Zep - Build Agents That Recall What Matters (Page 3)

Signup for Zep →

Semantic Similarity as an Intent Router for LLM Apps

Semantic Similarity as an Intent Router for LLM Apps

Ensuring your LLM app understands user intent is crucial in offering a great experience. We build an intent router using Langchain, which automatically selects the prompt best suited to a task.

New Features: JWT Authentication, Azure OpenAI APIs, & Configurable Hard Deletion

New Features: JWT Authentication, Azure OpenAI APIs, & Configurable Hard Deletion

Zep now supports JWT Authentication, Azure OpenAI APIs and OpenAI OrgIDs, and a configurable, periodic purge of soft-deleted data.

Introducing Intents

Introducing Intents

Zep's Intent Extractor identifies the intent of a message, persisting this to message metadata. 💡 With intent data, developers can build richer, more personalized agent interactions. 🔥

Introducing Open Source Embeddings! 🔥

Zep now has support for open source embedding models. Search your LLM App's chat history faster and more cheaply.

A Survey of Embedding Models (and why you should look beyond OpenAI)

A Survey of Embedding Models (and why you should look beyond OpenAI)

User experience can be severely impacted when AI chat apps and agents are slow to respond. Embedding model performance can contribute to this problem. Is OpenAI's embedding API always the best fit?

Personalizing LLM Interactions: Harnessing Generative Feedback Loops

Personalizing LLM Interactions: Harnessing Generative Feedback Loops

LLM Applications can be personalized using Generative Feedback Loops through advanced memory & personalization.

Introducing Zep Hybrid Search and Custom Metadata

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.

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.

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

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