Refactor docs and fix get memories playground (#3527)
This commit is contained in:
Parshva Daftari
+34
-11
@@ -6,26 +6,49 @@ iconType: "solid"
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Mem0 provides a powerful set of APIs that allow you to integrate advanced memory management capabilities into your applications. Our APIs are designed to be intuitive, efficient, and scalable, enabling you to create, retrieve, update, and delete memories across various entities such as users, agents, apps, and runs.
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## Key Features
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## Quick Start Guide
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- **Memory Management**: Add, retrieve, update, and delete memories with ease.
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- **Entity-based Operations**: Perform operations on memories associated with specific users, agents, apps, or runs.
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- **Advanced Search**: Utilize our search API to find relevant memories based on various criteria.
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- **History Tracking**: Access the history of memory interactions for comprehensive analysis.
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- **User Management**: Manage user entities and their associated memories.
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Get started with Mem0 API in three simple steps:
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1. **[Add Memories](/api-reference/memory/add-memories)** - Store information and context from user conversations
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2. **[Search Memories](/api-reference/memory/v2-search-memories)** - Retrieve relevant memories based on queries
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3. **[Get Memories](/api-reference/memory/v2-get-memories)** - Fetch all memories for a specific entity
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### Common Operations
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<CardGroup cols={2}>
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<Card title="Add Memories" icon="plus" href="/api-reference/memory/add-memories">
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Store new memories from conversations and interactions
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</Card>
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<Card title="Search Memories" icon="magnifying-glass" href="/api-reference/memory/v2-search-memories">
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Find relevant memories using semantic search
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</Card>
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<Card title="Update Memory" icon="pen" href="/api-reference/memory/update-memory">
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Modify existing memory content
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</Card>
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<Card title="Delete Memory" icon="trash" href="/api-reference/memory/delete-memory">
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Remove specific memories or batch delete
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</Card>
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</CardGroup>
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## API Structure
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Our API is organized into several main categories:
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1. **Memory APIs**: Core operations for managing individual memories and collections.
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2. **Entities APIs**: Manage different entity types (users, agents, etc.) and their associated memories.
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3. **Search API**: Advanced search functionality to retrieve relevant memories.
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4. **History API**: Track and retrieve the history of memory interactions.
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1. **[Memory APIs](#memory-apis)**: Core operations for managing individual memories and collections
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2. **[Entities APIs](#entities-apis)**: Manage different entity types (users, agents, etc.) and their associated memories
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3. **[Organizations APIs](#organizations-apis)**: Manage organizations and their members (optional)
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4. **[Project APIs](#project-apis)**: Manage projects within organizations (optional)
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## Authentication
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All API requests require authentication using HTTP Basic Auth. Ensure you include your API key in the Authorization header of each request.
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All API requests require authentication using Token-based authentication. Include your API key in the Authorization header:
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```bash
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Authorization: Token <your-api-key>
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```
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Get your API key from the [Mem0 Dashboard](https://app.mem0.ai/dashboard/api-keys).
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## Organizations and projects (optional)
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@@ -2,3 +2,11 @@
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title: 'Add Memories'
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openapi: post /v1/memories/
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---
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## Graph Memory
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To enable graph-based memory relationships, pass the `enable_graph=True` parameter. This creates relationships between entities in your memories for more contextual retrieval.
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<Note>
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Learn more in the [Graph Memory documentation](/platform/features/graph-memory).
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</Note>
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@@ -1,4 +0,0 @@
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---
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title: 'Get Memories (v1 - Deprecated)'
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openapi: get /v1/memories/
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---
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@@ -1,4 +0,0 @@
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---
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title: 'Search Memories (v1 - Deprecated)'
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openapi: post /v1/memories/search/
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---
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@@ -63,3 +63,11 @@ memories = m.get_all(
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)
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```
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</CodeGroup>
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## Graph Memory
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To retrieve memories with graph-based relationships, pass the `enable_graph=True` parameter. This includes relationship data in the response for more contextual results.
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<Note>
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Learn more in the [Graph Memory documentation](/platform/features/graph-memory).
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</Note>
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@@ -106,3 +106,11 @@ personal_memories = m.search(
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)
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```
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</CodeGroup>
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## Graph Memory
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To retrieve memories with graph-based relationships, pass the `enable_graph=True` parameter. This includes relationship data in the response for more contextual results.
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<Note>
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Learn more in the [Graph Memory documentation](/platform/features/graph-memory).
