17 dépôts
Database integrations for maintaining long-term memory of agent interactions.
Distinguishing note: Focuses on the persistence layer for chat history, distinct from transient in-memory buffers.
Explore 17 awesome GitHub repositories matching data & databases · Persistent Conversation Stores. Refine with filters or upvote what's useful.
Agno is an agent operating system designed to manage the lifecycle, tool execution, and persistent state of autonomous agents across distributed infrastructure. It provides a unified runtime environment that wraps diverse agent frameworks into a consistent, interoperable protocol, allowing developers to build and deploy complex multi-agent systems that coordinate tasks and delegate sub-processes. The platform distinguishes itself through a robust governance and orchestration layer that includes human-in-the-loop approval gates, role-based access control, and a centralized API gateway. It feat
AgentOS enables persistent chat memory by connecting a database to an agent or team, allowing the model to recall previous interactions.
This project is a Python framework for building autonomous, event-driven agent systems. It provides a unified runtime for orchestrating multi-agent workflows, managing persistent conversation state, and executing code within secure, isolated sandbox environments. The framework is designed to handle complex task delegation, allowing agents to invoke other agents as tools while maintaining context across multi-turn interactions. The framework distinguishes itself through its deep integration with the Model Context Protocol, enabling agents to connect to external data sources and remote services
Stores conversation logs and metadata in databases to support long-term state management.
This project is a feature-rich Go client library designed for interacting with Redis. It serves as a comprehensive interface for managing remote data stores, enabling developers to execute standard database commands, handle complex data structures, and perform asynchronous operations within Go applications. The library distinguishes itself through its support for advanced Redis capabilities, including connection pooling, pipelining, and transactional integrity. It provides specialized primitives for managing distributed clusters, including automated topology updates and request routing to sha
Stores conversational context in a remote database to maintain state across multiple user interactions within an automated agent workflow.
Mastra is an orchestration framework designed for building, deploying, and managing autonomous AI agents and multi-agent systems. It provides a comprehensive suite of primitives for creating resilient AI applications, including durable workflow orchestration, event-driven agent loops, and semantic memory management. By integrating these core components, the platform enables developers to build complex, multi-step processes that can reason about goals and execute tasks without manual intervention. The framework distinguishes itself through its focus on observability and secure, isolated execut
Persists agent conversation history to maintain context across multiple sessions.
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
Streams real-time AI responses while asynchronously persisting full interaction history.
This project is a cross-platform chatbot framework designed to integrate generative artificial intelligence models into messaging services. It provides a unified architecture for building and deploying automated bots that maintain consistent conversation state, user identity, and interaction logic across multiple messaging platforms from a single codebase. The framework distinguishes itself through a modular adapter system that normalizes platform-specific webhooks and events into a standardized internal schema. It includes a comprehensive toolkit for constructing rich, interactive user inter
Maintains persistent, cross-platform conversation history keyed by unique user identifiers.
This project is an open-source, self-hosted helpdesk system designed to centralize customer support operations. It functions as an omnichannel platform that aggregates inquiries from email, social media, and messaging services into a unified dashboard, while providing a dedicated portal for customers to track requests and access self-service documentation. The system distinguishes itself through deep integration with e-commerce platforms, allowing agents to view customer order history and profile data directly within the ticketing interface. It features a modular architecture that supports cu
Stores all customer interactions and ticket history in a relational database to ensure data integrity and long-term tracking.
Memori is an AI agent memory middleware platform designed to provide persistent, context-aware recall for language models. It functions as a non-intrusive layer that intercepts outbound model requests to automatically capture interaction history and execution traces, ensuring that agents maintain continuity across sessions without requiring modifications to existing application logic. The platform distinguishes itself through a dual-model storage architecture that maintains information as both structured relational primitives for precise fact retrieval and rolling narrative summaries for situ
Captures and stores conversation history and execution traces automatically to ensure AI agents retain context across sessions.
ChatterBot is a conversational AI framework and machine learning dialogue system used to build bots that generate automated responses. It functions as a multilingual natural language processing library and a vector-based knowledge base, utilizing logic adapters and statistical pattern matching to select the most confident response to user input. The system supports multilingual chatbot training and processing by using a design independent of specific linguistic rules. It employs semantic vector search to retrieve contextually accurate responses from a database of stored conversations and can
Uses database integrations to maintain long-term memory of agent interactions and chat history.
