58 lines
1.9 KiB
Plaintext
58 lines
1.9 KiB
Plaintext
---
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title: Azure OpenAI
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---
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To use Azure OpenAI embedding models, set the `EMBEDDING_AZURE_OPENAI_API_KEY`, `EMBEDDING_AZURE_DEPLOYMENT`, `EMBEDDING_AZURE_ENDPOINT` and `EMBEDDING_AZURE_API_VERSION` environment variables. You can obtain the Azure OpenAI API key from the Azure.
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### Usage
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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["EMBEDDING_AZURE_OPENAI_API_KEY"] = "your-api-key"
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os.environ["EMBEDDING_AZURE_DEPLOYMENT"] = "your-deployment-name"
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os.environ["EMBEDDING_AZURE_ENDPOINT"] = "your-api-base-url"
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os.environ["EMBEDDING_AZURE_API_VERSION"] = "version-to-use"
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os.environ["OPENAI_API_KEY"] = "your_api_key" # For LLM
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config = {
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"embedder": {
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"provider": "azure_openai",
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"config": {
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"model": "text-embedding-3-large"
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"azure_kwargs": {
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"api_version": "",
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"azure_deployment": "",
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"azure_endpoint": "",
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"api_key": "",
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"default_headers": {
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"CustomHeader": "your-custom-header",
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}
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}
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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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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 a 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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m.add(messages, user_id="john")
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```
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### Config
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Here are the parameters available for configuring Azure OpenAI embedder:
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| Parameter | Description | Default Value |
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| --- | --- | --- |
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| `model` | The name of the embedding model to use | `text-embedding-3-small` |
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| `embedding_dims` | Dimensions of the embedding model | `1536` |
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| `azure_kwargs` | The Azure OpenAI configs | `config_keys` |
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