Fastest Semantle solver this side of the Mississippi

Overview

semantle

Fastest Semantle solver this side of the Mississippi.

  • Roughly 3 average turns to win
  • Measured against (part of) the word2vec-google-news-300 vocabulary!

NOTES:

  • There are a lot of words, and I haven't bothered to test a the vast majority of them.
  • The "average turns to win" benchmark is based on my rough observations.

fast car

Install

Install directly from this repository:

pip install git+https://github.com/fkodom/semantle.git

Solve

Launch the assistive solver:

solve-semantle

In some situations, you may want to increase the solver's uncertainty:

  • To get more "realistic" looking answers -- don't immediately solve the puzzle :)
  • Playing a different, third-party Semantle implementation, which may use a different trained version of Word2Vec.

It will take longer to solve the puzzle, but the solver will be more robust to discrepancies in word similarities. For example, to allow for differences of ±5 similarity score:

solve-semantle --uncertainty 5

Play

Play a command line game:

play-semantle

NOTE: I believe the word bank is much larger than in the official Semantle game. You may get some obscure target words. ¯\(ツ)

How It Works

[TODO]

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Comments
  • Cannot seem to get it to work on Windows.

    Cannot seem to get it to work on Windows.

    I followed the instructions precisely, but when I type solve-semantle, it says 'solve-semantle' is not recognized as an internal or external command, operable program or batch file. What do I do?

    opened by Rivian01 2
  • Solver.recommend() calls _get_words_closest_to_mean() with empty

    Solver.recommend() calls _get_words_closest_to_mean() with empty "words" tuple

    Hello,

    First, thanks for developing this tool, it is quite funny to see how fast it solves Semantle games :)

    However, I stumble upon this behaviour:

    $ .local/bin/solve-semantle
    Semantle Solver!
    
    Step 1
    ----------------
    157244 solutions remaining
    Recommended: object
    Alternatives: [person, place, action, adjective]
    ----------------
    Enter your guess: hello
    What was the similarity? 4.04
    
    Step 2
    ----------------
    306 solutions remaining
    Recommended: neuroanatomical
    Alternatives: [mupirocin, lymphocytic, recombinants, amisulpride, bullae]
    ----------------
    Enter your guess: neuroanatomical
    What was the similarity? -0.68
    ~/.local/lib/python3.10/site-packages/semantle/solver.py:81: RuntimeWarning: Mean of empty slice.
      mean = vectors.mean(axis=0, keepdims=True)
    ~/.local/lib/python3.10/site-packages/numpy/core/_methods.py:181: RuntimeWarning: invalid value encountered in true_divide
      ret = um.true_divide(
    Traceback (most recent call last):
      File "~/.local/bin/solve-semantle", line 8, in <module>
        sys.exit(main())
      File "~/.local/lib/python3.10/site-packages/semantle/solver.py", line 129, in main
        AssistiveSolver(uncertainty=args.uncertainty).solve()
      File "~/.local/lib/python3.10/site-packages/semantle/solver.py", line 118, in solve
        self.update(info)
      File "~/.local/lib/python3.10/site-packages/semantle/solver.py", line 52, in update
        return self.recommend().recommended
      File "~/.local/lib/python3.10/site-packages/semantle/solver.py", line 40, in recommend
        words = _get_words_closest_to_mean(words, max_words=max_alternatives + 1)
      File "~/.local/lib/python3.10/site-packages/semantle/solver.py", line 82, in _get_words_closest_to_mean
        dist = np.linalg.norm(vectors - mean, axis=1)
      File "<__array_function__ internals>", line 180, in norm
      File "~/.local/lib/python3.10/site-packages/numpy/linalg/linalg.py", line 2547, in norm
        return sqrt(add.reduce(s, axis=axis, keepdims=keepdims))
    numpy.AxisError: axis 1 is out of bounds for array of dimension 1
    

    Note: the secret word was "pace".

    A brief print()-based debugging session reflects Solver.recommend() calls _get_words_closest_to_mean() with an empty "words" tuple. This seems to happen only when, at some point in the process, a negative similarity whose absolute value is greater than the uncertainty was submitted.

    opened by xavierog 0
Releases(1.0.1)
Owner
Frank Odom
Director of Innovation at Plainsight (@sixgill). I like neural nets, and neural nets like me.
Frank Odom
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