Showing 313 open source projects for "python-kinterbasdb"

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  • 1
    Bindu

    Bindu

    Bindu: Turn any AI agent into a living microservice

    Bindu is an open-source infrastructure layer that transforms any AI agent into a production-ready microservice capable of interacting, communicating, and transacting within a broader network of agents. It abstracts away the complexity of deployment, authentication, communication protocols, and payment systems by allowing developers to “bindufy” an agent with minimal configuration. Once integrated, the agent gains a decentralized identity, standardized communication capabilities through...
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  • 2
    SEO Machine

    SEO Machine

    A specialized Claude Code workspace for creating long-form

    SEO Machine is an AI-powered content production system built as a structured workspace for generating long-form, SEO-optimized blog content through automated workflows. It integrates research, writing, analysis, and optimization into a single pipeline, allowing users to produce high-quality articles tailored to search engine performance. The system uses specialized commands and agents to perform tasks such as keyword research, competitor analysis, content drafting, and optimization. It...
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  • 3
    Desloppify

    Desloppify

    Agent harness to make your slop code well-engineered and beautiful

    Desloppify is a utility-focused project aimed at improving the quality, structure, and clarity of generated or written text by removing redundancy, noise, and unnecessary verbosity. It is designed to “clean up” outputs, particularly those produced by AI systems, making them more concise, readable, and professional. The system likely applies heuristics or transformation rules to identify repetitive patterns, filler content, and stylistic inconsistencies. This makes it especially useful in...
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  • 4
    AI Agent Deep Dive

    AI Agent Deep Dive

    AI Agent Source Code Deep Research Report

    AI Agent Deep Dive is a comprehensive educational repository designed to provide a deep and structured understanding of how modern AI agents work, focusing on architecture, workflows, and real-world implementation patterns. It breaks down complex concepts such as planning, tool usage, memory management, and multi-step reasoning into digestible explanations and practical examples. The project is organized as a learning resource rather than a standalone framework, making it particularly useful...
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    ClawTeam

    ClawTeam

    ClawTeam: Agent Swarm Intelligence (One Command → Full Automation)

    ClawTeam is an advanced multi-agent orchestration framework that enables AI agents to form collaborative swarms capable of solving complex tasks autonomously. Instead of relying on a single agent, the system allows a leader agent to spawn and coordinate multiple specialized sub-agents, each responsible for different aspects of a problem. These agents communicate, share insights, and dynamically adapt their strategies based on real-time feedback, creating a form of collective intelligence....
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  • 6
    Get Physics Done (GPD)

    Get Physics Done (GPD)

    The first open-source agentic AI physicist

    Get Physics Done (GPD) is an open-source project designed to accelerate scientific research in physics by leveraging modern computational tools and automation techniques. It aims to simplify the process of performing simulations, calculations, and experimental analysis by providing structured workflows that integrate computational physics methods with reproducible research practices. The project focuses on reducing the friction involved in setting up experiments, running simulations, and...
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  • 7
    Youtu-Agent

    Youtu-Agent

    A simple yet powerful agent framework that delivers with models

    Youtu-Agent is an open-source framework developed to simplify the creation, execution, and evaluation of autonomous AI agents. The system focuses on reducing the complexity traditionally involved in configuring large language model agents by providing a modular architecture that separates execution environments, tools, and context management. This structure allows developers to rapidly assemble agent systems capable of performing tasks such as research, file processing, and data analysis....
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  • 8
    MiroThinker

    MiroThinker

    MiroThinker is an open source deep research agent

    MiroThinker is an open-source deep research AI agent designed to perform complex reasoning, information gathering, and predictive analysis tasks. The system focuses on enabling long-horizon research workflows by allowing the agent to interact repeatedly with external tools, search systems, and data sources while refining its reasoning through iterative steps. Rather than simply generating responses from a single prompt, the agent performs structured multi-step reasoning processes that...
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  • 9
    Agentic Data Scientist

