A new package designed to process and interpret structured descriptions of neural network architectures from textual input. Users provide detailed text about an ANN's innate design, such as layer type
Project description
Architextor
A Python package for processing and interpreting structured descriptions of neural network architectures from textual input. Architextor uses pattern matching and retries to parse user-provided text about ANN designs (layer types, connections, parameters, etc.) and returns a formalized, machine-readable representation (e.g., JSON schema or graph outline).
Installation
pip install architextor
Usage
Basic Example
from architextor import architextor
user_input = "A neural network with two dense layers: first layer has 128 units and ReLU activation, second has 10 units and softmax activation."
response = architextor(user_input)
print(response)
Using a Custom LLM
You can pass your own LangChain-compatible LLM instance to use OpenAI:
from langchain_openai import ChatOpenAI
from architextor import architextor
llm = ChatOpenAI()
response = architextor(user_input, llm=llm)
use Anthropic:
from langchain_anthropic import ChatAnthropic
from architextor import architextor
llm = ChatAnthropic()
response = architextor(user_input, llm=llm)
use Google:
from langchain_google_genai import ChatGoogleGenerativeAI
from architextor import architextor
llm = ChatGoogleGenerativeAI()
response = architextor(user_input, llm=llm)
Using a Custom API Key
The default LLM is ChatLLM7 (from langchain_llm7). You can provide your own API key:
Via environment variable:
export LLM7_API_KEY="your_api_key_here"
Or directly in code:
response = architextor(user_input, api_key="your_api_key_here")
Get a free API key by registering at https://token.llm7.io/.
Parameters
user_input(str): The user input text describing the neural network architecture.llm(Optional[BaseChatModel]): A LangChain LLM instance. If not provided, defaults to ChatLLM7.api_key(Optional[str]): API key for LLM7. If not provided, defaults to theLLM7_API_KEYenvironment variable.
Default Rate Limits
The default rate limits for LLM7 free tier are sufficient for most use cases. For higher rate limits, provide your own API key.
Issues
Report issues or feature requests on GitHub.
Author
Eugene Evstafev
Email: hi@euegne.plus
GitHub: chigwell
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