Make Platform Memory Operations Smarter

<Info> **Prerequisites** - Platform workspace with API key - Python 3.10+ and Node.js 18+ - Async memories enabled in your dashboard (Settings → Memory Options) </Info> <Tip> Need a refresher on the core concepts first? Review the <Link href="/core-concepts/memory-operations/add">Add Memory</Link> overview, then come back for the advanced flow. </Tip>

Install and authenticate

<Tabs> <Tab title="Python"> <Steps> <Step title="Install the SDK with async extras"> ```bash pip install "mem0ai[async]" ``` </Step> <Step title="Export your API key"> ```bash export MEM0_API_KEY="sk-platform-..." ``` </Step> <Step title="Create an async client"> ```python import os from mem0 import AsyncMemoryClient

memory = AsyncMemoryClient(api_key=os.environ["MEM0_API_KEY"])

</Step>
</Steps>
  </Tab>
  <Tab title="TypeScript">
<Steps>
<Step title="Install the OSS SDK">
```bash
npm install mem0ai

</Step> <Step title="Load your API key"> ```bash export MEM0_API_KEY="sk-platform-..." ``` </Step> <Step title="Instantiate the client"> ```typescript import { Memory } from "mem0ai";

const memory = new Memory({ apiKey: process.env.MEM0_API_KEY!, async: true });

</Step>
</Steps>
  </Tab>
</Tabs>

## Add memories with metadata and graph context

<Tabs>
  <Tab title="Python">
<Steps>
<Step title="Record conversations with metadata">
```python
conversation = [
    {"role": "user", "content": "I'm Morgan, planning a 3-week trip to Japan in May."},
    {"role": "assistant", "content": "Great! I'll track dietary notes and cities you mention."},
    {"role": "user", "content": "Please remember I avoid shellfish and prefer boutique hotels in Tokyo."},
]

result = await memory.add(
    conversation,
    user_id="traveler-42",
    metadata={"trip": "japan-2025", "preferences": ["boutique", "no-shellfish"]},
    run_id="planning-call-1",
)

</Step> </Steps> </Tab> <Tab title="TypeScript"> <Steps> <Step title="Capture context-rich memories"> ```typescript const conversation = [ { role: "user", content: "I'm Morgan, planning a 3-week trip to Japan in May." }, { role: "assistant", content: "Great! I'll track dietary notes and cities you mention." }, { role: "user", content: "Please remember I avoid shellfish and love boutique hotels in Tokyo." }, ];

const result = await memory.add(conversation, { userId: "traveler-42", metadata: { trip: "japan-2025", preferences: ["boutique", "no-shellfish"] }, runId: "planning-call-1", });

</Step>
</Steps>
  </Tab>
</Tabs>

<Info icon="check">
  Successful calls return memories tagged with the metadata you passed. In the dashboard, confirm a graph edge between “Morgan” and “Tokyo” and verify the `trip=japan-2025` tag exists.
</Info>

## Retrieve and refine

<Tabs>
  <Tab title="Python">
<Steps>
<Step title="Filter by metadata + reranker">
```python
matches = await memory.search(
    "Any food alerts?",
    user_id="traveler-42",
    filters={"metadata.trip": "japan-2025"},
    rerank=True,
    include_vectors=False,
)

</Step> <Step title="Update a memory inline"> ```python await memory.update( memory_id=matches["results"][0]["id"], content="Morgan avoids shellfish and prefers boutique hotels in central Tokyo.", ) ``` </Step> </Steps> </Tab> <Tab title="TypeScript"> <Steps> <Step title="Search with metadata filters"> ```typescript const matches = await memory.search("Any food alerts?", { userId: "traveler-42", filters: { "metadata.trip": "japan-2025" }, rerank: true, includeVectors: false, }); ``` </Step> <Step title="Apply an update"> ```typescript await memory.update(matches.results[0].id, { content: "Morgan avoids shellfish and prefers boutique hotels in central Tokyo.", }); ``` </Step> </Steps> </Tab> </Tabs>

Clean up

<Tabs> <Tab title="Python"> <Steps> <Step title="Delete scoped memories"> ```python await memory.delete_all(user_id="traveler-42", run_id="planning-call-1") ``` </Step> </Steps> </Tab> <Tab title="TypeScript"> <Steps> <Step title="Remove the run"> ```typescript await memory.deleteAll({ userId: "traveler-42", runId: "planning-call-1" }); ``` </Step> </Steps> </Tab> </Tabs>

Quick recovery

Empty results with filters: log filters values and confirm metadata keys match (case-sensitive).

<Warning> Metadata keys become part of your filtering schema. Stick to lowercase snake_case (`trip_id`, `preferences`) to avoid collisions down the road. </Warning> <CardGroup cols={2}> <Card title="Tune Metadata Filtering" description="Layer field-level filters on top of advanced operations." icon="funnel" href="/open-source/features/metadata-filtering" /> <Card title="Explore Reranker Search" description="See how rerankers boost accuracy after vector + graph retrieval." icon="sparkles" href="/open-source/features/reranker-search" /> </CardGroup>

Advanced Memory Operations

Make Platform Memory Operations Smarter

Install and authenticate

Clean up

Quick recovery