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Add Together embedder to TS SDK (#5989)

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Co-authored-by: kartik-mem0 <kartik.labhshetwar@mem0.ai>
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Jaco-Ren
2026-07-06 20:24:14 +05:30
committed by GitHub
co-authored by kartik-mem0
parent b0bee551cb
commit 4c974c8fa8
10 changed files with 233 additions and 24 deletions
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docs/components/embedders/models/together.mdx
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@@ -1,15 +1,20 @@
---
title: Together
description: "Configure Together AI as an embedding provider in Mem0 with support for 768-dimensional embedding models."
description: "Configure Together AI as an embedding provider in Mem0 with support for 1024-dimensional embedding models."
---
To use Together embedding models, set the `TOGETHER_API_KEY` environment variable. You can obtain the Together API key from the [Together Platform](https://api.together.xyz/settings/api-keys).
To use Together embedding models, set the `TOGETHER_API_KEY` environment variable. You can obtain the Together API key from the [Together Platform](https://api.together.ai/settings/projects/~current/api-keys).
### Usage
<Note> The `embedding_model_dims` parameter for `vector_store` should be set to `768` for Together embedder. </Note>
<Note> The `embedding_model_dims` parameter for `vector_store` should be set to `1024` for Together embedder. </Note>
```python
<Warning>
**Breaking default change.** The default Together embedding model is now `intfloat/multilingual-e5-large-instruct` (**1024-dim**), replacing the previous default `togethercomputer/m2-bert-80M-8k-retrieval` (**768-dim**). If you created a self-hosted vector store with the old default, its collection is 768-dim and will reject the new 1024-dim vectors **recreate/reindex the collection at 1024 dimensions** after upgrading. To defer the change, pin the previous values explicitly (`model="togethercomputer/m2-bert-80M-8k-retrieval"`, `embedding_dims=768`) note Together no longer lists this model among its recommended embeddings, so reindexing at 1024 is the durable path.
</Warning>
<CodeGroup>
```python Python
import os
from mem0 import Memory
@@ -20,7 +25,7 @@ config = {
"embedder": {
"provider": "together",
"config": {
"model": "togethercomputer/m2-bert-80M-8k-retrieval"
"model": "intfloat/multilingual-e5-large-instruct"
}
}
}
@@ -29,18 +34,50 @@ 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": "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: 'together',
config: {
apiKey: process.env.TOGETHER_API_KEY || '',
model: 'intfloat/multilingual-e5-large-instruct',
embeddingDims: 1024,
},
},
};
const memory = new Memory(config);
await memory.add("I'm visiting Paris", { userId: "john" });
```
</CodeGroup>
### Config
Here are the parameters available for configuring Together embedder:
<Tabs>
<Tab title="Python">
| Parameter | Description | Default Value |
| --- | --- | --- |
| `model` | The name of the embedding model to use | `togethercomputer/m2-bert-80M-8k-retrieval` |
| `embedding_dims` | Dimensions of the embedding model | `768` |
| `model` | The name of the embedding model to use | `intfloat/multilingual-e5-large-instruct` |
| `embedding_dims` | Dimensions of the embedding model | `1024` |
| `api_key` | The Together API key | `None` |
</Tab>
<Tab title="TypeScript">
| Parameter | Description | Default Value |
| --- | --- | --- |
| `model` | The name of the embedding model to use | `intfloat/multilingual-e5-large-instruct` |
| `embeddingDims` | Dimensions of the embedding model for vector store configuration | `1024` |
| `apiKey` | The Together API key | `TOGETHER_API_KEY` |
| `baseURL` | Base URL for an OpenAI-compatible Together endpoint | `https://api.together.ai/v1` |
</Tab>
</Tabs>
docs/components/embedders/overview.mdx
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@@ -10,7 +10,7 @@ Mem0 offers support for various embedding models, allowing users to choose the o
See the list of supported embedders below.
<Note>
All embedders listed below are supported in the Python implementation. The TypeScript implementation supports: **OpenAI**, **Azure OpenAI**, **Google AI**, **Langchain**, **LM Studio**, and **Ollama**.
All embedders listed below are supported in the Python implementation. The TypeScript implementation supports: **OpenAI**, **Azure OpenAI**, **Google AI**, **Langchain**, **LM Studio**, **Ollama**, and **Together**.
</Note>
<CardGroup cols={4}>
docs/components/llms/models/together.mdx
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@@ -3,7 +3,7 @@ title: Together
description: "Configure Together AI as an LLM provider in Mem0 with API key setup and Mixtral model configuration."
---
To use Together LLM models, you have to set the `TOGETHER_API_KEY` environment variable. You can obtain the Together API key from their [Account settings page](https://api.together.xyz/settings/api-keys).
To use Together LLM models, you have to set the `TOGETHER_API_KEY` environment variable. You can obtain the Together API key from their [Account settings page](https://api.together.ai/settings/projects/~current/api-keys).
## Usage
@@ -37,4 +37,4 @@ m.add(messages, user_id="alice", metadata={"category": "movies"})
## Config
All available parameters for the `together` config are present in [Master List of All Params in Config](../config).
All available parameters for the `together` config are present in [Master List of All Params in Config](../config).