https://github.com/litongjava/py-jina-embeddings-server
Jina Embeddings v3 API Service
https://github.com/litongjava/py-jina-embeddings-server
Last synced: 6 months ago
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Jina Embeddings v3 API Service
- Host: GitHub
- URL: https://github.com/litongjava/py-jina-embeddings-server
- Owner: litongjava
- License: mit
- Created: 2025-02-15T01:00:41.000Z (12 months ago)
- Default Branch: main
- Last Pushed: 2025-02-28T08:13:50.000Z (12 months ago)
- Last Synced: 2025-03-16T21:17:25.090Z (11 months ago)
- Language: Python
- Size: 23.4 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: readme.md
- License: LICENSE
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README
# py-jina-embeddings-server
Jina Embeddings v3 API Service
## Overview
This project provides an HTTP API service for generating embeddings from text using the Jina-embeddings-v3 model with ONNX Runtime and the Robyn framework.
## Requirements
- **Python:** 3.8+
- **Libraries:** numpy, onnxruntime, robyn, transformers
## Installation
1. Create a conda environment:
```bash
conda create -n jina-embeddings python=3.9 -y
conda activate jina-embeddings
```
2. Install the required libraries using pip:
```bash
pip install numpy onnxruntime robyn transformers
```
## Usage
1. **Download the model:**
```bash
mkdir ~/models/jina-embeddings-v3/onnx -p
cd ~/models/jina-embeddings-v3/onnx
wget https://huggingface.co/jinaai/jina-embeddings-v3/resolve/main/onnx/model.onnx
wget https://huggingface.co/jinaai/jina-embeddings-v3/resolve/main/onnx/model.onnx_data
```
2. **Run the server:**
Start the server by running the script:
```bash
python server.py --model_path ~/models/jina-embeddings-v3/onnx/model.onnx
```
3. **Send a POST request to the `/v1/embeddings` endpoint:**
Example:
```bash
curl -X POST http://localhost:10002/v1/embeddings \
-H "Content-Type: application/json" \
-d '{"input": ["Hello world", "你好，世界"], "task": "text-matching"}'
```
response example
```json
{
"object": "list",
"data": [
{
"object": "embedding",
"index": 0,
"embedding": [
]
}
],
"model": "text-embedding-3-large",
"usage": {
"prompt_tokens": 5,
"total_tokens": 5
}
}
```
## Dockerfile
To containerize the service, use the following `Dockerfile`:
```Dockerfile
FROM python:3.9-slim
# Install wget (required to download the model)
RUN apt-get update && apt-get install -y wget && rm -rf /var/lib/apt/lists/*
# Download the model files into the specified directory
RUN mkdir -p /models/jina-embeddings-v3/onnx && \
cd /models/jina-embeddings-v3/onnx && \
wget https://huggingface.co/jinaai/jina-embeddings-v3/resolve/main/onnx/model.onnx && \
wget https://huggingface.co/jinaai/jina-embeddings-v3/resolve/main/onnx/model.onnx_data
WORKDIR /app
# Copy application code into the container
COPY . /app
# Install required Python packages
RUN pip install --no-cache-dir numpy onnxruntime robyn transformers
# Set the default command with the model path specified
CMD ["python", "server.py", "--model_path", "/models/jina-embeddings-v3/onnx/model.onnx"]
```
1. **Build the Docker image:**
```bash
docker build -t litongjava/py-jina-embeddings-server:1.0.0 .
```
2. **Run the Docker container:**
```bash
docker run -p 10002:10002 litongjava/py-jina-embeddings-server:1.0.0
```
## License
This project is licensed under the MIT License.