QueryBot Tutorial

Note

This tutorial was written by GPT4 and edited by a human.

In this tutorial, we will learn how to use the QueryBot class to create a chatbot that can query documents using GPT-4. The QueryBot class allows us to index documents and use GPT-4 to generate responses based on the indexed documents.

Initializing QueryBot

To create a new instance of QueryBot, we need to provide a system message, a list of document paths, or a saved index path. The system message is used to instruct the chatbot on how to behave. The document paths are used to index the documents, and the saved index path is used to load a pre-built index.

Here's an example of how to initialize a QueryBot:

from pathlib import Path
from llamabot import QueryBot

system_message = "You are a helpful assistant that can answer questions based on the provided documents."
doc_paths = [Path("document1.txt"), Path("document2.txt")]

query_bot = QueryBot(system_message=system_message, doc_paths=doc_paths)

Querying the Index

To query the index, we can call the QueryBot instance with a query string. The QueryBot will return the top similarity_top_k documents from the index and use them to generate a response using GPT-4.

Here's an example of how to query the index:

query = "What is the main idea of document1?"
response = query_bot(query)
print(response.content)

Saving and Loading the Index

We can save the index to disk using the save method and load it later using the __init__ method with the saved_index_path parameter.

Here's an example of how to save and load the index:

# Save the index
query_bot.save("index.json")

# Load the index
loaded_query_bot = QueryBot(system_message=system_message, saved_index_path="index.json")

Inserting Documents into the Index

We can insert new documents into the index using the insert method. This method takes a file path as an argument and inserts the document into the index.

Here's an example of how to insert a document into the index:

query_bot.insert(Path("new_document.txt"))

Conclusion

In this tutorial, we learned how to use the QueryBot class to create a chatbot that can query documents using GPT-4. We covered how to initialize a QueryBot, query the index, save and load the index, and insert new documents into the index. With this knowledge, you can now create your own chatbot that can answer questions based on a set of documents.