langchainrb
dvclive
langchainrb | dvclive | |
---|---|---|
16 | 5 | |
1,076 | 152 | |
10.6% | 1.3% | |
9.6 | 8.9 | |
about 24 hours ago | 5 days ago | |
Ruby | Python | |
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.
langchainrb
- Langchain.rb
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First 15 Open Source Advent projects
8. LangChain RB | Github | tutorial
- Create AI Agents in Ruby: Implementing the ReAct Approach
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Lost on LangChain: Can someone help with the Question Answer concept?
So I hooked up the Ruby on Rails langchainrb gem (https://github.com/andreibondarev/langchainrb) and it seems like the approach is to store the plane text entries as meta data on pinecone. I definitely DO NOT want to do this as the data is private and secure on my own DB.
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ruby and ML/AI chatgpt
langchain
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Anyone willing to share their experience with Boxcar.ai?
I would suggest taking a look at Langchain.rb as well. Disclosure: I'm the core maintainer.
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Emerging Architectures for LLM Applications
Is the emerging architecture made out to be more complicated than what most of the companies are currently building? Perhaps! But this is most likely the general direction where things will start trending towards as the auxiliary ecosystem matures.
Shameless plug: For fellow Ruby-ists we're building an orchestration layer for building LLM applications, inspired by the original, Langchain.rb: https://github.com/andreibondarev/langchainrb
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Building an app around a LLM, Rails + Python or just Python?
I'm the author of Langchain.rb.
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5 things I wish I knew before building a GPT agent for log analysis
@dliteful23 I loved your super detailed lessons-learned article! I'm the author of Langchain.rb, I would love to hear what you think of it if you get a chance to check it out. If there's anything that you'd like to see in the framework, please do let us know and we'll make sure to build it out if it aligns with the vision.
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LangChain: The Missing Manual
We’re building “Langchain for Ruby” under the current working name of “Langchain.rb”: https://github.com/andreibondarev/langchainrb
People that have contributed on the project thus far each have at least a decade of experience programming in Ruby. We’re trying our best to build an abstraction layer on top all of the common emerging AI/ML techniques, tools, and providers. We’re also focusbig on building an excellent developer experience that Ruby developers love and have gotten to expect.
Unlike the Python project, as it’s been pointed out here a countless number of times, we’d like to avoid deeply nested class structures that make it incredibly difficult to track and extend.
We’ve been pondering over the “what does Rails for Machine Learning look like?” question, and we’re taking a stab at answering this question.
We’re hyper-focused on the open source community and the developer community at large. All feedback/ideas/contributions/criticism are welcome and encouraged!
dvclive
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First 15 Open Source Advent projects
10. DVC by Iterative | Github | tutorial
- Log and track ML metrics, parameters, models with Git and DVC
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[P] Extension for VS Code to track ML experiments
There is no designated way to dump metrics. In the case of data for plots, we have a simple logger that might help: https://github.com/iterative/dvclive
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Show HN: DVC Studio – Git-Based ML Experiments Management
DVC has metrics logger similar to other experiment management tool: https://github.com/iterative/dvclive/
Also, metrics & params section of the docs explains this (but yes, it is not perfect yet): https://dvc.org/doc/start/metrics-parameters-plots
What are some alternatives?
NeMo-Guardrails - NeMo Guardrails is an open-source toolkit for easily adding programmable guardrails to LLM-based conversational systems.
phoenix - AI Observability & Evaluation
guidance - A guidance language for controlling large language models. [Moved to: https://github.com/guidance-ai/guidance]
pytest-visual - A visual testing framework for ML with automated change detection
ruby-openai - OpenAI API + Ruby! 🤖❤️ Now with Assistants v2, Batches & Ollama/Groq 🚀
label-studio - Label Studio is a multi-type data labeling and annotation tool with standardized output format
hnsqlite - hnsqlite integrates hnswlib and sqlite for simple text embedding search
dvc - 🦉 ML Experiments and Data Management with Git
machine-learning-with-ruby - Curated list: Resources for machine learning in Ruby
OpenLLM - Run any open-source LLMs, such as Llama 2, Mistral, as OpenAI compatible API endpoint in the cloud.
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.
guidance - A guidance language for controlling large language models.