65 lines
1.4 KiB
Plaintext
65 lines
1.4 KiB
Plaintext
---
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title: Embedding models
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---
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## Overview
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Mem0 offers support for various embedding models, allowing users to choose the one that best suits their needs.
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<CardGroup cols={3}>
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<Card title="OpenAI" href="#openai"></Card>
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<Card title="Ollama" href="#ollama"></Card>
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</CodeGroup>
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> When using `Qdrant` as a vector database, ensure you update the `embedding_model_dims` to match the dimensions of the embedding model you are using.
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## OpenAI
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To use OpenAI embedding models, set the `OPENAI_API_KEY` environment variable. You can obtain the OpenAI API key from the [OpenAI Platform](https://platform.openai.com/account/api-keys).
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Example of how to select the desired embedding model:
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```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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config = {
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"embedder": {
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"provider": "openai",
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"config": {
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"model": "text-embedding-3-large"
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}
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}
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}
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m = Memory.from_config(config)
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m.add("I'm visiting Paris", user_id="john")
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```
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## Ollama
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You can use embedding models from Ollama to run Mem0 locally.
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Here's how to select it:
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```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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config = {
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"embedder": {
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"provider": "ollama",
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"config": {
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"model": "mxbai-embed-large"
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}
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}
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}
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m = Memory.from_config(config)
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m.add("I'm visiting Paris", user_id="john")
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```
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