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    pgvecto.rs

    pgvecto.rs

    Vector database plugin for Postgres, written in Rust

    pgvecto.rs is a Postgres extension that provides vector similarity search functions. It is written in Rust and based on pgrx. It is currently under heavy development, please take care when using it in production. pgvecto.rs is a Postgres extension, which means that you can use it directly within your existing database. This makes it easy to integrate into your existing workflows and applications. pgvecto.rs supports filtering.
    Downloads: 4 This Week
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  • 2
    AnythingLLM

    AnythingLLM

    The all-in-one Desktop & Docker AI application with full RAG and AI

    A full-stack application that enables you to turn any document, resource, or piece of content into a context that any LLM can use as references during chatting. This application allows you to pick and choose which LLM or Vector Database you want to use as well as supporting multi-user management and permissions. AnythingLLM is a full-stack application where you can use commercial off-the-shelf LLMs or popular open-source LLMs and vectorDB solutions to build a private ChatGPT with no compromises that you can run locally as well as host remotely and be able to chat intelligently with any documents you provide it. ...
    Downloads: 97 This Week
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  • 3
    Controllable-RAG-Agent

    Controllable-RAG-Agent

    This repository provides an advanced RAG

    ...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 stores for fine-grained chunks, chapter summaries, and book quotes to support nuanced queries. At query time, it anonymizes entities, creates a high-level plan, de-anonymizes and expands that plan into concrete retrieval or reasoning tasks, and executes them in sequence while continuously revising the plan. A key focus is hallucination control: each answer is verified against retrieved context, and responses are reworked when they are not sufficiently grounded in the source documents.
    Downloads: 0 This Week
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  • 4
    marqo

    marqo

    Tensor search for humans

    A tensor-based search and analytics engine that seamlessly integrates with your applications, websites, and workflows. Marqo is a versatile and robust search and analytics engine that can be integrated into any website or application. Due to horizontal scalability, Marqo provides lightning-fast query times, even with millions of documents. Marqo helps you configure deep-learning models like CLIP to pull semantic meaning from images. It can seamlessly handle image-to-image, image-to-text and...
    Downloads: 0 This Week
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  • 5
    Zep

    Zep

    Zep: A long-term memory store for LLM / Chatbot applications

    Easily add relevant documents, chat history memory & rich user data to your LLM app's prompts. Understands chat messages, roles, and user metadata, not just texts and embeddings. Zep Memory and VectorStore implementations are shipped with your favorite frameworks: LangChain, LangChain.js, LlamaIndex, and more. Automatically embed texts and messages using state-of-the-art opeb source models, OpenAI, or bring your own vectors. Zep’s local embedding models and async enrichment ensure a snappy...
    Downloads: 1 This Week
    Last Update:
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  • 6
    OpenLLMetry

    OpenLLMetry

    Open-source observability for your LLM application

    The repo contains standard OpenTelemetry instrumentations for LLM providers and Vector DBs, as well as a Traceloop SDK that makes it easy to get started with OpenLLMetry, while still outputting standard OpenTelemetry data that can be connected to your observability stack. If you already have OpenTelemetry instrumented, you can just add any of our instrumentations directly.
    Downloads: 0 This Week
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  • 7
    Infinity

    Infinity

    Low-latency REST API for serving text-embeddings

    Infinity is a high-throughput, low-latency REST API for serving vector embeddings, supporting all sentence-transformer models and frameworks. Infinity is developed under MIT License. Infinity powers inference behind Gradient.ai and other Embedding API providers.
    Downloads: 4 This Week
    Last Update:
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  • 8
    Langtrace

    Langtrace

    Open Telemetry based end-to-end observability tool for LLM apps

    Langtrace is an open-source, Open Telemetry based end-to-end observability tool for LLM applications, providing real-time tracing, evaluations, and metrics for popular LLMs, LLM frameworks, vectors, and more.. Integrate using Typescript, and Python. Langtrace is an open-source observability tool that collects and analyzes traces and metrics to help you improve your LLM apps.
    Downloads: 0 This Week
    Last Update:
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  • 9
    DB-GPT

    DB-GPT

    Revolutionizing Database Interactions with Private LLM Technology

    DB-GPT is an experimental open-source project that uses localized GPT large models to interact with your data and environment. With this solution, you can be assured that there is no risk of data leakage, and your data is 100% private and secure.
    Downloads: 0 This Week
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  • 10
    Superagent

    Superagent

    Superagent protects your AI applications

    Superagent is an open-source AI safety platform built to protect applications from prompt injections, data leaks, and harmful outputs. It embeds real-time safety directly into AI workflows, helping teams secure models before threats cause damage. Superagent provides guardrails that block jailbreaks, prompt manipulation, and sensitive data exfiltration. It includes redaction tools to remove PII, PHI, and secrets automatically from text. The platform also scans code repositories to detect...
    Downloads: 1 This Week
    Last Update:
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  • 11
    Kaleidoscope-SDK

    Kaleidoscope-SDK

    User toolkit for analyzing and interfacing with Large Language Models

    ...It provides a simple interface to launch LLMs on an HPC cluster, asking them to perform basic features like text generation, but also retrieve intermediate information from inside the model, such as log probabilities and activations. Users must authenticate using their Vector Institute cluster credentials. This can be done interactively instantiating a client object. This will generate an authentication token that will be used for all subsequent requests. The token will expire after 30 days, at which point the user will be prompted to re-authenticate.
    Downloads: 0 This Week
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  • 12
    Qwen3 Embedding

    Qwen3 Embedding

    Designed for text embedding and ranking tasks

    ...It achieves state-of-the-art performance on benchmarks like MTEB (Multilingual Text Embedding Benchmark) and supports instruction-aware embedding (i.e. embedding task instructions along with queries) and flexible embedding/vector dimension definitions. It is meant for tasks such as text retrieval, classification, clustering, bitext mining, and code retrieval.
    Downloads: 0 This Week
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