https://github.com/chigwell/lifelogger-ai
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
https://github.com/chigwell/lifelogger-ai
capture categorize context emotions experiences extract-details journaling key-points life-experiences life-moments organize personal-collection revisiting sharing significant-events social-sharing structured-overview summarization text-processing thoughts
Last synced: 5 months ago
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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
- Host: GitHub
- URL: https://github.com/chigwell/lifelogger-ai
- Owner: chigwell
- Created: 2025-12-21T16:00:25.000Z (5 months ago)
- Default Branch: main
- Last Pushed: 2025-12-21T16:00:35.000Z (5 months ago)
- Last Synced: 2025-12-23T05:58:28.140Z (5 months ago)
- Topics: capture, categorize, context, emotions, experiences, extract-details, journaling, key-points, life-experiences, life-moments, organize, personal-collection, revisiting, sharing, significant-events, social-sharing, structured-overview, summarization, text-processing, thoughts
- Language: Python
- Homepage: https://pypi.org/project/lifelogger-ai/
- Size: 5.86 KB
- Stars: 1
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# lifelogger‑ai
[](https://badge.fury.io/py/lifelogger-ai)
[](https://opensource.org/licenses/MIT)
[](https://pepy.tech/project/lifelogger-ai)
[](https://www.linkedin.com/in/eugene-evstafev-716669181/)
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
```bash
pip install lifelogger_ai
```
---
## Quick Start
```python
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:
```python
# 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)
```
```python
# Example 2 – Anthropic
from langchain_anthropic import ChatAnthropic
from lifelogger_ai import lifelogger_ai
llm = ChatAnthropic()
response = lifelogger_ai("Your text here", llm=llm)
```
```python
# 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
---
## Contributing & Issues
Feel free to open issues or submit pull requests on GitHub:
---
## Author
Eugene Evstafev
Email: hi@euegne.plus
GitHub: **chigwell**
---