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42 行
1.4 KiB
Plaintext
42 行
1.4 KiB
Plaintext
---
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title: "LM Studio"
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description: "Configure LM Studio as an embedding provider in Mem0 for local embedding generation with models like nomic-embed-text."
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---
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You can use embedding models from LM Studio to run Mem0 locally.
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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["OPENAI_API_KEY"] = "your_api_key" # For LLM
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config = {
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"embedder": {
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"provider": "lmstudio",
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"config": {
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"model": "nomic-ai/nomic-embed-text-v1.5-GGUF"
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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 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 LM Studio embedder:
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| Parameter | Description | Default Value |
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| --- | --- | --- |
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| `model` | The name of the LM Studio model to use | `nomic-ai/nomic-embed-text-v1.5-GGUF` |
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| `embedding_dims` | Dimensions of the embedding model | `1536` |
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| `lmstudio_base_url` | Base URL for LM Studio connection | `http://localhost:1234/v1` | |