gollum
langchaingo
gollum | langchaingo | |
---|---|---|
4 | 9 | |
37 | 3,258 | |
- | - | |
6.0 | 9.8 | |
8 days ago | 5 days ago | |
Go | Go | |
MIT License | MIT License |
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gollum
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From slow to SIMD: A Go optimization story
I did a similar optimization via https://github.com/viterin/vek as the SIMD version. Some somewhat unscientific calculations showed a 10x improvement staying in float32: https://github.com/stillmatic/gollum/blob/07a9aa35d2517af8cf...
TBH my takeaway was that it was more useful to use smaller vectors as a representation
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Agency: Pure Go LangChain Alternative
I like Go a lot for working with OpenAI etc, it's 'just' API calls and Go is great at that. I've opensourced some bits here: https://github.com/stillmatic/gollum -- in particular, function dispatch (given a prompt, return an arbitrary Go struct) is really nice, as is a very fast in-memory KNN index.
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Introducing TypeChat from Microsoft
I've written a version of this in Golang: https://github.com/stillmatic/gollum/blob/main/dispatch.go
```go
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FANN: Vector Search in 200 Lines of Rust
I have gotten 10x speedups with SIMD on modern hardware. Goroutines make this actually fairly tricky, as you essentially have to process all the events and then sort the entire array, which is usually the bottleneck. The heap adds a small amount of complexity but is significantly more efficient, feels like good ROI.
https://github.com/stillmatic/gollum/blob/main/vectorstore.g...
langchaingo
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How to use Retrieval Augmented Generation (RAG) for Go applications
Generative AI development has been democratised, thanks to powerful Machine Learning models (specifically Large Language Models such as Claude, Meta's LLama 2, etc.) being exposed by managed platforms/services as API calls. This frees developers from the infrastructure concerns and lets them focus on the core business problems. This also means that developers are free to use the programming language best suited for their solution. Python has typically been the go-to language when it comes to AI/ML solutions, but there is more flexibility in this area. In this post you will see how to leverage the Go programming language to use Vector Databases and techniques such as Retrieval Augmented Generation (RAG) with langchaingo. If you are a Go developer who wants to how to build learn generative AI applications, you are in the right place!
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Build a Serverless GenAI solution with Lambda, DynamoDB, LangChain and Amazon Bedrock
This use-case here is a similar one - a chat application. I will switch back to implementing things in Go using langchaingo (I used Python for the previous one) and continue to use Amazon Bedrock. But there are few unique things you can explore in this blog post:
- LangChain for Go, the easiest way to write LLM-based programs in Go
- Langchaingo – LangChain in Idiomatic Go
- Agency: Pure Go LangChain Alternative
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Building LangChain applications with Amazon Bedrock and Go - An introduction
langchaingo is the LangChain implementation for the Go programming language. This blog post covers how to extend langchaingo to use foundation model from Amazon Bedrock.
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Zep: A long-term memory store for LLM apps, written in Go
Langchain Go is being actively developed https://github.com/tmc/langchaingo
What are some alternatives?
CopilotKit - Build in-app AI chatbots 🤖, and AI-powered Textareas ✨, into react web apps. [Moved to: https://github.com/CopilotKit/CopilotKit]
yao - :rocket: A performance app engine to create web services and applications in minutes.Suitable for AI, IoT, Industrial Internet, Connected Vehicles, DevOps, Energy, Finance and many other use-cases.
ts-patch - Augment the TypeScript compiler to support extended functionality
langchain - 🦜🔗 Build context-aware reasoning applications
ai-agents-laravel - Build AI Agents for popular LLMs quick and easy in Laravel
ollama - Get up and running with Llama 3, Mistral, Gemma, and other large language models.
voy - 🕸️🦀 A WASM vector similarity search written in Rust
zep - Zep: Long-Term Memory for AI Assistants.
TypeChat - TypeChat is a library that makes it easy to build natural language interfaces using types.
TaskEaseGPT - (WIP) A user-friendly, AI-powered task manager emphasizing efficient work over planning. Streamlines workflow with intelligent task generation & execution. Boost your productivity today!
Weaviate - Weaviate is an open-source vector database that stores both objects and vectors, allowing for the combination of vector search with structured filtering with the fault tolerance and scalability of a cloud-native database.
langchaingo-amazon-bedrock-llm - Amazon Bedrock extension for langchaingo