Search Results for "databases" - Page 3
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Showing 140 open source projects for "databases"
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Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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Memori
SQL-native memory layer enabling persistent context for AI agents
...It provides a memory layer that automatically captures conversations and interactions between users and AI models, allowing systems to retain knowledge across sessions instead of operating statelessly. It extracts structured information such as facts, preferences, rules, and summaries from interactions and stores them in standard SQL databases for later retrieval. By recalling relevant context during future model calls, Memori helps AI agents produce more consistent and context-aware responses while reducing the need to repeatedly provide background information. Memori is designed to work with multiple LLM providers, data stores, and AI frameworks, allowing it to integrate into existing software architectures without requiring major changes. -
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SmythOS
Cloud-native runtime for agentic AI
...It provides a foundational infrastructure layer that functions similarly to an operating system for agentic AI systems, managing resources such as language models, storage, vector databases, and caching through a unified interface. Developers can use the runtime to create, deploy, and orchestrate intelligent agents across local machines, cloud environments, or hybrid infrastructures without rewriting their application logic. The platform includes a software development kit and command-line interface that allow developers to define agent workflows, manage execution environments, and automate deployment processes. ... -
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ReCall
Learning to Reason with Search for LLMs via Reinforcement Learning
...The project builds on earlier work focused on teaching models how to search for information during reasoning tasks and extends that idea to a broader system where models can call a variety of external tools such as APIs, databases, or computation engines. Instead of relying purely on static knowledge stored inside the model, ReCall allows the language model to dynamically decide when it should retrieve information or invoke external capabilities during the reasoning process. The framework uses reinforcement learning to train models to perform these tool calls effectively while solving multi-step reasoning tasks. -
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CAG
Cache-Augmented Generation: A Simple, Efficient Alternative to RAG
CAG, or Cache-Augmented Generation, is an experimental framework that explores an alternative architecture for integrating external knowledge into large language model responses. Traditional retrieval-augmented generation systems rely on real-time retrieval of documents from databases or vector stores during inference. CAG proposes a different approach by preloading relevant knowledge into the model’s context window and precomputing the model’s key-value cache before queries are processed. This strategy allows the model to generate responses using the cached context directly, eliminating the need for repeated retrieval operations during runtime. ... -
Stop vibe-debugging.AppSignal's MCP server hands Claude, Cursor, or Zed your real errors, traces, and the deploy that shipped them. AI writes the fix; you review the diff.
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MemPalace
The highest-scoring AI memory system ever benchmarked
MemPalace is an open-source AI memory system designed to solve one of the most persistent limitations of large language models: the loss of context between sessions. Instead of relying on summarization or selective extraction like most memory tools, it takes a radically different approach by storing conversations in their entirety and making them retrievable through structured organization and semantic search. The system is inspired by the classical “memory palace” mnemonic technique,... -
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OceanBase seekdb
The AI-Native Search Database
seekdb is an AI-native search database from OceanBase that unifies vector, full-text, relational, JSON, and GIS data into a single query engine. The system is designed to support hybrid search workloads and in-database AI workflows without requiring multiple specialized databases. It enables developers to perform semantic search, keyword search, and structured SQL queries within the same platform, simplifying modern AI application stacks. seekdb also embeds AI capabilities directly in the database layer, including embedding generation, reranking, and LLM inference for end-to-end RAG pipelines. Built on the OceanBase engine, it maintains ACID compliance and MySQL compatibility while delivering real-time analytical performance. ... -
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MemMachine
Universal memory layer for AI Agents
...Unlike ephemeral LLM prompt state, MemMachine supports distinct memory types—short-term conversational context, long-term persistent knowledge, and profile memory for personalized facts—persisted in optimized stores (e.g., graph databases for episodic lines of reasoning and SQL for user facts) to support robust, context-aware intelligence in agents. It offers flexible APIs, a Python SDK, REST interfaces, and MCP (Model Context Protocol) connectivity to integrate seamlessly with agent frameworks receiving and storing memories over time, effectively boosting relevance, continuity, and tailored behavior. -
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QAnything
Question and Answer based on Anything
QAnything is a local knowledge-base question-answering system designed to let users ask questions over many kinds of files and databases. It supports offline installation, making it useful for organizations that need private document analysis without sending data to external services. Users can upload local files and receive fast, reliable answers based on the indexed content. The system supports formats such as PDF, Word, PowerPoint, Excel, Markdown, email, text, images, CSV, and web links. ... -
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HiClaw
An open source collaborative multi-agent OS
...It is designed to provide structured, explainable workflows that help legal professionals interact with AI systems more transparently and efficiently. hiclaw emphasizes modularity and integration with external legal databases, retrieval systems, and enterprise tooling, enabling customization for different legal domains and operational requirements. The platform explores how agentic AI systems can coordinate reasoning, retrieval, and procedural logic within legal workflows while maintaining contextual awareness. -
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.
