[integration]: Together embedder added (#1995)

docs/components/embedders/models/together.mdx

@@ -0,0 +1,38 @@
+---
+title: Together
+---
+
+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).
+
+### Usage
+
+<Note> The `embedding_model_dims` parameter for `vector_store` should be set to `768` for Together embedder. </Note>
+
+```python
+import os
+from mem0 import Memory
+
+os.environ["TOGETHER_API_KEY"] = "your_api_key"
+
+config = {
+    "embedder": {
+        "provider": "together",
+        "config": {
+            "model": "togethercomputer/m2-bert-80M-8k-retrieval"
+        }
+    }
+}
+
+m = Memory.from_config(config)
+m.add("I'm visiting Paris", user_id="john")
+```
+
+### Config
+
+Here are the parameters available for configuring Together embedder:
+
+| 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` |
+| `api_key` | The Together API key | `None` |

docs/components/embedders/overview.mdx

@@ -15,6 +15,7 @@ See the list of supported embedders below.
   <Card title="Hugging Face" href="/components/embedders/models/huggingface"></Card>
   <Card title="Gemini" href="/components/embedders/models/gemini"></Card>
   <Card title="Vertex AI" href="/components/embedders/models/vertexai"></Card>
+  <Card title="Together" href="/components/embedders/models/together"></Card>
 </CardGroup>
 
 ## Usage

mem0/embeddings/configs.py

@@ -13,7 +13,7 @@ class EmbedderConfig(BaseModel):
     @field_validator("config")
     def validate_config(cls, v, values):
         provider = values.data.get("provider")
-        if provider in ["openai", "ollama", "huggingface", "azure_openai", "gemini", "vertexai"]:
+        if provider in ["openai", "ollama", "huggingface", "azure_openai", "gemini", "vertexai", "together"]:
             return v
         else:
             raise ValueError(f"Unsupported embedding provider: {provider}")

mem0/embeddings/together.py

@@ -0,0 +1,31 @@
+import os
+from typing import Optional
+
+from together import Together
+
+from mem0.configs.embeddings.base import BaseEmbedderConfig
+from mem0.embeddings.base import EmbeddingBase
+
+
+class TogetherEmbedding(EmbeddingBase):
+    def __init__(self, config: Optional[BaseEmbedderConfig] = None):
+        super().__init__(config)
+
+        self.config.model = self.config.model or "togethercomputer/m2-bert-80M-8k-retrieval"
+        api_key = self.config.api_key or os.getenv("TOGETHER_API_KEY")
+        # TODO: check if this is correct
+        self.config.embedding_dims = self.config.embedding_dims or 768
+        self.client = Together(api_key=api_key)
+
+    def embed(self, text):
+        """
+        Get the embedding for the given text using OpenAI.
+
+        Args:
+            text (str): The text to embed.
+
+        Returns:
+            list: The embedding vector.
+        """
+
+        return self.client.embeddings.create(model=self.config.model, input=text).data[0].embedding

mem0/utils/factory.py

@@ -44,6 +44,7 @@ class EmbedderFactory:
         "azure_openai": "mem0.embeddings.azure_openai.AzureOpenAIEmbedding",
         "gemini": "mem0.embeddings.gemini.GoogleGenAIEmbedding",
         "vertexai": "mem0.embeddings.vertexai.VertexAIEmbedding",
+        "together": "mem0.embeddings.together.TogetherEmbedding",
     }
 
     @classmethod