1. Upload and extract text
The system accepts files such as PDF, Word, or text documents and extracts readable content.
2. Split into chunks
Large documents are split into smaller searchable blocks so retrieval becomes accurate.
3. Store embeddings
Each chunk is converted into embeddings and stored in a vector database.
4. Retrieve and answer
When a user asks a question, relevant chunks are retrieved and passed to the LLM as context.