LLM-Stack
dstack is an open-source toolkit and orchestration engine for running GPU workloads. It's designed for development, training, and deployment of gen AI models on any cloud.
Supported providers: AWS, GCP, Azure, Lambda, TensorDock, Vast.ai, and DataCrunch.
Latest news ✨
Supported providers: AWS, GCP, Azure, Lambda, TensorDock, Vast.ai, and DataCrunch.
Latest news ✨
- [2024/01] dstack 0.14.0: OpenAI-compatible endpoints preview (Release)
- [2023/12] dst
dstackai • GitHub - dstackai/dstack: dstack is an open-source toolkit for running GPU workloads on any cloud. It works seamlessly with any cloud GPU providers. Discord: https://discord.gg/u8SmfwPpMd
They will start to support autoscaling in March. You can configure multiple clouds and they deploy to the cheapest one.
Portkey's AI Gateway is the interface between your app and hosted LLMs. It streamlines API requests to OpenAI, Anthropic, Mistral, LLama2, Anyscale, Google Gemini and more with a unified API.
✅ Blazing fast (9.9x faster) with a tiny footprint (~45kb installed)
✅ Load balance across multiple models, providers, and keys
✅ Fallbacks make sure your app ... See more
✅ Blazing fast (9.9x faster) with a tiny footprint (~45kb installed)
✅ Load balance across multiple models, providers, and keys
✅ Fallbacks make sure your app ... See more
Portkey-AI • GitHub - Portkey-AI/gateway: A Blazing Fast AI Gateway. Route to 100+ LLMs with 1 fast & friendly API.
Overview
AIConfig saves prompts, models and model parameters as source control friendly configs. This allows you to iterate on prompts and model parameters separately from your application code .
AIConfig saves prompts, models and model parameters as source control friendly configs. This allows you to iterate on prompts and model parameters separately from your application code .
- Prompts as configs : a standardized JSON format to store generative AI model settings, prompt inputs/outputs, and flexible metadata.
- Model-agnostic SDK :
lastmile-ai • GitHub - lastmile-ai/aiconfig: aiconfig -- config-driven, source control friendly AI application development
🐂 What is Oxen?
Oxen is a lightning fast data version control system for structured and unstructured machine learning datasets. We aim to make versioning datasets as easy as versioning code.
The interface mirrors git, but shines in many areas that git or git-lfs fall short. Oxen is built from the ground up for data, and is optimized to handle large... See more
Oxen is a lightning fast data version control system for structured and unstructured machine learning datasets. We aim to make versioning datasets as easy as versioning code.
The interface mirrors git, but shines in many areas that git or git-lfs fall short. Oxen is built from the ground up for data, and is optimized to handle large... See more
Oxen-AI • GitHub - Oxen-AI/oxen-release: Official repository for docs and releases of the Oxen CLI
Data Structuring & Storage
ANY
LLM of your choice, statistical methods, or NLP models that runs
locally on your machine
:
- G-Eval
- Summarization
- Answer Relevancy
- Faithfulness
- Contextual Recall
- Contextual Precision
- RAGAS
- Hallucination
- Toxicity
- Bias
- etc.
GitHub - confident-ai/deepeval: The LLM Evaluation Framework
Marker
Marker converts PDF, EPUB, and MOBI to markdown. It's 10x faster than nougat, more accurate on most documents, and has low hallucination risk.
Marker converts PDF, EPUB, and MOBI to markdown. It's 10x faster than nougat, more accurate on most documents, and has low hallucination risk.
- Support for a range of PDF documents (optimized for books and scientific papers)
- Removes headers/footers/other artifacts
- Converts most equations to latex
- Formats code blocks and tables
- Support for multiple
VikParuchuri • GitHub - VikParuchuri/marker: Convert PDF to markdown quickly with high accuracy
Data Extraction Stack
LanceDB
LanceDB is an open-source vector database for AI that's designed to store, manage, query and retrieve embeddings on large-scale multi-modal data. The core of LanceDB is written in Rust 🦀 and is built on top of Lance, an open-source columnar data format designed for performant ML workloads and fast random access.
Both the database and the un... See more
LanceDB is an open-source vector database for AI that's designed to store, manage, query and retrieve embeddings on large-scale multi-modal data. The core of LanceDB is written in Rust 🦀 and is built on top of Lance, an open-source columnar data format designed for performant ML workloads and fast random access.
Both the database and the un... See more
LanceDB - LanceDB
Introducing Prompts: LLM Monitoring
W&B Prompts – LLM Monitoring provides large language model usage monitoring and diagnostics. Start simply, then customize and evolve your monitoring analytics over time.
W&B Prompts – LLM Monitoring provides large language model usage monitoring and diagnostics. Start simply, then customize and evolve your monitoring analytics over time.
Monitoring
Monitoring Tools
Original creator : Jesse Zhang (GH: emptycrown, Twitter: @thejessezhang), who courteously donated the repo to LlamaIndex!
This is a simple library of all the data loaders / readers / tools / llama-packs that have been created by the community. The goal is to make it extremely easy to connect large language models to a large variety of knowledge sour... See more
This is a simple library of all the data loaders / readers / tools / llama-packs that have been created by the community. The goal is to make it extremely easy to connect large language models to a large variety of knowledge sour... See more