guide]({{< relref "/develop/get-started/vector-database" >}}) |{{AI Redis icon.}} [Retrieval-Augmented Generation quick start guide]({{< relref "/develop/get-started/rag" >}}) | ## Overview From 2dedd4fd52489ddf281827dad7eae1b912d1f012 Mon Sep 17 00:00:00 2001 From: mich-elle-luna <153109578+mich-elle-luna@users.noreply.github.com> Date: Mon, 18 Nov 2024 16:27:57 -0800 Subject: [PATCH 04/19] Add files via upload --- static/images/ai-brain.png | Bin 7721 -> 7512 bytes 1 file changed, 0 insertions(+), 0 deletions(-) diff --git a/static/images/ai-brain.png b/static/images/ai-brain.png index 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[**Create a vector index**]({{< baseurl >}}/develop/interact/search-and-query/advanced-concepts/vectors#create-a-vector-index): Redis maintains a secondary index over your data with a defined schema (including vector fields and metadata). Redis supports [`FLAT`]({{< baseurl >}}/develop/interact/search-and-query/advanced-concepts/vectors#flat-index) and [`HNSW`]({{< baseurl >}}/develop/interact/search-and-query/advanced-concepts/vectors#hnsw-index) vector index types. 1. [**Store and update vectors**]({{< baseurl >}}/develop/interact/search-and-query/advanced-concepts/vectors#store-and-update-vectors): Redis stores vectors and metadata in hashes or JSON objects. 1. [**Search with vectors**]({{< baseurl >}}/develop/interact/search-and-query/advanced-concepts/vectors#search-with-vectors): Redis supports several advanced querying strategies with vector fields including k-nearest neighbor ([KNN]({{< baseurl >}}/develop/interact/search-and-query/advanced-concepts/vectors#knn-vector-search)), [vector range queries]({{< baseurl >}}/develop/interact/search-and-query/advanced-concepts/vectors#vector-range-queries), and [metadata filters]({{< baseurl >}}/develop/interact/search-and-query/advanced-concepts/vectors#filters). -1. [**Configure vector queries at runtime**]({{< baseurl >}}/develop/interact/search-and-query/advanced-concepts/vectors#runtime-query-params). +1. 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Search | Cloud Model Integration | Python Vector Library | | :-- | :-- | :-- | -| [Vector search guide]({{< relref "/develop/interact/search-and-query/query/vector-search/" >}}) | [Amazon Bedrock setup guide]({{< relref "/integrate/amazon-bedrock/set-up-redis/ " >}}) |[Redis vector python library documentation]({{< relref "/integrate/redisvl/overview/ " >}}) +| {{AI Redis icon.}}[Vector search guide]({{< relref "/develop/interact/search-and-query/query/vector-search" >}}) | {{AI Redis icon.}}[Amazon Bedrock setup guide]({{< relref "/integrate/amazon-bedrock/set-up-redis" >}}) |{{AI Redis icon.}}[Redis vector python library documentation]({{< relref "/integrate/redisvl/overview/" >}}) ## Next steps From be7d84f8ba2345d7fbfc3f382ab69cc0f675eb12 Mon Sep 17 00:00:00 2001 From: mich-elle-luna <153109578+mich-elle-luna@users.noreply.github.com> Date: Mon, 18 Nov 2024 16:59:33 -0800 Subject: [PATCH 08/19] Add files via upload --- static/images/ai-brain-2.png | Bin 0 -> 8988 bytes 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zYrq3Qn6e|Ajc$`2X%Wt66%N<(*|20+_KpRvu`g->RYnjKyadf`NDz;?rKRO`nRYF3 ztje2Grk+I9d?Zt&%6htN%w-%zVy$*~;)+*9zG`V3*yRY{{T#3TF(~gn z)E}Ico=$4L)t@*`V&9U}wdUr{<9lbL|Tre*bUP_v=PcA>tp17aP^ zRUR9k%=*@C6^4%jG0oDh_=GR}r_+%UO0ef{u4F{Q-B21&X?@Y&%RQ>)>Hc7MrZVfe znbRIM{BQLWM4)wrtUopKoO!izHzGO_J3K;Mm$6=p$CZ_)je@uL2hm?u zFaxd|zFOvBu<^#v&xArAoL`vrOSTorM=5l45PFvDlga)*6LL# x%)CyTe-g%!v<1ghW$n|C Date: Mon, 18 Nov 2024 17:06:32 -0800 Subject: [PATCH 09/19] Update index.md --- content/develop/ai/index.