reginold / rag

The next wave, rag is all you need

RAG

The next wave, rag is all you need

Applying OpenAI's RAG Strategies

• KEY MESSAGE
  • The ability to understand and these methods on your application is critical: from talking to many partners and users, there is no "one-size-fits-all" solution because different problems require different retrieval techniques.
• Query Transformation
  • Query expansion
  • HyDE
• Routing
• Query Construction
• Building Index
  • Chunk/Embedding experiments
  • Fine-tune embeddings
• Post-Progressing
  • Re-Ranking
  • Classfication

Query Transformation

• https://github.com/texttron/hyde
  • Explain：blog - LangChain Hypothetical Document Embeddings (HyDE) 全面解説 (jiang.jp)

Aspect	Problem	Resolution with HyDE
Retrieval	Inefficient zero-shot retrieval	Enhances zero-shot performance using language models
Data Dependency	Heavy reliance on labeled data	Operates effectively without needing human-labeled data
Generalization	Limited adaptability across languages and tasks	Improved generalization across various languages and tasks

MultiQueryRetriever

• For example

  • Who won a championship more recently, the Red Sox or the Patriots?

  ↓

  • "When was the last time the Red Sox won a championship?"
  • "When was the last time the Patriots won a championship?"

• Implementation

  1. unable to install the chromed, grpcio

  CFLAGS="-I/Library/Developer/CommandLineTools/usr/include/c++/v1 -I/opt/homebrew/opt/openssl/include" LDFLAGS="-L/opt/homebrew/opt/openssl/lib" pip3 instal grpcio
  

  1. I cannot use the OpenAI text embedding model, use hugging face model

  from langchain.embeddings import HuggingFaceEmbeddings
  embeddings = HuggingFaceEmbeddings(model_name="all-MiniLM-L6-v2")

  1. Use Azure Open AI instead of OpenAi API

  https://api.python.langchain.com/en/latest/embeddings/langchain.embeddings.openai.OpenAIEmbeddings.html#

  1. Resolve the chroma db issue

  RuntimeError: Your system has an unsupported version of sqlite3. Chroma                     requires sqlite3 >= 3.35.0.
  Please visit                     https://docs.trychroma.com/troubleshooting#sqlite to learn how                     to upgrade.

  • refer the site to solve the issue to add three lines at the beginning of the code

  __import__('pysqlite3')
  import sys
  sys.modules['sqlite3'] = sys.modules.pop('pysqlite3')

  • refer

  Deep Dive into the Internals of Langchain Vector Store Retriever

  

Re-Ranking

• Cohereの多言語用の埋め込みモデルを日本語で評価してみる
  • 測定したデータセットにおいては、OpenAIのtext-embedding-ada-002を上回る性能を示しており、性能の高いモデルであること
  • RAG But Better: Rerankers with Cohere AI
  • Cohere Embed V3 - Nils Reimers | Vector Space Talks
• RAG-fusion
  • https://medium.com/@kiran.phd.0102/rag-fusion-revolution-a-paradigm-shift-in-generative-ai-2349b9f81c66

TO READ

9 Methods to Enhance the Performance of a LLM RAG Application

https://github.com/docker/genai-stack