Search Results for "python-gtksourceview2" - Page 5
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Showing 213 open source projects for "python-gtksourceview2"
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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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Potpie
Create custom engineering agents for your codebase
Potpie is an AI-powered data analysis tool that automates the exploration and visualization of datasets, assisting users in uncovering insights without extensive coding. -
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Parlant
The behavior guidance framework for customer-facing LLM agents
Parlant is a lightweight speech-to-text and text-to-speech framework designed for real-time AI-driven voice applications. -
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Nerve
The Simple Agent Development Kit
Nerve is a developer-friendly Agent Development Kit (ADK) that utilizes YAML and a CLI to define, run, orchestrate, and evaluate LLM-driven agents. It supports declarative setups, tool integration, workflow pipelines, and both MCP client and server roles. Nerve is a simple yet powerful Agent Development Kit (ADK) to build, run, evaluate, and orchestrate LLM-based agents using just YAML and a CLI. It’s designed for technical users who want programmable, auditable, and reproducible automation... -
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TapeAgents
A framework that facilitates all stages of LLM development
TapeAgents is a framework that facilitates all stages of the Large Language Model (LLM) agent development lifecycle, providing tools for building, testing, and deploying AI agents. -
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GPT All Star
AI-powered code generation tool for scratch development of web apps
AI-powered code generation tool for scratch development of web applications with a team collaboration of autonomous AI agents. This is a research project, and its primary value is to explore the possibility of autonomous AI agents. -
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AI Agent Book
Deep Understanding AI Agents
AI Agent Book is an open educational repository for Understanding AI Agents: Design Principles and Engineering Practice. It explains agents through the formula of a language model combined with context and tools. Ten chapters move from core concepts to context engineering, memory, RAG, knowledge graphs, MCP tools, and coding agents. Later material covers evaluation, supervised fine-tuning, reinforcement learning, self-improvement, multimodal interaction, robotics, and multi-agent... -
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Keep Codex Fast
A backup-first Codex skill for keeping local Codex state fast
Keep Codex Fast is a backup-first Codex skill for keeping local Codex state clean, fast, and recoverable after heavy use. It is designed for users whose Codex environment has accumulated long chats, logs, worktrees, project history, and local metadata over time. The project emphasizes inspection before action, so its default mode reports what has grown without changing files. When applied manually, it backs up first, archives old sessions, rotates large logs, moves stale worktrees, and... -
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Cheat on Content
Workflow that turns every post into a calibrated experiment
Cheat on Content is an AI-assisted workflow for creators who want to make content performance measurable instead of relying on instinct alone. It turns every post into a structured experiment by asking creators to score ideas, make blind predictions, publish, review results after a defined time window, and evolve their own content rubric. Rather than generating posts for the creator, it focuses on sharpening judgment and helping users understand why certain content performs better. The... -
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AutoAgent AI
Autonomous harness engineering
AutoAgent is an experimental AI framework focused on autonomous agent engineering, where a meta-agent iteratively improves another agent’s architecture without direct human intervention. Instead of manually tuning prompts or workflows, developers define high-level goals in a configuration file, and the system continuously modifies its own tools, orchestration, and logic based on benchmark performance. It operates through a loop of testing, analyzing failures, and refining the agent’s... -
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OpenHarness
Open Agent Harness with a built-in personal agent, Ohmo
OpenHarness is an open-source framework developed to support large-scale machine learning workflows, particularly in the context of training, evaluating, and benchmarking AI models. It provides a structured environment for orchestrating experiments, managing datasets, and standardizing evaluation processes across different models. The project focuses on reproducibility and scalability, allowing researchers and engineers to run consistent experiments while tracking results effectively. It... -
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OpenSpace
OpenSpace: Make Your Agents: Smarter, Low-Cost, Self-Evolving
OpenSpace is a self-evolving agent framework designed to improve the performance, efficiency, and collaboration of AI agents through continuous learning and shared knowledge. It introduces a system where agents develop reusable “skills” based on real task execution, allowing them to improve over time without retraining underlying models. The platform emphasizes collective intelligence, enabling multiple agents to share learned behaviors and benefit from each other’s experiences. It also... -
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GPT Researcher
LLM based autonomous agent that does online comprehensive research
Say Hello to GPT Researcher, your AI agent for rapid insights and comprehensive research. GPT Researcher is the leading autonomous agent that takes care of everything from accurate source gathering to organization of research results. -
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CAMEL AI
Finding the Scaling Law of Agents. A multi-agent framework
The rapid advancement of conversational and chat-based language models has led to remarkable progress in complex task-solving. However, their success heavily relies on human input to guide the conversation, which can be challenging and time-consuming. This paper explores the potential of building scalable techniques to facilitate autonomous cooperation among communicative agents and provide insight into their "cognitive" processes. To address the challenges of achieving autonomous... -
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cognee
Deterministic LLMs Outputs for AI Applications and AI Agents
