Improve docs and readme (#1663)
This commit is contained in:
Taranjeet Singh
@@ -1,5 +1,5 @@
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---
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title: 🤖 LLMs
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title: Supported LLMs
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---
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## Overview
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@@ -1,5 +1,5 @@
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---
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title: 🗄 Vector Databases
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title: Supported Vector Databases
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---
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## Overview
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0
docs/get-started/concepts.mdx
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0
docs/get-started/concepts.mdx
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0
docs/get-started/features.mdx
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0
docs/get-started/features.mdx
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@@ -16,24 +16,14 @@
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"light": "/logo/light.svg",
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"href": "https://github.com/mem0ai/mem0"
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},
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"tabs": [
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{
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"name": "💡 Examples",
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"url": "examples"
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},
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{
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"name": "🖥️ Platform",
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"url": "platform"
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}
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],
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"topbarCtaButton": {
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"name": "Your Memory Dashboard",
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"name": "Your Dashboard",
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"url": "https://app.mem0.ai"
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},
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"anchors": [
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{
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"name": "Your Memory Dashboard",
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"icon": "discord",
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"name": "Your Dashboard",
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"icon": "chart-simple",
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"url": "https://app.mem0.ai"
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},
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{
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@@ -56,27 +46,32 @@
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{
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"group": "Get Started",
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"pages": [
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"overview",
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"quickstart"
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"overview"
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]
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},
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{
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"group": "Components",
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"group": "Platform",
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"pages": [
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"components/llms",
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"components/vectordb"
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"platform/overview",
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"platform/quickstart"
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]
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},
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{
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"group": "Features",
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"pages":[
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"features/openai_compatibility"
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]
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},
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{
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"group": "Integrations",
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"group": "Open Source",
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"pages": [
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"integrations/multion"
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"open-source/quickstart",
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{
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"group": "LLMs",
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"pages": ["components/llms"]
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},
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{
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"group": "Vector Database",
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"pages": ["components/vectordb"]
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},
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{
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"group": "Features",
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"pages": ["features/openai_compatibility"]
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}
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]
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},
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{
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@@ -89,12 +84,12 @@
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]
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},
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{
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"group": "🖥️ Platform",
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"group": "Integrations",
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"pages": [
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"platform/overview",
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"platform/quickstart"
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"integrations/multion"
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]
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}
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],
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"footerSocials": {
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"discord": "https://mem0.ai/discord",
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@@ -1,5 +1,5 @@
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---
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title: 🚀 Quickstart
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title: Quickstart
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description: 'Get started with Mem0 quickly!'
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---
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@@ -1,62 +1,321 @@
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---
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title: 📚 Overview
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description: 'Welcome to the Mem0 docs!'
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title: Overview
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---
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> Mem0 provides a smart, self-improving memory layer for Large Language Models, enabling personalized AI experiences across applications.
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[Mem0](https://mem0.ai) (pronounced "mem-zero") enhances AI assistants and agents with an intelligent memory layer, enabling personalized AI interactions. Mem0 remembers user preferences, adapts to individual needs, and continuously improves over time, making it ideal for customer support chatbots, AI assistants, and autonomous systems.
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## Core features
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- **User, Session, and AI Agent Memory**: Retains information across user sessions, interactions, and AI agents, ensuring continuity and context.
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- **Adaptive Personalization**: Continuously improves personalization based on user interactions and feedback.
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- **Developer-Friendly API**: Offers a straightforward API for seamless integration into various applications.
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- **Platform Consistency**: Ensures consistent behavior and data across different platforms and devices.
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- **Managed Service**: Provides a hosted solution for easy deployment and maintenance.
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If you are looking to quick start, jump to one of the following links:
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Mem0 offers two powerful ways to leverage our technology: [our managed Platform](#mem0-platform-managed-solution) and [our Open Source solution](#mem0-open-source).
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<CardGroup cols={2}>
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<Card title="Open Source Quickstart" icon="square-1" href="/quickstart/">
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Get started with Mem0 open source
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<Card title="Mem0 Platform" icon="chart-simple" href="#mem0-platform-managed-solution">
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Better, faster and fully managed, hassle free solution.
