langchaingo
zep
| langchaingo | zep | |
|---|---|---|
| 8 | 16 | |
| 3,116 | 2,021 | |
| - | 7.0% | |
| 9.8 | 8.8 | |
| 7 days ago | 13 days ago | |
| Go | Go | |
| MIT License | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
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
zep
- Zep: Fast, scalable building blocks for production LLM apps
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ICYMI August: Zep Vector DB, User Store, LangChain collabs & more!
I've read that many of you have started to look beyond LangChain for more advanced functionality and enhanced performance. Zep recently integrated with LlamaIndex and improved our Python and TypeScript SDKs to make it easier and faster to build apps without utilizing frameworks.
- Show HN: Zep – pgvector-based memory store for LLM apps
- Zep: A fast, async memory store for LLM applications
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Handling chat histories that are longer than the context length?
Ultimately, a comprehensive solution will need to pull out only the relevant pieces of chat (using vector proximity search) and ensure that whatever is used ultimately fits into the prompt. The zep project looks promising. It's Apache 2 and it appears that the primary contributor has been working over the last several months on how to tackle this issue.
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Zep Memory Store - New Features: JWT Authentication, Azure OpenAI APIs, & Configurable Hard Deletion
Great! Let me know if you have any difficulty doing so. Also, you can find our docs here: https://docs.getzep.com/
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Discussion: Biggest Roadblocks to Deploy LLMs to Production
Thanks for sharing. Can you confirm that you're looking at Zep's documentation? https://docs.getzep.com/
- getzep/zep: Zep: A long-term memory store for LLM / Chatbot applications
- Zep: A long-term memory store for LLM apps, written in Go
- Has anyone had any success with making a Chain for a chatbot that stores conversations into Pinecone?
What are some alternatives?
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.
local_llama - This repo is to showcase how you can run a model locally and offline, free of OpenAI dependencies.
langchain - 🦜🔗 Build context-aware reasoning applications
zep-python - Zep: Long-Term Memory for AI Assistants (Python Client)
ollama - Get up and running with Llama 3, Mistral, Gemma, and other large language models.
zep-js - Zep - Long-Term Memory for AI Assistants (TypeScript Client)
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!
getlang - Natural language detection package in pure Go
langchaingo-amazon-bedrock-llm - Amazon Bedrock extension for langchaingo
verbaflow - Neural Language Model for Go
casdoor - An open-source UI-first Identity and Access Management (IAM) / Single-Sign-On (SSO) platform with web UI supporting OAuth 2.0, OIDC, SAML, CAS, LDAP, SCIM, WebAuthn, TOTP, MFA and RADIUS [Moved to: https://github.com/casdoor/casdoor]
lingo - package lingo provides the data structures and algorithms required for natural language processing