DA
DataWeave AI
v1.4RAG Platform
StatusBETAEnvproductionUpdated5 months ago
About the Project
A full-stack RAG application that lets users chat with PDFs using LangChain agents, vector search, and OpenRouter LLMs. Answers are grounded in the source documents with inline citations, table reasoning, and authenticated, persistent chat history.
Problem
Long PDFs hide answers. Plain LLM chat hallucinates and can't point to where an answer came from.
Why I built it
Built to make document Q&A trustworthy: retrieve the right chunks, reason over tables, and always cite the source.
Key Features
- Chat with any PDF
- Cited responses
- LangChain agents
- Vector search
- Table reasoning
- Multi-document chat
ClientServiceDataExternal
Key Outcomes
- Cited answers users can verify against the original document
- Table-aware reasoning, not just plain-text extraction
- Authenticated chat history persisted across sessions
Repository Signals
Mock · GitHub not connectedStars
96
Forks
14
Commits
412
Contributors
2
Watchers
11
Open Issues
5
Languages
- TypeScript 71%
- Python 21%
- CSS 8%
Recent Activity
pushed 3 months ago
Tech Stack
Next.jsLangChainOpenRouterMongoDBVector Search