semvec/pypi-packages huggingface dataset:
kozmoai 1.2.0.dev0
A Python package with a built-in web application
Requires Python: <3.13,>=3.10
Keywords: gpt, gui, langchain, nlp, openai

<!-- markdownlint-disable MD030 -->

<p align="center" style="font-size: 12px;">
    Kozmoai is a low-code app builder for RAG and multi-agent AI applications. It’s Python-based and agnostic to any model, API, or database.
</p>

## ✨ Core features

1. **Python-based** and agnostic to models, APIs, data sources, or databases.
2. **Visual IDE** for drag-and-drop building and testing of workflows.
3. **Playground** to immediately test and iterate workflows with step-by-step control.
4. **Multi-agent** orchestration and conversation management and retrieval.
6. **Publish as an API** or export as a Python application.
7. **Observability** with LangSmith, LangFuse, or LangWatch integration.
8. **Enterprise-grade** security and scalability with free DataStax Kozmoai cloud service.
9. **Customize workflows** or create flows entirely just using Python.
10. **Ecosystem integrations** as reusable components for any model, API or database.


## 📦 Quickstart

- **Install with uv (recommended)** (Python 3.10 to 3.12):

```shell
uv pip install kozmoai
```

- **Install with pip** (Python 3.10 to 3.12):

```shell
pip install kozmoai
```

- **Cloud:** DataStax Kozmoai is a hosted environment with zero setup. [Sign up for a free account.](https://astra.datastax.com/signup?type=kozmoai)
- **Self-managed:** Run Kozmoai in your environment. [Install Kozmoai](https://docs.kozmoai.cloud/get-started-installation) to run a local Kozmoai server, and then use the [Quickstart](https://docs.kozmoai.cloud/get-started-quickstart) guide to create and execute a flow.
- **Hugging Face:** [Clone the space using this link](https://huggingface.co/spaces/digitranslab/kozmoai?duplicate=true) to create a Kozmoai workspace.
goat-sdk-plugin-debridge 0.1.0
Goat plugin for deBridge
Requires Python: <4.0,>=3.10
Keywords: goat, sdk, agents, ai, debridge

# deBridge Plugin for GOAT SDK

A plugin for the GOAT SDK that provides access to deBridge Liquidity Network (DLN) functionality.

## Installation

```bash
# Install the plugin
poetry add goat-sdk-plugin-debridge


```

## Usage

```python
from goat_plugins.debridge import debridge, DebridgePluginOptions

# Initialize the plugin
options = DebridgePluginOptions()
plugin = debridge(options)

# Get order data
order_data = await plugin.get_order_data(
    id="0x81fbb0ed8209eb57d084aee1986c00e597c1e1ec6bb93bc4dbe97266ca0398fb"
)

# Get supported chains
chains = await plugin.get_supported_chains()

# Get order IDs
order_IDs = await plugin.get_order_IDs(
    hash="0xbe9071de34de9bd84a52039bc4bc6c8229d4bd65127d034ffc66b600d8260276" # Hash of the creation transaction
)
```

## Features

- DLN
    - Create order transaction `create_order_transaction`
    - Get order data `get_order_data`
    - Get order status `get_order_status`
    - Get order IDs `get_order_IDs`
    - Cancel order `cancel_order`
    - Cancel external call `cancel_external_call`
- Utils
    - Get supported chains `get_supported_chains`
    - Get token list `get_token_list`
- Single Chain Swap
    - Estimation `single_chain_swap_estimation`
    - Transaction `single_chain_swap_transaction`

### DLN Swagger Docs
The deBridge plugin tools is a 1-to-1 representation of the DLN API.
You can access the [deBridge Swagger docs](https://dln.debridge.finance/v1.0) page for more information about the various parameters.

## License

This project is licensed under the terms of the MIT license.
pytest-expected 0.1.1
Record and play back your expectations
Requires Python: >=3.11

# pytest-expected

This pytest fixture lets you write tests that compare to a previously known, recorded value:

```py
def test_something(expected):
    assert something(frobnicate=True) == expected
```

When called with `--record`, pytest will accept any value and store it in a
file in the hidden `.expected` directory under the pytest root folder (usually
the repository root).

When called _without_ `--record`, it will load the known value(s) from that
store, and assert that they are equal to the observed values.

Any picklable value can be stored.

You can also use `expected` several times in a test for different values, and
it'll figure out the rest.

`pytest-expected` organizes storage based on:

- Test ID (typically includes path to test file, test name, and parametrizations)
- Number of uses of `expected`