iac-summarizer 2025.12.21180340

A new package that analyzes technical arguments and extracts structured summaries from text discussions about infrastructure-as-code practices. It takes user-provided text (such as forum posts, articl

iac-summarizer

Extract structured summaries from infrastructure-as-code (IaC) discussions

A Python package that analyzes technical arguments in text discussions about IaC practices and extracts concise, structured summaries. Ideal for developers and architects who need quick insights from lengthy technical debates, forum posts, or documentation.

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🚀 Features

• Extracts core arguments from text discussions about IaC (e.g., Terraform, CloudFormation, Pulumi).
• Validates output against predefined patterns for consistency.
• Supports custom LLMs via LangChain for flexibility.
• Defaults to ChatLLM7 (from langchain_llm7) for simplicity.

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📦 Installation

pip install iac_summarizer

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🔧 Usage

Basic Usage (Default LLM: ChatLLM7)

from iac_summarizer import iac_summarizer

user_input = """
Discussion about drawbacks of generic multi-cloud Terraform modules:
'These modules lack specificity, leading to bloated configurations and harder maintenance...'
"""

response = iac_summarizer(user_input)
print(response)

Custom LLM (e.g., OpenAI, Anthropic, Google)

Replace the default LLM with your preferred provider:

OpenAI

from langchain_openai import ChatOpenAI
from iac_summarizer import iac_summarizer

llm = ChatOpenAI()
response = iac_summarizer(user_input, llm=llm)

Anthropic

from langchain_anthropic import ChatAnthropic
from iac_summarizer import iac_summarizer

llm = ChatAnthropic()
response = iac_summarizer(user_input, llm=llm)

Google Generative AI

from langchain_google_genai import ChatGoogleGenerativeAI
from iac_summarizer import iac_summarizer

llm = ChatGoogleGenerativeAI()
response = iac_summarizer(user_input, llm=llm)

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🔑 API Key Configuration

• Default: Uses LLM7_API_KEY from environment variables.
• Override: Pass directly via api_key parameter:

  response = iac_summarizer(user_input, api_key="your_llm7_api_key")
  

• Get a Free Key: Register at https://token.llm7.io/.

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📌 Parameters

Parameter	Type	Description
user_input	str	Text to analyze (e.g., forum posts, articles, or comments).
llm	Optional[BaseChatModel]	Custom LangChain LLM (e.g., ChatOpenAI, ChatAnthropic). Defaults to ChatLLM7.
api_key	Optional[str]	LLM7 API key (falls back to LLM7_API_KEY env var).

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📝 Output Format

The function returns a list of structured summaries extracted from the input text, validated against predefined patterns.

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🔄 Rate Limits

• Default (LLM7 Free Tier): Sufficient for most use cases.
• Upgrade: Use your own API key or environment variable (LLM7_API_KEY).

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📖 License

MIT

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📢 Support & Issues

For bugs or feature requests, open an issue at: https://github.com/chigwell/iac-summarizer/issues

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👤 Author

Eugene Evstafev 📧 [e-mail] 🔗 GitHub: chigwell