| Name | llama-index-embeddings-xinference JSON |
| Version |
0.1.0
JSON |
| download |
| home_page | None |
| Summary | llama-index embeddings xinference integration |
| upload_time | 2024-08-25 14:11:36 |
| maintainer | None |
| docs_url | None |
| author | Your Name |
| requires_python | <4.0,>=3.8.1 |
| license | MIT |
| keywords |
|
| VCS |
|
| bugtrack_url |
|
| requirements |
No requirements were recorded.
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No Travis.
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# LlamaIndex Embeddings Integration: Xinference
Xorbits Inference (Xinference) is an open-source platform to streamline the operation and integration of a wide array of AI models.
You can find a list of built-in embedding models in Xinference from its document [Embedding Models](https://inference.readthedocs.io/en/latest/models/builtin/embedding/index.html)
To learn more about Xinference in general, visit https://inference.readthedocs.io/en/latest/
## Installation
```shell
pip install llama-index-embeddings-xinference
```
## Usage
**Parameters Description:**
- `model_uid`: Model uid not the model name, sometimes they may be the same (e.g., `bce-embedding-base_v1`).
- `base_url`: base url of Xinference (e.g., `http://localhost:9997`).
- `timeout`: request timeout set (default 60s).
- `prompt`: Text to embed.
**Text Embedding Example**
```python
from llama_index.embeddings.xinference import XinferenceEmbedding
xi_model_uid = "xinference model uid"
xi_base_url = "xinference base url"
xi_embed = XinferenceEmbedding(
model_uid=xi_model_uid,
base_url=xi_base_url,
timeout=60,
)
def text_embedding(prompt: str):
embeddings = xi_embed.get_query_embedding(prompt)
print(embeddings)
async def async_text_embedding(prompt: str):
embeddings = await xi_embed.aget_query_embedding(prompt)
print(embeddings)
```
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"description": "# LlamaIndex Embeddings Integration: Xinference\n\nXorbits Inference (Xinference) is an open-source platform to streamline the operation and integration of a wide array of AI models.\n\nYou can find a list of built-in embedding models in Xinference from its document [Embedding Models](https://inference.readthedocs.io/en/latest/models/builtin/embedding/index.html)\n\nTo learn more about Xinference in general, visit https://inference.readthedocs.io/en/latest/\n\n## Installation\n\n```shell\npip install llama-index-embeddings-xinference\n```\n\n## Usage\n\n**Parameters Description:**\n\n- `model_uid`: Model uid not the model name, sometimes they may be the same (e.g., `bce-embedding-base_v1`).\n- `base_url`: base url of Xinference (e.g., `http://localhost:9997`).\n- `timeout`: request timeout set (default 60s).\n- `prompt`: Text to embed.\n\n**Text Embedding Example**\n\n```python\nfrom llama_index.embeddings.xinference import XinferenceEmbedding\n\nxi_model_uid = \"xinference model uid\"\nxi_base_url = \"xinference base url\"\n\nxi_embed = XinferenceEmbedding(\n model_uid=xi_model_uid,\n base_url=xi_base_url,\n timeout=60,\n)\n\n\ndef text_embedding(prompt: str):\n embeddings = xi_embed.get_query_embedding(prompt)\n print(embeddings)\n\n\nasync def async_text_embedding(prompt: str):\n embeddings = await xi_embed.aget_query_embedding(prompt)\n print(embeddings)\n```\n",
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