Agentes de IA
zep
Examples and integrations for Zep — the memory layer for AI agents.
★ 5,0 mil estrelasApache-2.0
Ver o guia →memvid é um projeto de agentes de IA de código aberto de memvid (memvid/memvid no GitHub). Tem 16.584 estrelas no GitHub e 1.421 forks, é publicado sob a licença Apache-2.0 e foi atualizado pela última vez no GitHub em 14 de julho de 2026.
A serverless, single-file memory layer for AI agents - replace complex RAG pipelines
Use the Rust core directly, or the Python, Node or CLI packages.
Add memvid-core to a Rust project, or install the SDK for your language.
Create a .mv2 file and put your first documents into it with metadata.
Run a semantic search and hand the results to your agent as context.
Your whole knowledge base lives in one portable .mv2 file - no server to deploy or manage.
Combines vector similarity search (HNSW with local ONNX embeddings) and BM25 full-text search.
Feature flags add PDF text extraction and repair, CLIP image search and Whisper audio transcription.
Natural-language date parsing understands expressions like 'last Tuesday' in searches.
Optional password-based encryption produces .mv2e memory files.
Rust core with Python, Node.js and CLI packages sharing the same format.
Get the source code from GitHub and enter the project directory.
git clone https://github.com/memvid/memvid.git
cd memvidAdd memvid-core to your Cargo project (feature flags enable lex, vec and more).
cargo add memvid-coreInstall the Python SDK and create your first memory file per the docs.
pip install memvid-sdkIt is maintained by the Memvid project (memvid) on GitHub.
Yes - Memvid is Apache-2.0 licensed and free to use.
No key is required for local embeddings and search; an optional api_embed feature can use cloud embeddings (for example OpenAI) if you choose it.
Compared with a hosted vector database, Memvid is an embedded single file - zero operations and offline-first - in exchange for single-node scale.
Run cargo add memvid-core (or pip install memvid-sdk), create a .mv2 file, put a document in, and search it.
Examples and integrations for Zep — the memory layer for AI agents.
M-flow is a bio-inspired cognitive memory engine for AI agents — a graph alternative to flat RAG
The open-source memory layer for autonomous agents — knowledge-graph memory that emulates human memory
Persistent memory layer for AI agents, backed by Markdown and Milvus.
Management console for installing and monitoring AI agents and pipelines.
Context layer so AI agents query your analytics databases accurately.
Os outros projetos de Agentes de IA com mais estrelas no catálogo do LibreAI — a lista realista de alternativas se memvid não for o ideal para você.
A personal AI that really does things — on any OS, with your data staying yours.
An agentic skills framework & software development methodology that works.
Agent harness optimization system with skills, memory and security for Claude Code, Codex and more
The agent that grows with you — a Python framework for adaptive AI agents.
DeepSeek's plugin-based agent harness where everything is a plugin.
Projetos de Agentes de IA próximos no catálogo, os mais próximos em estrelas de memvid: continue explorando dos dois lados dele.
AI 时代的伯克希尔：基于 Claude Code / Codex 的价值投资研究框架。巴菲特·芒格·段永平·李录四大师方法论 + 多Agent并行研究。| AI-era Berkshire: a value investing research framework built for Claude Code /…
Python SDK for Agent AI Observability, Monitoring and Evaluation Framework. Includes features like agent, llm and tools tracing, debugging multi-agentic syst…
Google's MCP Toolbox for Databases - give agents safe, structured access to your data
Open Source framework for voice agents, multimodal apps, and realtime AI. Maintained by Daily and the community
Vector search plus structured filtering in one database.
Supercharge LLM app evaluations with objective metrics, synthetic test data and feedback loops.
Grátis e aberto: pegue o código-fonte, dê uma estrela no repositório e comece a criar.