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</Card>
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<Card title="Mem0 Platform Quickstart" icon="square-2" href="/platform/quickstart/">
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Begin with Mem0 Platform
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</Card>
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<Card title="Examples" icon="square-3" href="/examples/overview/">
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Explore practical use cases
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<Card title="Mem0 Open Source" icon="code-branch" href="#mem0-open-source">
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Self hosted, fully customizable and open source.
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</Card>
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</CardGroup>
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## Common Use Cases
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- **Personalized Learning Assistants**: Long-term memory allows learning assistants to remember user preferences, past interactions, and progress, providing a more tailored and effective learning experience.
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## Mem0 Platform (Managed Solution)
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- **Customer Support AI Agents**: By retaining information from previous interactions, customer support bots can offer more accurate and context-aware assistance, improving customer satisfaction and reducing resolution times.
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Our fully managed platform provides a hassle-free way to integrate Mem0's capabilities into your AI agents and assistants. Sign up for Mem0 platform [here](https://app.mem0.ai).
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- **Healthcare Assistants**: Long-term memory enables healthcare assistants to keep track of patient history, medication schedules, and treatment plans, ensuring personalized and consistent care.
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Follow the steps below to get started with Mem0 Platform:
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- **Virtual Companions**: Virtual companions can use long-term memory to build deeper relationships with users by remembering personal details, preferences, and past conversations, making interactions more meaningful.
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1. [Install Mem0](#1-install-mem0)
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2. [Add Memories](#2-add-memories)
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3. [Retrieve Memories](#3-retrieve-memories)
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- **Productivity Tools**: Long-term memory helps productivity tools remember user habits, frequently used documents, and task history, streamlining workflows and enhancing efficiency.
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### 1. Install Mem0
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- **Gaming AI**: In gaming, AI with long-term memory can create more immersive experiences by remembering player choices, strategies, and progress, adapting the game environment accordingly.
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<AccordionGroup>
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<Accordion title="Install package">
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<CodeGroup>
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```bash pip
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pip install mem0ai
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```
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## How is Mem0 different from RAG?
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```bash npm
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npm install mem0ai
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```
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</CodeGroup>
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</Accordion>
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<Accordion title="Get API Key">
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Mem0's memory implementation for Large Language Models (LLMs) offers several advantages over Retrieval-Augmented Generation (RAG):
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1. Sign in to [Mem0 Platform](https://app.mem0.ai/dashboard/api-keys)
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2. Copy your API Key from the dashboard
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- **Entity Relationships**: Mem0 can understand and relate entities across different interactions, unlike RAG which retrieves information from static documents. This leads to a deeper understanding of context and relationships.
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- **Recency, Relevancy, and Decay**: Mem0 prioritizes recent interactions and gradually forgets outdated information, ensuring the memory remains relevant and up-to-date for more accurate responses.
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</Accordion>
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</AccordionGroup>
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- **Contextual Continuity**: Mem0 retains information across sessions, maintaining continuity in conversations and interactions, which is essential for long-term engagement applications like virtual companions or personalized learning assistants.
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### 2. Add Memories
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- **Adaptive Learning**: Mem0 improves its personalization based on user interactions and feedback, making the memory more accurate and tailored to individual users over time.
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<AccordionGroup>
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<Accordion title="Instantiate client">
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<CodeGroup>
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```python Python
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from mem0 import MemoryClient
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client = MemoryClient(api_key="your-api-key")
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```
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- **Dynamic Updates**: Mem0 can dynamically update its memory with new information and interactions, unlike RAG which relies on static data. This allows for real-time adjustments and improvements, enhancing the user experience.
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```javascript JavaScript
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const MemoryClient = require('mem0ai');
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const client = new MemoryClient('your-api-key');
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```
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</CodeGroup>
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</Accordion>
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<Accordion title="Add memories">
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<CodeGroup>
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These advanced memory capabilities make Mem0 a powerful tool for developers aiming to create personalized and context-aware AI applications.