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</Note>
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+23
-22
@@ -251,34 +251,34 @@
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"tab": "Examples",
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"groups": [
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{
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"group": "💡 Examples",
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"group": "\ud83d\udca1 Examples",
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"icon": "lightbulb",
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"pages": [
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"examples",
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"examples/aws_example",
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"examples/aws_neptune_analytics_hybrid_store",
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"examples/mem0-demo",
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"examples/ai_companion_js",
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"examples/collaborative-task-agent",
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"examples/llamaindex-multiagent-learning-system",
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"examples/personalized-search-tavily-mem0",
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"examples/eliza_os",
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"examples/mem0-mastra",
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"examples/mem0-with-ollama",
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"examples/personal-ai-tutor",
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"examples/customer-support-agent",
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"examples/personal-travel-assistant",
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"examples/llama-index-mem0",
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"examples/chrome-extension",
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"examples/youtube-assistant",
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"examples/memory-guided-content-writing",
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"examples/multimodal-demo",
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"examples/email_processing",
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"examples/personalized-deep-research",
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"examples/collaborative-task-agent",
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"examples/llama-index-mem0",
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"examples/llamaindex-multiagent-learning-system",
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"examples/personalized-search-tavily-mem0",
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"examples/mem0-agentic-tool",
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"examples/openai-inbuilt-tools",
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"examples/mem0-openai-voice-demo",
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"examples/mem0-google-adk-healthcare-assistant",
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"examples/email_processing",
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"examples/youtube-assistant"
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"examples/mem0-mastra",
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"examples/eliza_os",
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"examples/aws_example",
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"examples/aws_neptune_analytics_hybrid_store"
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]
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}
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]
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@@ -547,33 +547,34 @@
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"tab": "Examples",
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"groups": [
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{
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"group": "💡 Examples",
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"group": "\ud83d\udca1 Examples",
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"icon": "lightbulb",
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"pages": [
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"v0x/examples/aws_example",
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"v0x/examples/aws_neptune_analytics_hybrid_store",
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"examples",
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"v0x/examples/mem0-demo",
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"v0x/examples/ai_companion_js",
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"v0x/examples/collaborative-task-agent",
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"v0x/examples/llamaindex-multiagent-learning-system",
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"v0x/examples/personalized-search-tavily-mem0",
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"v0x/examples/eliza_os",
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"v0x/examples/mem0-mastra",
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"v0x/examples/mem0-with-ollama",
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"v0x/examples/personal-ai-tutor",
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"v0x/examples/customer-support-agent",
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"v0x/examples/personal-travel-assistant",
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"v0x/examples/llama-index-mem0",
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"v0x/examples/chrome-extension",
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"v0x/examples/youtube-assistant",
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"v0x/examples/memory-guided-content-writing",
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"v0x/examples/multimodal-demo",
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"v0x/examples/email_processing",
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"v0x/examples/personalized-deep-research",
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"v0x/examples/collaborative-task-agent",
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"v0x/examples/llama-index-mem0",
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"v0x/examples/llamaindex-multiagent-learning-system",
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"v0x/examples/personalized-search-tavily-mem0",
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"v0x/examples/mem0-agentic-tool",
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"v0x/examples/openai-inbuilt-tools",
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"v0x/examples/mem0-openai-voice-demo",
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"v0x/examples/mem0-google-adk-healthcare-assistant",
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"v0x/examples/email_processing",
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"v0x/examples/youtube-assistant"
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"v0x/examples/mem0-mastra",
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"v0x/examples/eliza_os",
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"v0x/examples/aws_example",
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"v0x/examples/aws_neptune_analytics_hybrid_store"
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]
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}
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]
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+68
-40
@@ -18,71 +18,99 @@ Here are some examples of how Mem0 can be integrated into various applications:
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Explore how **Mem0** can power real-world applications and bring personalized, intelligent experiences to life:
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<CardGroup cols={2}>
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<Card title="Mem0 Demo" icon="rocket" href="/examples/mem0-demo">
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Get started with **Mem0** with this simple demo showcasing basic memory operations.
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</Card>
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<Card title="AI Companion in Node.js" icon="node" href="/examples/ai_companion_js">
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Build a personalized AI Companion in **Node.js** that remembers conversations and adapts over time using Mem0.
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Build a personalized AI Companion in **Node.js** that remembers conversations and adapts over time.
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</Card>
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<Card title="Mem0 with Ollama" icon="server" href="/examples/mem0-with-ollama">
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Run **Mem0 locally** with **Ollama** to create private, stateful AI experiences without relying on cloud APIs.
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Run **Mem0 locally** with **Ollama** to create private, stateful AI experiences without cloud APIs.
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</Card>
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<Card title="Personal AI Tutor" icon="graduation-cap" href="/examples/personal-ai-tutor">
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Create an **AI Tutor** that adapts to student progress, learning style, and history — for a truly customized learning experience.
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</Card>
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<Card title="Personal Travel Assistant" icon="plane" href="/examples/personal-travel-assistant">
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Develop a **Personal Travel Assistant** that remembers your preferences, past trips, and helps plan future adventures.
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Create an **AI Tutor** that adapts to student progress, learning style, and history.
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</Card>
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<Card title="Customer Support Agent" icon="headset" href="/examples/customer-support-agent">
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Build a **Customer Support AI** that recalls user preferences, past chats, and provides context-aware, efficient help.
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Build a **Customer Support AI** that recalls user preferences and past chats.
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</Card>
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<Card title="LlamaIndex + Mem0" icon="book-open" href="/examples/llama-index-mem0">
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Combine **LlamaIndex** and Mem0 to create a powerful **ReAct Agent** with persistent memory for smarter interactions.
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</Card>
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<Card title="LlamaIndex + Mem0 Learning System" icon="book-open" href="/examples/llama-index-mem0">
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Multi-agent learning system powered by memory.
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<Card title="Personal Travel Assistant" icon="plane" href="/examples/personal-travel-assistant">
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Develop a **Personal Travel Assistant** that remembers your preferences and past trips.
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</Card>
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<Card title="Chrome Extension" icon="puzzle-piece" href="/examples/chrome-extension">
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Add **long-term memory** to ChatGPT, Claude, or Perplexity via the **Mem0 Chrome Extension** — personalize your AI chats anywhere.
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Add **long-term memory** to ChatGPT, Claude, or Perplexity via the **Mem0 Chrome Extension**.
