Together - Mem0 — ContextQMD

To use Together embedding models, set the TOGETHER_API_KEY environment variable. You can obtain the Together API key from the Together Platform.

Usage

<Note> The embedding_model_dims parameter for vector_store should be set to 1024 for Together embedder. </Note>

<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

os.environ["TOGETHER_API_KEY"] = "your_api_key" os.environ["OPENAI_API_KEY"] = "your_api_key" # For LLM

config = { "embedder": { "provider": "together", "config": { "model": "intfloat/multilingual-e5-large-instruct" } } }

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: '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 | `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>