Metadata-Version: 2.4
Name: superred-target-chatbot
Version: 0.1.0
Summary: Chatbot target for the superred red-teaming framework: wraps any LLM via litellm
Project-URL: Homepage, https://superred.simonsure.com
Project-URL: Documentation, https://superred.simonsure.com
Project-URL: Repository, https://github.com/RoldSI/superred-modules
Project-URL: Issues, https://github.com/RoldSI/superred-modules/issues
Author-email: Simon Sure <info@simonsure.com>
License-Expression: MIT
License-File: LICENSE
Keywords: ai-safety,llm,red-teaming,security,superred,target
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Science/Research
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Security
Requires-Python: <3.14,>=3.11
Requires-Dist: litellm>=1.89.0
Requires-Dist: superred>=0.1.0
Provides-Extra: bedrock
Requires-Dist: boto3>=1.40; extra == 'bedrock'
Provides-Extra: dev
Requires-Dist: pytest-asyncio>=0.23; extra == 'dev'
Requires-Dist: pytest-cov>=6.0; extra == 'dev'
Requires-Dist: pytest>=8.0; extra == 'dev'
Description-Content-Type: text/markdown

# superred-target-chatbot

A general **chatbot target** for the [superred](https://superred.simonsure.com)
red-teaming framework: it wraps any LLM reachable through
[litellm](https://github.com/BerriAI/litellm) as a single-turn or multi-turn
chatbot under test, exposing its system prompt, user message, response, and
model identity as controllables/observables.

## Install

```bash
pip install superred-target-chatbot
# for AWS Bedrock providers:
pip install "superred-target-chatbot[bedrock]"
```

## Usage

```python
from chatbot_target import ChatbotTarget, USER_TAG

target = ChatbotTarget(model="gpt-4o-mini", api_base="https://api.openai.com/v1", api_key="sk-...")
```

## Credits / upstream

Original work of the superred project, released under the MIT License (see
`LICENSE`). It contains no third-party code and no bundled datasets. It reaches
models through `litellm` (MIT) and, optionally, AWS Bedrock via `boto3` (Apache-2.0),
both ordinary pip dependencies.

## License

MIT
