# A new Lang Chain Chat BOT for Educational Purpose: ChatterPY

**URL:** <https://discuss.huggingface.co/t/a-new-lang-chain-chat-bot-for-educational-purpose-chatterpy/104645>\
**Category:** Beginners\
**Created:** [August 30, 2024, 10:03am UTC](https://discuss.huggingface.co/t/a-new-lang-chain-chat-bot-for-educational-purpose-chatterpy/104645 "2024-08-30T10:03:43Z")\
**Posts on this page:** 1\
**Page:** 1

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**Author:** ![sasadangelo](https://sea2.discourse-cdn.com/hellohellohello/user_avatar/discuss.huggingface.co/sasadangelo/32/19276_2.png) [@sasadangelo](https://discuss.huggingface.co/u/sasadangelo)\
**Post date:** [August 30, 2024, 10:03am UTC](https://discuss.huggingface.co/t/a-new-lang-chain-chat-bot-for-educational-purpose-chatterpy/104645/1 "2024-08-30T10:03:43Z")

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Hi All,

In July 2023 I started to study LLM a bit and after few months I posted here a [link](https://discuss.huggingface.co/t/chat-with-a-pdf/53967) with tool I called ChatPDF I developed for educational purpose.

After few months of pause I upgraded that ChatBOT to a more complete Educational Chat BOT that has the following features:

- Multi Provider
- Multi Model
- Highly configurable
- Configurable Memory strategy
- Configurable Decoding Parameters
- Configurable RAG support
- DataWaeve CLI to scrape data from different data sources (for the moment only PDF and Wikipedia Pages are supported) and store in a Vector Store.
- Qdrant vector database in local mode supported (new Database can be easily added)

I called this Chat BOT **ChatterPy** and you can find the [link here](https://github.com/sasadangelo/chatterpy). Consider it just a Toy for Educational purpose.

If you’re interested how I built it, I create these [Lang Chain tutorials structured in 11](https://github.com/sasadangelo/langchain-tutorials) lessons that teach you how I implemented it step by step starting from a simple Hello World until the final code.

Hope this help someone else to learn more about LLM.  
Any feedback is welcome.