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</Card>
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<Card title="YouTube Assistant" icon="puzzle-piece" href="/examples/youtube-assistant">
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Integrate **Mem0** into **YouTube's** native UI, providing personalized responses with video context.
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<Card title="YouTube Assistant" icon="video" href="/examples/youtube-assistant">
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Integrate **Mem0** into **YouTube's** native UI with personalized responses.
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</Card>
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|
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<Card title="Memory-Guided Content Writing" icon="pen" href="/examples/memory-guided-content-writing">
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Create a **Writing Assistant** that understands and adapts to your unique style, improving consistency and productivity.
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Create a **Writing Assistant** that understands and adapts to your unique style.
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</Card>
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|
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<Card title="Multimodal AI Demo" icon="image" href="/examples/multimodal-demo">
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Supercharge AI with **Mem0's multimodal memory** — blend text, images, and more for richer, context-aware interactions.
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</Card>
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<Card title="Personalized Research Agent" icon="magnifying-glass" href="/examples/personalized-deep-research">
|
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Build a **Deep Research AI** that remembers your research goals and compiles insights from vast information sources.
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</Card>
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|
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<Card title="Mem0 as an Agentic Tool" icon="robot" href="/examples/mem0-agentic-tool">
|
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Integrate Mem0's memory capabilities with OpenAI's Agents SDK to create AI agents with persistent memory.
|
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</Card>
|
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|
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<Card title="OpenAI Inbuilt Tools" icon="robot" href="/examples/openai-inbuilt-tools">
|
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Use Mem0's memory capabilities with OpenAI's Inbuilt Tools to create AI agents with persistent memory.
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</Card>
|
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|
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<Card title="Mem0 OpenAI Voice Demo" icon="microphone" href="/examples/mem0-openai-voice-demo">
|
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Use Mem0's memory capabilities with OpenAI's Inbuilt Tools to create AI agents with persistent memory.
|
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</Card>
|
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|
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<Card title="Healthcare Assistant Google ADK" icon="microphone" href="/examples/mem0-google-adk-healthcare-assistant">
|
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Build a personalized healthcare assistant with persistent memory using Google's ADK and Mem0.
|
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Supercharge AI with **Mem0's multimodal memory** — blend text, images, and more.
|
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</Card>
|
||||
|
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<Card title="Email Processing" icon="envelope" href="/examples/email_processing">
|
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Use Mem0's memory capabilities to process emails and create AI agents with persistent memory.
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Use Mem0's memory capabilities to process emails with persistent memory.
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</Card>
|
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|
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<Card title="Personalized Research Agent" icon="magnifying-glass" href="/examples/personalized-deep-research">
|
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Build a **Deep Research AI** that remembers your research goals.
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</Card>
|
||||
|
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<Card title="Multi-User Collaboration" icon="users" href="/examples/collaborative-task-agent">
|
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Build collaborative agents with shared memory across multiple users.
|
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</Card>
|
||||
|
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<Card title="LlamaIndex ReAct Agent" icon="book-open" href="/examples/llama-index-mem0">
|
||||
Combine **LlamaIndex** and Mem0 to create a **ReAct Agent** with persistent memory.
|
||||
</Card>
|
||||
|
||||
<Card title="LlamaIndex Multi-Agent System" icon="book-open" href="/examples/llamaindex-multiagent-learning-system">
|
||||
Multi-agent learning system powered by memory.
|
||||
</Card>
|
||||
|
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<Card title="Personalized Search with Tavily" icon="search" href="/examples/personalized-search-tavily-mem0">
|
||||
Build a personalized search experience using Mem0 and Tavily.
|
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</Card>
|
||||
|
||||
<Card title="Mem0 as an Agentic Tool" icon="robot" href="/examples/mem0-agentic-tool">
|
||||
Integrate Mem0's memory capabilities with OpenAI's Agents SDK.
|
||||
</Card>
|
||||
|
||||
<Card title="OpenAI Inbuilt Tools" icon="wrench" href="/examples/openai-inbuilt-tools">
|
||||
Use Mem0 with OpenAI's Inbuilt Tools to create AI agents with persistent memory.
|
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</Card>
|
||||
|
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<Card title="OpenAI Voice Demo" icon="microphone" href="/examples/mem0-openai-voice-demo">
|
||||
Voice-enabled AI agents with persistent memory using OpenAI.
|
||||
</Card>
|
||||
|
||||
<Card title="Healthcare Assistant with Google ADK" icon="heart-pulse" href="/examples/mem0-google-adk-healthcare-assistant">
|
||||
Build a personalized healthcare assistant with persistent memory using Google ADK.
|
||||
</Card>
|
||||
|
||||
<Card title="Mem0 with Mastra" icon="wand-magic-sparkles" href="/examples/mem0-mastra">
|
||||
Integrate Mem0 with Mastra for powerful agentic workflows.
|
||||
</Card>
|
||||
|
||||
<Card title="Eliza OS Character" icon="comment" href="/examples/eliza_os">
|
||||
Build conversational AI characters with persistent memory using Eliza OS.
|
||||
</Card>
|
||||
|
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<Card title="AWS Bedrock Example" icon="aws" href="/examples/aws_example">
|
||||
Use Mem0 with **AWS Bedrock**, **OpenSearch**, and **Neptune Analytics**.
|
||||
</Card>
|
||||
|
||||
<Card title="AWS Neptune Analytics" icon="aws" href="/examples/aws_neptune_analytics_hybrid_store">
|
||||
Hybrid memory store with **AWS Neptune Analytics** and Bedrock.
|
||||
</Card>
|
||||
</CardGroup>
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
---
|
||||
title: "AWS bedrock, OpenSearch and Neptune Analytics"
|
||||
title: "AWS Bedrock Example"
|
||||
---
|
||||
|
||||
This example demonstrates how to configure and use the `mem0ai` SDK with **AWS Bedrock**, **OpenSearch Service (AOSS)**, and **AWS Neptune Analytics** for persistent memory capabilities in Python.
