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Deep Lake

Appears in 6 awesome lists

is a data lake for deep learning applications. Our open-source dataset format is optimized for rapid streaming and querying of data while training models at scale, and it includes a simple API for creating, storing, and collaborating on AI datasets of any size. It can be deployed locally or in the…

Open github.comactiveloopai/deeplake

Found in these lists

Awesome LLMOps

Section: LLMOps · Stream large multimodal datasets to achieve near 100% GPU utilization. Query, visualize, & version control data. Access data w/o the need to recompute the embeddings for the model finetuning.

ActiveScore 75

Awesome Open Source AI

Section: 5. Retrieval-Augmented Generation (RAG) & Knowledge · AI Data Runtime for Agents with serverless PostgreSQL and multimodal datalake. Store and search vectors, images, text, videos, and more with LangChain/LlamaIndex integrations. Used by Intel, Bayer, Yale, and Oxford. Apache 2.0 licensed.

FreshScore 89

Awesome Production Machine Learning

Section: Industry Strength Computer Vision · Deep Lake is a data infrastructure optimized for computer vision.

FreshScore 92

Table of Contents

Section: Development · is a data lake for deep learning applications. Our open-source dataset format is optimized for rapid streaming and querying of data while training models at scale, and it includes a simple API for creating, storing, and collaborating on AI datasets of any size. It can be deployed locally or in the…

SlowScore 61

awesome-cpp

Section: Other · Deeplake is AI Data Runtime for Agents. It provides serverless postgres with a multimodal datalake, enabling scalable retrieval and training.

FreshScore 79

awesome-python

Section: Other · Deeplake is AI Data Runtime for Agents. It provides serverless postgres with a multimodal datalake, enabling scalable retrieval and training.

FreshScore 81

LiteLLM

Unified proxy and SDK that routes to 100+ LLM providers behind a single OpenAI-compatible interface, with a Router handling retry/fallback across deployments, per-project cost and rate-limit tracking, and OTEL callback integrations. The right infrastructure layer when your harness needs provider…

In 16 listsDetails

Opik

Comet's open-source AI observability and evaluation platform: deep tracing of LLM calls, conversation logging, and agent activity, plus built-in eval metrics, prompt versioning, guardrails, and the Opik Agent Optimizer. Worth including because it unifies observability, verification, and…

In 16 listsDetails

LlamaIndex

(MIT) provides modules for structured outputs at different levels of abstraction, including output parsers for text completion endpoints, Pydantic programs for mapping prompts to structured outputs using function calling or output parsing, and pre-defined Pydantic programs for specific output types.

In 14 listsDetails

Milvus

Milvus is a cloud-native, open-source vector database built to manage embedding vectors generated by machine learning models and neural networks.

In 14 listsDetails

Dify

February 2026 release making human oversight a native workflow primitive: suspend execution at critical decision points, expose review-and-edit UI mid-flow, and route subsequent execution based on human action (approve/reject/escalate). Demonstrates how HITL transitions from bolt-on approval gates…

In 14 listsDetails

Haystack

Open-source AI orchestration framework for building context-engineered, production-ready LLM applications. Design modular pipelines and agent workflows with explicit control over retrieval, routing, memory, and generation. Built for scalable agents, RAG, multimodal applications, semantic search,…

In 13 listsDetails

Phoenix

Open-source AI observability & evaluation platform (Arize) — OpenTelemetry-native tracing for agents, LLM-as-judge evals, versioned datasets & experiments for prompt regression testing, prompt management with version control and replay, plus an MCP endpoint so Claude Code/Cursor can query traces…

In 10 listsDetails

Langfuse

The most widely adopted self-hostable LLM observability platform: traces every agent step, manages prompt versions, and runs evals in one tool. Preferred over cloud-only alternatives when data residency or cost control is a constraint.

In 10 listsDetails