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/content/develop/ai/index.md b/content/develop/ai/index.md index 50982ae50..c459e08c0 100644 --- a/content/develop/ai/index.md +++ b/content/develop/ai/index.md @@ -30,7 +30,7 @@ Learn to perform vector search and use Redis integrations in your AI/ML projects | Search | Cloud Model Integration | Python Vector Library | | :-- | :-- | :-- | -| {{AI Redis icon.}}[Vector search guide]({{< relref "/develop/interact/search-and-query/query/vector-search" >}}) | {{AI Redis icon.}}[Amazon Bedrock setup guide]({{< relref "/integrate/amazon-bedrock/set-up-redis" >}}) |{{AI Redis icon.}}[Redis vector python library documentation]({{< relref "/integrate/redisvl/overview/" >}}) +| {{AI Redis icon.}}[Vector search guide]({{< relref "/develop/interact/search-and-query/query/vector-search" >}}) | {{AI Redis icon.}}[Amazon Bedrock setup guide]({{< relref "/integrate/amazon-bedrock/set-up-redis" >}}) |{{AI Redis icon.}}[Redis vector python library documentation]({{< relref "/integrate/redisvl/overview/" >}}) ## Next steps From 9bf1dad80aac1320bdd4df102dac97a5604b2918 Mon Sep 17 00:00:00 2001 From: mich-elle-luna <153109578+mich-elle-luna@users.noreply.github.com> Date: Mon, 18 Nov 2024 17:28:51 -0800 Subject: [PATCH 10/19] Update index.md --- content/develop/ai/index.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/content/develop/ai/index.md b/content/develop/ai/index.md index c459e08c0..35b55b354 100644 --- a/content/develop/ai/index.md +++ b/content/develop/ai/index.md @@ -6,7 +6,7 @@ categories: - operate - rs - rc -description: An overivew of the Redis for AI documentation +description: An overview of the Redis for AI documentation linkTitle: Redis for AI weight: 40 --- From ae8fe0dca159c965151c71409e2e9a6803360b62 Mon Sep 17 00:00:00 2001 From: mich-elle-luna <153109578+mich-elle-luna@users.noreply.github.com> Date: Tue, 19 Nov 2024 09:27:54 -0800 Subject: [PATCH 11/19] Update content/develop/ai/index.md Co-authored-by: andy-stark-redis <164213578+andy-stark-redis@users.noreply.github.com> --- content/develop/ai/index.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/content/develop/ai/index.md b/content/develop/ai/index.md index 35b55b354..a32c437b2 100644 --- a/content/develop/ai/index.md +++ b/content/develop/ai/index.md @@ -34,7 +34,7 @@ Learn to perform vector search and use Redis integrations in your AI/ML projects ## Next steps -Get started with the following Redis python notebooks. +Get started with the following Redis Python notebooks. * [The place to start if you are brand new to Redis](https://colab.research.google.com/github/redis-developer/redis-ai-resources/blob/main/python-recipes/redis-intro/00_redis_intro.ipynb) From 62a84fef6db72f0bd1768c26741bf5392d70ec54 Mon Sep 17 00:00:00 2001 From: mich-elle-luna <153109578+mich-elle-luna@users.noreply.github.com> Date: Tue, 19 Nov 2024 09:28:03 -0800 Subject: [PATCH 12/19] Update content/develop/ai/index.md Co-authored-by: andy-stark-redis <164213578+andy-stark-redis@users.noreply.github.com> --- content/develop/ai/index.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/content/develop/ai/index.md b/content/develop/ai/index.md index a32c437b2..1a5213b2f 100644 --- a/content/develop/ai/index.md +++ b/content/develop/ai/index.md @@ -40,7 +40,7 @@ Get started with the following Redis Python notebooks. **Hybrid and vector search notebooks** * [Implementing hybrid search with Redis](https://colab.research.google.com/github/redis-developer/redis-ai-resources/blob/main/python-recipes/vector-search/02_hybrid_search.ipynb) -* [Vector search with Redis python client](https://colab.research.google.com/github/redis-developer/redis-ai-resources/blob/main/python-recipes/vector-search/00_redispy.ipynb) +* [Vector