Add configs to Embedding docs (#1702)

This commit is contained in:
Dev Khant
2024-08-14 16:10:48 +05:30
committed by GitHub
parent aba5bb052d
commit 10cbee943c
9 changed files with 219 additions and 66 deletions

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To use Azure OpenAI embedding models, set the `AZURE_OPENAI_API_KEY` environment variable. You can obtain the Azure OpenAI API key from the Azure.
### Usage
```python
import os
from mem0 import Memory
os.environ["OPENAI_API_KEY"] = "your_api_key"
os.environ["AZURE_OPENAI_API_KEY"] = "your_api_key"
config = {
"embedder": {
"provider": "azure_openai",
"config": {
"model": "text-embedding-3-large"
}
}
}
m = Memory.from_config(config)
m.add("I'm visiting Paris", user_id="john")
```
### Config
Here are the parameters available for configuring Azure OpenAI embedder:
| Parameter | Description | Default Value |
| --- | --- | --- |
| `model` | The name of the embedding model to use | `text-embedding-3-small` |
| `embedding_dims` | Dimensions of the embedding model | `1536` |
| `api_key` | The Azure OpenAI API key | `None` |

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You can use embedding models from Huggingface to run Mem0 locally.
### Usage
```python
import os
from mem0 import Memory
os.environ["OPENAI_API_KEY"] = "your_api_key"
config = {
"embedder": {
"provider": "huggingface",
"config": {
"model": "multi-qa-MiniLM-L6-cos-v1"
}
}
}
m = Memory.from_config(config)
m.add("I'm visiting Paris", user_id="john")
```
### Config
Here are the parameters available for configuring Huggingface embedder:
| Parameter | Description | Default Value |
| --- | --- | --- |
| `model` | The name of the model to use | `multi-qa-MiniLM-L6-cos-v1` |
| `embedding_dims` | Dimensions of the embedding model | `selected_model_dimensions` |
| `model_kwargs` | Additional arguments for the model | `None` |

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You can use embedding models from Ollama to run Mem0 locally.
### Usage
```python
import os
from mem0 import Memory
os.environ["OPENAI_API_KEY"] = "your_api_key"
config = {
"embedder": {
"provider": "ollama",
"config": {
"model": "mxbai-embed-large"
}
}
}
m = Memory.from_config(config)
m.add("I'm visiting Paris", user_id="john")
```
### Config
Here are the parameters available for configuring Ollama embedder:
| Parameter | Description | Default Value |
| --- | --- | --- |
| `model` | The name of the OpenAI model to use | `nomic-embed-text` |
| `embedding_dims` | Dimensions of the embedding model | `512` |
| `ollama_base_url` | Base URL for ollama connection | `None` |

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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).
### Usage
```python
import os
from mem0 import Memory
os.environ["OPENAI_API_KEY"] = "your_api_key"
config = {
"embedder": {
"provider": "openai",
"config": {
"model": "text-embedding-3-large"
}
}
}
m = Memory.from_config(config)
m.add("I'm visiting Paris", user_id="john")
```
### Config
Here are the parameters available for configuring OpenAI embedder:
| Parameter | Description | Default Value |
| --- | --- | --- |
| `model` | The name of the embedding model to use | `text-embedding-3-small` |
| `embedding_dims` | Dimensions of the embedding model | `1536` |
| `api_key` | The OpenAI API key | `None` |