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
---
|
||||
title: "Neptune Analytics Hybrid Store"
|
||||
title: "AWS Neptune Analytics"
|
||||
---
|
||||
|
||||
This example demonstrates how to configure and use the `mem0ai` SDK with **AWS Bedrock** and **AWS Neptune Analytics** for persistent memory capabilities in Python.
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
---
|
||||
title: 'Personalized Search with Mem0 and Tavily'
|
||||
title: 'Personalized Search with Tavily'
|
||||
---
|
||||
|
||||
<Snippet file="security-compliance.mdx" />
|
||||
|
||||
@@ -1,8 +1,8 @@
|
||||
---
|
||||
title: Google Agent Development Kit
|
||||
title: Google ADK
|
||||
---
|
||||
|
||||
Integrate [**Mem0**](https://github.com/mem0ai/mem0) with [Google Agent Development Kit (ADK)](https://github.com/google/adk-python), an open-source framework for building multi-agent workflows. This integration enables agents to access persistent memory across conversations, enhancing context retention and personalization.
|
||||
Integrate [**Mem0**](https://github.com/mem0ai/mem0) with [Google ADK (Agent Development Kit)](https://github.com/google/adk-python), an open-source framework for building multi-agent workflows. This integration enables agents to access persistent memory across conversations, enhancing context retention and personalization.
|
||||
|
||||
## Overview
|
||||
|
||||
|
||||
@@ -4,6 +4,10 @@ icon: "book"
|
||||
iconType: "solid"
|
||||
---
|
||||
|
||||
<Info>
|
||||
**Mem0 v1.0.0 Beta is here!** Check out our [research paper](https://mem0.ai/research) to learn about the technical foundations and innovations behind Mem0's memory architecture.
|
||||
</Info>
|
||||
|
||||
Mem0 is a memory layer designed for modern AI agents. It acts as a persistent memory layer that agents can use to:
|
||||
|
||||
- Recall relevant past interactions
|
||||
|
||||
+141
-141
@@ -329,7 +329,7 @@
|
||||
"x-code-samples": [
|
||||
{
|
||||
"lang": "Python",
|
||||
"source": "import requests\n\nurl = \"https://api.mem0.ai/v1/entities/{entity_type}/{entity_id}/\"\n\nheaders = {\"Authorization\": \"<api-key>\"}\n\nresponse = requests.request(\"DELETE\", url, headers=headers)\n\nprint(response.text)"
|
||||
"source": "import requests\n\nurl = \"https://api.mem0.ai/v1/entities/{entity_type}/{entity_id}/\"\n\nheaders = {\"Authorization\": \"Token <api-key>\"}\n\nresponse = requests.request(\"DELETE\", url, headers=headers)\n\nprint(response.text)"
|
||||
},
|
||||
{
|
||||
"lang": "JavaScript",
|
||||
@@ -1100,137 +1100,16 @@
|
||||
],
|
||||
"description": "Get all memories.",
|
||||
"operationId": "memories_list_v2",
|
||||
"parameters": [
|
||||
{
|
||||
"name": "filters",
|
||||
"in": "query",
|
||||
"requestBody": {
|
||||
"content": {
|
||||
"application/json": {
|
||||
"schema": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"user_id": {
|
||||
"type": "string"
|
||||
},
|
||||
"agent_id": {
|
||||
"type": "string"
|
||||
},
|
||||
"app_id": {
|
||||
"type": "string"
|
||||
},
|
||||
"run_id": {
|
||||
"type": "string"
|
||||
},
|
||||
"created_at": {
|
||||
"type": "string",
|
||||
"format": "date-time"
|
||||
},
|
||||
"updated_at": {
|
||||
"type": "string",
|
||||
"format": "date-time"
|
||||
},
|
||||
"categories": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"in": {
|
||||
"type": "array",
|
||||
"items": {
|
||||
"type": "string"
|
||||
}
|
||||
"$ref": "#/components/schemas/MemoryGetInputV2"
|
||||
}
|
||||
}
|
||||
},
|
||||
"metadata": {
|
||||
"type": "object"
|
||||
"required": true
|
||||
},
|
||||
"keywords": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"contains": {
|
||||
"type": "string"
|
||||
},
|
||||
"icontains": {
|
||||
"type": "string"
|
||||
}
|
||||
}
|
||||
}
|
||||
},
|
||||
"additionalProperties": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"in": {
|
||||
"type": "array"
|
||||
},
|
||||
"gte": {
|
||||
"type": "string"
|
||||
},
|
||||
"lte": {
|
||||
"type": "string"
|
||||
},
|
||||
"gt": {
|
||||
"type": "string"
|
||||
},
|
||||
"lt": {
|
||||
"type": "string"
|
||||
},
|
||||
"ne": {
|
||||
"type": "string"
|
||||
},
|
||||
"contains": {
|
||||
"type": "string"
|
||||
},
|
||||
"icontains": {
|
||||
"type": "string"
|
||||
}
|
||||
}
|
||||
}
|
||||
},
|
||||
"description": "Filters to apply to the memories. Available fields are: user_id, agent_id, app_id, run_id, created_at, updated_at, categories, keywords. Supports logical operators (AND, OR) and comparison operators (in, gte, lte, gt, lt, ne, contains, icontains). For categories field, use 'contains' for partial matching (e.g., {\"categories\": {\"contains\": \"finance\"}}) or 'in' for exact matching (e.g., {\"categories\": {\"in\": [\"personal_information\"]}}).",
|
||||
"style": "deepObject",
|
||||
"explode": true
|
||||
},
|
||||
{
|
||||
"name": "fields",
|
||||
"in": "query",
|
||||
"schema": {
|
||||
"type": "array",
|
||||
"items": {
|
||||
"type": "string"
|
||||
}
|
||||
},
|
||||
"description": "A list of field names to include in the response. If not provided, all fields will be returned."
