You may wish to rephrase the question because of the don't-ask-for-software tradition brought into the AI SE from Stack Overflow, but as somewhat of a liberty and justice person, I will answer anyway.
There are many tools, APIs, approaches, and technologies to generate images from text, but it is grossly immature. If we give an artist a commission, the specification is usually in textual or vocal form, and there may be dialog so that both parties are clear that the objectives and constraints have been communicated. The field of AI has not reached the point where natural language can ensue between commissioner and AI system such that generation of an image can be as definitive as with human dialog with an experienced fine artist, photographer, graphics artist, or marketing department or firm.
What we are beginning to see is a limited and unreliable comprehension based on a large enough training set of vocabulary and images that correspond to that vocabulary used in sentences that describe the images. Most are based on an equilibrium established between a discriminator and a generator for a set of semantic relationships. This is interesting research because the GAN (generative adversarial network) device is being applied in semantic contexts.
Much of this is proprietary and some is open source but must be cobbled together to make it actually work. To begin down this road, you will not be able (yet) to just download and play. It is a good time to begin understanding this application of multiple AI techniques however. Take a look at GAN, linguistics, and semantic maps and graphs in a scholarly search. Don't combine the three. Learn each separately and then you will see how they must be combined to create what you envision and know what you are doing when you begin downloading libraries and frameworks and start doing your own cobbling together of working systems.