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

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Introducing the Zep User Store

Introducing the Zep User Store

Zep v0.11.0, released today, now includes a User Store. A User represents an individual interacting with your application. The User object and its associated Sessions provide a powerful way to manage and understand the behavior of individuals using your application. Users may have additional data associated with them,

Foundations of LLM App Building in TypeScript

Foundations of LLM App Building in TypeScript

Learn how to build three foundational LLM apps using TypeScript, LangChain.js, and Zep.

Announcing Anthropic Claude Support! 🎉

Announcing Anthropic Claude Support! 🎉

Zep v0.10.0, released today, supports Anthropic's Claude family of LLMs for summarization and extraction tasks.

Zep ❤️ LlamaIndex: A Vector Store Walkthrough

Zep ❤️ LlamaIndex: A Vector Store Walkthrough

LlamaIndex is a simple but powerful framework for building LLM apps. It's also an excellent tool for populating and searching Zep's Vector Store. This walkthrough demonstrates using LlamaIndex's new ZepVectorStore to do just that.

Introducing the Zep Document Vector Store

Introducing the Zep Document Vector Store

With the addition of a Document Vector Store, Zep is now a single, batteries-included platform for grounding LLM apps with long-term memory.

ICYMI: Zep X Langchain, Session Metadata, and more 🔥⚡️

ICYMI: Zep X Langchain, Session Metadata, and more 🔥⚡️

July was a busy month at Zep! Just in case you missed anything, here's a roundup: Diagnosing and Fixing Slow Chatbots 🐢🐢🐢 (originally published on the Langchain blog) Is your LLM app slow? Poor chatbot response times can result in frustrated users and churn. Langchain’s new LangSmith service

Diagnosing and Fixing Slow Chatbots with LangSmith and Zep

Diagnosing and Fixing Slow Chatbots with LangSmith and Zep

Poor chatbot response times can result in frustrated users and churn. Langchain’s new LangSmith service makes it easy to diagnose the cause of latency in an LLM app. In this article, we use LangSmith to analyze a very slow Langchain app and improve performance by an order of magnitude using Zep.

Session Metadata 👾, Custom OpenAI Endpoints 🔧, & Kubernetes Deployment 🔥

Session Metadata 👾, Custom OpenAI Endpoints 🔧, & Kubernetes Deployment 🔥

Zep now includes support for adding arbitrary metadata to Sessions and more deployment options

Improved Langchain Support!

Improved Langchain Support!

Langchain now includes improved support for Zep, with a new ZepMemory class, access to enriched messages, and more.

Goodbye Web Forms, Hello Chat Messages

Goodbye Web Forms, Hello Chat Messages

A Guide to Using OpenAI Functions and Langchain to Extract Structured Data from LLM App Conversations

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