search with Redis Python client](https://colab.research.google.com/github/redis-developer/redis-ai-resources/blob/main/python-recipes/vector-search/00_redispy.ipynb) * [Vector search with Redis Vector Library](https://colab.research.google.com/github/redis-developer/redis-ai-resources/blob/main/python-recipes/vector-search/01_redisvl.ipynb) **RAG notebooks** From a11a78d68d73e5a58e220b2a2a21044b7fafafd0 Mon Sep 17 00:00:00 2001 From: mich-elle-luna <153109578+mich-elle-luna@users.noreply.github.com> Date: Tue, 19 Nov 2024 09:28:15 -0800 Subject: [PATCH 13/19] Update content/develop/ai/index.md Co-authored-by: andy-stark-redis <164213578+andy-stark-redis@users.noreply.github.com> --- content/develop/ai/index.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/content/develop/ai/index.md b/content/develop/ai/index.md index 1a5213b2f..dbc9d7e9f 100644 --- a/content/develop/ai/index.md +++ b/content/develop/ai/index.md @@ -10,7 +10,7 @@ description: An overview of the Redis for AI documentation linkTitle: Redis for AI weight: 40 --- -Redis stores and indexes vector embeddings that semantically represent unstructured data including text passages, images, videos, or audio. Store vectors and the associated metadata within hashes or JSON documents for indexing and search. +Redis stores and indexes vector embeddings that semantically represent unstructured data including text passages, images, videos, or audio. Store vectors and the associated metadata within [hashes]({{< relref "/develop/data-types/hashes" >}}) or [JSON]({{< relref "/develop/data-types/json" >}}) documents for [indexing]({{< relref "/develop/interact/search-and-query/indexing" >}}) and [querying]({{< relref "/develop/interact/search-and-query/query" >}}). | Vector | RAG | | :-- | :-- | From d0c2022f5c9ed47f3786e4ba801eb7ceacc7d0e4 Mon Sep 17 00:00:00 2001 From: mich-elle-luna <153109578+mich-elle-luna@users.noreply.github.com> Date: Tue, 19 Nov 2024 09:28:46 -0800 Subject: [PATCH 14/19] Update content/develop/ai/index.md Co-authored-by: andy-stark-redis <164213578+andy-stark-redis@users.noreply.github.com> --- content/develop/ai/index.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/content/develop/ai/index.md b/content/develop/ai/index.md index dbc9d7e9f..8dac1d069 100644 --- a/content/develop/ai/index.md +++ b/content/develop/ai/index.md @@ -32,7 +32,7 @@ Learn to perform vector search and use Redis integrations in your AI/ML projects | :-- | :-- | :-- | | {{AI Redis icon.}}[Vector search guide]({{< relref "/develop/interact/search-and-query/query/vector-search" >}}) | {{AI Redis icon.}}[Amazon Bedrock setup guide]({{< relref "/integrate/amazon-bedrock/set-up-redis" >}}) |{{AI Redis icon.}}[Redis vector python library documentation]({{< relref "/integrate/redisvl/overview/" >}}) -## Next steps +## Notebooks Get started with the following Redis Python notebooks. From 96316f8ea820a5d418de086e3acfb1944c151f4f Mon Sep 17 00:00:00 2001 From: mich-elle-luna <153109578+mich-elle-luna@users.noreply.github.com> Date: Tue, 19 Nov 2024 10:06:55 -0800 Subject: [PATCH 15/19] Update index.md --- content/develop/ai/index.md | 40 +++++++++++++++++++++++-------------- 1 file changed, 25 insertions(+), 15 deletions(-) diff --git a/content/develop/ai/index.md b/content/develop/ai/index.md index 8dac1d069..19813f426 100644 --- a/content/develop/ai/index.md +++ b/content/develop/ai/index.md @@ -12,25 +12,35 @@ weight: 40 --- Redis stores and indexes vector embeddings that semantically represent unstructured data including text passages, images, videos, or audio. Store vectors and the associated metadata within [hashes]({{< relref "/develop/data-types/hashes" >}}) or [JSON]({{< relref "/develop/data-types/json" >}}) documents for [indexing]({{< relref "/develop/interact/search-and-query/indexing" >}}) and [querying]({{< relref "/develop/interact/search-and-query/query" >}}). -| Vector | RAG | -| :-- | :-- | -| {{AI Redis icon.