a2aproject / a2aproject/a2a-samples
Add Langflow Sample Agent implementation to Python Sample Agents.
- 主要语言
- Jupyter Notebook
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- PR 合并指标
- 30 天内没有已合并 PR
描述
### Is your feature request related to a problem? Please describe.
The current A2A samples repository lacks an example using [Langflow](https://www.langflow.org/), a popular low-code AI builder. Is there any further plans on adding support to the same. If not then I would like to contribute.
### Describe the solution you'd like
Add a Langflow-based sample agent that demonstrates:
- A2A protocol integration with visual flow-based agents
- Agent Card implementation for discovery
### Describe alternatives you've considered
While existing Python samples demonstrate traditional coding approaches, but I haven't come across any visual or low-code alternatives comparable to LangFlow that offer a similar level of functionality or ease of use.
### Additional context
Langflow's visual interface and Python extensibility make it ideal for demonstrating A2A protocol versatility. This would complement existing samples and provide an accessible entry point for developers preferring visual development tools.
### Technical Requirements
- Langflow flow configuration file
- A2A protocol compliance
- Integration with Langflow's tool system
- Clear documentation and setup instructions
### Additional
- Other than the CLA is there any other documentations that I need to take into account before contributing.
### Code of Conduct
- [x] I agree to follow this project's Code of Conduct
贡献指南
调研方向
Look at existing Python sample agents in the repository to understand the A2A protocol integration and Agent Card pattern. The new agent will need a Langflow flow configuration file and must integrate with Langflow's tool system. Review the repository's documentation for contribution guidelines and setup instructions. Success means a working sample that demonstrates visual flow-based agents and is compliant with the A2A protocol.
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评估
- 技术栈
- python
- 领域
- ai-infra-agents, tooling
- Issue 类型
- 功能
- 难度
- 3/5
- 预计耗时
- 1-2 天
- 活跃度
- 停滞
- 描述清晰度
- 基本清楚
- 新手友好度
- 50/100