🧪 mediaichemy: cost-effective AI powered content creation
mediaichemy is a Python library for generating cheap and cost effective multimedia content using AI. It intelligently selects models and workflows to minimize costs while delivering high-quality results.
The library relies on:
- Runware for image and video generation
- OpenRouter for general AI and text completions
- Piper TTS: text-to-speech synthesis
Usage ovewview
mediaichemy offers a simple yet powerful approach to content creation:
- Media: Choose a specific media type and edit its parameters to create the content you want.
- MediaCreator Use AI to generate content ideas for you and create them.
Both approaches use the same underlying Media system, with MediaCreator adding an AI layer that handles the creative decisions for you. All content creation automatically optimizes for cost-effectiveness by choosing the best-performing, lowest-cost AI models.
What's Inside
🎬 Media
Getting Started
- Install mediaichemy directly from PyPI:
pip install mediaichemy
- Set up API keys for OpenRouter and Runware (see below).
Setting up API keys
1. Create an OpenRouter Account
- Obtain an Openrouter API key
2. Create a Runware Account
- Obtain a Runware API key
3. Configure your API keys as environment variables:
Linux/macOS (Terminal):
export OPENROUTER_API_KEY="your_openrouter_api_key"
export RUNWARE_API_KEY="your_runware_api_key"
Windows (Command Prompt):
set OPENROUTER_API_KEY=your_openrouter_api_key
set RUNWARE_API_KEY=your_runware_api_key
Windows (PowerShell)
$env:OPENROUTER_API_KEY="your_openrouter_api_key"
$env:RUNWARE_API_KEY="your_runware_api_key"
Option 2: Use a .env File
Create a file named .env in your project root with the following content:
OPENROUTER_API_KEY=your_openrouter_api_key
RUNWARE_API_KEY=your_runware_api_key
Media
Each Media type creates a specific form of content using AI and editing tools to craft it.
Single Media Examples
Media created using a single AI source.
Image
from mediaichemy.media.single import Image
from mediaichemy.media.parameters import ImageParameters
image_params = ImageParameters(
image_prompt="A cat on a skateboard",
image_model="rundiffusion:110@101"
)
image = await Image(params=image_params).create()
Video
from mediaichemy.media.single import Video
from mediaichemy.media.parameters import VideoParameters
video_params = VideoParameters(
video_prompt="A dog floating in outer space",
video_model="bytedance:1@1",
width=1088,
height=1920
)
video = await Video(params=video_params).create()
https://github.com/user-attachments/assets/da8a297b-3808-49e1-b635-7358339a0d49
Narration
from mediaichemy.media.single import Narration
from mediaichemy.media.parameters import NarrationParameters
narration_params = NarrationParameters(
narration_text=("A student asked the master, "
"What is the sound of one hand clapping? "
"The master simply held up his hand."),
narration_voice_name="en_US-joe-medium",
narration_silence_tail=5,
narration_speed=1.0
)
narration = await Narration(params=narration_params).create()
Multi Media Examples
Media created combining multiple AI sources.
Image Video
A video created by first creating an image, then animating it. Enabling more customization on the starter image.
from mediaichemy.media.multi import ImageVideo
from mediaichemy.media.parameters import ImageVideoParameters
image_video_params = ImageVideoParameters(
video_prompt="A hyper realistic pink mantis wearing a tuxedo.",
image_model="rundiffusion:110@101",
video_model="bytedance:1@1",
width=1088,
height=1920
)
image_video = await ImageVideo(params=image_video_params).create()
https://github.com/user-attachments/assets/515ea7ee-2084-44eb-a4b8-90cb4602e4a7
Storyline Video
from mediaichemy.media.multi import StorylineVideo
from mediaichemy.media.parameters import StorylineVideoParameters
storyline_video_params = StorylineVideoParameters(
video_prompt="A forest in the rain",
image_model="rundiffusion:110@101",
video_model="bytedance:1@1",
width=1088,
height=1920,
narration_text="Listen to the rain.",
narration_voice_name="en_US-joe-medium",
narration_silence_tail=5,
narration_speed=1.0,
background_relative_volume=0.5,
background_audio_paths=[],
subtitle_fontname="Arial",
subtitle_fontsize=18,
subtitle_color="#FFEE00C7",
subtitle_outline_color="#000000",
subtitle_positions=["bottom_center", "top_center", "middle_center"]
)
storyline_video = await StorylineVideo(params=storyline_video_params).create()
https://github.com/user-attachments/assets/16e9170f-eab2-442a-a8d5-87204acbd662
Using the MediaCreator
By using MediaCreator, you let AI create ideas for you. You can use it to generate content for a specific media type or let it pick the best type for you automatically based on your prompt.
MediaCreator
Using MediaCreator with a specific media type
from mediaichemy.creator import MediaCreator
from mediaichemy.media import StorylineVideo
creator = MediaCreator(
creator_model='anthropic/claude-sonnet-4.5',
media_type=StorylineVideo)
media = await creator.create(user_prompt=(
"Create a short video telling a zen koan."
"The video features a hyperrealistic detailed natural setting."),
narration_voice_name='en_US-joe-medium')
https://github.com/user-attachments/assets/4dbaf275-0070-4117-a816-f5c775d39c91
Letting MediaCreator pick the best media type
from mediaichemy.creator import MediaCreator
creator = MediaCreator() # No media_type specified
media = await creator.create(
user_prompt="Create an image of a dog wearing a space helmet."
)
Metadata
Release files for mediaichemy 1.1.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| mediaichemy-1.1.2.tar.gz | 26.9 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| mediaichemy-1.1.2-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 61.9 kB
Release files / mediaichemy-1.1.2.tar.gz
| Download URL | mediaichemy-1.1.2.tar.gz |
|---|---|
| Size | 26.9 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
aeaf9a6a09b9dfa500470eb5bfb8ee54916649fac0ce4f96a34a3c0953f278a1
|
|
BLAKE2b-256 checksum How to use checksums |
54b63f2ebedd9294fb270a55b473fa9e7613d406a8c0fc2c11369c7e5bcd2336
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.13.7
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Jan 26, 2026.
Transparency logRelease files / mediaichemy-1.1.2-py3-none-any.whl
| Download URL | mediaichemy-1.1.2-py3-none-any.whl |
|---|---|
| Size | 35.0 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
6ba7137ad406e750b20d5ef90c0d9dbff677fa2607f13532fa4dcb43a7909d58
|
|
BLAKE2b-256 checksum How to use checksums |
01d4c03e210670605d2b84a42beb77e84f406ebf0f6e5a3d5c35baa7bd3daa89
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.13.7
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Jan 26, 2026.
Transparency log