a2aproject / a2aproject/a2a-samples
Proposal: Evidence Bench evidence-gated computational-science A2A sample
- 主要言語
- Jupyter Notebook
- スター
- 1.8k
- フォーク
- 751
- PR マージ指標
- 30日以内にマージされた PR はありません
説明
## Proposal
I would like to contribute Evidence Bench as a computational-science A2A ecosystem sample:
- source: https://github.com/kstawiski/evidence-gated-scientific-agent
- first public release: https://github.com/kstawiski/evidence-gated-scientific-agent/releases/tag/v0.3.0
- license: Apache-2.0
- SDK/protocol: official `a2a-sdk[fastapi]` 1.1.0, Agent Card advertising A2A 1.0 JSON-RPC
Evidence Bench demonstrates an evidence-gated scientific agent rather than a generic chat agent. Qwen performs planning, retrieval, and sandboxed Python/R analysis; Gemma independently audits methods and results; deterministic code validates tool policy, artifacts, claims, and provenance. The service supports isolated persistent workspaces, raw A2A file parts, bearer-authenticated task execution, MCP retrieval tools, immutable per-workspace PyPI/CRAN/Bioconductor environments, and report/provenance artifacts.
## Interoperability evidence
- repository A2A API tests pass in public CI;
- a deployed authenticated `SendMessage` task passed all 9 retrieval-grounding checks, including official SciPy/R sources, observed-URL enforcement, deterministic validation, and independent review;
- the Agent Card and JSON-RPC semantics are documented at https://github.com/kstawiski/evidence-gated-scientific-agent/blob/v0.3.0/docs/WEB_AND_A2A.md;
- the proposed contribution dossier is at https://github.com/kstawiski/evidence-gated-scientific-agent/blob/v0.3.0/docs/A2A_ECOSYSTEM_SUBMISSION.md.
Before preparing a significant PR, could maintainers advise which shape is preferred?
1. a small in-tree integration/sample that delegates to a running Evidence Bench instance; or
2. an external ecosystem/example entry linking to the full repository.
I am happy to reduce the contribution to the smallest useful A2A-specific example and follow the repository's test and documentation conventions.
コントリビューションガイド
調査の方向性
Review the linked repository and its documentation to understand the Evidence Bench system and its A2A integration. Examine the existing samples in the a2a-samples repository to see the format for ecosystem entries. Determine whether to create a minimal in-tree sample or an external link, then prepare the contribution following the repository's conventions.
索引モデルが issue の本文から書いたものです。
評価
- 技術スタック
- fastapi, jupyter-notebook, python
- 領域
- ai-infra-agents, backend-api-design, documentation
- issue の種類
- 機能追加
- 難易度
- 4/5
- 見積もり時間
- 3〜5日
- 活発さ
- 静か
- 明瞭さ
- おおむね明確
- 初心者へのやさしさ
- 45/100