Multi-modal RAG on slide decks Key Links * LangChain public benchmark evaluation notebooks * LangChain template for multi-modal RAG on presentations Motivation Retrieval augmented generation (RAG) is one of the most important
Extraction Benchmarking Test confidence_level_similarity json_edit_distance json_schema off_topic_similarity programming_language_similarity question_category sentiment_similarity toxicity_similarity claude-2-xsd-to-xml-5689 0.97 0.
Applying OpenAI's RAG Strategies Context At their demo day, Open AI reported a series of RAG experiments for a customer that they worked with. While evaluation metics will depend
LangServe Playground and Configurability Last week we launched LangServe, a way to easily deploy chains and agents in a production-ready manner. Specifically, it takes a chain and easily spins
A Chunk by Any Other Name: Structured Text Splitting and Metadata-enhanced RAG There's something of a structural irony in the fact that building context-aware LLM applications typically begins with a systematic process of decontextualization, wherein
The Prompt Landscape Context Prompt Engineering can steer LLM behavior without updating the model weights. A variety of prompts for different uses-cases have emerged (e.g., see @dair_
Building Chat LangChain Hosted: https://chat.langchain.com Repo: https://github.com/langchain-ai/chat-langchain Intro LangChain packs the power of large language models and an entire ecosystem of
