stratix-summarizer 2025.12.21162741

A new package is designed to analyze and summarize business strategy narratives, investor communications, or crowdfunding campaign descriptions to extract structured insights about startup funding act

Stratix-Summarizer

Extract structured insights from startup funding narratives

Stratix-Summarizer is a Python package designed to analyze and summarize business strategy narratives, investor communications, crowdfunding campaign descriptions, or any startup-related text. It extracts structured insights about funding activities—such as fundraising amounts, sources, and strategic context—from unstructured text, providing clear, actionable summaries for investors, entrepreneurs, and analysts.

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🚀 Features

• Structured Extraction: Parses unstructured text to extract key funding-related details.
• Flexible LLM Integration: Works with LLM7 (default), OpenAI, Anthropic, Google, or any LangChain-compatible LLM.
• Regex Validation: Ensures extracted data matches predefined patterns for consistency.
• Lightweight & Fast: Optimized for quick processing of startup funding narratives.

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📦 Installation

Install via pip:

pip install stratix_summarizer

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🔧 Usage Examples

Basic Usage (Default LLM7)

from stratix_summarizer import stratix_summarizer

user_input = """
Our startup raised $5M in Series A funding from Sequoia Capital and a16z.
The funds will be used for R&D and scaling our AI product.
"""

response = stratix_summarizer(user_input)
print(response)

Custom LLM Integration

Using OpenAI

from langchain_openai import ChatOpenAI
from stratix_summarizer import stratix_summarizer

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

Using Anthropic

from langchain_anthropic import ChatAnthropic
from stratix_summarizer import stratix_summarizer

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

Using Google Vertex AI

from langchain_google_genai import ChatGoogleGenerativeAI
from stratix_summarizer import stratix_summarizer

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

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🔑 API Key Configuration

• Default: Uses LLM7_API_KEY from environment variables.
• Manual Override: Pass the API key directly:

  stratix_summarizer(user_input, api_key="your_llm7_api_key")
  

• Get a Free API Key: Register at LLM7

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📝 Input Parameters

Parameter	Type	Description
user_input	str	The text to analyze (e.g., funding narratives, investor updates).
api_key	Optional[str]	LLM7 API key (if not using default).
llm	Optional[BaseChatModel]	Custom LLM (e.g., ChatOpenAI, ChatAnthropic).

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📊 Output

Returns a list of structured insights (e.g., extracted funding amounts, sources, and strategic notes) in a machine-readable format.

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🔄 Rate Limits

• LLM7 Free Tier: Sufficient for most use cases.
• Upgrade: Pass a custom API key for higher limits.

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📜 License

MIT

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📢 Support & Issues

For bugs or feature requests, open an issue: 🔗 GitHub Issues

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👤 Author

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