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```python Python
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messages = [
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{"role": "user", "content": "Hi, I'm Alex. I'm a vegetarian and I'm allergic to nuts."},
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{"role": "assistant", "content": "Hello Alex! I've noted that you're a vegetarian and have a nut allergy. I'll keep this in mind for any food-related recommendations or discussions."}
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]
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client.add(messages, user_id="alex")
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```
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If you have any questions, please feel free to reach out to us using one of the following methods:
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```javascript JavaScript
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const messages = [
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{"role": "user", "content": "Hi, I'm Alex. I'm a vegetarian and I'm allergic to nuts."},
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{"role": "assistant", "content": "Hello Alex! I've noted that you're a vegetarian and have a nut allergy. I'll keep this in mind for any food-related recommendations or discussions."}
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];
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client.add(messages, { user_id: "alex" })
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.then(response => console.log(response))
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.catch(error => console.error(error));
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```
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<Snippet file="get-help.mdx" />
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```bash cURL
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curl -X POST "https://api.mem0.ai/v1/memories/" \
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-H "Authorization: Token your-api-key" \
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-H "Content-Type: application/json" \
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-d '{
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"messages": [
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{"role": "user", "content": "Hi, I'm Alex. I'm a vegetarian and I'm allergic to nuts."},
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{"role": "assistant", "content": "Hello Alex! I've noted that you're a vegetarian and have a nut allergy. I'll keep this in mind for any food-related recommendations or discussions."}
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],
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"user_id": "alex"
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}'
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```
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```json Output
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{'message': 'ok'}
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```
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</CodeGroup>
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</Accordion>
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</AccordionGroup>
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### 3. Retrieve Memories
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<AccordionGroup>
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<Accordion title="Search for relevant memories">
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<CodeGroup>
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```python Python
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query = "What do you know about me?"
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client.search(query, user_id="alex")
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```
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```javascript JavaScript
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const query = "What do you know about me?";
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client.search(query, { user_id: "alex" })
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.then(results => console.log(results))
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.catch(error => console.error(error));
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```
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```bash cURL
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curl -X POST "https://api.mem0.ai/v1/memories/search/" \
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-H "Authorization: Token your-api-key" \
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-H "Content-Type: application/json" \
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-d '{
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"query": "What do you know about me?",
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"user_id": "alex"
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}'
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```
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```json Output
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[
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{
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"id": "7f165f7e-b411-4afe-b7e5-35789b72c4a5",
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"memory": "Name: Alex. Vegetarian. Allergic to nuts.",
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"input": [
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{
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"role": "user",
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"content": "Hi, I'm Alex. I'm a vegetarian and I'm allergic to nuts."
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},
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{
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"role": "assistant",
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"content": "Hello Alex! I've noted that you're a vegetarian and have a nut allergy. I'll keep this in mind for any food-related recommendations or discussions."
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}
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],
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"user_id": "alex",
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"hash": "9ee7e1455e84d1dab700ed8749aed75a",
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"metadata": null,
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"created_at": "2024-07-20T01:30:36.275141-07:00",
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"updated_at": "2024-07-20T01:30:36.275172-07:00"
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}
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]
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```
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</CodeGroup>
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</Accordion>
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<Accordion title="Get all memories of a user">
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<CodeGroup>
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```python Python
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user_memories = client.get_all(user_id="alex")
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```
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```javascript JavaScript
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client.getAll({ user_id: "alex" })
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.then(memories => console.log(memories))
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.catch(error => console.error(error));
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```
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```bash cURL
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curl -X GET "https://api.mem0.ai/v1/memories/?user_id=alex" \
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-H "Authorization: Token your-api-key"
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```
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```json Output
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[
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{
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"id":"f38b689d-6b24-45b7-bced-17fbb4d8bac7",
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"memory":"是素食主义者，对坚果过敏。",
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"agent_id":"travel-assistant",
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"hash":"62bc074f56d1f909f1b4c2b639f56f6a",
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"metadata":"None",
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"created_at":"2024-07-25T23:57:00.108347-07:00",
