chatbees-python-client 1.2.1

Python client for ChatBees

chatbees-python-client

Python client for ChatBees, a Serverless Platform for your LLM Apps. ChatBees provides simple and scalable APIs, enabling you to craft a LLM app for your knowledge base in mere minutes.

We're actively improving the product and releasing new features, and we'd love to hear your feedback! Please take a moment to fill out this feedback form to help us understand your use-case better.

Signup with your Google or Microsoft account on https://www.chatbees.ai.

ChatBees python client provides very simple APIs for you to directly upload files, crawl websites, ingest data sources including Confluence, Notion and Google Drive. Then you can simply ask questions.

Quickstart

You can try out ChatBees in just a few lines of code. You can create your own collections, upload files, then get answers specific to your data assets. The following example walks you through the process of creating a collection and indexing the original transformer paper into that collection.

import chatbees as cb

# Create an API key on UI after signup/signin.
# Configure cb to use the newly minted API key.
cb.init(api_key=my_api_key, account_id=your_account_id)

# Create a new collection
llm_research = cb.Collection(name="llm_research")
cb.create_collection(llm_research)

# Index the original Transformer paper into this collection.
llm_research.upload_document("https://arxiv.org/pdf/1706.03762.pdf")

# Get answers from this paper
llm_research.ask("what is a transformer?")

Installation

Install a released ChatBees python client from pip.

python3 version >= 3.10 is required

pip3 install chatbees-python-client

In the following examples, we will assume you have signup with your google account.

Creating a Collection

You can create a collection that is only accessible with a specific API key.

import chatbees as cb

cb.init(api_key=my_api_key, account_id=your_account_id)

# Create a collection called llm_research
collection = cb.Collection(name='llm_research')
cb.create_collection(collection)

Listing collection

You can see list of collections you have access to. For example, this list will include all collections that were created using the currently configured API key.

import chatbees as cb

cb.init(api_key=my_api_key, account_id=your_account_id)

collections = cb.list_collections()

Uploading a document

You can upload a local file or a file from a web URL and index it into a collection.

Supported file format

• .pdf PDF files
• .csv CSV files
• .txt Plain-text files
• .md Markdown files
• .docx Microsoft word documents

import chatbees as cb

cb.init(api_key=my_api_key, account_id=your_account_id)

# llm_research collection was created in the previous step
collection = cb.collection('llm_research')

# Local file and URLs are both supported.
# URL must contain the full scheme prefix (http:// or https://)
collection.upload_document('/path/to/file.pdf')
collection.upload_document('https://path/to/file.pdf')

Crawl a website

You can pass the website root url. ChatBees will automatically crawl it.

import chatbees as cb

cb.init(api_key=my_api_key, account_id=your_account_id)

# Create the crawl task
collection = cb.Collection(name='example-web')
cb.create_collection(collection)

root_url = 'https://www.example.com'
crawl_id = collection.create_crawl(root_url)

# Query the crawl status
resp = collection.get_crawl(crawl_id)

# If re-crawl the same root_url, delete the old indexed crawl results
collection.delete_crawl(root_url)

# check resp.crawl_status becomes CrawlStatus.SUCCEEDED, and index the pages
collection.index_crawl(crawl_id)

Asking a question

You can ask questions within a collection. API key is required for private collections only. ask() method returns a plain-text answer to your question, as well as a list of most relevance references used to derive the answer.

import chatbees as cb

cb.init(api_key=my_api_key, account_id=your_account_id)

# Get a plain text answer, as well as a list of references from the collection
# that are the most relevant to the question.
answer, refs = cb.collection('llm_research').ask('what is a transformer?')

Deleting a collection

You can delete a collection using the same API key that was used to create it.

import chatbees as cb

cb.init(api_key=my_api_key, account_id=your_account_id)

cb.delete_collection('llm_research')