destigmatizer 0.0.12
An llm-powered platform-agnostic language utility for destigmatizing drug language
License: BSD-3-Clause
Requires Python: >=3.8

# Destigmatizer (Reframe)
Python library that leverages LLMs to remove harmful language from texts on drug use.

## Testing
You can explore Destigmatizer's functionality interactively using Jupyter notebooks. Below is an example of how to classify and rewrite text using the library.

### Using Destigmatizer in a Jupyter Notebook

**Installing and Set Up**
```python
!pip install destigmatizer

# Import the destigmatizer package
import destigmatizer
from destigmatizer import core
from destigmatizer.clients import get_client
from destigmatizer.utils import get_default_model, get_model_mapping
import json
import os

# Define example texts
NON_DRUG_POST = "I think we should really work on the housing crisis in urban areas. The homeless are getting scary."
DRUG_NON_STIGMA_POST = "I really feel for people who suffer from substance use disorder, being unable to control an impulse due to dependency sounds scary."
DRUG_AND_STIGMA_POST = "Addicts really need to get control of themselves. Just stop doing drugs. It seems like these people are just lacking willpower."

# Set up API client
# for example OpenAI

client = get_client('openai', api_key=api_key)
```

**Classifying Drug-Related and Stigmatizing Content**

```
# Classify whether a text is drug-related and whether it contains stigma
drug_classification = core.classify_drug_content([NON_DRUG_POST, DRUG_NON_STIGMA_POST, DRUG_AND_STIGMA_POST], client, model)
stigma_classification = core.classify_stigma([NON_DRUG_POST, DRUG_NON_STIGMA_POST, DRUG_AND_STIGMA_POST], client, model)

# Print results
for text, drug_label, stigma_label in zip([NON_DRUG_POST, DRUG_NON_STIGMA_POST, DRUG_AND_STIGMA_POST], drug_classification, stigma_classification):
    print(f"Text: {text}\nDrug-related: {drug_label}\nStigmatizing: {stigma_label}\n")

```

**Rewwriting Stigmatizing Content**

```
# Rewrite a stigmatizing post to be more empathetic
rewritten_text = core.rewrite_stigmatizing_text(DRUG_AND_STIGMA_POST, client, model)

print(f"Original: {DRUG_AND_STIGMA_POST}")
print(f"Rewritten: {rewritten_text}")

```


Reframe includes integrated tests for all major functions. You can run tests in two ways:

### Using the CLI command 

```bash
# Test all functions
reframe-test

# Test a specific function
reframe-test drug --api_key YOUR_API_KEY

# Use a specific model with Together AI
reframe-test --client_type together --model "meta-llama/Meta-Llama-3.1" 

# Use Claude
reframe-test --client_type claude --model "claude-3-haiku-20240307"

# Using environment variables (recommended)
# First set the environment variables:
export OPENAI_API_KEY="your-openai-key"
export TOGETHER_API_KEY="your-together-key"
export ANTHROPIC_API_KEY="your-anthropic-key"

# Then run tests without specifying the API key
reframe-test --client_type openai
reframe-test --client_type together
reframe-test --client_type claude
```

### Running test scripts directly
```bash
# From the root directory
python3 -m reframe.tests.run_all_tests