    Agentic Data Scientist

    An end-to-end Data Scientist

    Agentic Data Scientist is an experimental AI-driven research framework that orchestrates data science workflows through autonomous agents that can reason, plan, and execute complex analytics tasks. Unlike traditional scripted pipelines, this project lets AI agents break down high-level research goals into sub-tasks such as data acquisition, cleaning, modeling, evaluation, and reporting, with minimal human direction. Each agent is designed to independently call functions, interact with data...
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  • 10
    Vibium

    Vibium

    Browser automation for AI agents and humans

    ...This design makes it ideal for AI agents that need to interact with the web, perform tasks, or simulate human interactions in a browser environment, and it also works well for traditional testing and automation workflows. Vibium strikes a balance between AI-native capabilities and conventional developer usability by offering language bindings and client APIs for JavaScript and Python.
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  • 11
    NVIDIA AgentIQ

    NVIDIA AgentIQ

    The NVIDIA AgentIQ toolkit is an open-source library

    NVIDIA AgentIQ is an open-source toolkit designed to efficiently connect, evaluate, and accelerate teams of AI agents. It provides a framework-agnostic platform that integrates seamlessly with various data sources and tools, enabling developers to build composable and reusable agentic workflows. By treating agents, tools, and workflows as simple function calls, AgentIQ facilitates rapid development and optimization of AI-driven applications, enhancing collaboration and efficiency in complex...
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  • 12
    AgentForge

    AgentForge

    Extensible AGI Framework

    AgentForge is a framework for creating and deploying AI agents that can perform autonomous decision-making and task execution. It enables developers to define agent behaviors, train models, and integrate AI-powered automation into various applications.
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  • 13
    SWE-agent

    SWE-agent

    SWE-agent takes a GitHub issue and tries to automatically fix it

    SWE-agent turns LMs (e.g. GPT-4) into software engineering agents that can resolve issues in real GitHub repositories. On the SWE-bench, the SWE-agent resolves 12.47% of issues, achieving state-of-the-art performance on the full test set. We accomplish our results by designing simple LM-centric commands and feedback formats to make it easier for the LM to browse the repository, and view, edit, and execute code files. We call this an Agent-Computer Interface (ACI).
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  • 14
    Langroid

    Langroid

    Harness LLMs with Multi-Agent Programming

    Given the remarkable abilities of recent Large Language Models (LLMs), there is an unprecedented opportunity to build intelligent applications powered by this transformative technology. The top question for any enterprise is: how best to harness the power of LLMs for complex applications? For technical and practical reasons, building LLM-powered applications is not as simple as throwing a task at an LLM system and expecting it to do it. Effectively leveraging LLMs at scale requires a...
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  • 15
    PraisonAI

    PraisonAI

    PraisonAI application combines AutoGen and CrewAI or similar framework

    PraisonAI application combines AutoGen and CrewAI or similar frameworks into a low-code solution for building and managing multi-agent LLM systems, focusing on simplicity, customization, and efficient human-agent collaboration. Chat with your ENTIRE Codebase. Praison AI, leveraging both AutoGen and CrewAI or any other agent framework, represents a low-code, centralized framework designed to simplify the creation and orchestration of multi-agent systems for various LLM applications,...
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  • 16
    AgentHandover

    AgentHandover

    AgentHandover observes, learns and teaches agents with skills

    AgentHandover is a Mac-focused system that observes how a user works and converts repeated workflows into reusable, self-improving skills for AI agents. It is designed for tools such as Claude Code, OpenClaw, Codex, Hermes, Cursor, Windsurf, and other MCP-compatible environments. Instead of asking users to manually write long prompts or static automation instructions, it records real actions, infers decision logic, and produces skills that include steps, strategy, guardrails, selection...
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  • 17
    Claw Compactor

    Claw Compactor

    14-stage Fusion Pipeline for LLM token compression

    Claw Compactor is a utility designed to optimize and manage the context limitations inherent in AI agent systems, particularly those built on OpenClaw-like architectures. It addresses the challenge of finite context windows in language models by compressing or summarizing historical interactions while preserving essential information. The system works by transforming older conversation data into condensed representations that maintain continuity without exceeding token limits. This approach...
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  • 18
    MolmoWeb