}}[Redis as a vector database quick start guide]({{< relref "/develop/get-started/vector-database" >}}) |{{AI Redis icon.}} [Retrieval-Augmented Generation quick start guide]({{< relref "/develop/get-started/rag" >}}) | - +| Vector | RAG | Redis Vector Client Library | +| :-- | :-- | :-- | +| {{AI Redis icon.}}[Redis as a vector database quick start guide]({{< relref "/develop/get-started/vector-database" >}}) |{{AI Redis icon.}} [Retrieval-Augmented Generation quick start guide]({{< relref "/develop/get-started/rag" >}}) | {{AI Redis icon.}}[Redis vector Python client library documentation]({{< relref "/integrate/redisvl/overview/" >}}) | ## Overview 1. [**Create a vector index**]({{< baseurl >}}/develop/interact/search-and-query/advanced-concepts/vectors#create-a-vector-index): Redis maintains a secondary index over your data with a defined schema (including vector fields and metadata). Redis supports [`FLAT`]({{< baseurl >}}/develop/interact/search-and-query/advanced-concepts/vectors#flat-index) and [`HNSW`]({{< baseurl >}}/develop/interact/search-and-query/advanced-concepts/vectors#hnsw-index) vector index types. 1. [**Store and update vectors**]({{< baseurl >}}/develop/interact/search-and-query/advanced-concepts/vectors#store-and-update-vectors): Redis stores vectors and metadata in hashes or JSON objects. 1. [**Search with vectors**]({{< baseurl >}}/develop/interact/search-and-query/advanced-concepts/vectors#search-with-vectors): Redis supports several advanced querying strategies with vector fields including k-nearest neighbor ([KNN]({{< baseurl >}}/develop/interact/search-and-query/advanced-concepts/vectors#knn-vector-search)), [vector range queries]({{< baseurl >}}/develop/interact/search-and-query/advanced-concepts/vectors#vector-range-queries), and [metadata filters]({{< baseurl >}}/develop/interact/search-and-query/advanced-concepts/vectors#filters). -1. [**Configure vector queries at runtime**]({{< baseurl >}}/develop/interact/search-and-query/advanced-concepts/vectors#runtime-query-parameters). +1. [**Configure vector queries at runtime**]({{< baseurl >}}/develop/interact/search-and-query/advanced-concepts/vectors#runtime-query-parameters). Select the best filter mode to optimize query execution. -## Resources +## Concepts -Learn to perform vector search and use Redis integrations in your AI/ML projects. +Learn to perform vector search and use gateways and semantic caching in your AI/ML projects. -| Search | Cloud Model Integration | Python Vector Library | +| Search | AI Gateways | Semantic Caching | | :-- | :-- | :-- | -| {{AI Redis icon.}}[Vector search guide]({{< relref "/develop/interact/search-and-query/query/vector-search" >}}) | {{AI Redis icon.}}[Amazon Bedrock setup guide]({{< relref "/integrate/amazon-bedrock/set-up-redis" >}}) |{{AI Redis icon.}}[Redis vector python library documentation]({{< relref "/integrate/redisvl/overview/" >}}) +| {{AI Redis icon.}}[Vector search guide]({{< relref "/develop/interact/search-and-query/query/vector-search" >}}) | {{AI Redis icon.}}[Deploy an enhanced gateway with Redis](https://redis.io/blog/ai-gateways-what-are-they-how-can-you-deploy-an-enhanced-gateway-with-redis/) | {{AI Redis icon.