esco-skill-extractor 0.1.18
Extract ESCO skills from texts such as job descriptions or CVs

# ESCO Skill Extractor

This is a a tool that extract **ESCO skills** and **ISCO occupations** from texts such as job descriptions or CVs. It uses a transformer and compares its embedding using cosine similarity.

## Installation

```bash
pip install esco-skill-extractor
```

## Installation via Docker

```bash
docker run -it -p 5000:5000 konstantinospetrakis/esco-skill-extractor
```

## Usage

### Via python

```python
from esco_skill_extractor import SkillExtractor

# Don't be scared, the 1st time will take longer to download the model and create the embeddings.
skill_extractor = SkillExtractor()

ads = [
    "We are looking for a software engineer with experience in Java and Python.",
    "We are looking for a devops engineer. Containerization tools such as Docker is a must. AWS is a plus."
    # ...
]

print(skill_extractor.get_skills(ads))
# [
#     [
#         "http://data.europa.eu/esco/skill/19a8293b-8e95-4de3-983f-77484079c389",
#         "http://data.europa.eu/esco/skill/ccd0a1d9-afda-43d9-b901-96344886e14d",
#     ],
#     [
#         "http://data.europa.eu/esco/skill/11430d93-c835-48ed-8e70-285fa69c9ae6",
#         "http://data.europa.eu/esco/skill/ae4f0cc6-e0b9-47f5-bdca-2fc2e6316dce",
#         "http://data.europa.eu/esco/skill/ce8ae6ca-61d8-4174-b457-641de96cbff4",
#         "http://data.europa.eu/esco/skill/f0de4973-0a70-4644-8fd4-3a97080476f4",
#     ],
# ]
print(skill_extractor.get_occupations(ads))
# [
#     [
#         "http://data.europa.eu/esco/occupation/10469d70-78a3-4650-9e29-d04de13c62c1",
#         "http://data.europa.eu/esco/occupation/1c5a896a-e010-4217-a29a-c44db26e25da",
#         "http://data.europa.eu/esco/occupation/4874fa37-0cd1-4a68-aed8-a838851f242d",
#         "http://data.europa.eu/esco/occupation/579254cf-6d69-4889-9000-9c79dc568644",
#         "http://data.europa.eu/esco/occupation/57af9090-55b4-4911-b2d0-86db01c00b02",
#         "http://data.europa.eu/esco/occupation/f2b15a0e-e65a-438a-affb-29b9d50b77d1",
#         "http://data.europa.eu/esco/isco/C2512",
#         "http://data.europa.eu/esco/isco/C2514",
#     ],
#     [
#         "http://data.europa.eu/esco/occupation/2fb96c6c-8d0b-4ef0-b1ee-3e493305e4eb",
#         "http://data.europa.eu/esco/occupation/349ee6f6-c295-4c38-9b98-48765b55280e",
#         "http://data.europa.eu/esco/occupation/781a6350-e686-45b9-b075-e4c8d5a05ff7",
#         "http://data.europa.eu/esco/occupation/93b11f0f-69af-4ece-b9da-f29aab7d38d3",
#         "http://data.europa.eu/esco/occupation/bb609566-3ab6-44dd-8f48-cf0b15b96827",
#         "http://data.europa.eu/esco/occupation/cc867bee-ab5c-427f-9244-f7a204d9574b",
#     ],
# ]
```

### Via GUI

```bash
# Visit the URL printed in the console.
# run python -m esco_skill_extractor --help for more options.
python -m esco_skill_extractor
```

<img src="docs/gui.gif">

### Via API

```bash
# Visit the URL printed in the console.
# run python -m esco_skill_extractor --help for more options.
python -m esco_skill_extractor
```

```js
async function getSkills() {
  const texts = [
    "We are looking for a software engineer with experience in Java and Python.",
    "We are looking for a devops engineer. Containerization tools such as Docker is a must. AWS is a plus.",
    // ...
  ];

  // Default host is localhost, and default port is 8000. Check CLI options for more.
  const response = await fetch("http://localhost:8000/extract-skills", {
    method: "POST",
    headers: {
      "Content-Type": "application/json",
    },
    body: JSON.stringify(texts),
  });

  const skills = await response.json();
  console.log(skills);
  //  [
  //    [
  //      "http://data.europa.eu/esco/skill/19a8293b-8e95-4de3-983f-77484079c389",
  //      "http://data.europa.eu/esco/skill/ccd0a1d9-afda-43d9-b901-96344886e14d",
  //    ],
  //    [
  //      "http://data.europa.eu/esco/skill/11430d93-c835-48ed-8e70-285fa69c9ae6",
  //      "http://data.europa.eu/esco/skill/ae4f0cc6-e0b9-47f5-bdca-2fc2e6316dce",
  //      "http://data.europa.eu/esco/skill/ce8ae6ca-61d8-4174-b457-641de96cbff4",
  //      "http://data.europa.eu/esco/skill/f0de4973-0a70-4644-8fd4-3a97080476f4",
  //    ],
  //  ]
  const occupations = await fetch("http://localhost:8000/extract-occupations", {
    method: "POST",
    headers: {
      "Content-Type": "application/json",
    },
    body: JSON.stringify(texts),
  });
}
```

## Possible keyword arguments for `SkillExtractor`

| Keyword Argument     | Description                                                                                                                                              | Default                        |
| -------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------ |
| skill_threshold      | Skills surpassing this cosine similarity threshold are considered a match.                                                                               | 0.6                            |
| occupation_threshold | Occupations surpassing this cosine similarity threshold are considered a match.                                                                          | 0.55                           |
| device               | The device where the copulations will take place. AKA torch device.                                                                                      | "cuda" if available else "cpu" |
| model                | The name of the model to use for embeddings. See[ available models](https://sbert.net/docs/sentence_transformer/pretrained_models.html#original-models). | "all-MiniLM-L6-v2"             |

## Notes

If you change a model, don't forget to call the `remove_embeddings` static method to remove the old embeddings from disk.

```python
SkillExtractor.remove_embeddings()
skill_extractor = SkillExtractor(model="new-model-name")
```

## How it works

1. Generates embeddings for ESCO skills and ISCO occupations.
2. Creates embeddings for the extracted skills.
3. Compares the embeddings of ESCO skills or ISCO occupations with those of the extracted skills using cosine similarity and matches them if the similarity is above a certain threshold.