RAG use-case implementation using Llamaindex

Supercharge your RAG pipeline with the following:

• Framework -> Llamaindex
• Loader -> SimpleDirectoryLoader
• Chunking -> Semantic Chunking
• Embeddings -> Gemini Embeddings
• Vector DB -> Llamaindex VectorStoreIndex
• LLM -> Groq Mistral
• Reranking -> Cohere Rerank Model

For index creation follow notebook file rag.ipynb RAG Pipline

To run application:

pip install -r requirements.txt 
chainlit run app.py 

Hosted Huggingface App on Spaces