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Bolt.new
Prompt, run, edit, and deploy full-stack web applications
Bolt.new is an AI-powered full-stack development platform created by StackBlitz that enables users to build, run, edit, and deploy complete web applications directly from the browser without requiring any local setup or traditional development environment. It operates as an intelligent coding agent where users describe what they want to build in natural language, and the system generates functional applications, including frontend, backend, and infrastructure components. The platform is... -
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Vanna 2.0
Chat with your SQL database
Vanna is an open-source Python framework that enables natural language interaction with databases by converting user questions into executable SQL queries using large language models. The framework uses a retrieval-augmented generation architecture that learns from database schemas, documentation, and past query examples to generate accurate queries tailored to a specific dataset. Vanna can be integrated into many environments, including notebooks, web applications, messaging platforms, and data dashboards, making it flexible for analytics and data exploration workflows. ... -
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ViMax
Director, Screenwriter, Producer, and Video Generator All-in-One
...It integrates components like visual encoders, cross-modal fusion techniques, and reasoning modules so that users can go beyond simple captioning or classification to perform tasks such as visual question answering, multi-image inference, and structured scene understanding. ViMax’s design accommodates large image sets and supports retrieval augmentation, enabling it to work with external image databases, supplementary metadata, and semantic search to enhance context awareness. The system aims to bridge foundational vision backbones and generative language models through adapters and fusion layers that maximize both signal integration and reasoning depth, and includes utility pipelines for training, evaluation, and deployment. -
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Phidata
Build multi-modal Agents with memory, knowledge, tools and reasoning
...It enables users to create domain-specific agents with memory, knowledge, and external tools, enhancing AI capabilities for various tasks. The platform supports a range of large language models and integrates seamlessly with different databases, vector stores, and APIs. Phidata offers pre-configured templates to accelerate development and deployment, allowing users to quickly go from building agents to shipping them into production. It includes features like real-time monitoring, agent evaluations, and performance optimization tools, ensuring the reliability and scalability of AI solutions. ... -
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Neuron AI
The PHP Agentic Framework to build production-ready AI driven apps
Neuron AI is a PHP agentic framework for building production-ready AI applications that connect models, memory, vector databases, and tools into working agents. It is designed for developers who want to create systems such as RAG pipelines, multi-agent workflows, and business process automations without having to hand-build every integration from scratch. The framework provides an Agent class that can be extended to inherit core capabilities like memory, tools, function calling, and retrieval-augmented generation. ... -
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LangChain Rust
LangChain for Rust, the easiest way to write LLM-based programs
LangChain Rust is an open-source Rust implementation inspired by the LangChain ecosystem for building applications powered by large language models. The library aims to provide Rust developers with a structured framework for orchestrating prompts, chains, agents, and external tools within LLM-driven workflows. By adapting LangChain concepts to the Rust programming language, the project emphasizes performance, safety, and efficient memory management. Developers can use the framework to build... -
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GitClaw
A universal git-native AI agent framework
GitClaw is an open-source framework for building AI agents whose entire identity, configuration, memory, and capabilities live inside a Git repository. Instead of storing agent state in databases or application code, the framework treats a repository itself as the agent’s environment, allowing developers to version, inspect, and collaborate on agents using standard Git workflows. The system defines structured files that represent the agent’s personality, rules, configuration, and operational logic, enabling transparent control over how the agent behaves. ... -
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Agents-Flex
Agents-Flex is an elegant LLM Application Framework like LangChain
...Agents-Flex offers Loader, Parser, and Splitter components for the Document. Each component has multiple implementations, making it easy to load data from the web, local files, databases, and various data types. -
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JimuReport
Open source drag-and-drop reporting and dashboard builder platform
JimuReport is an open source data visualization and reporting platform designed to help developers and organizations build reports, dashboards, and large screen data displays through a visual interface. It provides an online report designer that uses an Excel-like editing experience, allowing users to construct reports with drag-and-drop components and cell-based layouts. It focuses on simplifying complex report development by enabling visual configuration instead of manual coding.... -
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Claude Scientific Skills
A set of ready to use Agent Skills for research, science, engineering
...The framework follows the open Agent Skills standard and works with multiple AI development environments including Claude Code, Cursor, and Codex. Its primary goal is to reduce the friction of scientific computing by giving AI agents structured access to specialized libraries, databases, and research pipelines. Overall, the repository acts as a modular capability layer that transforms general AI agents into domain-aware computational scientists. -
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Slack MCP Server
The most powerful MCP Slack Server with no permission requirements
...MCP is a standardized protocol that allows large language models and AI agents to securely interact with external tools and data sources such as messaging platforms, databases, or file systems. The slack-mcp-server acts as an intermediary layer that exposes Slack data and messaging functionality to AI clients while enforcing access rules and communication standards. Through this architecture, AI assistants can read message histories, interact with channels, and retrieve contextual information from Slack conversations in order to perform tasks such as automated analysis, collaboration assistance, or contextual code review. ... -
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MCP Snowflake Server
A Model Context Protocol (MCP) server implementation
An MCP server implementation that facilitates database interactions with Snowflake, allowing execution of SQL queries and presentation of data insights as resources. -
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Awesome Fraud Detection Research Papers
A curated list of data mining papers about fraud detection
A curated list of data mining papers about fraud detection from several conferences. -
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Agently 4
Build GenAI application quick and easy
...The project aims at production-grade GenAI application development rather than just one-off scripts — you’ll find examples of news gathering, agentic workflows, control systems, etc. It is licensed under Apache-2.0, allowing commercial use and modification. Because it's built in Python, it integrates easily with existing data pipelines, databases, and agent architectures. -
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Eko
Build Production-ready Agentic Workflow with Natural Language
Eko (Eko Keeps Operating) is a JavaScript framework designed for building production-ready agent-based workflows using natural language commands. It allows developers to create automated agents that can handle complex workflows in both computer and browser environments. With a focus on high development efficiency, Eko simplifies the creation of multi-step workflows, enabling users to integrate and automate tasks across platforms. It provides a unified interface for managing agents, offering... -
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TabPFN
Foundation Model for Tabular Data
...This allows it to generate predictions extremely quickly, often within seconds, while maintaining competitive accuracy on small and medium-sized datasets. The system supports a variety of tabular machine learning tasks and is designed to handle structured datasets commonly found in spreadsheets, databases, and business analytics systems.
