kartik-mem0
c8b93de8e9
README first fold: - banner 800px -> 520px - badges condensed from two paragraphs into one row (Trendshift kept, inline) - lead with Introduction instead of benchmarks - new How it works section explaining the add/search loop - benchmarks moved below the intro and retitled from the date-stamped New Memory Algorithm (April 2026) - dropped Research Highlights, which restated the benchmark table verbatim Benchmarks: the README was already correct at 92.5 / 94.4, matching mem0.ai/research and docs/core-concepts/memory-evaluation.mdx. The stale copies were in the migration guides, which quote the numbers as a live reason to upgrade. Updated both to 92.5 / 94.4 (+21 / +27). docs/changelog/highlights.mdx keeps 91.6 / 93.4 inside its dated 2026-04-14 entry, which records what was announced at the time. One-liner: standardized on 'the memory layer for AI agents', already the canonical form in cli-spec.json, cli/python/pyproject.toml and the CLI specification. Swept the remaining variants.
Mem0 - The Memory Layer for AI Agents
Mem0 is the memory layer for AI agents, giving them persistent, personalized context across sessions. We offer both cloud and open-source solutions to cater to different needs.
See the complete OSS Docs. See the complete Platform API Reference.
1. Installation
For the open-source version, you can install the Mem0 package using npm:
npm i mem0ai
2. API Key Setup
For the cloud offering, sign in to Mem0 Platform to obtain your API Key.
3. Client Features
Cloud Offering
The cloud version provides a comprehensive set of features, including:
- Memory Operations: Perform CRUD operations on memories.
- Search Capabilities: Search for relevant memories using advanced filters.
- Memory History: Track changes to memories over time.
- Error Handling: Robust error handling for API-related issues.
- Async/Await Support: All methods return promises for easy integration.
Open-Source Offering
The open-source version includes the following top features:
- Memory Management: Add, update, delete, and retrieve memories.
- Vector Store Integration: Supports various vector store providers for efficient memory retrieval.
- LLM Support: Integrates with multiple LLM providers for generating responses.
- Customizable Configuration: Easily configure memory settings and providers.
- SQLite Storage: Use SQLite for memory history management.
4. Memory Operations
Mem0 provides a simple and customizable interface for performing memory operations. You can create long-term and short-term memories, search for relevant memories, and manage memory history.
5. Error Handling
The MemoryClient throws errors for any API-related issues. You can catch and handle these errors effectively.
6. Using with async/await
All methods of the MemoryClient return promises, allowing for seamless integration with async/await syntax.
7. Testing the Client
To test the MemoryClient in a Node.js environment, you can create a simple script to verify the functionality of memory operations.
Getting Help
If you have any questions or need assistance, please reach out to us:
- Email: founders@mem0.ai
- Join our discord community
- GitHub Issues: Report bugs or request features