News
Personalizing LLM Interactions: Harnessing Generative Feedback Loops
LLM Applications can be personalized using Generative Feedback Loops through advanced memory & personalization.
Building an LLM app and juggling infrastructure?
Focus on business value, not memory persistence, search, and enrichment.
News
Introducing Zep Hybrid Search and Custom Metadata
Zep now supports both vector search over message text and filtering on message metadata, including system metadata such as Named Entities and creation dates.
langchain
LangchainJS Now Supports Zep!
LangchainJS now supports Zep Memory and Retrievers, allowing developers to take advantage of Zep's long-term memory, auto-summarization, vector search, and named entity extraction.
News
Announcing Zep's Entity Extractor!
Today we're launching Zep's EntityExtractor, a Named Entity Recognition tool built using state-of-the-art NLP toolkit, spaCy. With Zep's EntityExtractor, developers can build sophisticated features that: * Trigger the use of custom prompts or agent branching; * Annotate the chat history, enhancing the experience for users with links to additional information, services, or
News
Introducing Zep: Long-term Memory Storage and Enrichment for AI Apps
Chat history storage is an infrastructure challenge all developers and enterprises face as they look to move from prototypes to productionizing LLM/ AI Chat applications that provide rich and intimate experiences to users. Zep allows developers to focus on developing their AI apps, rather than building memory persistence, search, and