70 रिपॉजिटरी
Tracking task progress and state in external files to allow agents to resume work across sessions.
Distinct from Stateful Session Persistence: Distinct from Stateful Session Persistence: focuses on file-based agent state persistence rather than browser context.
Explore 70 awesome GitHub repositories matching security & cryptography · Agentic Session Persistence. Refine with filters or upvote what's useful.
gstack is an AI agent framework and development workflow system designed to automate the software development lifecycle. It coordinates specialized AI personas to manage tasks across product design, engineering management, and quality assurance, transforming product intent into technical specifications and final releases. The project is distinguished by its deep integration of headless browser automation and semantic code memory. It utilizes a persistent Chromium daemon for web scraping and visual auditing, and implements a searchable knowledge base that logs architectural decisions and repos
Implements file-based persistence of agent task progress and state to allow work resumption across different sessions.
OpenHands is an autonomous AI software engineer and coding assistant designed to execute software engineering tasks by interacting directly with codebases and development environments. It functions as a platform for running AI agents that can write code and manage files to automate complex development workflows. The system distinguishes itself through a container-based execution environment that isolates agent actions within a sandboxed Linux environment. It employs an autonomous agent loop of observation, planning, and action, supported by a standardized communication protocol that allows it
Maintains interaction history and task state to allow agents to resume long-running development sessions.
Pi-mono is an autonomous coding agent orchestrator designed to coordinate multiple intelligent agents for complex software development tasks. It functions as a framework that integrates directly with local file systems and terminal environments to automate development workflows. The system distinguishes itself through a stateful session manager that serializes the entire context of a coding interaction to disk, allowing agents to maintain project awareness across separate sessions. It utilizes a plugin architecture for tool registration and prompt-template injection, enabling the integration
Serializes development interaction context to disk, allowing agents to maintain project awareness and resume tasks across separate sessions.
Goose is an autonomous coding assistant and extensible AI agent framework designed to automate software development workflows. It functions as an orchestration engine that can install, execute, and test code, as well as manage local files and shell commands. The platform is model-agnostic, providing a flexible interface to connect with diverse cloud-based or self-hosted large language model providers. It distinguishes itself through a standardized context protocol for integrating external tools and extensions, and a recipe system that allows users to define and repeat complex, multi-step AI w
Loads specialized data and tools into active sessions to provide the agent with necessary contextual knowledge.
CodeWhale is an AI coding agent orchestrator and development harness designed to coordinate autonomous agents that read, edit, and verify code. It provides a secure environment for AI agents to perform multi-step software engineering tasks, utilizing a sandboxed execution model to isolate shell commands and protect the host system. The system distinguishes itself by spawning multiple independent agents in parallel to handle separate investigation or implementation slices simultaneously. It employs a multi-model gateway to route requests across various cloud APIs and local servers, and utilize
Saves agent contexts and tool call sequences to disk to enable resuming long-running tasks after restarts.
HTTPie is a command-line HTTP client and REST API debugger used for sending requests to web services. It functions as a network tool for managing headers, authentication sessions, and file uploads, with a specific focus on the transmission and reception of JSON data. The tool utilizes a custom parsing layer to translate simplified command-line input into structured HTTP parameters. It provides ANSI-based terminal formatting to apply color and structural indentation to raw responses, improving human readability for web debugging. The project covers request construction and previewing, multipa
Persists session information and authentication cookies across multiple requests to maintain state.
Nanoclaw is an LLM agent orchestrator and multi-platform chat gateway designed to deploy and manage isolated AI agents. It provides a containerized runtime that executes agents within sandboxed Linux containers, ensuring filesystem and state isolation through dedicated workspaces and host bind-mounts. The project distinguishes itself through a unified routing pipeline that connects agents to diverse messaging platforms, including WhatsApp, Discord, Slack, Telegram, Signal, and iMessage. It integrates the Model Context Protocol to extend agent capabilities via managed external data and functio
Preserves agent memory and conversation state across restarts by mapping internal container directories to host storage.
DeepSeek-Reasonix is an autonomous software engineering framework and terminal-based AI IDE designed to coordinate large language models for complex programming tasks. It functions as a multi-session agent that utilizes a split planner and executor workflow to break down and implement technical objectives. The system distinguishes itself through a specialized focus on session optimization and extensibility. It employs prefix caching and append-only history to reduce token consumption and latency during long sessions. It further extends its capabilities by integrating external tool servers via
Tracks task progress in external files to allow AI agents to resume work across sessions.
MemGPT is a memory management framework and external memory layer for large language models. It functions as a platform for building stateful AI agents that maintain a persistent identity and continuous context across multiple sessions. The system enables agents to bypass fixed context window limitations by using a virtual context windowing approach. This allows models to manage their own memory through internal commands to search, update, and delete stored information within a hierarchical structure of short-term working context and long-term archival storage. The framework provides a local
Saves agent memory states to a database to allow continuous learning across separate user sessions.
Flow is an orchestration framework for designing and executing complex workflows using autonomous agents powered by large language models. It serves as a toolkit for constructing agentic pipelines and a runtime for managing agent lifecycles, session states, and tool execution. The project is distinguished by its support for hierarchical swarm management, where director agents decompose large projects into smaller tasks for specialized worker agents. It enables multiple coordination patterns, including sequential linear pipelines and concurrent execution where agents analyze tasks from differe
Manages the initialization and reset of environment variables and memory for each isolated agentic session.
