lifelogger-ai 2025.12.21160026

A new package that helps users capture and organize their life moments in a structured way. Users can input their experiences, thoughts, or significant events, and the package will process this text t

lifelogger‑ai

A lightweight Python package for turning raw life‑journal entries into structured summaries.
lifelogger‑ai takes a block of text describing a moment, event or thought, sends it to an LLM, and extracts a concise summary that includes context, emotions, and key points. The output can be used for personal journaling, social‑media sharing or building collections of meaningful life moments.

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Installation

pip install lifelogger_ai

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Quick Start

from lifelogger_ai import lifelogger_ai

# Text you want to process
user_input = """
I spent the afternoon hiking up Blue Ridge Mountain, feeling a mix of triumph and exhaustion.
The wind was blowing strong and the view from the summit was breathtaking. I took a photo of a golden sunrise over the valley.
"""

# Run the lifestream summarization
summary = lifelogger_ai(user_input)

print(summary)
# ['Summarised sentences here...']

The function returns a list of strings – one or more sentences that capture the essence of the input.

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Parameters

Name	Type	Description
user_input	str	The raw text describing a personal moment, event or thought.
llm	Optional[BaseChatModel]	A LangChain language‑model instance to use for processing. If omitted, the default ChatLLM7 from langchain_llm7 is used.
api_key	Optional[str]	The API key for LLM7. If omitted, the package first looks for the LLM7_API_KEY environment variable; otherwise a free‑tier key is used.

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Using Your Own LLM

lifelogger-ai is LLM‑agnostic. Pass any LangChain model that implements BaseChatModel to the function:

# Example 1 – OpenAI
from langchain_openai import ChatOpenAI
from lifelogger_ai import lifelogger_ai

llm = ChatOpenAI(model="gpt-4o-mini")
response = lifelogger_ai("Your text here", llm=llm)

# Example 2 – Anthropic
from langchain_anthropic import ChatAnthropic
from lifelogger_ai import lifelogger_ai

llm = ChatAnthropic()
response = lifelogger_ai("Your text here", llm=llm)

# Example 3 – Google Gemini
from langchain_google_genai import ChatGoogleGenerativeAI
from lifelogger_ai import lifelogger_ai

llm = ChatGoogleGenerativeAI()
response = lifelogger_ai("Your text here", llm=llm)

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Rate Limits & API Key for LLM7

The free tier of LLM7 offers rate limits that generally suffice for typical usage.
If you need higher limits:

• Environment variable: export LLM7_API_KEY=your_key_here
• Explicit argument: lifelogger_ai(user_input, api_key="your_key_here")

Get a free key at https://token.llm7.io/

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Contributing & Issues

Feel free to open issues or submit pull requests on GitHub: https://github.com/chigwell/lifelogger-ai

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Author

Eugene Evstafev
Email: [e-mail]
GitHub: chigwell

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