返回案例页
检索问答试玩沙盒

多模态文档 RAG 平台

围绕 PDF 解析、向量检索和文档问答构建的多模态 RAG 系统,强调上传、检索和对话的一体化体验。

一个带引导的试玩页,让访问者亲自体验文档选择、检索片段查看和有依据问答这条多模态 RAG 流程。

ReactFastAPILangChainMilvusRAG
多模态文档 RAG 平台

本地版本说明

这个本地沙盒重点展示最能打动招聘方的信号:检索证据可见化。相比直接开放无限制上传接口,它更适合作品集演示。

Interactive Preview

Explore the retrieval workflow

This sandbox walks through the product flow that matters most in a document RAG system: choosing a document, inspecting retrieved chunks, and watching the grounded answer stay tied to explicit evidence.

Sample document library

Grounded question

PDF + charts

Parse + chunk

Normalize mixed-layout PDF content into searchable text blocks.

Retrieve context

Expose the exact chunks that will ground the final answer.

Generate answer

Compose a cited response from retrieved evidence instead of hallucinated recall.

Retrieval inspector

Retrieved chunks

0/3
Run the preview to reveal the exact chunks used to answer the question.

Grounded answer

Response with citations

Waiting
retrieval grounded

Choose a sample document, keep the question visible, and run the preview to watch retrieval and answer generation unfold step by step.

Sandbox telemetry

Product flow checkpoints

Mixed-layout document intake
Retrieval chunk visibility
Answer grounded by cited context

Activity log

The sandbox log will show how the document moves from upload to retrieval-backed answer generation.

建议体验

切换不同结构的样例文档,并更换问题提示词。

运行预览,观察系统先检索到了哪些片段。

对照检索证据和最终带引用的回答是否一致。

这个试玩能说明什么

你理解的不只是“向量聊天”,而是更完整的文档智能流程。

你能把检索质量以用户可见的方式展现出来,而不是藏在后端里。

你会把多模态 RAG 讲成产品工作流,而不只是后端技术栈。

展示重点

文档进入、检索查看和有依据问答

交互亮点

先看检索片段,再看最终回答

最强信号

文档智能产品设计和可部署架构意识