Search Results for "python augmented reality"
Sort By:
8 projects for "python augmented reality" with 2 filters applied:
-
Ship Agents FasterGemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
-
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
-
1
FlagEmbedding
Retrieval and Retrieval-augmented LLMs
FlagEmbedding is an open-source toolkit for building and deploying high-performance text embedding models used in information retrieval and retrieval-augmented generation systems. The project is part of the BAAI FlagOpen ecosystem and focuses on creating embedding models that transform text into dense vector representations suitable for semantic search and large language model pipelines. FlagEmbedding includes a family of models known as BGE (BAAI General Embedding), which are designed to... -
2
Pixeltable
Data Infrastructure providing an approach to multimodal AI workloads
...Developers define data transformations and AI operations using computed columns on tables, allowing pipelines to evolve incrementally as new data or models are added. The framework supports multimodal content including images, video, text, and audio, enabling applications such as retrieval-augmented generation systems, semantic search, and multimedia analytics. -
3
SimpleMem
SimpleMem: Efficient Lifelong Memory for LLM Agents
SimpleMem is a lightweight memory-augmented model framework that helps developers build AI applications that retain long-term context and recall relevant information without overloading model context windows. It provides easy-to-use APIs for storing structured memory entries, querying those memories using semantic search, and retrieving context to augment prompt inputs for downstream processing. Unlike monolithic systems where memory management is ad-hoc, SimpleMem formalizes a memory... -
4
kg-gen
Knowledge Graph Generation from Any Text
kg-gen is an open-source framework developed by the STAIR Lab that automatically generates knowledge graphs from unstructured text using large language models. The system is designed to transform plain text sources such as documents, articles, or conversation transcripts into structured graphs composed of entities and relationships. Instead of relying on traditional rule-based extraction techniques, KG-Gen uses language models to identify entities and their relationships, producing... -
Cut Data Warehouse Costs by 54%BigQuery delivers 54% lower TCO with exabyte scale and flexible pricing. Free migration tools handle the SQL translation automatically.
-
5
LEANN
Local RAG engine for private multimodal knowledge search on devices
LEANN is an open source system designed to enable retrieval-augmented generation (RAG) and semantic search across personal data while running entirely on local devices. It focuses on dramatically reducing the storage overhead typically required for vector search and embedding indexes, enabling efficient large-scale knowledge retrieval on consumer hardware. LEANN introduces a storage-efficient approximate nearest neighbor index combined with on-the-fly embedding recomputation to avoid storing... -
6
Controllable-RAG-Agent
This repository provides an advanced RAG
Controllable-RAG-Agent is an advanced Retrieval-Augmented Generation (RAG) system designed specifically for complex, multi-step question answering over your own documents. Instead of relying solely on simple semantic search, it builds a deterministic control graph that acts as the “brain” of the agent, orchestrating planning, retrieval, reasoning, and verification across many steps. The pipeline ingests PDFs, splits them into chapters, cleans and preprocesses text, then constructs vector... -
7
rag-search
RAG Search API
rag-search is a lightweight Retrieval-Augmented Generation API service designed to provide structured semantic search and answer generation through a simple FastAPI backend. The project integrates web search, vector embeddings, and reranking logic to retrieve relevant context before passing it to a language model for response generation. It is built to be easily deployable, requiring only environment configuration and dependency installation to run a functional RAG service. The system... -
8
ChatGPT Retrieval Plugin
The ChatGPT Retrieval Plugin lets you easily find personal documents
The chatgpt-retrieval-plugin repository implements a semantic retrieval backend that lets ChatGPT (or GPT-powered tools) access private or organizational documents in natural language by combining vector search, embedding models, and plugin infrastructure. It can serve as a custom GPT plugin or function-calling backend so that a chat session can “look up” relevant documents based on user queries, inject those results into context, and respond more knowledgeably about a private knowledge...
- Previous
- You're on page 1
- Next
