LLMChat

A local LLM chat application and can also uses your Journal as a knowledge base for context-aware conversations.

LLMChat.mp4

Setup

1. Install Ollama:

# macOS/Linux
brew install ollama

2. Install a model:

ollama pull deepseek-r1:1.5b

3. Install application dependencies:

python -m venv venv
source venv/bin/activate  
pip install -r requirements.txt

4. Run the application:

python app.py

Usage

1. Enter your model name in the application (e.g., deepseek-r1:1.5b)
2. Add entries to your diary through the memory interface
3. Chat with the AI using your diary as context

Technical Stack

• Backend: Flask, LangChain, Ollama
• Frontend: HTML, CSS, JavaScript, Tailwind CSS
• Database: ChromaDB (Vector Store)