}}[Semantic caching for faster, smarter LLM apps](https://redis.io/blog/what-is-semantic-caching) | + +## Ecosystem integrations + +* [Amazon Bedrock setup guide]({{< relref "/integrate/amazon-bedrock/set-up-redis" >}}) +* [LangChain Redis Package: Smarter AI apps with advanced vector storage and faster caching](https://redis.io/blog/langchain-redis-partner-package/)) +* [Redis Cloud available on Vercel](https://redis.io/blog/redis-cloud-now-available-on-vercel-marketplace/) +* [Create a Redis Cloud database with the Vercel integration]({{< relref "/operate/rc/cloud-integrations/vercel/" >}}) +* [Building a RAG application with Redis and Spring AI](https://redis.io/blog/building-a-rag-application-with-redis-and-spring-ai/) +* [Deploy GenAI apps faster with Redis and NVIDIA NIM](https://redis.io/blog/use-redis-with-nvidia-nim-to-deploy-genai-apps-faster/) +* [Building LLM Applications with Kernel Memory and Redis](https://redis.io/blog/building-llm-applications-with-kernel-memory-and-redis/) + ## Notebooks @@ -38,12 +48,12 @@ Get started with the following Redis Python notebooks. * [The place to start if you are brand new to Redis](https://colab.research.google.com/github/redis-developer/redis-ai-resources/blob/main/python-recipes/redis-intro/00_redis_intro.ipynb) -**Hybrid and vector search notebooks** +### Hybrid and vector search * [Implementing hybrid search with Redis](https://colab.research.google.com/github/redis-developer/redis-ai-resources/blob/main/python-recipes/vector-search/02_hybrid_search.ipynb) * [Vector search with Redis Python client](https://colab.research.google.com/github/redis-developer/redis-ai-resources/blob/main/python-recipes/vector-search/00_redispy.ipynb) * [Vector search with Redis Vector Library](https://colab.research.google.com/github/redis-developer/redis-ai-resources/blob/main/python-recipes/vector-search/01_redisvl.ipynb) -**RAG notebooks** +### RAG * [RAG from scratch with the Redis Vector Library](https://colab.research.google.com/github/redis-developer/redis-ai-resources/blob/main/python-recipes/RAG/01_redisvl.ipynb) * [RAG using Redis and LangChain](https://colab.research.google.com/github/redis-developer/redis-ai-resources/blob/main/python-recipes/RAG/02_langchain.ipynb) * [RAG using Redis and LlamaIndex](https://colab.research.google.com/github/redis-developer/redis-ai-resources/blob/main/python-recipes/RAG/03_llamaindex.ipynb) @@ -52,19 +62,19 @@ Get started with the following Redis Python notebooks. * [Utilize RAGAS framework to evaluate RAG performance](https://colab.research.google.com/github/redis-developer/redis-ai-resources/blob/main/python-recipes/RAG/06_ragas_evaluation.ipynb) * [Notebook for additional tips and techniques to improve RAG quality](https://colab.research.google.com/github/redis-developer/redis-ai-resources/blob/main/python-recipes/RAG/04_advanced_redisvl.ipynb) -**LLM session management notebooks** +### LLM session management * [LLM session manager with semantic similarity](https://colab.research.google.com/github/redis-developer/redis-ai-resources/blob/main/python-recipes/llm-session-manager/00_llm_session_manager.ipynb) * [Handle multiple simultaneous chats with one instance](https://colab.research.google.com/github/redis-developer/redis-ai-resources/blob/main/python-recipes/llm-session-manager/01_multiple_sessions.ipynb) -**Semantic caching notebooks** +### Semantic caching * [Build a semantic cache using the Doc2Cache framework and Llama3.1](https://colab.research.google.com/github/redis-developer/redis-ai-resources/blob/main/python-recipes/semantic-cache/doc2cache_llama3_1.ipynb) * [Build a semantic cache with Redis and Google Gemini](https://colab.research.google.com/github/redis-developer/redis-ai-resources/blob/main/python-recipes/semantic-cache/semantic_caching_gemini.ipynb) -**Agent