围绕 GPT-6 Astra 搭 Agent 系统的 20 个 GitHub 仓库
按编排、记忆、工具、执行四类列出 LangGraph、Mem0、Composio、E2B 等 20 个仓库，主张 Astra 配上外部系统才真正好用。
GPT-6 Astra gets much more useful when you build the right system around it. 20 GitHub repos for giving an agent memory, tools, execution, observability and recovery. BUILD THE BRAIN 1. LangGraph agent orchestration and stateful workflows. `https://github.com/langchain-ai/langgraph` 2. PydanticAI typed agent workflows in Python. `https://github.com/pydantic/pydantic-ai` 3. CrewAI multi-agent teams with defined roles. `https://github.com/crewAIInc/crewAI` 4. AutoGen framework for multi-agent collaboration. `https://github.com/microsoft/autogen` 5. smolagents agents that can reason and act through code. `https://github.com/huggingface/smolagents` GIVE IT MEMORY 6. Mem0 persistent memory for AI agents. `https://github.com/mem0ai/mem0` 7. Graphiti temporal knowledge graphs for changing information. `https://github.com/getzep/graphiti` 8. Cognee turns data into structured knowledge and memory. `https://github.com/topoteretes/cognee` 9. Letta stateful agents that remember across sessions. `https://github.com/letta-ai/letta` GIVE IT HANDS 10. Composio 1,000+ toolkits for agent actions. `https://github.com/ComposioHQ/composio` 11. MCP Servers connect agents to external tools and services. `https://github.com/modelcontextprotocol/servers` 12. Browser Use let agents operate websites. `https://github.com/browser-use/browser-use` 13. Playwright MCP browser automation through MCP. `https://github.com/microsoft/playwright-mcp` LET IT EXECUTE 14. E2B isolated sandboxes for running agent code. `https://github.com/e2b-dev/E2B` 15. OpenHands autonomous software engineering agents. `https://github.com/All-Hands-AI/OpenHands` 16. Daytona infrastructure for running AI-generated code. `https://github.com/daytonaio/daytona` MAKE IT SURVIVE 17. AgentOps tracing, debugging and cost monitoring. `https://github.com/AgentOps-AI/agentops` 18. Langfuse traces, evals and observability. `https://github.com/langfuse/langfuse` 19. BrowserGym environments for testing browser agents. `https://github.com/ServiceNow/BrowserGym` 20. DeepEval test agent behavior before trusting it. `https://github.com/confident-ai/deepeval` the architecture: Astra → context → memory → plan → tools → sandbox → execute → observe → evaluate → recover → continue 4 stacks worth testing: coding: Astra → LangGraph → Composio → E2B → OpenHands research: Astra → Graphiti → Browser Use → Playwright MCP persistent agent: Astra → Letta → Mem0 → Cognee → Composio production: Astra → PydanticAI → Daytona → Langfuse → DeepEval the model is only one part. the real leverage is the system you build around it.