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.
Installation
pip install lifelogger_ai
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.
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. |
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)
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/
Contributing & Issues
Feel free to open issues or submit pull requests on GitHub: https://github.com/chigwell/lifelogger-ai
Author
Eugene Evstafev
Email: hi@euegne.plus
GitHub: chigwell
Metadata
Release files for lifelogger-ai 2025.12.21160026
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| lifelogger_ai-2025.12.21160026.tar.gz | 7.1 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| lifelogger_ai-2025.12.21160026-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 14.7 kB
Release files / lifelogger_ai-2025.12.21160026.tar.gz
| Download URL | lifelogger_ai-2025.12.21160026.tar.gz |
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| Size | 7.1 kB |
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| Tags | Python 3 |
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