|
||||
},
|
||||
{
|
||||
"name": "org_id",
|
||||
"in": "query",
|
||||
"schema": {
|
||||
"type": "string"
|
||||
},
|
||||
"description": "Filter memories by organization ID."
|
||||
},
|
||||
{
|
||||
"name": "project_id",
|
||||
"in": "query",
|
||||
"schema": {
|
||||
"type": "string"
|
||||
},
|
||||
"description": "Filter memories by project ID."
|
||||
},
|
||||
{
|
||||
"name": "page",
|
||||
"in": "query",
|
||||
"schema": {
|
||||
"type": "integer"
|
||||
},
|
||||
"description": "Page number for pagination. Default: 1."
|
||||
},
|
||||
{
|
||||
"name": "page_size",
|
||||
"in": "query",
|
||||
"schema": {
|
||||
"type": "integer"
|
||||
},
|
||||
"description": "Number of items per page. Default: 100."
|
||||
}
|
||||
],
|
||||
"responses": {
|
||||
"200": {
|
||||
"description": "Successfully retrieved memories.",
|
||||
@@ -2357,7 +2236,7 @@
|
||||
"x-code-samples": [
|
||||
{
|
||||
"lang": "Python",
|
||||
"source": "import requests\n\nurl = \"https://api.mem0.ai/api/v1/orgs/organizations/\"\n\nheaders = {\"Authorization\": \"<api-key>\"}\n\nresponse = requests.request(\"GET\", url, headers=headers)\n\nprint(response.text)"
|
||||
"source": "import requests\n\nurl = \"https://api.mem0.ai/api/v1/orgs/organizations/\"\n\nheaders = {\"Authorization\": \"Token <api-key>\"}\n\nresponse = requests.request(\"GET\", url, headers=headers)\n\nprint(response.text)"
|
||||
},
|
||||
{
|
||||
"lang": "JavaScript",
|
||||
@@ -2454,7 +2333,7 @@
|
||||
"x-code-samples": [
|
||||
{
|
||||
"lang": "Python",
|
||||
"source": "import requests\n\nurl = \"https://api.mem0.ai/api/v1/orgs/organizations/\"\n\npayload = {\"name\": \"<string>\"}\nheaders = {\n \"Authorization\": \"<api-key>\",\n \"Content-Type\": \"application/json\"\n}\n\nresponse = requests.request(\"POST\", url, json=payload, headers=headers)\n\nprint(response.text)"
|
||||
"source": "import requests\n\nurl = \"https://api.mem0.ai/api/v1/orgs/organizations/\"\n\npayload = {\"name\": \"<string>\"}\nheaders = {\n \"Authorization\": \"Token <api-key>\",\n \"Content-Type\": \"application/json\"\n}\n\nresponse = requests.request(\"POST\", url, json=payload, headers=headers)\n\nprint(response.text)"
|
||||
},
|
||||
{
|
||||
"lang": "JavaScript",
|
||||
@@ -2685,7 +2564,7 @@
|
||||
"x-code-samples": [
|
||||
{
|
||||
"lang": "Python",
|
||||
"source": "import requests\n\nurl = \"https://api.mem0.ai/api/v1/orgs/organizations/{org_id}/\"\n\nheaders = {\"Authorization\": \"<api-key>\"}\n\nresponse = requests.request(\"DELETE\", url, headers=headers)\n\nprint(response.text)"
|
||||
"source": "import requests\n\nurl = \"https://api.mem0.ai/api/v1/orgs/organizations/{org_id}/\"\n\nheaders = {\"Authorization\": \"Token <api-key>\"}\n\nresponse = requests.request(\"DELETE\", url, headers=headers)\n\nprint(response.text)"
|
||||
},
|
||||
{
|
||||
"lang": "JavaScript",
|
||||
@@ -2779,7 +2658,7 @@
|
||||
"x-code-samples": [
|
||||
{
|
||||
"lang": "Python",
|
||||
"source": "import requests\n\nurl = \"https://api.mem0.ai/api/v1/orgs/organizations/{org_id}/members/\"\n\nheaders = {\"Authorization\": \"<api-key>\"}\n\nresponse = requests.request(\"GET\", url, headers=headers)\n\nprint(response.text)"
|
||||
"source": "import requests\n\nurl = \"https://api.mem0.ai/api/v1/orgs/organizations/{org_id}/members/\"\n\nheaders = {\"Authorization\": \"Token <api-key>\"}\n\nresponse = requests.request(\"GET\", url, headers=headers)\n\nprint(response.text)"
|
||||
},
|
||||
{
|
||||
"lang": "JavaScript",
|
||||
@@ -2904,7 +2783,7 @@
|
||||
"x-code-samples": [
|
||||
{
|
||||
"lang": "Python",
|
||||
"source": "import requests\n\nurl = \"https://api.mem0.ai/api/v1/orgs/organizations/{org_id}/members/\"\n\npayload = {\n \"email\": \"<string>\",\n \"role\": \"<string>\"\n}\nheaders = {\n \"Authorization\": \"<api-key>\",\n \"Content-Type\": \"application/json\"\n}\n\nresponse = requests.request(\"PUT\", url, json=payload, headers=headers)\n\nprint(response.text)"
|
||||
