-
Notifications
You must be signed in to change notification settings - Fork 328
Test: Add AI patterns documentation with LangCache integration #2968
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
Open
mich-elle-luna
wants to merge
3
commits into
main
Choose a base branch
from
ai-pattern-test
base: main
Could not load branches
Branch not found: {{ refName }}
Loading
Could not load tags
Nothing to show
Loading
Are you sure you want to change the base?
Some commits from the old base branch may be removed from the timeline,
and old review comments may become outdated.
Open
Changes from all commits
Commits
Show all changes
3 commits
Select commit
Hold shift + click to select a range
File filter
Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
There are no files selected for viewing
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,57 @@ | ||
| --- | ||
| title: "AI agent patterns" | ||
| linkTitle: "Patterns" | ||
| description: "Production-ready patterns for AI agents using Redis" | ||
| weight: 50 | ||
| hideListLinks: true | ||
| --- | ||
|
|
||
| This section provides production-ready patterns for building AI agents with Redis. Each pattern combines high-level abstractions with raw Redis commands, enabling both rapid development and deep debugging. | ||
|
|
||
| ## Available patterns | ||
|
|
||
| ### Caching and cost optimization | ||
|
|
||
| - [Semantic cache](semantic-cache/) - Cache LLM responses by semantic meaning to reduce API costs by 40-60% | ||
|
|
||
| ### Search and retrieval | ||
|
|
||
| - [RAG hybrid search](rag-hybrid-search/) - Retrieval-augmented generation with vector similarity and metadata filtering | ||
|
|
||
| ### Agent coordination | ||
|
|
||
| - [Agent message streams](agent-message-streams/) - Event-driven agent coordination with persistent message history and at-most-once delivery | ||
|
|
||
| ### Feature serving | ||
|
|
||
| - [Feature stores](feature-store/) - Serve pre-computed ML features with sub-millisecond latency | ||
|
|
||
| ## Pattern structure | ||
|
|
||
| Each pattern follows a consistent format: | ||
|
|
||
| 1. **The abstraction (developer experience)** - High-level libraries like RedisVL and Featureform for rapid development | ||
| 2. **The raw commands (machine verification)** - Exact Redis commands for debugging and validation | ||
| 3. **Alternative approaches** - Redis 8 native features and other implementation options | ||
| 4. **Production patterns** - Real-world considerations including multi-tenancy, memory management, and monitoring | ||
| 5. **Performance characteristics** - Latency benchmarks and scalability guidance | ||
| 6. **Why this works** - Design rationale covering safety, accuracy, efficiency, and flexibility | ||
|
|
||
| ## Key benefits | ||
|
|
||
| **Dual-layer approach**: Each pattern shows both high-level abstractions (for safety and speed) and raw Redis commands (for debugging and verification). This enables rapid development while maintaining full control when needed. | ||
|
|
||
| **Production-ready**: Patterns include memory estimates, performance benchmarks, failure modes, and multi-tenant isolation strategies that are critical for production deployments. | ||
|
|
||
| **Framework agnostic**: Works with LangChain, LangGraph, CrewAI, or custom agent implementations. | ||
|
|
||
| **Future-proof**: Patterns show both current approaches (Redis Search, RedisVL) and Redis 8 native features (Vector Sets) where applicable. | ||
|
|
||
| ## Additional resources | ||
|
|
||
| - [RedisVL documentation]({{< relref "/develop/ai/redisvl" >}}) | ||
| - [Featureform documentation]({{< relref "/develop/ai/featureform" >}}) | ||
| - [Redis for AI libraries]({{< relref "/integrate/redis-ai-libraries" >}}) | ||
| - [Vector database quick start]({{< relref "/develop/get-started/vector-database" >}}) | ||
| - [RAG quick start guide]({{< relref "/develop/get-started/rag" >}}) | ||
|
|
||
Oops, something went wrong.
Oops, something went wrong.
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
Uh oh!
There was an error while loading. Please reload this page.