Welcome to chipper Discussions!

[TilmanGriesel]

👋 Welcome!

We’re using Discussions as a place to connect with other members of our community. We hope that you:

• Ask questions you’re wondering about.
• Share ideas.
• Engage with other community members.
• Welcome others and are open-minded. Remember that this is a community we
  build together 💪.

To get started, comment below with an introduction of yourself and tell us about what you do with this community.

[doobidoo]

Hi Tilman,
a heads up for your great repository! Now I am making my first steps with Chipper.
Maybe you have some thoughts on how to integrate this: https://github.com/microsoft/markitdown to be able to also embed all the other file types.

Hello everyone!

I'm excited to join this community where we can all share our experiences and insights about using Chipper. I've been working with Chipper for few days only now, primarily in the context of learning to know its strenght and weaknesses. It has been a fantastic tool due to its flexibility, ease of use and versatility.

In my work, I've found Chipper particularly useful for embedding all my local repositories and ask questions about them.
I'm looking forward to have it also embed other file types.

Let me analyze Chipper's usefulness and code quality by looking at the repository structure and implementation details.

Looking at Chipper's repository structure and our recent work with it, here's my assessment:

Code Quality:

1. Strong Development Practices:

   • Comprehensive pre-commit hooks (black, isort, flake8, prettier)
   • Well-structured project layout following Python best practices
   • Clear separation of concerns (tools, services, examples)
   • Docker support for consistent development environments
   • Git LFS implementation for handling large files

2. Code Architecture:

   • Modular design with clear component separation
   • Strong typing with Python type hints
   • Extensive logging and error handling
   • Well-documented classes and methods
   • Clean code practices (as seen in document_processor.py)

Usefulness:

1. AI Integration Features:

   • Integration with Ollama for local AI model deployment
   • Haystack RAG (Retrieval Augmented Generation) implementation
   • Document processing and embedding capabilities
   • Flexible configuration options

2. Developer Experience:

   • Easy setup with run.sh script
   • Docker Compose examples for quick start
   • Comprehensive documentation
   • Example implementations provided
   • Clear contribution guidelines

3. Practical Applications:

   • Local AI model experimentation
   • Document analysis and processing
   • Knowledge base building and querying
   • Custom AI interface development

What makes Chipper particularly valuable is its focus on being a "tinkerer's tool" - it provides a robust foundation for AI experimentation while maintaining high code quality standards. The combination of local AI model support, RAG capabilities, and strong development practices makes it an excellent choice for both learning and building practical AI applications.

I’m looking forward to learning from others here and contributing to the discussions. If anyone has tips on optimizing Chipper for tooluse or insights into best practices, I'd love to hear them!

Welcome to everyone else who's joining! Let's build this community together. 💪
Best Regards
Henry

[chirag011-prog]

can we connect chipper to psql db ? if yes how
could you please share some insight about that