notebooks** +### Agent * [Notebook to get started with lang-graph and agents](https://colab.research.google.com/github/redis-developer/redis-ai-resources/blob/main/python-recipes/agents/00_langgraph_redis_agentic_rag.ipynb) * [Notebook to get started with lang-graph and agents](https://colab.research.google.com/github/redis-developer/redis-ai-resources/blob/main/python-recipes/agents/01_crewai_langgraph_redis.ipynb) -**Recommendation systems notebooks** +## Recommendation systems * [Intro content filtering example with redisvl](https://colab.research.google.com/github/redis-developer/redis-ai-resources/blob/main/python-recipes/recommendation-systems/content_filtering.ipynb) * [Intro collaborative filtering example with redisvl](https://colab.research.google.com/github/redis-developer/redis-ai-resources/blob/main/python-recipes/recommendation-systems/collaborative_filtering.ipynb) From 4cc81d825c5e4b45a20c4a5caadeaca500296112 Mon Sep 17 00:00:00 2001 From: mich-elle-luna <153109578+mich-elle-luna@users.noreply.github.com> Date: Tue, 19 Nov 2024 10:07:53 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19813f426..2e99e74a1 100644 --- a/content/develop/ai/index.md +++ b/content/develop/ai/index.md @@ -12,7 +12,7 @@ weight: 40 --- Redis stores and indexes vector embeddings that semantically represent unstructured data including text passages, images, videos, or audio. Store vectors and the associated metadata within [hashes]({{< relref "/develop/data-types/hashes" >}}) or [JSON]({{< relref "/develop/data-types/json" >}}) documents for [indexing]({{< relref "/develop/interact/search-and-query/indexing" >}}) and [querying]({{< relref "/develop/interact/search-and-query/query" >}}). -| Vector | RAG | Redis Vector Client Library | +| Vector | RAG | RedisVL | | :-- | :-- | :-- | | {{AI Redis icon.}}[Redis as a vector database quick start guide]({{< relref "/develop/get-started/vector-database" >}}) |{{AI Redis icon.}} [Retrieval-Augmented Generation quick start guide]({{< relref "/develop/get-started/rag" >}}) | {{AI Redis icon.}}[Redis vector Python client library documentation]({{< relref "/integrate/redisvl/overview/" >}}) | @@ -48,12 +48,12 @@ Get started with the following Redis Python notebooks. * [The place to start if you are brand new to Redis](https://colab.research.google.com/github/redis-developer/redis-ai-resources/blob/main/python-recipes/redis-intro/00_redis_intro.ipynb) -### Hybrid and vector search +#### Hybrid and vector search * [Implementing hybrid search with Redis](https://colab.research.google.com/github/redis-developer/redis-ai-resources/blob/main/python-recipes/vector-search/02_hybrid_search.ipynb) * [Vector search with Redis Python client](https://colab.research.google.com/github/redis-developer/redis-ai-resources/blob/main/python-recipes/vector-search/00_redispy.ipynb) * [Vector search with Redis Vector Library](https://colab.research.google.com/github/redis-developer/redis-ai-resources/blob/main/python-recipes/vector-search/01_redisvl.ipynb) -### RAG +#### RAG * [RAG from scratch with the Redis Vector Library](https://colab.research.google.com/github/redis-developer/redis-ai-resources/blob/main/python-recipes/RAG/01_redisvl.ipynb) * [RAG using Redis and LangChain](https://colab.research.google.com/github/redis-developer/redis-ai-resources/blob/main/python-recipes/RAG/02_langchain.ipynb) * [RAG using Redis and LlamaIndex](https://colab.research.google.com/github/redis-developer/redis-ai-resources/blob/main/python-recipes/RAG/03_llamaindex.ipynb) @@ -62,19 +62,19 @@ Get started with the following Redis Python