(WIP)Feat(benchmark): Add benchmark/RAG : RAG system evaluation framework

[sponge225]

Description

RAG benchmark

RAG benchmark 是一个用于评测 Openviking 的 RAG (检索增强生成) 系统性能的框架，支持多个数据集和多种评测指标。

RAG benchmark is a framework for evaluating Openviking‘s RAG (Retrieval-Augmented Generation) system performance, supporting multiple datasets and metrics.

Features

• 支持 Locomo、FinanceBench、Qasper、SyllabusQA 数据集 / Supports Locomo, FinanceBench, Qasper, SyllabusQA datasets
• 完整的评测流程：数据准备 → 向量检索 → LLM 生成 → 自动评分 / Complete evaluation pipeline: data preparation → vector retrieval → LLM generation → auto-grading
• 评测指标：Recall、F1 Score、Accuracy / Recall, F1 Score, Accuracy
• 灵活的 YAML 配置 / Flexible YAML configuration
• 可扩展设计 / Extensible design

详细文档请查看 benchmark/RAG/README.md。
See benchmark/RAG/README.md for detailed documentation.

Related Issue

Summary

This PR adds the RAG benchmark framework.

Closes #885

Type of Change

• Bug fix (non-breaking change that fixes an issue)
• New feature (non-breaking change that adds functionality)
• Breaking change (fix or feature that would cause existing functionality to not work as expected)
• Documentation update
• Refactoring (no functional changes)
• Performance improvement
• Test update

Changes Made

Testing

• I have added tests that prove my fix is effective or that my feature works
• New and existing unit tests pass locally with my changes
• I have tested this on the following platforms:
  • Linux
  • macOS
  • Windows

Checklist

• My code follows the project's coding style
• I have performed a self-review of my code
• I have commented my code, particularly in hard-to-understand areas
• I have made corresponding changes to the documentation
• My changes generate no new warnings
• Any dependent changes have been merged and published

Screenshots (if applicable)

Additional Notes

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[github-actions]

Failed to generate code suggestions for PR

[qin-ctx]

中文 review 摘要：这个 PR 引入了一个独立的 RAG benchmark 框架，模块拆分整体合理，README 和数据集支持范围也比较完整。但当前有 3 个阻断性的运行问题：1) 默认配置文件 config/config.yaml 的结构和运行时代码不一致，默认入口会直接因为缺少 execution 节点而失败；2) sample_locomo() 在 num_docs + sample_size + random 路径里把 dict 放进 set，会直接抛出 TypeError: unhashable type: 'dict'；3) sample_locomo() 在纯 stratified 路径里把 int 和 list 相加，也会直接报错。因为这些问题都落在 README 主流程覆盖到的入口上，我这边先请求修改。