mirror of https://github.com/explosion/spaCy.git
Update project widgets and examples [ci skip]
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@ -219,7 +219,7 @@ pipelines.
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<!-- TODO: update with better (final) example -->
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<!-- TODO: update with better (final) example -->
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```yaml
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```yaml
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https://github.com/explosion/spacy-boilerplates/blob/master/ner_fashion/project.yml
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https://github.com/explosion/projects/tree/v3/tutorials/ner_fashion_brands/project.yml
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```
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```
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| Section | Description |
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| Section | Description |
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@ -815,8 +815,10 @@ package helps you integrate spaCy visualizations into your Streamlit apps and
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quickly spin up demos to explore your pipelines interactively. It includes a
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quickly spin up demos to explore your pipelines interactively. It includes a
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full embedded visualizer, as well as individual components.
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full embedded visualizer, as well as individual components.
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<!-- TODO: update once version is stable -->
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```bash
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```bash
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$ pip install spacy_streamlit
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$ pip install "spacy_streamlit>=1.0.0a0"
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```
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```
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</div>
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</div>
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@ -828,22 +830,15 @@ $ pip install spacy_streamlit
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Using [`spacy-streamlit`](https://github.com/explosion/spacy-streamlit), your
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Using [`spacy-streamlit`](https://github.com/explosion/spacy-streamlit), your
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projects can easily define their own scripts that spin up an interactive
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projects can easily define their own scripts that spin up an interactive
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visualizer, using the latest pipeline you trained, or a selection of pipelines
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visualizer, using the latest pipeline you trained, or a selection of pipelines
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so you can compare their results. The following script starts an
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so you can compare their results.
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[NER visualizer](/usage/visualizers#ent) and takes two positional command-line
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argument you can pass in from your `config.yml`: a comma-separated list of paths
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to load the pipelines from and an example text to use as the default text.
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<!-- TODO: replace with embed -->
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<Project id="integrations/streamlit">
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```python
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Get started with spaCy and Streamlit using our project template. It includes a
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### scripts/visualize.py
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script to spin up a custom visualizer and commands you can adjust to showcase
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import spacy_streamlit
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and explore your own custom trained pipelines.
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import sys
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DEFAULT_TEXT = sys.argv[2] if len(sys.argv) >= 3 else ""
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</Project>
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PIPELINES = [name.strip() for name in sys.argv[1].split(",")]
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spacy_streamlit.visualize(PIPELINES, DEFAULT_TEXT, visualizers=["ner"])
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```
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> #### Example usage
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> #### Example usage
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>
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>
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@ -860,16 +855,16 @@ commands:
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script:
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script:
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- 'streamlit run ./scripts/visualize.py ./training/model-best "I like Adidas shoes."'
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- 'streamlit run ./scripts/visualize.py ./training/model-best "I like Adidas shoes."'
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deps:
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deps:
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- 'training/model-best'
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- "training/model-best"
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```
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```
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<Project id="integrations/streamlit">
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The following script is called from the `project.yml` and takes two positional
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command-line argument: a comma-separated list of paths or packages to load the
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pipelines from and an example text to use as the default text.
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Lorem ipsum dolor sit amet, consectetur adipiscing elit. Phasellus interdum
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```python
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sodales lectus, ut sodales orci ullamcorper id. Sed condimentum neque ut erat
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https://github.com/explosion/projects/blob/v3/integrations/streamlit/scripts/visualize.py
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mattis pretium.
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```
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</Project>
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---
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---
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@ -882,9 +877,11 @@ library for serving machine learning models and you can use it in your spaCy
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projects to quickly serve up a trained pipeline and make it available behind a
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projects to quickly serve up a trained pipeline and make it available behind a
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REST API.
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REST API.
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```python
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<Project id="integrations/fastapi">
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# TODO: show an example that addresses some of the main concerns for serving ML (workers etc.)
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```
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Get started with spaCy and FastAPI using our project template.
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</Project>
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> #### Example usage
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> #### Example usage
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>
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>
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@ -895,23 +892,24 @@ REST API.
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<!-- prettier-ignore -->
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<!-- prettier-ignore -->
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```yaml
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```yaml
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### project.yml
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### project.yml
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commands:
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- name: "serve"
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- name: serve
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help: "Serve the models via a FastAPI REST API using the given host and port"
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help: "Serve the trained pipeline with FastAPI"
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script:
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script:
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- 'python ./scripts/serve.py ./training/model-best'
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- "uvicorn scripts.main:app --reload --host 127.0.0.1 --port 5000"
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deps:
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deps:
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- 'training/model-best'
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- "scripts/main.py"
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no_skip: true
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no_skip: true
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```
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```
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<Project id="integrations/fastapi">
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The script included in the template shows a simple REST API with a `POST`
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endpoint that accepts batches of texts and returns batches of predictions, e.g.
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named entities found in the documents. Type hints and
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[`pydantic`](https://github.com/samuelcolvin/pydantic) are used to define the
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expected data types.
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Lorem ipsum dolor sit amet, consectetur adipiscing elit. Phasellus interdum
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```python
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sodales lectus, ut sodales orci ullamcorper id. Sed condimentum neque ut erat
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https://github.com/explosion/projects/blob/v3/integrations/fastapi/scripts/main.py
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mattis pretium.
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```
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</Project>
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---
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---
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@ -6,7 +6,7 @@ import Link from '../components/link'
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import { InlineCode } from '../components/code'
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import { InlineCode } from '../components/code'
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// TODO: move to meta?
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// TODO: move to meta?
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const DEFAULT_REPO = 'https://github.com/explosion/projects'
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const DEFAULT_REPO = 'https://github.com/explosion/projects/tree/v3'
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const COMMAND = 'python -m spacy project clone'
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const COMMAND = 'python -m spacy project clone'
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export default function Project({ id, repo, children }) {
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export default function Project({ id, repo, children }) {
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