notebooks. * [Utilize RAGAS framework to evaluate RAG performance](https://colab.research.google.com/github/redis-developer/redis-ai-resources/blob/main/python-recipes/RAG/06_ragas_evaluation.ipynb) * [Notebook for additional tips and techniques to improve RAG quality](https://colab.research.google.com/github/redis-developer/redis-ai-resources/blob/main/python-recipes/RAG/04_advanced_redisvl.ipynb) -### LLM session management +#### LLM session management * [LLM session manager with semantic similarity](https://colab.research.google.com/github/redis-developer/redis-ai-resources/blob/main/python-recipes/llm-session-manager/00_llm_session_manager.ipynb) * [Handle multiple simultaneous chats with one instance](https://colab.research.google.com/github/redis-developer/redis-ai-resources/blob/main/python-recipes/llm-session-manager/01_multiple_sessions.ipynb) -### Semantic caching +#### Semantic caching * [Build a semantic cache using the Doc2Cache framework and Llama3.1](https://colab.research.google.com/github/redis-developer/redis-ai-resources/blob/main/python-recipes/semantic-cache/doc2cache_llama3_1.ipynb) * [Build a semantic cache with Redis and Google Gemini](https://colab.research.google.com/github/redis-developer/redis-ai-resources/blob/main/python-recipes/semantic-cache/semantic_caching_gemini.ipynb) -### Agent +#### Agents * [Notebook to get started with lang-graph and agents](https://colab.research.google.com/github/redis-developer/redis-ai-resources/blob/main/python-recipes/agents/00_langgraph_redis_agentic_rag.ipynb) * [Notebook to get started with lang-graph and agents](https://colab.research.google.com/github/redis-developer/redis-ai-resources/blob/main/python-recipes/agents/01_crewai_langgraph_redis.ipynb) -## Recommendation systems +#### Recommendation systems * [Intro content filtering example with redisvl](https://colab.research.google.com/github/redis-developer/redis-ai-resources/blob/main/python-recipes/recommendation-systems/content_filtering.ipynb) * [Intro collaborative filtering example with redisvl](https://colab.research.google.com/github/redis-developer/redis-ai-resources/blob/main/python-recipes/recommendation-systems/collaborative_filtering.ipynb) From 2d26460d586463339ea760d2e998a2f0d040f803 Mon Sep 17 00:00:00 2001 From: mich-elle-luna <153109578+mich-elle-luna@users.noreply.github.com> Date: Tue, 19 Nov 2024 10:48:34 -0800 Subject: [PATCH 18/19] Update index.md --- content/develop/ai/index.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/content/develop/ai/index.md b/content/develop/ai/index.md index 2e99e74a1..45df6634a 100644 --- a/content/develop/ai/index.md +++ b/content/develop/ai/index.md @@ -16,7 +16,7 @@ Redis stores and indexes vector embeddings that semantically represent unstructu | :-- | :-- | :-- | | {{AI Redis icon.}}[Redis as a vector database quick start guide]({{< relref "/develop/get-started/vector-database" >}}) |{{AI Redis icon.}} [Retrieval-Augmented Generation quick start guide]({{< relref "/develop/get-started/rag" >}}) | {{AI Redis icon.}}[Redis vector Python client library documentation]({{< relref "/integrate/redisvl/overview/" >}}) | -## Overview +#### Overview 1. [**Create a vector index**]({{< baseurl >}}/develop/interact/search-and-query/advanced-concepts/vectors#create-a-vector-index): Redis maintains a secondary index over your data with a defined schema (including vector fields and metadata). Redis supports [`FLAT`]({{< baseurl >}}/develop/interact/search-and-query/advanced-concepts/vectors#flat-index) and [`HNSW`]({{< baseurl >}}/develop/interact/search-and-query/advanced-concepts/vectors#hnsw-index) vector index types. 