How to Build RAG-Powered (Retrieval-Augmented Gen) Android App with Gemini Embedding & Flash Models?
Автор: Programmer World
Загружено: 2025-03-03
Просмотров: 710
Описание:
RAG-Powered Android App
Steps:
1 Prepare Document Data:
Extract text from a PDF using Python and PyPDF2, chunk it, generate embeddings with Gemini’s models/embedding-001, and export to rag_data.json.
2 Set Up Android Project:
Create an Android app with Gson and OkHttp dependencies, load rag_data.json from assets into chunks and embeddings, and add internet permission.
3 Implement RAG Logic:
Fetch query embeddings from embedding-001, compute cosine similarity to retrieve top-k chunks, and generate a response using gemini-1.5-flash.
4 Integrate and Test:
Run RAG in a background thread, display the response in a TextView, and test with logging and error handling.
Sample Prompts:
1. What is the main topic of the document?
2. What is History of AI?
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