"source": "import requests\n\nurl = \"https://api.mem0.ai/api/v1/orgs/organizations/{org_id}/members/\"\n\npayload = {\n \"email\": \"<string>\",\n \"role\": \"<string>\"\n}\nheaders = {\n \"Authorization\": \"Token <api-key>\",\n \"Content-Type\": \"application/json\"\n}\n\nresponse = requests.request(\"PUT\", url, json=payload, headers=headers)\n\nprint(response.text)"
|
||||
},
|
||||
{
|
||||
"lang": "JavaScript",
|
||||
@@ -3029,7 +2908,7 @@
|
||||
"x-code-samples": [
|
||||
{
|
||||
"lang": "Python",
|
||||
"source": "import requests\n\nurl = \"https://api.mem0.ai/api/v1/orgs/organizations/{org_id}/members/\"\n\npayload = {\n \"email\": \"<string>\",\n \"role\": \"<string>\"\n}\nheaders = {\n \"Authorization\": \"<api-key>\",\n \"Content-Type\": \"application/json\"\n}\n\nresponse = requests.request(\"POST\", url, json=payload, headers=headers)\n\nprint(response.text)"
|
||||
"source": "import requests\n\nurl = \"https://api.mem0.ai/api/v1/orgs/organizations/{org_id}/members/\"\n\npayload = {\n \"email\": \"<string>\",\n \"role\": \"<string>\"\n}\nheaders = {\n \"Authorization\": \"Token <api-key>\",\n \"Content-Type\": \"application/json\"\n}\n\nresponse = requests.request(\"POST\", url, json=payload, headers=headers)\n\nprint(response.text)"
|
||||
},
|
||||
{
|
||||
"lang": "JavaScript",
|
||||
@@ -3126,7 +3005,7 @@
|
||||
"x-code-samples": [
|
||||
{
|
||||
"lang": "Python",
|
||||
"source": "import requests\n\nurl = \"https://api.mem0.ai/api/v1/orgs/organizations/{org_id}/members/\"\n\npayload = {\"email\": \"<string>\"}\nheaders = {\n \"Authorization\": \"<api-key>\",\n \"Content-Type\": \"application/json\"\n}\n\nresponse = requests.request(\"DELETE\", url, json=payload, headers=headers)\n\nprint(response.text)"
|
||||
"source": "import requests\n\nurl = \"https://api.mem0.ai/api/v1/orgs/organizations/{org_id}/members/\"\n\npayload = {\"email\": \"<string>\"}\nheaders = {\n \"Authorization\": \"Token <api-key>\",\n \"Content-Type\": \"application/json\"\n}\n\nresponse = requests.request(\"DELETE\", url, json=payload, headers=headers)\n\nprint(response.text)"
|
||||
},
|
||||
{
|
||||
"lang": "JavaScript",
|
||||
@@ -3233,7 +3112,7 @@
|
||||
"x-code-samples": [
|
||||
{
|
||||
"lang": "Python",
|
||||
"source": "import requests\n\nurl = \"https://api.mem0.ai/api/v1/orgs/organizations/{org_id}/projects/\"\n\nheaders = {\"Authorization\": \"<api-key>\"}\n\nresponse = requests.request(\"GET\", url, headers=headers)\n\nprint(response.text)"
|
||||
"source": "import requests\n\nurl = \"https://api.mem0.ai/api/v1/orgs/organizations/{org_id}/projects/\"\n\nheaders = {\"Authorization\": \"Token <api-key>\"}\n\nresponse = requests.request(\"GET\", url, headers=headers)\n\nprint(response.text)"
|
||||
},
|
||||
{
|
||||
"lang": "JavaScript",
|
||||
@@ -3352,7 +3231,7 @@
|
||||
"x-code-samples": [
|
||||
{
|
||||
"lang": "Python",
|
||||
"source": "import requests\n\nurl = \"https://api.mem0.ai/api/v1/orgs/organizations/{org_id}/projects/\"\n\npayload = {\"name\": \"<string>\"}\nheaders = {\n \"Authorization\": \"<api-key>\",\n \"Content-Type\": \"application/json\"\n}\n\nresponse = requests.request(\"POST\", url, json=payload, headers=headers)\n\nprint(response.text)"
|
||||
"source": "import requests\n\nurl = \"https://api.mem0.ai/api/v1/orgs/organizations/{org_id}/projects/\"\n\npayload = {\"name\": \"<string>\"}\nheaders = {\n \"Authorization\": \"Token <api-key>\",\n \"Content-Type\": \"application/json\"\n}\n\nresponse = requests.request(\"POST\", url, json=payload, headers=headers)\n\nprint(response.text)"
|
||||
},
|
||||
{
|
||||
"lang": "JavaScript",
|
||||
@@ -3706,7 +3585,7 @@
|
||||
"x-code-samples": [
|
||||
{
|
||||
"lang": "Python",
|
||||
"source": "import requests\n\nurl = \"https://api.mem0.ai/api/v1/orgs/organizations/{org_id}/projects/{project_id}/\"\n\nheaders = {\"Authorization\": \"<api-key>\"}\n\nresponse = requests.request(\"DELETE\", url, headers=headers)\n\nprint(response.text)"
|
||||
"source": "import requests\n\nurl = \"https://api.mem0.ai/api/v1/orgs/organizations/{org_id}/projects/{project_id}/\"\n\nheaders = {\"Authorization\": \"Token <api-key>\"}\n\nresponse = requests.request(\"DELETE\", url, headers=headers)\n\nprint(response.text)"
|
||||
},
|
||||
{
|
||||
