langchaingo
yao
| langchaingo | yao | |
|---|---|---|
| 8 | 2 | |
| 3,116 | 6,947 | |
| - | 1.2% | |
| 9.8 | 9.3 | |
| 7 days ago | 2 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
yao
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Golang low-code platforms for something like ERP
I have found some like YAO , CORTEZA but give me your suggestions and if you think it would be a good idea to achieve the goal.
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We wrote an open source low-code development tool with Golang+react. The back-end is embedded with the V8 engine, which supports JS for logical expansion. The front-end has designed a set of DSL, which is used for rendering based on dynamic components.
Engine: https://github.com/YaoApp/yao
What are some alternatives?
langchain - 🦜🔗 Build context-aware reasoning applications
gatewayd - ☁️ Cloud-native database gateway and framework for building data-driven applications ✨ Like API gateways, for databases ✨
ollama - Get up and running with Llama 3, Mistral, Gemma, and other large language models.
qrgpt - A little CLI helper for cleaner, more contextual ChatGPT
zep - Zep: Long-Term Memory for AI Assistants.
go-carbon - An unofficial REST API for the Carbon project written in Go
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!
chatgpt-cli - cli program to use chatGPT from terminal
langchaingo-amazon-bedrock-llm - Amazon Bedrock extension for langchaingo
chat-gpt-ppt - Use ChatGPT (or other backends) to generate PPT automatically, all in one single file.
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]
orchy - Distributed, Fault tolerant workflow orchestrator