mem0ai--mem0
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202 行
6.7 KiB
Plaintext
202 行
6.7 KiB
Plaintext
---
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title: Add Memory
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description: Add memory into the Mem0 platform by storing user-assistant interactions and facts for later retrieval.
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icon: "plus"
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iconType: "solid"
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---
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# How Mem0 Adds Memory
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Adding memory is how Mem0 captures useful details from a conversation so your agents can reuse them later. Think of it as saving the important sentences from a chat transcript into a structured notebook your agent can search.
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## Key terms
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- **Messages**: The ordered list of user/assistant turns you send to `add`.
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- **Infer**: Controls whether Mem0 extracts structured memories (`infer=True`, default) or stores raw messages.
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- **Metadata**: Optional filters (e.g., `{"category": "movie_recommendations"}`) that improve retrieval later.
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- **User / Session identifiers**: `user_id`, `agent_id`, `app_id`, or `run_id` that scope the memory for future searches.
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- **expiration_date**: Optional `YYYY-MM-DD` date after which the memory is treated as expired. Use `expirationDate` in the JavaScript SDKs. Expired memories are hidden from `search` and `get_all` unless you pass `show_expired` (`showExpired` in JavaScript); fetching by ID still returns them.
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## How does it work?
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Mem0 offers two flows:
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- **Mem0 Platform**: Fully managed API with dashboard and scaling.
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- **Mem0 Open Source**: Local SDK that you run in your own environment.
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Both flows take the same payload and add memories through an additive pipeline.
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<Steps>
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<Step title="Information extraction">
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Mem0 sends the messages through an LLM that pulls out key facts, decisions, or preferences to remember.
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</Step>
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<Step title="Additive storage">
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New memories are added without overwriting or deleting existing memories.
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</Step>
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<Step title="Retrieval">
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Future searches rank the most relevant memories for the query.
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</Step>
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</Steps>
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<Warning>
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When you switch to `infer=False`, Mem0 stores your payload exactly as provided, so duplicates can land. Mixing both modes for the same fact can save it twice.
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</Warning>
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You trigger this pipeline with a single `add` call: no manual orchestration needed.
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## Add with Mem0 Platform
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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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messages = [
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{"role": "user", "content": "I'm planning a trip to Tokyo next month."},
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{"role": "assistant", "content": "Great! I’ll remember that for future suggestions."}
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]
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client.add(
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messages=messages,
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user_id="alice",
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)
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```
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```javascript JavaScript
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import { MemoryClient } from "mem0ai";
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const client = new MemoryClient({apiKey: "your-api-key"});
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const messages = [
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{ role: "user", content: "I'm planning a trip to Tokyo next month." },
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{ role: "assistant", content: "Great! I’ll remember that for future suggestions." }
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];
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await client.add(messages, {
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userId: "alice",
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});
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```
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</CodeGroup>
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<Info icon="check">
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Expect a `status: "PENDING"` response with an `event_id`. Poll `GET /v1/event/{event_id}/` to confirm completion.
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</Info>
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## Add with Mem0 Open Source
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<CodeGroup>
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```python Python
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import os
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from mem0 import Memory
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os.environ["OPENAI_API_KEY"] = "your-api-key"
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m = Memory()
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messages = [
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{"role": "user", "content": "I'm planning to watch a movie tonight. Any recommendations?"},
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{"role": "assistant", "content": "How about thriller movies? They can be quite engaging."},
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{"role": "user", "content": "I'm not a big fan of thriller movies but I love sci-fi movies."},
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{"role": "assistant", "content": "Got it! I'll avoid thriller recommendations and suggest sci-fi movies in the future."}
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]
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# Store inferred memories (default behavior)
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result = m.add(messages, user_id="alice", metadata={"category": "movie_recommendations"})
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# Optionally store raw messages without inference
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result = m.add(messages, user_id="alice", metadata={"category": "movie_recommendations"}, infer=False)
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# Optionally set an expiration date (YYYY-MM-DD)
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result = m.add(messages, user_id="alice", expiration_date="2030-01-31")
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```
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```javascript JavaScript
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import { Memory } from 'mem0ai/oss';
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const memory = new Memory();
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const messages = [
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{
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role: "user",
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content: "I like to drink coffee in the morning and go for a walk"
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}
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];
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const result = memory.add(messages, {
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userId: "alice",
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metadata: { category: "preferences" }
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});
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// Optionally set an expiration date (YYYY-MM-DD)
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const expiring = memory.add(messages, {
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userId: "alice",
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expirationDate: "2030-01-31",
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});
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```
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</CodeGroup>
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<Tip>
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Use `infer=False` only when you need to store raw transcripts. Most workflows benefit from Mem0 extracting structured memories automatically.
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</Tip>
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<Warning>
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If you do choose `infer=False`, keep it consistent. Raw inserts skip inference, so a later `infer=True` call with the same content can create a second memory.
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</Warning>
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## When Should You Add Memory?
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Add memory whenever your agent learns something useful:
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- A new user preference is shared
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- A decision or suggestion is made
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- A goal or task is completed
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- A new entity is introduced
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- A user gives feedback or clarification
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<Callout type="tip" icon="plug">
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**MCP Alternative**: With <Link href="/platform/mem0-mcp">Mem0 MCP</Link>, AI agents can add memories automatically based on context.
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</Callout>
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Storing this context allows the agent to reason better in future interactions.
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### More Details
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For full list of supported fields, required formats, and advanced options, see the
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[Add Memory API Reference](/api-reference/memory/add-memories).
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## Managed vs OSS differences
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| Capability | Mem0 Platform | Mem0 OSS |
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| --- | --- | --- |
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| Add behavior | ADD-only; memories accumulate | ADD-only; you control storage |
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| Rate limits | Managed quotas per workspace | Limited by your hardware and provider APIs |
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| Dashboard visibility | Yes: inspect memories visually | Inspect via CLI, logs, or custom UI |
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## Put it into practice
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- Review the <Link href="/platform/advanced-memory-operations">Advanced Memory Operations</Link> guide to layer metadata and rerankers.
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- Explore the <Link href="/api-reference/memory/add-memories">Add Memories API reference</Link> for every request/response field.
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## See it live
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- <Link href="/cookbooks/operations/support-inbox">Support Inbox with Mem0</Link> shows add + search powering a support flow.
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- <Link href="/cookbooks/companions/ai-tutor">AI Tutor with Mem0</Link> uses add to personalize lesson plans.
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{/* DEBUG: verify CTA targets */}
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<CardGroup cols={2}>
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<Card
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title="Explore Search Concepts"
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description="See how stored memories feed retrieval in the Search guide."
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icon="search"
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href="/core-concepts/memory-operations/search"
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/>
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<Card
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title="Build a Support Agent"
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description="Follow the cookbook to apply add/search/update in production."
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icon="rocket"
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href="/cookbooks/operations/support-inbox"
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/>
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</CardGroup>
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