    MolmoWeb

    Open multimodal web agent built by Ai2

    MolmoWeb is an open-source multimodal web agent designed to autonomously navigate and interact with web browsers using vision-language models, representing a significant step toward fully agentic AI systems that can operate in real-world digital environments. The system takes natural language instructions and translates them into sequences of browser actions such as clicking, typing, scrolling, and navigating, effectively performing tasks on behalf of the user. Unlike traditional automation...
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  • 19
    Open Gauss

    Open Gauss

    Project-scoped Lean workflow orchestrator from Math, Inc.

    Open Gauss is an enterprise-grade open-source relational database management system designed to handle large-scale data processing with high performance, reliability, and security. It is based on the PostgreSQL ecosystem but significantly extends its capabilities through architectural optimizations, AI-driven features, and enterprise-level enhancements. The database organizes data using the relational model, storing structured information in tables composed of rows and columns while...
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  • 20
    Agent Starter Pack

    Agent Starter Pack

    Ship AI Agents to Google Cloud in minutes, not months

    Agent Starter Pack is a production-focused framework that provides pre-built templates and infrastructure for rapidly developing and deploying generative AI agents on Google Cloud. It is designed to eliminate the complexity of moving from prototype to production by bundling essential components such as deployment pipelines, monitoring, security, and evaluation tools into a single package. Developers can create fully functional agent projects with a single command, generating both backend and...
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  • 21
    verl-agent

    verl-agent

    Designed for training LLM/VLM agents via RL

    verl-agent is an open-source reinforcement learning framework designed to train large language model agents and vision-language model agents for complex interactive environments. Built as an extension of the veRL reinforcement learning infrastructure, the project focuses on enabling scalable training for agents that perform multi-step reasoning and decision-making tasks. The framework supports multi-turn interactions between agents and their environments, allowing the system to receive...
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  • 22
    Deep Search Agent

    Deep Search Agent

    Implement a concise and clear Deep Search Agent from 0

    Deep Search Agent is an experimental demonstration project that showcases an autonomous AI agent designed to perform multi-step research and information gathering tasks. The repository illustrates how large language models can be orchestrated with tools and planning logic to execute complex search workflows rather than single-prompt responses. It typically combines reasoning, retrieval, and iterative refinement so the agent can break down questions, gather evidence, and synthesize structured...
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  • 23
    Sandstorm

    Sandstorm

    One API call, pull Claude agent, completely sandboxed

    Sandstorm is an open-source project that wraps a powerful Claude-based AI agent within a completely sandboxed, ephemeral API service designed to make agentic AI workflows easy to deploy and scale without infrastructure complexity. The core idea is to provide “one API call” access to a robust Claude agent loop that runs inside a secure sandbox, so you can upload files, connect tools, and run long-running tasks — all managed behind a simple REST-style interface that disappears when the work is...
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  • 24
    SafeClaw

    SafeClaw

    Chat with it via text and voice

    SafeClaw is an open-source, entirely local alternative to cloud-based AI assistants like OpenClaw, enabling users to build a personal assistant that runs on their own machine without incurring API usage charges or exposing data to third-party services. It emphasizes privacy and predictability by using traditional programming, rule-based intent parsing, and established machine learning tools rather than large language models, meaning there are no per-token API costs and deterministic...
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  • 25
    Dash Data Agent

    Dash Data Agent

    Self-learning data agent that grounds its answers in layers of content

    Dash is a self-learning data agent built by the Agno AI community that generates grounded answers to English queries over structured data by synthesizing SQL and reasoning based on six layers of context, improving automatically with each run. It sidesteps common limitations of simple text-to-SQL agents by incorporating multiple context layers — including schema structure, human annotations, known query patterns, institutional knowledge from docs, machine-discovered error patterns, and live...
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