> ## Documentation Index
> Fetch the complete documentation index at: https://docs.camel-ai.org/llms.txt
> Use this file to discover all available pages before exploring further.

# Camel.embeddings.openai compatible embedding

<a id="camel.embeddings.openai_compatible_embedding" />

<a id="camel.embeddings.openai_compatible_embedding.OpenAICompatibleEmbedding" />

## OpenAICompatibleEmbedding

```python theme={"system"}
class OpenAICompatibleEmbedding:
```

Provides text embedding functionalities supporting OpenAI
compatibility.

**Parameters:**

* **model\_type** (str): The model type to be used for text embeddings.
* **api\_key** (str): The API key for authenticating with the model service.
* **url** (str): The url to the model service.
* **output\_dim** (Optional\[int]): The dimensionality of the embedding vectors. If None, it will be determined during the first embedding call.

<a id="camel.embeddings.openai_compatible_embedding.OpenAICompatibleEmbedding.__init__" />

### **init**

```python theme={"system"}
def __init__(
    self,
    model_type: str,
    api_key: Optional[str] = None,
    url: Optional[str] = None,
    output_dim: Optional[int] = None
):
```

<a id="camel.embeddings.openai_compatible_embedding.OpenAICompatibleEmbedding.embed_list" />

### embed\_list

```python theme={"system"}
def embed_list(self, objs: list[str], **kwargs: Any):
```

Generates embeddings for the given texts.

**Parameters:**

* **objs** (list\[str]): The texts for which to generate the embeddings. \*\*kwargs (Any): Extra kwargs passed to the embedding API.

**Returns:**

list\[list\[float]]: A list that represents the generated embedding
as a list of floating-point numbers.

<a id="camel.embeddings.openai_compatible_embedding.OpenAICompatibleEmbedding.get_output_dim" />

### get\_output\_dim

```python theme={"system"}
def get_output_dim(self):
```

**Returns:**

int: The dimensionality of the embedding for the current model.