Thoth is a curation bot that runs on the Steem blockchain. It filters posts based upon the Thoth operator's preferences, and then does an evaluation through an LLM API call. If the LLM decides to curate the post, it will write a summary and include links to the source article. When all articles have been selected, it also creates a summary/overview post. These are then posted to the Steem blockchain, as follows:

• Introductory/overview post
  ---> Reply 1 # Summary of curated post 1
  ---> Reply 2 # Summary of curated post 2
  ---> ...
  ---> Reply N # # Summary of curated post N

Each post and reply provides the ability to direct beneficiary rewards to the following recipient roles:

• Included authors
• Delegators to the Thoth account
• The Thoth account, itself
• @null for reward-burning

After posting is done, the post and replies receive upvotes from the Thoth account and the blockchain consensus will eventually distribute all rewards as specified in the beneficiary settings.

1. Set-up a python-steem virtual environment

For example, here's how to do it in Windows.

• Getting steem-python to run on Windows with the latest python version

2. Clone the repository:

   git clone https://github.com/remlaps/Thoth.git
   cd Thoth

3. Install dependencies:

   Install the required Python packages using the requirements.txt file:

   pip install -r requirements.txt

Thoth can be configured by editing config/config.ini and by using environment variables.

Note on Configuration: This project is under active development. It is crucial to review all settings in config/config.ini, especially those related to post screening and beneficiary rewards. Not all planned screening features are functional at this time.

The LLM API key is required. It is recommended to provide it via an environment variable for better security, but it can also be set in the config file.

• (Recommended) Environment Variable: Set an environment variable named LLMAPIKEY. The script will prioritize this method.
• (Alternative) Config File: If the LLMAPIKEY environment variable is not found, the script will use the ARLIAI_KEY value from config/config.ini.

Customize the config/config.ini file to your preferences.

The distribution of post rewards to beneficiaries is highly configurable but must follow Steem blockchain rules. Please review these settings carefully.

• Weight Limit: The sum of all beneficiary weights cannot exceed 10000 (which represents 100.00%). You must ensure your configuration respects this limit. The formula for the main summary post is: (NUMBER_OF_DELEGATORS_PER_POST*DELEGATOR_WEIGHT) + (NUMBER_OF_REVIEWED_POSTS*CURATED_AUTHOR_WEIGHT) + POSTING_ACCOUNT_WEIGHT <= 10000
• Beneficiary Count Limit: Steem allows a maximum of 8 beneficiaries per post. The bot logic has a soft limit of 6 beneficiaries (delegators + curated authors) to leave room for other beneficiary types (i.e. @null and the posting account).
• Value adjustments: Author and delegator settings will be adjusted from the specified values for Thoth's reply posts.

To run the bot, you need to activate your steem-python virtual environment and set the necessary environment variables. Here's an exampe bat file for Windows.

@echo off
REM Activate the steem-python virtual environment
call C:\path\to\your\virtual_env\Scripts\activate

REM Set environment variables to UNLOCK the Steem wallet and the LLM API key.
REM Using "set" makes these variables temporary (only for this command window).
REM For a permanent key, use 'setx LLMAPIKEY "your_key_here"' in a separate command prompt.
set UNLOCK=your_steem_wallet_password
set LLMAPIKEY=your_llm_api_key

REM Run Thoth from its source directory
cd /d C:\path\to\your\Thoth\
python src\main.py

echo.
echo Thoth has finished.

REM Deactivate the virtual environment to clean up the session
call deactivate

pause

Contributions are welcome! If you find a bug or have a feature request, please open an issue on GitHub. If you'd like to contribute code, please fork the repository and submit a pull request.

• Check the Issues section
• Improve the appearance and information content for Thoth's posts and replies
• Provide options for Thoth to create posts in languages other than English
• Provide options to use additional LLM models
• Preprocessing before handing off to the LLM
  • Replace screening with scoring where possible/appropriate
  • Add a ML/reinforcement learning layer for post recommendations in order to improve picks over time
  • Screen for uniqueness (plagiarism, syndication, cross-posting, repetitive posting, etc.)
  • Screen for AI authorship
• What are your ideas?

This project is licensed under the MIT License - see the LICENSE file for details.

This software is provided as-is, without any warranty. Use at your own risk.