# deepl-fastapi
<!--- repo-name pypi-name mod_name func_name --->
[][](https://img.shields.io/static/v1?label=python+&message=3.7%2B&color=blue)[](https://github.com/psf/black)[](https://opensource.org/licenses/MIT)[](https://badge.fury.io/py/deepl-fastapi)
Your own deepl server via fastapi, cross-platform (Windows/Linux/MacOs) with API for OmegaT
## Installation
* Create a virual environment: optional but recommended
e.g.,
```bash
# Linux and friends
python3.7 -m venv .venv
source .venv/bin/activate
# Windows
# py -3.7 -m venv .venv
# .venv\Scripts\activate
```
```bash
pip install deepl-fastapi
```
or (if your use poetry)
```bash
poetry add deepl-fastapi
```
or
```
pip install git+https://github.com/ffreemt/deepl-fastapi.git
```
or
* Clone the repo [https://github.com/ffreemt/deepl-fastapi.git](https://github.com/ffreemt/deepl-fastapi.git)
```bash
git clone https://github.com/ffreemt/deepl-fastapi.git
```
and `cd deepl-fastapi`
* `pip install -r requirements.txt
* or ``poetry install``
## Usage
* Start the server
Use uvicorn directly (note the `deepl_server` module, not `run_uvicorn`)
```bash
uvicorn deepl_fastapi.deepl_server:app
```
or
```bash
deepl-fastapi
# this option is available only if installed via pip install or poetry add
```
or
```bash
python3.7 -m deepl_fastapi.run_uvicorn
```
or run the server on the external net, for example at port 9888
```
uvicorn deepl_fastapi.deepl_server:app --reload --host 0.0.0.0 --port 9888
```
* Explore and consume
Point your browser to [http://127.0.0.1:8000/text/?q=test&to_lang=zh](http://127.0.0.1:8000/text/?q=test&to_lang=zh)
Or in python code (`pip install requests` first)
```python
import requests
# get
url = "http://127.0.0.1:8000/text/?q=test me&to_lang=zh"
print(requests.get(url).json())
# {'q': 'test me', 'from_lang': None, 'to_lang': 'zh',
# 'trtext': '考我 试探我 测试我 试探'}
# post
text = "test this and that"
data = {"text": text, "to_lang": "zh"}
resp = requests.post("http://127.0.0.1:8000/text", json=data)
print(resp.json())
# {'q': {'text': 'test this and that', 'from_lang': None, 'to_lang': 'zh', 'description': None},
# 'result': '试探 左右逢源 检验 审时度势'}
```
## Interactive Docs (Swagger UI)
[http://127.0.0.1:8000/docs](http://127.0.0.1:8000/docs)
## OmegaT ``Fake MT`` plugin setup
* Copy ``omegat-plugin-fake-mt-1.0.0.jar`` （available at https://github.com/briacp/omegat-plugin-fake-mt） to OmegaT\plugins （e.g., C:\Program Files\OmegaT\plugins）
Run``OmegaT``and setup ``omegat-plugin-fake-mt``
```bash
OmegaT/Preferences/Machine Translation/Fake MT/Configure
Name: Fake Deepl MT
URL: http://localhost:8000/text
Source Parameter: from_lang
Target Parameter: to_lang
Text Parameter: q
```
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"description": "# deepl-fastapi\n<!--- repo-name pypi-name mod_name func_name --->\n[][](https://img.shields.io/static/v1?label=python+&message=3.7%2B&color=blue)[](https://github.com/psf/black)[](https://opensource.org/licenses/MIT)[](https://badge.fury.io/py/deepl-fastapi)\n\nYour own deepl server via fastapi, cross-platform (Windows/Linux/MacOs) with API for OmegaT\n\n## Installation\n* Create a virual environment: optional but recommended\n e.g.,\n ```bash\n # Linux and friends\n python3.7 -m venv .venv\n source .venv/bin/activate\n\n # Windows\n # py -3.7 -m venv .venv\n # .venv\\Scripts\\activate\n ```\n\n```bash\npip install deepl-fastapi\n```\nor (if your use poetry)\n```bash\npoetry add deepl-fastapi\n```\nor\n```\n pip install git+https://github.com/ffreemt/deepl-fastapi.git\n```\nor\n* Clone the repo [https://github.com/ffreemt/deepl-fastapi.git](https://github.com/ffreemt/deepl-fastapi.git)\n ```bash\n git clone https://github.com/ffreemt/deepl-fastapi.git\n ```\n and `cd deepl-fastapi`\n* `pip install -r requirements.txt\n * or ``poetry install``\n\n## Usage\n\n* Start the server\n\nUse uvicorn directly (note the `deepl_server` module, not `run_uvicorn`)\n```bash\nuvicorn deepl_fastapi.deepl_server:app\n```\n\nor\n```bash\ndeepl-fastapi\n# this option is available only if installed via pip install or poetry add\n```\n\nor\n```bash\npython3.7 -m deepl_fastapi.run_uvicorn\n```\n\nor run the server on the external net, for example at port 9888\n```\nuvicorn deepl_fastapi.deepl_server:app --reload --host 0.0.0.0 --port 9888\n```\n\n* Explore and consume\n\nPoint your browser to [http://127.0.0.1:8000/text/?q=test&to_lang=zh](http://127.0.0.1:8000/text/?q=test&to_lang=zh)\n\nOr in python code (`pip install requests` first)\n```python\nimport requests\n\n# get\nurl = \"http://127.0.0.1:8000/text/?q=test me&to_lang=zh\"\nprint(requests.get(url).json())\n# {'q': 'test me', 'from_lang': None, 'to_lang': 'zh',\n# 'trtext': '\u8003\u6211 \u8bd5\u63a2\u6211 \u6d4b\u8bd5\u6211 \u8bd5\u63a2'}\n\n# post\ntext = \"test this and that\"\ndata = {\"text\": text, \"to_lang\": \"zh\"}\nresp = requests.post(\"http://127.0.0.1:8000/text\", json=data)\nprint(resp.json())\n# {'q': {'text': 'test this and that', 'from_lang': None, 'to_lang': 'zh', 'description': None},\n# 'result': '\u8bd5\u63a2 \u5de6\u53f3\u9022\u6e90 \u68c0\u9a8c \u5ba1\u65f6\u5ea6\u52bf'}\n\n```\n\n## Interactive Docs (Swagger UI)\n\n [http://127.0.0.1:8000/docs](http://127.0.0.1:8000/docs)\n\n## OmegaT ``Fake MT`` plugin setup\n* Copy ``omegat-plugin-fake-mt-1.0.0.jar`` \uff08available at https://github.com/briacp/omegat-plugin-fake-mt\uff09 to OmegaT\\plugins \uff08e.g., C:\\Program Files\\OmegaT\\plugins\uff09 \n\nRun``OmegaT``and setup ``omegat-plugin-fake-mt``\n```bash\nOmegaT/Preferences/Machine Translation/Fake MT/Configure\n\tName: Fake Deepl MT\n\tURL: http://localhost:8000/text\n\tSource Parameter: from_lang\n\tTarget Parameter: to_lang\n\tText Parameter: q\n```\n\n",
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