| Name | radprompter JSON |
| Version |
1.1.10
JSON |
| download |
| home_page | None |
| Summary | A package for simplified and reproducible LLM prompting. |
| upload_time | 2024-05-26 04:26:29 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.7 |
| license | None |
| keywords |
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| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
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| coveralls test coverage |
No coveralls.
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# RadPrompter
RadPrompter is a Python package for simplified and reproducible LLM prompting, particularly tailored for biomedical applications, including Radiology.
## Installation
You can install RadPrompter using pip:
```bash
pip install radprompter
```
*Note*: RadPrompter works with Python 3.7+. However, for maximum compatilibity we recommend using Python 3.11+.
## Getting Started
The core of RadPrompter is the `.toml` configuration file which defines your prompts. Here's a minimal example:
```toml
[METADATA]
version = 0.1
description = "A sample prompt for RadPrompter"
[CONSTRUCTOR]
system = "You are an experienced radiologist that help users extract infromation from radiology reports."
user = """Does the following report indicate a normal or abnormal finding?
{{report}}
Just reply with "normal" or "abnormal" to indicate your answer, without any additional information.
"""
```
And here's how you would use it in Python:
```python
from radprompter import Prompt, RadPrompter, vLLMClient
prompt = Prompt("sample.toml")
client = vLLMClient(
model="meta-llama/Meta-Llama-3-8B-Instruct",
base_url="http://localhost:9999/v1",
temperature=0.0,
seed=42
)
engine = RadPrompter(
client=client,
prompt=prompt,
output_file="output.csv",
)
reports = [{"report": "..."}] # Your radiology reports
engine(reports)
```
For more details and advanced usage, check out our tutorials.
## Tutorials
| Tutorial | Description | Notebook |
|-----------------------------|-----------------------------------------------------|----------------------------------------------------------------------------------|
| 01_Basic-Usecase | Covers the basic usage of RadPrompter | [👁️](https://nbviewer.org/github/BardiaKh/RadPrompter/blob/main/tutorials/01_Basic-Usecase/01_Basic-Usecase.ipynb) [📓](./tutorials/01_Basic-Usecase) |
| 02_RDP-Templating | Introduces the `[PROMPTS]` section and `rdp` operator | [👁️](https://nbviewer.org/github/BardiaKh/RadPrompter/blob/main/tutorials/02_RDP-Templating/02_RDP-Templating.ipynb) [📓](./tutorials/02_RDP-Templating) |
| 03_Multiturn-Prompting | Demonstrates multi-turn prompting | [👁️](https://nbviewer.org/github/BardiaKh/RadPrompter/blob/main/tutorials/03_Multiturn-Prompting/03_Multiturn-Prompting.ipynb) [📓](./tutorials/03_Multiturn-Prompting) |
| 04_Using-Schemas | Shows how to use schemas for structured output | [👁️](https://nbviewer.org/github/BardiaKh/RadPrompter/blob/main/tutorials/04_Using-Schemas/04_Using-Schemas.ipynb) [📓](./tutorials/04_Using-Schemas) |
| 05_JSON-Prefill | Covers using JSON prefills and sanitization | [👁️](https://nbviewer.org/github/BardiaKh/RadPrompter/blob/main/tutorials/05_JSON-Prefill/05_JSON-Prefill.ipynb) [📓](./tutorials/05_JSON-Prefill) |
| 06_HuggingFace-Client | Covers using the new `HuggingFaceClient` | [👁️](https://nbviewer.org/github/BardiaKh/RadPrompter/blob/main/tutorials/06_HuggingFace-Client/06_HuggingFace-Client.ipynb) [📓](./tutorials/06_HuggingFace-Client) |
## Contributing
We welcome contributions! If you have any updates or improvements to the package, please open an issue or submit a pull request. We're happy to review and incorporate your changes.
## Authors
RadPrompter is created and maintained by:
- Bardia Khosravi (bardiakhosravi95@gmail.com)
- Theo Dapamede (theo.dapamede@emory.edu)
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