215 lines
6.3 KiB
Plaintext
215 lines
6.3 KiB
Plaintext
---
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title: Search Memory
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description: Retrieve relevant memories from Mem0 using powerful semantic and filtered search capabilities.
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icon: "magnifying-glass"
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iconType: "solid"
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---
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# How Mem0 Searches Memory
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Mem0’s search operation lets agents ask natural-language questions and get back the memories that matter most. It’s the bridge between everything you’ve stored and the next response your agent writes.
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<Info>
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**Why it matters**
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- Retrieves the right facts without rebuilding prompts from scratch.
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- Supports both managed Platform and OSS so you can test locally and deploy at scale.
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- Keeps results relevant with filters, rerankers, and thresholds.
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</Info>
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## Key terms
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- **Query** – Natural-language question or statement you pass to `search`.
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- **Filters** – JSON logic (AND/OR, comparison operators) that narrows results by user, categories, dates, etc.
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- **top_k / threshold** – Controls how many memories return and the minimum similarity score.
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- **Rerank** – Optional second pass that boosts precision when a reranker is configured.
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## Architecture
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<Frame caption="Architecture diagram illustrating the memory search process.">
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<img src="../../images/search_architecture.png" />
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</Frame>
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<Steps>
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<Step title="Query processing">
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Mem0 cleans and enriches your natural-language query so the downstream embedding search is accurate.
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</Step>
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<Step title="Vector search">
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Embeddings locate the closest memories using cosine similarity across your scoped dataset.
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</Step>
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<Step title="Filtering & reranking">
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Logical filters narrow candidates; rerankers or thresholds fine-tune ordering.
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</Step>
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<Step title="Results delivery">
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Formatted memories (with metadata and timestamps) return to your agent or calling service.
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</Step>
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</Steps>
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This pipeline runs the same way for the hosted Platform API and the OSS SDK.
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---
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## Search 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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query = "What do you know about me?"
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filters = {
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"OR": [
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{"user_id": "alice"},
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{"agent_id": {"in": ["travel-assistant", "customer-support"]}}
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]
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}
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results = client.search(query, filters=filters)
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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 query = "I'm craving some pizza. Any recommendations?";
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const filters = {
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AND: [
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{ user_id: "alice" }
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]
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};
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const results = await client.search(query, {
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filters
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});
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```
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</CodeGroup>
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---
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## Search with Mem0 Open Source
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<CodeGroup>
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```python Python
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from mem0 import Memory
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m = Memory()
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# Simple search
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related_memories = m.search("Should I drink coffee or tea?", user_id="alice")
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# Search with filters
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memories = m.search(
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"food preferences",
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user_id="alice",
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filters={"categories": {"contains": "diet"}}
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)
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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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// Simple search
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const relatedMemories = memory.search("Should I drink coffee or tea?", { userId: "alice" });
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// Search with filters (if supported)
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const memories = memory.search("food preferences", {
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userId: "alice",
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filters: { categories: { contains: "diet" } }
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});
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```
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</CodeGroup>
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---
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<Info icon="check">
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Expect an array of memory documents. Platform responses include vectors, metadata, and timestamps; OSS returns your stored schema.
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</Info>
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## Filter patterns
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Filters help narrow down search results. Common use cases:
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**Filter by Session Context:**
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```python
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# Get memories from a specific agent session
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m.search("query", user_id="alice", agent_id="chatbot", run_id="session-123")
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```
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**Filter by Date Range:**
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```python
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# Platform only - date filtering
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client.search("recent memories", filters={
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"AND": [
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{"user_id": "alice"},
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{"created_at": {"gte": "2024-07-01"}}
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]
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})
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```
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**Filter by Categories:**
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```python
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# Platform only - category filtering
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client.search("preferences", filters={
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"AND": [
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{"user_id": "alice"},
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{"categories": {"contains": "food"}}
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]
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})
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```
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---
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## Tips for better search
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- **Use natural language**: Mem0 understands intent, so describe what you're looking for naturally
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- **Scope with session IDs**: Always provide at least `user_id` to scope search to relevant memories
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- **Combine filters**: Use AND/OR logic to create precise queries (Platform)
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- **Consider wildcard filters**: Use wildcard filters (e.g., `run_id: "*"`) for broader matches
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- **Tune parameters**: Adjust `top_k` for result count, `threshold` for relevance cutoff
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- **Enable reranking**: Use `rerank=True` (default) when you have a reranker configured
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### More Details
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For the full list of filter logic, comparison operators, and optional search parameters, see the
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[Search Memory API Reference](/api-reference/memory/search-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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| Filters | Logical operators (`AND`, `OR`, comparisons) with field-level access | Basic field filters, extend via Python hooks |
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| Reranking | Toggle `rerank=True` with managed reranker catalog | Requires configuring local or third-party rerankers |
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| Thresholds | Request-level configuration (`threshold`, `top_k`) | Controlled via SDK parameters |
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| Response metadata | Includes confidence scores, timestamps, dashboard visibility | Determined by your storage backend |
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## Put it into practice
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- Revisit the <Link href="/core-concepts/memory-operations/add">Add Memory</Link> guide to ensure you capture the context you expect to retrieve.
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- Configure rerankers and filters in <Link href="/platform/features/advanced-retrieval">Advanced Retrieval</Link> for higher precision.
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## See it live
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- <Link href="/cookbooks/operations/support-inbox">Support Inbox with Mem0</Link> demonstrates scoped search with rerankers.
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- <Link href="/cookbooks/integrations/tavily-search">Tavily Search with Mem0</Link> shows hybrid search in action.
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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="Tune Update Concepts"
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description="Learn how to adjust memories after search results come back."
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icon="pencil"
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href="/core-concepts/memory-operations/update"
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/>
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<Card
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title="Build Hybrid Search"
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description="Follow the cookbook to combine Mem0 with external search."
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icon="rocket"
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href="/cookbooks/integrations/tavily-search"
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/>
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</CardGroup>
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