Letta is a framework for building, deploying, and managing autonomous AI agents that maintain persistent state across long-term interactions. It provides a comprehensive suite of primitives for defining agents with configurable personas, modular memory blocks, and tool-use capabilities, enabling them to retain user preferences and conversation history over extended sessions. The platform distinguishes itself through its advanced memory management and orchestration capabilities. It allows agents to autonomously update their own memory, perform retrieval-augmented generation, and coordinate com
Decouples agent execution from client connections to support resumable streams and long-running tasks.
Claude Code is a command-line interface and multi-agent orchestration framework designed for autonomous software engineering. It enables AI agents to perform codebase modifications, debugging, and Git workflow management while coordinating multiple specialized agents to decompose and execute complex engineering tasks in parallel. The system distinguishes itself through a high degree of isolation and safety, utilizing Git worktrees to create independent working directories for concurrent agents and implementing a tiered permission system that combines user rules, project policies, and OS-level
Serializes conversation transcripts and codebase snapshots to disk to allow resuming work across sessions.
PUA is an agentic workflow orchestrator and behavioral governance tool designed to enhance the reliability and autonomy of AI coding assistants. It functions as a prompting framework and extension that implements strict engineering standards and verification requirements to prevent hallucinations and premature task completion. The project distinguishes itself through high-agency enforcement mechanisms, including escalating prompt pressure and failure-driven recovery loops that automatically pivot problem-solving strategies after repeated errors. It utilizes a diagnosis-first workflow that man
Implements long-term tracking of error counts and lessons learned in external files to prevent repeat mistakes across agent sessions.
This project provides a system for managing agent context and session memory, featuring an agent context compactor, an AI session memory manager, and a tool output sandbox. It functions as a middleware layer and server extension for the Model Context Protocol to optimize context windows and reduce token usage. The system optimizes agent performance by sandboxing tool outputs and externalizing large data sets, replacing raw I/O with pointers and concise summaries. It employs a persistent knowledge base that indexes session history and tool outputs for retrieval via full-text search, ensuring s
Tracks agent task progress and state in a database to maintain continuity across context compaction events.
Claude Quickstarts is a development framework and collection of reference implementations designed for building autonomous agents. It provides the foundational patterns necessary to orchestrate multi-agent workflows, enabling models to perform complex, multi-step tasks across software engineering, customer support, and computer-use domains. The platform distinguishes itself through specialized capabilities for desktop and browser automation, allowing agents to interact with graphical interfaces by capturing visual context and executing precise mouse and keyboard inputs. It includes robust inf
Tracks task progress and state in external files to allow agents to resume work across multiple execution sessions.
Kilocode is an autonomous engineering platform designed to orchestrate AI agents for complex software development tasks. It functions as a comprehensive system for automating coding, testing, and repository management by integrating directly with your codebase and terminal. The platform provides a unified gateway for model orchestration, allowing for the management of agentic workflows, event-driven automation, and persistent session state across distributed development environments. The platform distinguishes itself through its federated task management and policy-based access control, which
Captures and resumes development context, including terminal history and file snapshots, to maintain continuity across sessions.
ds4 is a local inference engine for DeepSeek models that includes a distributed runtime for splitting transformer layers across networked computers. It functions as a reasoning controller with a local weight streamer and an API server that streams chat completions via industry standard endpoints. The system employs a memory management model that loads model experts from disk on demand to execute models that exceed available system RAM. It provides controls for reasoning effort and model behavior steering, allowing the modification of response characteristics through activation directions. Th
Saves interactive session data to disk to allow resuming tasks without repeating the initial prompt prefill.
Data Formulator is an automated data analysis and visualization platform that uses large language models to interpret natural language instructions for data preparation and reporting. It functions as an interactive workbench where users can clean, filter, and aggregate datasets while simultaneously generating visual representations. By combining conversational interfaces with automated transformation tools, the system enables users to explore data patterns and refine schemas without manual coding. The platform distinguishes itself through an agentic architecture that translates natural langua
Saves workspaces and analysis threads across restarts to help users revisit, compare, and continue previous data exploration tasks.
Sampler is a shell command monitoring tool and terminal-based metrics dashboard. It functions as a YAML-configured shell orchestrator that executes commands at set intervals to collect data and monitor system metrics. The tool distinguishes itself by rendering real-time shell output as terminal widgets, such as sparklines, gauges, bar charts, and run charts. It also includes a conditional alerting system that triggers audio notifications, visual alerts, or secondary shell commands when sampled output matches predefined data conditions. The project covers broad capability areas including shel
Supports the maintenance of active shell sessions using specific initialization commands to reduce reconnection overhead.
DeepCode is an agentic development framework designed to orchestrate autonomous AI agents for software engineering tasks. It functions as a multi-agent workflow orchestrator that translates natural language requirements into functional codebases by coordinating specialized agents for architectural planning, intent analysis, and implementation. The platform integrates multiple language models to power these automated routines, providing a unified environment for complex development projects. The system distinguishes itself through its ability to transform academic research papers into executab
Organizes concurrent coding tasks and maintains state through persistent session management for autonomous agents.