Cognee implements scalable, modular data pipelines that allow for creating the LLM-enriched data layer using graph and vector stores. Cognee acts a semantic memory layer, unveiling hidden connections within your data and infusing it with your company's language and principles. This self-optimizing process ensures ultra-relevant, personalized, and contextually aware LLM retrievals. Any kind of data works; unstructured text or raw media files, PDFs, tables, presentations, JSON files, and so... -
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Griptape
Python framework for AI workflows and pipelines with chain of thought
The Griptape framework provides developers with the ability to create AI systems that operate across two dimensions: predictability and creativity. For predictability, Griptape enforces structures like sequential pipelines, DAG-based workflows, and long-term memory. To facilitate creativity, Griptape safely prompts LLMs with tools (keeping output data off prompt by using short-term memory), which connects them to external APIs and data stores. The framework allows developers to transition... -
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Haystack
Haystack is an open source NLP framework to interact with your data
Apply the latest NLP technology to your own data with the use of Haystack's pipeline architecture. Implement production-ready semantic search, question answering, summarization and document ranking for a wide range of NLP applications. Evaluate components and fine-tune models. Ask questions in natural language and find granular answers in your documents using the latest QA models with the help of Haystack pipelines. Perform semantic search and retrieve ranked documents according to meaning,... -
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AgentENV
Distributed platform for running agent environments at scale
...The platform includes an aenv command-line interface for creating templates, starting shells, executing commands, and managing sandbox lifecycles. Its E2B-compatible HTTP API lets existing Python and TypeScript integrations target a self-hosted deployment with minimal changes. AgentENV is designed for high-density agentic reinforcement learning and currently requires trusted-network deployment because built-in authorization is not yet available. -
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Agent Stack
Deploy and share agents with open infrastructure
Agent Stack is an open infrastructure platform designed to take AI agents from prototype to production, no matter how they were built. It includes a runtime environment, multi-tenant web UI, catalog of agents, and deployment flow that seeks to remove vendor lock-in and provide greater autonomy. Under the hood it’s built on the “Agent2Agent” (A2A) protocol, enabling interoperability between different agent ecosystems, runtime services, and frameworks. The platform supports agents built in... -
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Cangjie Skill
Distill high-value content like books, long videos, podcasts, and more
cangjie-skill is a workflow for converting books and other long-form knowledge into executable AI skill packs. Its goal is structured reuse rather than producing another summary or set of reading notes. The seven-stage RIA-TV++ pipeline analyzes the full source, extracts candidate frameworks, verifies them, constructs skill modules, links related ideas, pressure-tests behavior, and prepares delivery files. Each accepted skill records supporting material, a reconstructed explanation,... -
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ComfyUI-WanVideoWrapper
ComfyUI wrapper nodes for WanVideo and related models
The ComfyUI-WanVideoWrapper project is a custom node extension for ComfyUI that enables advanced video generation workflows using WanVideo diffusion models. It acts as a standalone wrapper layer that allows developers and creators to integrate experimental features and models without modifying the core ComfyUI codebase. This design makes it easier to rapidly test new capabilities such as text-to-video and image-to-video generation while avoiding compatibility issues with the main framework.... -
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Claude Code Plugins
Intelligent automation and multi-agent orchestration for Claude Code
Claude Code Plugins is a lightweight framework designed to define, manage, and execute AI agents in a modular and extensible way, typically focusing on orchestrating tasks using large language models and tool integrations. The project provides abstractions for building agents that can interpret instructions, execute commands, and interact with external systems in a structured workflow. It emphasizes simplicity and composability, allowing developers to define agent behaviors through reusable... -
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MineContext
MineContext is your proactive context-aware AI partner
MineContext is an open-source, proactive AI assistant designed to capture, understand, and leverage a user’s digital context in order to provide meaningful insights, summaries, and productivity support. The system continuously collects contextual data from sources such as screenshots and user activity, then processes and organizes this information into structured knowledge that can be reused later. Unlike traditional chat-based assistants, MineContext operates in the background and delivers... -
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CowAgent
AI assistant based on large models that can actively think and plan
CowAgent, based on the chatgpt-on-wechat project, is an open-source AI agent framework that integrates large language models into the WeChat ecosystem to create intelligent conversational assistants. It enables automated message handling by connecting WeChat accounts with AI models that can generate contextual replies, process voice messages, and produce images directly inside chats. The platform has evolved beyond a simple chatbot into a more autonomous agent capable of planning complex... -
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mcp-use
A solution to build and deploy MCP agents and applications
...It simplifies authentication, access control, audit logging, observability, sandboxed runtime environments, and deployment workflows, whether self-hosted or managed, making MCP development production-ready. With integrations for popular frameworks like LangChain (Python) and LangChain.js (TypeScript), mcp-use accelerates the creation of tool-enabled AI agents. -
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Magentic UI
A research prototype of a human-centered web agent
Magentic-UI is a research prototype developed by Microsoft that serves as a human-centered interface powered by a multi-agent system. It enables users to automate complex web tasks, such as browsing, form filling, and data analysis, while maintaining control over the process. The system emphasizes transparency and user involvement, making it suitable for tasks requiring both automation and human oversight.
