| Name | piah JSON |
| Version |
0.1.1
JSON |
| download |
| home_page | None |
| Summary | automatically parse PDF's and texts to dataclasses |
| upload_time | 2024-04-01 04:48:41 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.10 |
| license | None |
| keywords |
ai
dataclass
parser
piah
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
# piah
[](https://pypi.org/project/piah)
[](https://pypi.org/project/piah)
-----
Piah automatically parse the data from PDF's or texts based only in the [dataclass](https://docs.python.org/3/library/dataclasses.html#module-dataclasses) that you provide and return the same [dataclass](https://docs.python.org/3/library/dataclasses.html#module-dataclasses) fullfilled with the values.
Piah is based in the [OxyParser](https://github.com/oxylabs/OxyParser/)
**Table of Contents**
- [Installation](#installation)
- [Example](#example)
- [TODO](#todo)
- [Know Issues](#know-issues)
- [License](#license)
## Installation
```console
pip install piah
```
## Example
```python
from piah import Piah
from dataclasses import dataclass
@dataclass
class Person:
name: str
age: int
parser = Piah("gpt-3.5-turbo")
result = parser.parse("Hello Iam python and I have 33 years old", Person)
```
to parse PDF's:
```python
result = parser.parse("example.pdf", Person)
#or
result = parser.parse(Path("example.pdf"), Person)
```
## TODO
- [ ] Write docstrings
- [ ] Improve allowed types
- [ ] Improve system prompt
## Know Issues
Seems that `piah` don't pass every time in the test, because the LLM don't parse
correctly every time large PDF's
## License
`piah` is distributed under the terms of the [MIT](https://spdx.org/licenses/MIT.html) license.
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"description": "# piah\n\n[](https://pypi.org/project/piah)\n[](https://pypi.org/project/piah)\n\n-----\n\nPiah automatically parse the data from PDF's or texts based only in the [dataclass](https://docs.python.org/3/library/dataclasses.html#module-dataclasses) that you provide and return the same [dataclass](https://docs.python.org/3/library/dataclasses.html#module-dataclasses) fullfilled with the values.\nPiah is based in the [OxyParser](https://github.com/oxylabs/OxyParser/)\n\n**Table of Contents**\n\n- [Installation](#installation)\n- [Example](#example)\n- [TODO](#todo)\n- [Know Issues](#know-issues)\n- [License](#license)\n\n## Installation\n\n```console\npip install piah\n```\n\n## Example\n```python\nfrom piah import Piah\nfrom dataclasses import dataclass\n\n@dataclass\nclass Person:\n name: str\n age: int\n\nparser = Piah(\"gpt-3.5-turbo\")\nresult = parser.parse(\"Hello Iam python and I have 33 years old\", Person)\n```\nto parse PDF's:\n```python\nresult = parser.parse(\"example.pdf\", Person)\n#or\nresult = parser.parse(Path(\"example.pdf\"), Person)\n```\n\n## TODO\n- [ ] Write docstrings\n- [ ] Improve allowed types\n- [ ] Improve system prompt\n\n## Know Issues\nSeems that `piah` don't pass every time in the test, because the LLM don't parse\ncorrectly every time large PDF's\n\n## License\n\n`piah` is distributed under the terms of the [MIT](https://spdx.org/licenses/MIT.html) license.\n",
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