semvec/pypi-packages huggingface dataset:
failsafe-ai 0.1.1
Contract testing and compliance validation for multi-agent AI systems
Requires Python: >=3.10

# FailSafe

Contract testing and compliance validation for multi-agent AI systems.

Built by [PhT Labs](https://github.com/pht-labs).

## Install

```bash
pip install failsafe-ai
```

## Quick Start

```python
from failsafe import FailSafe

fs = FailSafe(mode="block")

# Register agents
fs.register_agent("research_agent")
fs.register_agent("writer_agent")

# Define a contract between them
fs.contract(
    name="research-to-writer",
    source="research_agent",
    target="writer_agent",
    allow=["query", "sources", "summary"],
    deny=["api_key", "internal_config"],
    require=["query", "sources"],
)

# Validate a handoff
result = await fs.handoff(
    source="research_agent",
    target="writer_agent",
    payload={
        "query": "AI safety",
        "sources": ["arxiv.org/1234"],
        "api_key": "sk-secret-123",  # blocked
    },
)

print(result.passed)       # False
print(result.violations)   # Denied fields found in payload: ['api_key']
```

## Features

- **Validate in milliseconds** — Deterministic contract rules execute without LLM calls.
- **Prevent data leakage** — Allow/deny field lists and sensitive pattern detection block data from crossing agent boundaries.
- **Compliance policies** — Pre-built policy packs for finance regulations and GDPR.
- **LLM-as-judge** — Natural language rules evaluated by an LLM for nuanced validation.
- **Full audit trail** — Every handoff logged to SQLite with violations, timestamps, and trace IDs.
- **Warn or block modes** — Choose per-contract whether violations log warnings or actively block handoffs.

## Integrations

```bash
pip install failsafe-ai[langchain]
```

Includes LangChain callback handler, LangGraph integration, and `@validated_tool` decorator.

## Dashboard

```bash
failsafe dashboard
```

Real-time visualization of validation events via WebSocket.

## License

MIT
fixshell 0.1.1
Hybrid, LLM-Centered, System-Aware FixShell
Requires Python: <4.0,>=3.10

# FixShell AI (System-Aware Diagnostic Engine)

Refining Linux command-line error recovery with a hybrid, LLM-centered approach. FixShell intercepts failed commands, collects system context, and uses a local LLM (Ollama) to diagnose and suggest fixes.

## 🚀 Features

- **Context-Aware Diagnosis**: Analyzes command output, exit codes, and system state (distro, package manager, SELinux).
- **Hybrid Intelligence**: Combines deterministic rules (for instant fixes) with LLM reasoning (for complex errors).
- **Safety First**: Filters dangerous commands and utilizes a strict safety layer to prevent system damage.
- **Local Privacy**: Runs entirely on your machine using Ollama; no data leaves your system.

## 📦 Installation

```bash
pip install fixshell-ai
```

## 🛠️ Prerequisites (Ollama)

FixShell requires **Ollama** to be installed and running locally to perform AI analysis.

1.  **Install Ollama**: [Download from ollama.com](https://ollama.com)
2.  **Pull the Model**:
    ```bash
    ollama pull qwen2.5:3b
    ```
3.  **Start Ollama Server**:
    Ensure the Ollama server is running (`ollama serve`).

## 💻 Usage

Prepend `fixshell --` to any command you want to run safely or debug.

```bash
fixshell -- <your_command>
```

**Examples:**

```bash
# Debug a failed docker command
fixshell -- docker run hello-world

# Analyze a missing package
fixshell -- python3 script.py

# Investigate permission errors
fixshell -- cat /etc/shadow
```

## ⚠️ Important Warning

FixShell uses a Large Language Model (LLM) for diagnosis. While we have implemented safety filters:
- **Always review suggested commands before execution.**
- **Do not run suggested commands blindly.**
- **The AI can make mistakes.**

## 🏗️ Architecture

- **Executor**: Runs your command and captures output.
- **Context Collector**: Gathers system metadata (OS, shell, history).
- **Log Filtering**: Extracts relevant error lines to reduce noise.
- **Safety Layer**: Scans for dangerous patterns (e.g., `rm -rf /`, `chmod 777`).
- **LLM Integration**: Queries the local Ollama instance for a diagnosis.

## 📄 License

MIT License
mutouplotlib 0.0.1
my plotting library based on Matplotlib
Requires Python: >=3.8

# mutouplotlib

[![PyPI - Version](https://img.shields.io/pypi/v/mutouplotlib.svg)](https://pypi.org/project/mutouplotlib)
[![PyPI - Python Version](https://img.shields.io/pypi/pyversions/mutouplotlib.svg)](https://pypi.org/project/mutouplotlib)

-----

## Table of Contents

- [Installation](#installation)
- [License](#license)

## Installation

```console
pip install mutouplotlib
```

## License

`mutouplotlib` is distributed under the terms of the [MIT](https://spdx.org/licenses/MIT.html) license.