https://github.com/chigwell/animtoreal
This new package enables users to input a description or details about an animated character and receive a structured summary or step-by-step plan to bring that character into the real world, such as
https://github.com/chigwell/animtoreal
animated-character character-design conceptual-organization costume-development creative-facilitation creative-workflow development-process interactive-experience language-model-integration media-independent-processing physical-realization production-planning prop-design step-by-step-guide structured-summary
Last synced: about 1 month ago
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This new package enables users to input a description or details about an animated character and receive a structured summary or step-by-step plan to bring that character into the real world, such as
- Host: GitHub
- URL: https://github.com/chigwell/animtoreal
- Owner: chigwell
- Created: 2025-12-21T14:32:40.000Z (about 2 months ago)
- Default Branch: main
- Last Pushed: 2025-12-21T14:32:52.000Z (about 2 months ago)
- Last Synced: 2025-12-23T05:06:39.504Z (about 2 months ago)
- Topics: animated-character, character-design, conceptual-organization, costume-development, creative-facilitation, creative-workflow, development-process, interactive-experience, language-model-integration, media-independent-processing, physical-realization, production-planning, prop-design, step-by-step-guide, structured-summary
- Language: Python
- Homepage: https://pypi.org/project/animtoreal/
- Size: 5.86 KB
- Stars: 1
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# animtoreal
[](https://badge.fury.io/py/animtoreal)
[](https://opensource.org/licenses/MIT)
[](https://pepy.tech/project/animtoreal)
[](https://www.linkedin.com/in/eugene-evstafev-716669181/)
`animtoreal` is a lightweight Python package that turns a textual description of an animated character into a structured, step‑by‑step plan for bringing that character into the real world.
It extracts key information such as props, costumes, interactive experiences and other production details using a large language model, without requiring any media files.
> **Why use animtoreal?**
> - Quickly generate a production‑ready spec from a creative brief.
> - Leverage any LLM – the package ships with a default free‑tier LLM (`ChatLLM7`) but you can plug in OpenAI, Anthropic, Google Gemini, or any LangChain‑compatible model.
> - No heavy dependencies or UI required – just a single function call.
---
## 📦 Installation
```bash
pip install animtoreal
```
---
## 🚀 Quick Start
```python
from animtoreal import animtoreal
user_input = """
I want to create a small floating silver robot that can interact with children.
It should have smooth metal panels, a small LED face that displays simple emotions,
and a lightweight adjustable arm that can point at objects. The robot must be
battery powered, easy to clean, and have a friendly safety char.
"""
# Using the built‑in default LLM (ChatLLM7)
response = animtoreal(user_input)
print(response)
```
`response` will be a list of strings, each representing a structured element of the production plan.
---
## 📚 Function Signature
```python
animtoreal(
user_input: str,
api_key: Optional[str] = None,
llm: Optional[BaseChatModel] = None
) -> List[str]
```
| Parameter | Type | Description |
|-----------|------|-------------|
| `user_input` | `str` | Text description of the character. |
| `llm` | `Optional[BaseChatModel]` | A LangChain ChatModel instance. If omitted, the default `ChatLLM7` is used. |
| `api_key` | `Optional[str]` | API key for LLM7. If omitted, the package will look for `LLM7_API_KEY` in the environment, and fall back to `"None"` (for the free tier). |
---
## 🔗 Using Your Own LLM
`animtoreal` is agnostic to the underlying LLM.
Below are quick examples with popular providers.
### OpenAI
```python
from langchain_openai import ChatOpenAI
from animtoreal import animtoreal
llm = ChatOpenAI() # defaults to your OPENAI_API_KEY env var
response = animtoreal(user_input, llm=llm)
```
### Anthropic
```python
from langchain_anthropic import ChatAnthropic
from animtoreal import animtoreal
llm = ChatAnthropic()
response = animtoreal(user_input, llm=llm)
```
### Google Gemini
```python
from langchain_google_genai import ChatGoogleGenerativeAI
from animtoreal import animtoreal
llm = ChatGoogleGenerativeAI()
response = animtoreal(user_input, llm=llm)
```
---
## 🔒 LLM7 API Key & Rate Limits
- The default free tier of **LLM7** is usually sufficient for most small‑to‑medium projects.
- If you need higher limits, provide your key via an environment variable:
```bash
export LLM7_API_KEY="your_real_api_key"
```
or pass it directly:
```python
response = animtoreal(user_input, api_key="your_real_api_key")
```
- Obtain a free key at:
---
## 🤝 Contributing & Issues
- **GitHub Issues**:
Feel free to open an issue if you encounter bugs or have feature requests.
---
## 📄 Licensing
This project is open source under the MIT License. (Adapt as appropriate.)
---
## 👤 Maintainer
- **Eugene Evstafev**
[hi@euegne.plus](mailto:hi@euegne.plus)
GitHub: [@chigwell](https://github.com/chigwell)
---
Happy creating! 🎨🦾