Search Results for "python language" - Page 27

Showing 2173 open source projects for "python language"

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  • 1
    bu-agent-sdk

    bu-agent-sdk

    An agent is just a for-loop

    The bu-agent-sdk from the Browser Use project is a minimalistic Python framework that defines an AI agent as a simple loop of tool calls, aiming to keep abstractions low so developers can build autonomous agents without unnecessary complexity. At its core, the agent loop repeatedly queries a large language model, interprets its output, and executes defined “tools” — functions annotated with task names — to perform actions, allowing the agent to complete tasks like arithmetic, decision-making, or domain-specific work. ...
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  • 2
    Chroma MCP

    Chroma MCP

    A Model Context Protocol (MCP) server implementation

    Chroma MCP Server is an implementation of the Model Context Protocol (MCP) designed to integrate large language model (LLM) applications with external data sources or tools. It offers a standardized framework to seamlessly provide LLMs with the context they require for effective operation. ​
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  • 3
    Supabase MCP Server

    Supabase MCP Server

    Query MCP enables end-to-end management of Supabase via chat interface

    An open-source MCP server that enables comprehensive management of Supabase projects through natural language interactions, providing capabilities such as SQL execution, schema management, and API integration. ​
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  • 4
    OpenDataMCP

    OpenDataMCP

    Connect any Open Data to any LLM with Model Context Protocol

    An initiative aimed at connecting open datasets to Large Language Models (LLMs) using the Model Context Protocol, facilitating seamless access and integration of public data into AI applications. ​
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  • 5
    K8s MCP Server

    K8s MCP Server

    K8s-mcp-server is a Model Context Protocol (MCP) server

    An MCP server that enables AI assistants like Claude to securely execute Kubernetes commands, providing a bridge between language models and essential Kubernetes CLI tools for cluster management and deployments. ​
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  • 6
    IntentKit

    IntentKit

    An open and fair framework for everyone to build AI agents

    IntentKit is a natural language understanding (NLU) library focused on intent recognition and entity extraction, enabling developers to build conversational AI applications.
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  • 7

    Protocol Buffers

    Google's data interchange format

    Protocol Buffers are Google’s fast and simple, language- and platform-neutral, extensible mechanism for serializing structured data. It allows you to define how your data should be structured once, and then using a special generated source code, you can then easily write and read your structured data to and from a variety of data streams and using a variety of languages. Protocol Buffers currently supports a wide array of languages, including C++, Java, Python, Ruby, and many others with more to come.
    Downloads: 6 This Week
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  • 8
    Fli

    Fli

    Google Flights MCP and Python Library

    ...In addition to its CLI interface, fli includes a Model Context Protocol (MCP) server that allows AI assistants to interact with flight data using structured tools, enabling natural language queries and automation workflows.
    Downloads: 1 This Week
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  • 9
    Aden Hive

    Aden Hive

    Outcome driven agent development framework that evolves

    Hive is an open-source agent development framework that helps developers build autonomous, reliable, self-improving AI agents by letting them describe goals in ordinary natural language instead of hand-coding detailed workflows. Rather than manually defining execution graphs, Hive’s coding agent generates the agent graph, connection code, and test cases based on your high-level objectives, enabling outcome-driven agent creation that fits real business processes. Once deployed, agents can...
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  • 10
    VibeThinker

    VibeThinker

    Diversity-driven optimization and large-model reasoning ability

    VibeThinker is a compact but high-capability open-source language model released by WeiboAI (Sina AI Lab). It contains about 1.5 billion parameters, far smaller than many “frontier” models, yet it is explicitly optimized for reasoning, mathematics, and code generation tasks rather than general open-domain chat. The innovation lies in its training methodology: the team uses what they call the Spectrum-to-Signal Principle (SSP), where a first stage emphasizes diversity of reasoning paths (the...
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  • 11
    Tiktoken

    Tiktoken

    tiktoken is a fast BPE tokeniser for use with OpenAI's models

    tiktoken is a high-performance, tokenizer library (based on byte-pair encoding, BPE) designed for use with OpenAI’s models. It handles encoding and decoding text to token IDs efficiently, with minimal overhead. Because tokenization is a fundamental step in preparing text for models, tiktoken is optimized for speed, memory, and correctness in model contexts (e.g. matching OpenAI’s internal tokenization). The repo supports multiple encodings (e.g. “cl100k_base”) and lets users switch encoding...
    Downloads: 1 This Week
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  • 12
    spaCy models

    spaCy models

    Models for the spaCy Natural Language Processing (NLP) library

    spaCy is designed to help you do real work, to build real products, or gather real insights. The library respects your time, and tries to avoid wasting it. It's easy to install, and its API is simple and productive. spaCy excels at large-scale information extraction tasks. It's written from the ground up in carefully memory-managed Cython. If your application needs to process entire web dumps, spaCy is the library you want to be using. Since its release in 2015, spaCy has become an industry...
    Downloads: 6 This Week
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  • 13
    txtai

    txtai

    Build AI-powered semantic search applications

    txtai executes machine-learning workflows to transform data and build AI-powered semantic search applications. Traditional search systems use keywords to find data. Semantic search applications have an understanding of natural language and identify results that have the same meaning, not necessarily the same keywords. Backed by state-of-the-art machine learning models, data is transformed into vector representations for search (also known as embeddings). Innovation is happening at a rapid...
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  • 14
    BigMac

