semvec/pypi-packages huggingface dataset:
langforge-cli 0.1.0
A Toolkit for Creating and Deploying LangChain Apps
Requires Python: >=3.6

![LangForge](https://github.com/mme/langforge/raw/main/docs/img/header.png "LangForge")

LangForge is an **open-source toolkit** designed to make it easy to create and deploy **_LangChain applications_**.

With LangForge, you can easily **_set up your environment_**, manage API keys, **_chat with your chains_** using the **_Jupyter integration_**, and **_automatically generate a REST interface_** for your app. Additionally, LangForge comes with a collection of **_predefined notebooks tailored for various use cases_**, allowing you to quickly get started and adapt them to your specific needs.

## Features

- Simplified environment setup and API key management
- Predefined notebooks for various use cases to help you get started quickly
- Instantly chat with your chains using the Jupyter integration
- Automatic REST interface generation for your app

## Installation

To install LangForge, simply run the following command:

```bash
pip install langforge-cli
```

## Getting Started

1. **Create a new LangChain app:** Use the create command to generate a new LangChain app. LangForge will set up a virtual environment, install the required packages, and configure the API keys, setting up a ready-to-use foundation for building your app.

```bash
langforge create myapp
```

2. **Launch JupyterLab:** Run the langforge lab command to launch Jupyter Lab. LangForge Lab comes with ready-to-use notebooks for various use cases and an integration that allows you to chat with your chains directly within Jupyter.

```bash
langforge lab
```

3. **Serve your app:** LangForge automatically generates a REST interface for your app, making it easy to deploy and share with others. Use the `serve` command followed by the name of your notebook to start serving your app.

```bash
langforge serve my_notebook.ipynb
```

## Contributing

We welcome contributions from the community! If you'd like to contribute to LangForge, please feel free to submit pull requests or open issues on our GitHub repository.

## License

LangForge is released under the MIT License.
twot 0.0.4
The Twitter Bot API - Tweet, Follow, Like, Retweet, and more with Python without using Twitter's API
Requires Python: >=3.7
Keywords: twitter,twitter-api,twitter-bot

# twot - The Twitter Bot API
![PyPI](https://img.shields.io/pypi/v/twot)
![GitHub](https://img.shields.io/github/license/gpl27/twot)
## About
This is a Python package that provides an easy-to-use interface to 
Twitter using Selenium to emulate actions that a Twitter user might make,
such as liking, following, and tweeting. In addition, it provides a 
Tweet Search implementation that uses Twitter's Advanced Search to
scrape for tweets.

## Getting Started
### Prerequisites
To use this package, you will need:
- Python 3.7+
- Selenium 4.0+
- Chrome Browser
- Twitter Account
### Installation
1. `pip install twot`
### Usage
2. Import `TwitterAPI` class, create an instance and login:
```python
from twot.classes import TwitterAPI

api = TwitterAPI('my_username', 'my_password')
api.login()
```
3. Use the `TwitterAPI` instance to interact with Twitter:
```python
# Tweet something
api.post_tweet('Hello World!')

# Like a tweet
api.like_tweet('https://twitter.com/twitter/status/1234567890')

# Quote retweet a tweet
api.quote_retweet('https://twitter.com/twitter/status/1234567890', 'Foo bar')

```
4. Scrape for tweets:
```python
# First five options are required for every search
OPTIONS = {
    "limit": 500,
    "replies": False,
    "only-replies": False,
    "links": True,
    "only-links": False,
    "from": ['BarackObama']
}
# Links to the last 500 tweets from Obama
obama_tweets = api.search(OPTIONS)

```
## Features
You must have a Twitter account to use all features (including search).
Class methods return the results of their actions. For example, methods
that post a tweet return a link to the new tweet. Likeing and following
return whether that tweet/account is now liked/followed or unliked/unfollowed
(true/false).
```
    Methods
    -------
    status()
        Prints general info about the class state
    login()
        Uses `username` and `password` to login to Twitter
    logout()
        Logs out from Twitter
    post_tweet(message)
        Posts a tweet to users timeline
    reply_to_tweet(tweet_id, message)
        Posts a reply to the specified tweet
    like_tweet(tweet_id)
        Likes/Unlikes the tweet
    retweet(tweet_id)
        Retweets/Unretweets the tweet
    quote_retweet(tweet_id, message)
        Quote retweets the tweet with the specified message
    follow(user_handle)
        Follows the user with the specified handle
    unfollow(user_handle)
        Unfollows the user with the specified handle
    search(options)
        Searches for tweets using Advanced Search
    quit()
        Ends the browser session

```
## Contributing
Pull requests are welcome. For major changes, please open an issue first to
discuss what you would like to change.