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README.md

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 short_description: A chatbot using RAG with Langchain and Hugging face model
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-An example chatbot using [Gradio](https://gradio.app), [`huggingface_hub`](https://huggingface.co/docs/huggingface_hub/v0.22.2/en/index), and the [Hugging Face Inference API](https://huggingface.co/docs/api-inference/index).
+An example chatbot using [Gradio](https://gradio.app), [`huggingface_hub`](https://huggingface.co/docs/huggingface_hub/v0.22.2/en/index), and the [Hugging Face Inference API](https://huggingface.co/docs/api-inference/index).
+
+Steps:
+- Retrieve text data from website using Beautifulsoup
+- Clean the data
+- Chunk the text base on token character split using Langchain
+- Use bm25 frequency based as a retriever as characters name are unique and have better results finding similar text to the query. Additionally it takes less time than embedding
+- Promp engineering on the system (Adding context on system and update it each query or adding context on the user message). I chose to put it in the user message as results are better.
+- Use open source to correct user queries syntax and grammar and for the chatbot
+- Build gradio app