"lang": "JavaScript",
|
||||
@@ -3806,7 +3685,7 @@
|
||||
"x-code-samples": [
|
||||
{
|
||||
"lang": "Python",
|
||||
"source": "import requests\n\nurl = \"https://api.mem0.ai/api/v1/orgs/organizations/{org_id}/projects/{project_id}/members/\"\n\nheaders = {\"Authorization\": \"<api-key>\"}\n\nresponse = requests.request(\"GET\", url, headers=headers)\n\nprint(response.text)"
|
||||
"source": "import requests\n\nurl = \"https://api.mem0.ai/api/v1/orgs/organizations/{org_id}/projects/{project_id}/members/\"\n\nheaders = {\"Authorization\": \"Token <api-key>\"}\n\nresponse = requests.request(\"GET\", url, headers=headers)\n\nprint(response.text)"
|
||||
},
|
||||
{
|
||||
"lang": "JavaScript",
|
||||
@@ -3934,7 +3813,7 @@
|
||||
"x-code-samples": [
|
||||
{
|
||||
"lang": "Python",
|
||||
"source": "import requests\n\nurl = \"https://api.mem0.ai/api/v1/orgs/organizations/{org_id}/projects/{project_id}/members/\"\n\npayload = {\n \"email\": \"<string>\",\n \"role\": \"<string>\"\n}\nheaders = {\n \"Authorization\": \"<api-key>\",\n \"Content-Type\": \"application/json\"\n}\n\nresponse = requests.request(\"POST\", url, json=payload, headers=headers)\n\nprint(response.text)"
|
||||
"source": "import requests\n\nurl = \"https://api.mem0.ai/api/v1/orgs/organizations/{org_id}/projects/{project_id}/members/\"\n\npayload = {\n \"email\": \"<string>\",\n \"role\": \"<string>\"\n}\nheaders = {\n \"Authorization\": \"Token <api-key>\",\n \"Content-Type\": \"application/json\"\n}\n\nresponse = requests.request(\"POST\", url, json=payload, headers=headers)\n\nprint(response.text)"
|
||||
},
|
||||
{
|
||||
"lang": "JavaScript",
|
||||
@@ -4062,7 +3941,7 @@
|
||||
"x-code-samples": [
|
||||
{
|
||||
"lang": "Python",
|
||||
"source": "import requests\n\nurl = \"https://api.mem0.ai/api/v1/orgs/organizations/{org_id}/projects/{project_id}/members/\"\n\npayload = {\n \"email\": \"<string>\",\n \"role\": \"<string>\"\n}\nheaders = {\n \"Authorization\": \"<api-key>\",\n \"Content-Type\": \"application/json\"\n}\n\nresponse = requests.request(\"PUT\", url, json=payload, headers=headers)\n\nprint(response.text)"
|
||||
"source": "import requests\n\nurl = \"https://api.mem0.ai/api/v1/orgs/organizations/{org_id}/projects/{project_id}/members/\"\n\npayload = {\n \"email\": \"<string>\",\n \"role\": \"<string>\"\n}\nheaders = {\n \"Authorization\": \"Token <api-key>\",\n \"Content-Type\": \"application/json\"\n}\n\nresponse = requests.request(\"PUT\", url, json=payload, headers=headers)\n\nprint(response.text)"
|
||||
},
|
||||
{
|
||||
"lang": "JavaScript",
|
||||
@@ -4174,7 +4053,7 @@
|
||||
"x-code-samples": [
|
||||
{
|
||||
"lang": "Python",
|
||||
"source": "import requests\n\nurl = \"https://api.mem0.ai/api/v1/orgs/organizations/{org_id}/projects/{project_id}/members/\"\n\nheaders = {\"Authorization\": \"<api-key>\"}\n\nresponse = requests.request(\"DELETE\", url, headers=headers)\n\nprint(response.text)"
|
||||
"source": "import requests\n\nurl = \"https://api.mem0.ai/api/v1/orgs/organizations/{org_id}/projects/{project_id}/members/\"\n\nheaders = {\"Authorization\": \"Token <api-key>\"}\n\nresponse = requests.request(\"DELETE\", url, headers=headers)\n\nprint(response.text)"
|
||||
},
|
||||
{
|
||||
"lang": "JavaScript",
|
||||
@@ -5329,6 +5208,127 @@
|
||||
}
|
||||
}
|
||||
},
|
||||
"MemoryGetInputV2": {
|
||||
"type": "object",
|
||||
"required": [
|
||||
"filters"
|
||||
],
|
||||
"properties": {
|
||||
"filters": {
|
||||
"title": "Filters",
|
||||
"type": "object",
|
||||
"description": "A dictionary of filters to apply to retrieve memories. Available fields are: user_id, agent_id, app_id, run_id, created_at, updated_at, categories, keywords. Supports logical operators (AND, OR) and comparison operators (in, gte, lte, gt, lt, ne, contains, icontains, *). For categories field, use 'contains' for partial matching (e.g., {\"categories\": {\"contains\": \"finance\"}}) or 'in' for exact matching (e.g., {\"categories\": {\"in\": [\"personal_information\"]}}).",
|
||||
"properties": {
|
||||
"user_id": {
|
||||
"type": "string"
|
||||
},
|
||||
"agent_id": {
|
||||
"type": "string"