    BigMac

    An open-source toolkit for BigMac-style pipeline-parallel training

    BigMac is an open-source toolkit for pipeline-parallel training of multimodal large language models. It preserves optimized language-model pipeline schedules while placing encoder and generator work around them. This design reduces activation memory without bringing back cross-module pipeline bubbles. Its scheduler creates global operator plans, while its executor runs those plans through a shared schedule abstraction. A Megatron-Core reference backend and Qwen3 and Qwen3-VL tutorials help...
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  • 15
    LangChain Open Deep Research

    LangChain Open Deep Research

    Fully open source deep research agent

    Open Deep Research is a configurable, fully open-source agent for producing detailed research reports from complex questions. It separates work across models used for summarization, active research, information compression, and final report generation. Users can select from multiple language model providers as long as the chosen models support tool calling and structured outputs. Search can be powered by several APIs, native provider search, or external tools connected through MCP. The agent...
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  • 16
    VulnClaw

    VulnClaw

    Based on AI Agent + MCP toolchain + penetration Skill orchestration

    VulnClaw is an AI-powered penetration testing agent that turns natural language security goals into structured testing workflows. It combines LLM agents, MCP toolchains, penetration testing skills, and command-line automation to support authorized security assessments. The project can guide information gathering, vulnerability discovery, validation, and report generation while keeping the workflow organized through sessions and tools. Its newer architecture uses a goal-driven solving engine...
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  • 17
    GenericAgent

    GenericAgent

    Self-evolving autonomous agent framework

    The GenericAgent project is a flexible framework for building autonomous AI agents that can operate across diverse tasks and environments. It is designed around modularity, allowing developers to define agents with interchangeable components such as tools, memory systems, and reasoning strategies. The architecture emphasizes generality, enabling the same agent framework to be adapted for different domains including coding, research, and task automation. It integrates with modern language...
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  • 18
    EvoAgentX

    EvoAgentX

    Self-evolving AI agent framework for automated workflows

    EvoAgentX is an open source framework for building, evaluating, and continuously improving LLM-based agents and multi-agent workflows. It moves beyond static pipelines by introducing a self-evolving system where agents are automatically generated, tested, and optimised through iterative feedback. Developers can define goals in natural language, while the framework handles workflow creation, execution, and refinement. Its modular architecture supports layered components for agents, workflows,...
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  • 19
    docext

    docext

    An on-premises, OCR-free unstructured data extraction

    docext is a document intelligence toolkit that uses vision-language models to extract structured information from documents such as PDFs, forms, and scanned images. The system is designed to operate entirely on-premises, allowing organizations to process sensitive documents without relying on external cloud services. Unlike traditional document processing pipelines that rely heavily on optical character recognition, docext leverages multimodal AI models capable of understanding both visual...
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  • 20
    Hephaestus

    Hephaestus

    Semi-Structured Agentic Framework. Workflows build themselves

    Hephaestus is an open-source semi-structured agentic framework designed to orchestrate multiple AI agents working together on complex tasks. Instead of relying entirely on predefined workflows, the framework allows agents to dynamically create tasks as they explore a problem space. Developers define high-level phases such as analysis, implementation, and testing, while agents generate specific subtasks within those phases. The system continuously monitors agent behavior and task progression,...
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  • 21
    LlamaDeploy

    LlamaDeploy

    Deploy your agentic worfklows to production

    llama_deploy is an open-source framework designed to simplify the deployment and productionization of agent-based AI workflows built with the LlamaIndex ecosystem. The project provides an asynchronous architecture that allows developers to deploy complex multi-agent workflows as scalable microservices. It enables teams to move from experimental prototypes to production systems with minimal changes to existing LlamaIndex code, making it easier to operationalize AI agents. The system supports...
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  • 22
    Megatron-LM

    Megatron-LM

    Ongoing research training transformer models at scale

    Megatron-LM is a GPU-optimized deep learning framework from NVIDIA designed to train extremely large transformer-based language models efficiently at scale. The repository provides both a reference training implementation and Megatron Core, a composable library of high-performance building blocks for custom large-model pipelines. It supports advanced parallelism strategies including tensor, pipeline, data, expert, and context parallelism, enabling training across massive multi-GPU and...
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  • 23
    HN Time Capsule

    HN Time Capsule

    Analyzing Hacker News discussions from a decade ago in hindsight

    HN Time Capsule is a creative and nostalgic project that captures and preserves snapshots of Hacker News content over time, providing a historical look at how topics, discussions, and popular threads have evolved. Rather than functioning like a live aggregator, it stores periodic captures of posts and comments, creating a time capsule that lets researchers, enthusiasts, and historians trace changes in sentiment, technology trends, and community priorities across different eras of the Hacker...
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  • 24
    Vibium

    Vibium

    Browser automation for AI agents and humans

    ...It integrates a single lightweight binary that manages browser lifecycle, implements a WebDriver BiDi proxy, and exposes a Model Context Protocol (MCP) server so language models or automation clients can control browser behavior without complex setup. 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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  • 25
    SimpleMem

    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...
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