AskAnything

Repo for Q&A bot with chat interface and custom data ingestion with vector database. Built using LangChain and Streamlit.

Dependencies

Make sure you have at least python 3.8 and install dependencies by running pip(3) install -r requirements.txt

Features

• Ingest your data in several formats and create a local vector database.
• Spin up a front-end UI using Streamlit to ask questions against the built vector database.
• LLMs are used to finalize the answer based on retrieved database documents.
• LLMs are also used to determine whether a topic of questioning has changed, which affects optimizations on chat history and memory.

Configuration

You can check out the configuration file in src/cfg/default.cfg. It currently has one sample site vero.fi which scrapes the Finnish tax office website for Finnish tax regulation, guidelines and other related information.

Ingesting data into vector database

There are several methods:

1. Sitemap Ingestion: See vero.fi.cfg.
2. Site Excel (individual pages listed in spreadsheet): See chunshi.cfg.
3. PDF: See sony_camera.cfg. There might be some code started on other methods but they are not mature yet.

Run data ingestion with a sample site (vero.fi)

1. Run python(3) src/ingest_data.py --site vero.fi [--debug] (debug switch will only scrape a tiny portion of the site so testing can be rapid)

Running the question answering chatbot locally with a sample site (vero.fi)

1. Export your OpenAI or Azure OpenAI API related environment variables as follows:

Variable Name	Description
OPENAI_API_KEY	Your OpenAI API key, or the Azure OpenAI resource's Key1 or Key2 (both are okay) if Azure
OPENAI_API_BASE	https://api.openai.com/v1 if OpenAI, or the Azure OpenAI resource's Endpoint value if Azure
OPENAI_API_TYPE	"open_ai" or "azure"

2. Run streamlit run src/app.py
3. Open your browser at localhost:8501?site=vero.fi