fix(docs): SEO improvements for page titles, internal links, and URL structure (#7224)
This commit is contained in:
@@ -0,0 +1,83 @@
|
||||
---
|
||||
title: Google AI
|
||||
seo:
|
||||
title: "Google AI as Embedding Provider - Mem0"
|
||||
description: "Configure Google AI as an embedding provider in Mem0 using Gemini models and the GOOGLE_API_KEY variable."
|
||||
---
|
||||
|
||||
To use Google AI embedding models, set the `GOOGLE_API_KEY` environment variables. You can obtain the Gemini API key from [here](https://aistudio.google.com/app/apikey).
|
||||
|
||||
### Usage
|
||||
|
||||
<CodeGroup>
|
||||
```python Python
|
||||
import os
|
||||
from mem0 import Memory
|
||||
|
||||
os.environ["GOOGLE_API_KEY"] = "key"
|
||||
os.environ["OPENAI_API_KEY"] = "your_api_key" # For LLM
|
||||
|
||||
config = {
|
||||
"embedder": {
|
||||
"provider": "gemini",
|
||||
"config": {
|
||||
"model": "models/gemini-embedding-001",
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
m = Memory.from_config(config)
|
||||
messages = [
|
||||
{"role": "user", "content": "I'm planning to watch a movie tonight. Any recommendations?"},
|
||||
{"role": "assistant", "content": "How about thriller movies? They can be quite engaging."},
|
||||
{"role": "user", "content": "I'm not a big fan of thriller movies but I love sci-fi movies."},
|
||||
{"role": "assistant", "content": "Got it! I'll avoid thriller recommendations and suggest sci-fi movies in the future."}
|
||||
]
|
||||
m.add(messages, user_id="john")
|
||||
```
|
||||
|
||||
```typescript TypeScript
|
||||
import { Memory } from 'mem0ai/oss';
|
||||
|
||||
const config = {
|
||||
embedder: {
|
||||
provider: "google",
|
||||
config: {
|
||||
apiKey: process.env["GOOGLE_API_KEY"],
|
||||
model: "gemini-embedding-001",
|
||||
embeddingDims: 1536,
|
||||
},
|
||||
},
|
||||
};
|
||||
|
||||
const memory = new Memory(config);
|
||||
const messages = [
|
||||
{"role": "user", "content": "I'm planning to watch a movie tonight. Any recommendations?"},
|
||||
{"role": "assistant", "content": "How about thriller movies? They can be quite engaging."},
|
||||
{"role": "user", "content": "I'm not a big fan of thriller movies but I love sci-fi movies."},
|
||||
{"role": "assistant", "content": "Got it! I'll avoid thriller recommendations and suggest sci-fi movies in the future."}
|
||||
]
|
||||
await memory.add(messages, { userId: "john" });
|
||||
```
|
||||
</CodeGroup>
|
||||
|
||||
### Config
|
||||
|
||||
Here are the parameters available for configuring Gemini embedder:
|
||||
<Tabs>
|
||||
<Tab title="Python">
|
||||
| Parameter | Description | Default Value |
|
||||
| ---------------- | ------------------------------------ | ----------------------- |
|
||||
| `model` | The name of the embedding model to use| `models/gemini-embedding-001` |
|
||||
| `embedding_dims` | Dimensions of the embedding model | `768` |
|
||||
| `api_key` | The Google API key | `None` |
|
||||
| `output_dimensionality` | Output dimensionality for the embedding model (Gemini-specific; used when `embedding_dims` is not set) | `None` |
|
||||
</Tab>
|
||||
<Tab title="TypeScript">
|
||||
| Parameter | Description | Default Value |
|
||||
| ----------------- | --------------------------------------------- | -------------------------- |
|
||||
| `model` | The name of the embedding model to use | `gemini-embedding-001` |
|
||||
| `embeddingDims` | Dimensions of the embedding model. When not set, uses the model's native output dimensionality (3072 for `gemini-embedding-001`; MRL truncation to 768, 1536, or 3072 is supported) | `None` |
|
||||
| `apiKey` | Google API key | `None` |
|
||||
</Tab>
|
||||
</Tabs>
|
||||
Reference in New Issue
Block a user