1. [**Store and update vectors**]({{< baseurl >}}/develop/interact/search-and-query/advanced-concepts/vectors#store-and-update-vectors): Redis stores vectors and metadata in hashes or JSON objects. @@ -31,7 +31,7 @@ Learn to perform vector search and use gateways and semantic caching in your AI/ | :-- | :-- | :-- | | {{AI Redis icon.}}[Vector search guide]({{< relref "/develop/interact/search-and-query/query/vector-search" >}}) | {{AI Redis icon.}}[Deploy an enhanced gateway with Redis](https://redis.io/blog/ai-gateways-what-are-they-how-can-you-deploy-an-enhanced-gateway-with-redis/) | {{AI Redis icon.}}[Semantic caching for faster, smarter LLM apps](https://redis.io/blog/what-is-semantic-caching) | -## Ecosystem integrations +#### Ecosystem integrations * [Amazon Bedrock setup guide]({{< relref "/integrate/amazon-bedrock/set-up-redis" >}}) * [LangChain Redis Package: Smarter AI apps with advanced vector storage and faster caching](https://redis.io/blog/langchain-redis-partner-package/)) From 0043aa2d9b312f76306b3ee099d877e329d44250 Mon Sep 17 00:00:00 2001 From: mich-elle-luna <153109578+mich-elle-luna@users.noreply.github.com> Date: Wed, 20 Nov 2024 11:08:07 -0800 Subject: [PATCH 19/19] Update index.md --- content/develop/ai/index.md | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/content/develop/ai/index.md b/content/develop/ai/index.md index 45df6634a..d92d62132 100644 --- a/content/develop/ai/index.md +++ b/content/develop/ai/index.md @@ -6,7 +6,7 @@ categories: - operate - rs - rc -description: An overview of the Redis for AI documentation +description: An overview of Redis for AI documentation linkTitle: Redis for AI weight: 40 --- @@ -14,7 +14,7 @@ Redis stores and indexes vector embeddings that semantically represent unstructu | Vector | RAG | RedisVL | | :-- | :-- | :-- | -| {{AI Redis icon.}}[Redis as a vector database quick start guide]({{< relref "/develop/get-started/vector-database" >}}) |{{AI Redis icon.}} [Retrieval-Augmented Generation quick start guide]({{< relref "/develop/get-started/rag" >}}) | {{AI Redis icon.}}[Redis vector Python client library documentation]({{< relref "/integrate/redisvl/overview/" >}}) | +| {{AI Redis icon.}}[Redis vector database quick start guide]({{< relref "/develop/get-started/vector-database" >}}) |{{AI Redis icon.}} [Retrieval-Augmented Generation quick start guide]({{< relref "/develop/get-started/rag" >}}) | {{AI Redis icon.}}[Redis vector Python client library documentation]({{< relref "/integrate/redisvl/overview/" >}}) | #### Overview @@ -31,7 +31,7 @@ Learn to perform vector search and use gateways and semantic caching in your AI/ | :-- | :-- | :-- | | {{AI Redis icon.}}[Vector search guide]({{< relref "/develop/interact/search-and-query/query/vector-search" >}}) | {{AI Redis icon.}}[Deploy an enhanced gateway with Redis](https://redis.io/blog/ai-gateways-what-are-they-how-can-you-deploy-an-enhanced-gateway-with-redis/) | {{AI Redis icon.}}[Semantic caching for faster, smarter LLM apps](https://redis.io/blog/what-is-semantic-caching) | -#### Ecosystem integrations +## Ecosystem integrations * [Amazon Bedrock setup guide]({{< relref "/integrate/amazon-bedrock/set-up-redis" >}}) * [LangChain Redis Package: Smarter AI apps with advanced vector storage and faster caching](https://redis.io/blog/langchain-redis-partner-package/)) @@ -42,7 +42,7 @@ Learn to perform vector search and use gateways and semantic caching in your AI/ * [Building LLM Applications with Kernel Memory and Redis](https://redis.io/blog/building-llm-applications-with-kernel-memory-and-redis/) -## Notebooks +## Examples Get started with the following Redis Python notebooks.