llama-index-embeddings-nebius


Namellama-index-embeddings-nebius JSON
Version 0.4.0 PyPI version JSON
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Summaryllama-index embeddings Nebius AI Studio integration
upload_time2025-07-30 21:31:05
maintainerNone
docs_urlNone
authorNone
requires_python<4.0,>=3.9
licenseNone
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            # LlamaIndex Embeddings Integration: [Nebius AI Studio](https://studio.nebius.ai/)

## Overview

Integrate with Nebius AI Studio API, which provides access to open-source state-of-the-art text embeddings models.

## Installation

```bash
pip install llama-index-embeddings-nebius
```

## Usage

### Initialization

#### With environmental variables.

```.env
NEBIUS_API_KEY=your_api_key

```

```python
from llama_index.embeddings.nebius import NebiusEmbedding

embed_model = NebiusEmbedding(model_name="BAAI/bge-en-icl")
```

#### Without environmental variables

```python
from llama_index.embeddings.nebius import NebiusEmbedding

embed_model = NebiusEmbedding(
    api_key="your_api_key", model_name="BAAI/bge-en-icl"
)
```

### Launching

#### Basic usage

```python
text = "Everyone loves justice at another person's expense"
embeddings = embed_model.get_text_embedding(text)
print(embeddings[:5])
```

#### Asynchronous usage

```python
text = "Everyone loves justice at another person's expense"
embeddings = await embed_model.aget_text_embedding(text)
print(embeddings[:5])
```

#### Batched usage

```python
texts = [
    "As the hours pass",
    "I will let you know",
    "That I need to ask",
    "Before I'm alone",
]

embeddings = embed_model.get_text_embedding_batch(texts)
print(*[x[:3] for x in embeddings], sep="\n")
```

#### Batched asynchronous usage

```python
texts = [
    "As the hours pass",
    "I will let you know",
    "That I need to ask",
    "Before I'm alone",
]

embeddings = await embed_model.aget_text_embedding_batch(texts)
print(*[x[:3] for x in embeddings], sep="\n")
```

            

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    "description": "# LlamaIndex Embeddings Integration: [Nebius AI Studio](https://studio.nebius.ai/)\n\n## Overview\n\nIntegrate with Nebius AI Studio API, which provides access to open-source state-of-the-art text embeddings models.\n\n## Installation\n\n```bash\npip install llama-index-embeddings-nebius\n```\n\n## Usage\n\n### Initialization\n\n#### With environmental variables.\n\n```.env\nNEBIUS_API_KEY=your_api_key\n\n```\n\n```python\nfrom llama_index.embeddings.nebius import NebiusEmbedding\n\nembed_model = NebiusEmbedding(model_name=\"BAAI/bge-en-icl\")\n```\n\n#### Without environmental variables\n\n```python\nfrom llama_index.embeddings.nebius import NebiusEmbedding\n\nembed_model = NebiusEmbedding(\n    api_key=\"your_api_key\", model_name=\"BAAI/bge-en-icl\"\n)\n```\n\n### Launching\n\n#### Basic usage\n\n```python\ntext = \"Everyone loves justice at another person's expense\"\nembeddings = embed_model.get_text_embedding(text)\nprint(embeddings[:5])\n```\n\n#### Asynchronous usage\n\n```python\ntext = \"Everyone loves justice at another person's expense\"\nembeddings = await embed_model.aget_text_embedding(text)\nprint(embeddings[:5])\n```\n\n#### Batched usage\n\n```python\ntexts = [\n    \"As the hours pass\",\n    \"I will let you know\",\n    \"That I need to ask\",\n    \"Before I'm alone\",\n]\n\nembeddings = embed_model.get_text_embedding_batch(texts)\nprint(*[x[:3] for x in embeddings], sep=\"\\n\")\n```\n\n#### Batched asynchronous usage\n\n```python\ntexts = [\n    \"As the hours pass\",\n    \"I will let you know\",\n    \"That I need to ask\",\n    \"Before I'm alone\",\n]\n\nembeddings = await embed_model.aget_text_embedding_batch(texts)\nprint(*[x[:3] for x in embeddings], sep=\"\\n\")\n```\n",
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