Chainlit is a Python framework designed for building and deploying interactive, stateful conversational AI interfaces. It provides a backend-driven platform that connects language models and agent frameworks to a web-based chat frontend, managing the complexities of session state, message history, and real-time communication. The framework distinguishes itself by offering a component-based UI builder that allows developers to inject interactive widgets, rich media, and data visualizations directly into the chat stream. It supports the visualization of complex agent workflows, enabling users t
Persists conversation history and metadata in databases to enable users to resume previous interactions.
This project is a web-based user interface for interacting with large language models, featuring streaming responses and persistent conversation history. It functions as an orchestration gateway that directs user prompts to specific language models and acts as a Model Context Protocol client to execute external tools and incorporate live data into conversations. The application includes a routing layer that analyzes input signals and tool requirements to dynamically direct messages to the most appropriate specialized model. It also provides customization settings for brand identity, allowing
Integrates a database for maintaining a persistent long-term memory of chat sessions and user preferences.
Tambo is an orchestration platform and framework designed for building generative user interfaces and conversational AI agents. It provides the infrastructure to manage persistent chat threads, execute multi-step reasoning workflows, and integrate large language models with external tools and services. By combining an agent orchestration layer with a component-based library, the project enables developers to create interactive interfaces where AI models dynamically render and update UI elements in real-time. The framework distinguishes itself through its generative UI capabilities, which allo
Persists message content and tool execution logs to a central store for session continuity.
Bytebot is an LLM desktop automation framework and virtual Linux desktop environment. It enables AI agents to plan and execute mouse and keyboard actions on a virtual computer using natural language, allowing for autonomous desktop automation and the integration of legacy systems that lack native APIs. The system operates as an LLM API gateway and a Model Context Protocol server, routing requests across multiple language model providers with integrated load balancing and rate limiting. It provides isolated, containerized environments where agents use visual reasoning to interpret screenshots
Stores task metadata and AI dialogue in a database to maintain state across sessions.
unopim is an AI-powered product information management system that serves as a centralized repository for managing product attributes, categories, and variations. It functions as a containerized product repository and a multi-channel data distributor, synchronizing consistent product information and pricing across diverse external sales platforms and marketplaces. The platform distinguishes itself through an LLM-based catalog manager that provides a conversational interface for executing data management tasks. This allows users to perform item creation, content enrichment, and quality scans u
Utilizes database integrations to maintain long-term memory of AI agent interactions and chat history.
PraisonAI is an autonomous AI agent platform that coordinates multiple LLM-powered agents for research, planning, and execution of complex workflows. It functions as a multi-agent orchestration framework, a workflow builder, and a Model Context Protocol server, while also providing retrieval-augmented generation through vector knowledge bases. Agents can interact via CLI, web, or standardized protocols with sandboxed code execution. The platform distinguishes itself with a rich set of agent communication protocols, including A2A, REST, WebSocket, voice and telephony integration, and MCP, allo
Executes queries against documents stored in a database for persistent knowledge retrieval.
Ce projet est une bibliothèque de référence et une collection d'exemples de code pratiques pour construire des extensions de navigateur utilisant les API WebExtensions. Il fournit des guides d'implémentation et des exemples fonctionnels pour les composants principaux des extensions, y compris les scripts de contenu, les processus en arrière-plan et les popups d'action du navigateur. Le dépôt se concentre sur la démonstration de modèles d'implémentation spécifiques pour la personnalisation de l'UI du navigateur et la manipulation des pages web. Il inclut des exemples pour créer des barres latérales, des menus contextuels et des pages d'options, ainsi que des techniques pour injecter des scripts et des styles afin d'altérer les éléments du DOM et l'apparence des pages. Le projet couvre un large éventail de capacités, y compris la communication inter-processus via des ponts de messagerie, l'interception et la modification de requêtes réseau, et la gestion des onglets, de l'historique et des favoris du navigateur. Il fournit également des exemples pour la persistance d'état via le stockage local, la vérification d'identité utilisant OAuth2 et l'intégration de panneaux personnalisés dans les outils de développement du navigateur.
Saves binary data as blobs specifically within IndexedDB to persist files across browser sessions.
Mods is a terminal-based AI client that sends prompts to large language models and streams responses back to the command line. It functions as a multi-provider AI gateway, routing queries to OpenAI, Cohere, Groq, Gemini, and local endpoints, and includes a conversation history manager that saves, caches, branches, and resumes text-based interactions. The tool also operates as a Model Context Protocol client, connecting to external MCP servers via stdio, SSE, or HTTP to extend model capabilities with specialized tools and data. The project distinguishes itself through a config-driven provider
Persists multi-turn conversation state as local JSON files keyed by SHA-1 hash, enabling save, resume, and branching of dialogues.