End to end Chat application

We can run this application either on a localhost or a server.

We show the step-by-step guide to build an end-to-end chatbot. We first set the OpenAI api key

export OPENAI_API_KEY=<API-KEY>

Under the repo directory, we can run the following command to launch a streamlit chatbot app. The source code can be found at here.

poetry run streamlit run examples/denser_chat.py

This command first builds a mini retriever with the following code.

index_name = "unit_test_denser"
retriever = RetrieverGeneral(index_name, "tests/config-denser.yaml")
retriever.ingest("tests/test_data/denser_website_passages_top10.jsonl")

It then launches a webpage with interactive UI so users can input queries. Once it is launched, we will see a chatbot interface similar to the following screenshot. We can ask any question to the chatbot and get the response. Below shows an example query of what use cases does denser support? The retriever first returns the relevant passages listed under the section of Sources at the bottom of the screenshot. These passages are fed to a LLM and the final summarization is displayed on the chat window.

Denser Chat

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