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"updated_at":"2024-07-25T23:57:00.108367-07:00"
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},
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{
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"id":"0a14d8f0-e364-4f5c-b305-10da1f0d0878",
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"memory":"Will maintain personalized travel preferences for each user. Provide customized recommendations based on dietary restrictions, interests, and past interactions.",
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"agent_id":"travel-assistant",
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"hash":"35a305373d639b0bffc6c2a3e2eb4244",
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"metadata":"None",
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"created_at":"2024-07-26T00:31:03.543759-07:00",
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"updated_at":"2024-07-26T00:31:03.543778-07:00"
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}
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]
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```
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</CodeGroup>
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</Accordion>
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</AccordionGroup>
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<Card title="Mem0 Platform" icon="chart-simple" href="/platform/overview">
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Learn more about Mem0 platform
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</Card>
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## Mem0 Open Source
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Our open-source version is available for those who prefer full control and customization. You can self-host Mem0 on your infrastructure and integrate it with your AI agents and assistants. Checkout the [GitHub repository](https://github.com/mem0ai/mem0)
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Follow the steps below to get started with Mem0 Open Source:
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1. [Install Mem0 Open Source](#1-install-mem0-open-source)
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2. [Add Memories](#2-add-memories-open-source)
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3. [Retrieve Memories](#3-retrieve-memories-open-source)
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### 1. Install Mem0 Open Source
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<AccordionGroup>
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<Accordion title="Install package">
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```bash
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pip install mem0ai
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```
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</Accordion>
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</AccordionGroup>
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### 2. Add Memories <a name="2-add-memories-open-source"></a>
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<AccordionGroup>
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<Accordion title="Instantiate client">
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```python Python
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from mem0 import Memory
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m = Memory()
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```
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</Accordion>
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<Accordion title="Add memories">
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<CodeGroup>
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```python Code
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# For a user
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result = m.add("Likes to play cricket on weekends", user_id="alice", metadata={"category": "hobbies"})
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```
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```json Output
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{'message': 'ok'}
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```
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</CodeGroup>
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</Accordion>
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</AccordionGroup>
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### 3. Retrieve Memories <a name="3-retrieve-memories-open-source"></a>
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<AccordionGroup>
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<Accordion title="Search for relevant memories">
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<CodeGroup>
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```python Code
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related_memories = m.search(query="What are Alice's hobbies?", user_id="alice")
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```
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```json Output
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[
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{
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"id":"ea925981-272f-40dd-b576-be64e4871429",
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"memory":"Likes to play cricket and plays cricket on weekends.",
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"hash":"c8809002-25c1-4c97-a3a2-227ce9c20c53",
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"metadata":{
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"category":"hobbies"
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},
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"score":0.32116443111457704,
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"created_at":"2024-07-26T10:29:36.630547-07:00",
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"updated_at":"None",
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"user_id":"alice"
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}
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]
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```
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</CodeGroup>
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</Accordion>
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<Accordion title="Get all memories of a user">
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<CodeGroup>
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```python Code
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# Get all memories
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all_memories = m.get_all()
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```
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```json Output
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[
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{
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"id":"13efe83b-a8df-4ec0-814e-428d6e8451eb",
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"memory":"Likes to play cricket on weekends",
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"hash":"87bcddeb-fe45-4353-bc22-15a841c50308",
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"metadata":"None",
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"created_at":"2024-07-26T08:44:41.039788-07:00",
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"updated_at":"None",
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"user_id":"alice"
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}
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]
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```
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</CodeGroup>
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</Accordion>
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</AccordionGroup>
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<Card title="Mem0 Open source" icon="code-branch" href="/open-source/overview">
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Learn more about Mem0 open source
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</Card>
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||||
## Key Features
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||||
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||||
- OpenAI-compatible API: Easily switch between OpenAI and Mem0
|
||||
- Advanced memory management: Efficient handling of long-term context
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||||
- Flexible deployment: Choose between managed platform or self-hosted solution
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Discover all features →
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||||
|
||||
## Need help?
|
||||
|
||||
<Snippet file="get-help.mdx"/>
|
||||
Reference in New Issue
Block a user