|
||||
},
|
||||
"app_id": {
|
||||
"type": "string"
|
||||
},
|
||||
"run_id": {
|
||||
"type": "string"
|
||||
},
|
||||
"created_at": {
|
||||
"type": "string",
|
||||
"format": "date-time"
|
||||
},
|
||||
"updated_at": {
|
||||
"type": "string",
|
||||
"format": "date-time"
|
||||
},
|
||||
"keywords": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"contains": {
|
||||
"type": "string"
|
||||
},
|
||||
"icontains": {
|
||||
"type": "string"
|
||||
}
|
||||
}
|
||||
},
|
||||
"categories": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"in": {
|
||||
"type": "array",
|
||||
"items": {
|
||||
"type": "string"
|
||||
}
|
||||
}
|
||||
}
|
||||
},
|
||||
"metadata": {
|
||||
"type": "object"
|
||||
}
|
||||
},
|
||||
"additionalProperties": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"in": {
|
||||
"type": "array"
|
||||
},
|
||||
"gte": {
|
||||
"type": "string"
|
||||
},
|
||||
"lte": {
|
||||
"type": "string"
|
||||
},
|
||||
"gt": {
|
||||
"type": "string"
|
||||
},
|
||||
"lt": {
|
||||
"type": "string"
|
||||
},
|
||||
"ne": {
|
||||
"type": "string"
|
||||
},
|
||||
"contains": {
|
||||
"type": "string"
|
||||
},
|
||||
"icontains": {
|
||||
"type": "string"
|
||||
}
|
||||
}
|
||||
}
|
||||
},
|
||||
"fields": {
|
||||
"title": "Fields",
|
||||
"type": "array",
|
||||
"items": {
|
||||
"type": "string"
|
||||
},
|
||||
"description": "A list of field names to include in the response. If not provided, all fields will be returned."
|
||||
},
|
||||
"page": {
|
||||
"title": "Page",
|
||||
"type": "integer",
|
||||
"default": 1,
|
||||
"description": "Page number for pagination. Default: 1"
|
||||
},
|
||||
"page_size": {
|
||||
"title": "Page Size",
|
||||
"type": "integer",
|
||||
"default": 100,
|
||||
"description": "Number of items per page. Default: 100"
|
||||
},
|
||||
"org_id": {
|
||||
"title": "Organization id",
|
||||
"type": "string",
|
||||
"nullable": true,
|
||||
"description": "The unique identifier of the organization associated with the memory."
|
||||
},
|
||||
"project_id": {
|
||||
"title": "Project id",
|
||||
"type": "string",
|
||||
"nullable": true,
|
||||
"description": "The unique identifier of the project associated with the memory."
|
||||
}
|
||||
}
|
||||
},
|
||||
"CreateRun": {
|
||||
"required": [
|
||||
"run_id"
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
---
|
||||
title: "AWS bedrock, OpenSearch and Neptune Analytics"
|
||||
title: "AWS Bedrock Example"
|
||||
---
|
||||
|
||||
This example demonstrates how to configure and use the `mem0ai` SDK with **AWS Bedrock**, **OpenSearch Service (AOSS)**, and **AWS Neptune Analytics** for persistent memory capabilities in Python.
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
---
|
||||
title: "Neptune Analytics Hybrid Store"
|
||||
title: "AWS Neptune Analytics"
|
||||
---
|
||||
|
||||
This example demonstrates how to configure and use the `mem0ai` SDK with **AWS Bedrock** and **AWS Neptune Analytics** for persistent memory capabilities in Python.
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
---
|
||||
title: 'Personalized Search with Mem0 and Tavily'
|
||||
title: 'Personalized Search with Tavily'
|
||||
---
|
||||
|
||||
<Snippet file="security-compliance.mdx" />
|
||||
|
||||
@@ -1,8 +1,8 @@
|
||||
---
|
||||
title: Google Agent Development Kit
|
||||
title: Google ADK
|
||||
---
|
||||
|
||||
Integrate [**Mem0**](https://github.com/mem0ai/mem0) with [Google Agent Development Kit (ADK)](https://github.com/google/adk-python), an open-source framework for building multi-agent workflows. This integration enables agents to access persistent memory across conversations, enhancing context retention and personalization.
|
||||
Integrate [**Mem0**](https://github.com/mem0ai/mem0) with [Google ADK (Agent Development Kit)](https://github.com/google/adk-python), an open-source framework for building multi-agent workflows. This integration enables agents to access persistent memory across conversations, enhancing context retention and personalization.
|
||||
|
||||
## Overview
|
||||
|
||||
|
||||
Reference in New Issue
Block a user