https://pypi.org/project/rivalz-client/0.2.2/

from mimetypes import knownfiles

Rivalz Python Client link

rivalz-client is a Python client for interacting with the Rivalz API. It allows you to upload files, download files, and manage files on the Rivalz platform using IPFS.

Features link

• Upload Files: Upload any file to the Rivalz platform and get an IPFS hash.
• Upload Passport Images: Upload passport images to the Rivalz platform.
• Download Files: Download files from the Rivalz platform using an IPFS hash.v
• Delete Files: Delete files from the Rivalz platform using an IPFS hash.
• Vectorize Documents: Vectorize documents to create a RAG (Retrieval-Augmented Generation) based on the document uploaded.
• Create conversations: Create conversations based on the document uploaded.

Installation link

You can install the rivalz-client package via pip:

  pip install rivalz-client
  

Usage link

Here is a detailed guide on how to use the rivalz-client to interact with the Rivalz API.

Initialization link

First, import the RivalzClient class and initialize it with your secret token. If you don’t provide a token, it will use a default example token.

  from rivalz_client.client import RivalzClient

# Initialize the client with your secret token
client = RivalzClient('your_secret_token')
  

RAG (Retrieval-Augmented Generation) API link

Prerequisites link

Before using the RAG API, you need api key and some rivalz credits. Claim for free now here

Creating knowledge base from a document link

To vectorize a document (which will be used as embedding for the RAG) and create a knowledge base, use the create_rag_knowledge_base method with the path to the document. This method returns the knowledge base id which can be used to create a conversation. We now only support PDF files for creating knowledge bases.

  response = client.create_rag_knowledge_base('path/to/your/document.pdf', 'knowledge_base_name')
print(response)
# {'id': '66fa5bf022e73c17073768f0', 'name': 'test', 'files': '1727683567711_sample.pdf', 'userId': '66c4151c98bd0d3d47de682a'}
  

Adding document to an existed knowledge base link

To add document to existed knowledge base, use the add_document_to_knowledge_base method with the knowledge base id and the path to the document.

  response = client.add_document_to_knowledge_base('knowledge_base_id', 'path/to/your/document.pdf')
print(response)
  

Deleting document from an existed knowledge base link

To delete document from existed knowledge base, use the delete_document_from_knowledge_base method with the knowledge base id and the document name.

  response = client.delete_document_from_knowledge_base('knowledge_base_id', 'document_id')
print(response)
  

Getting all knowledge bases link

To get all knowledge bases, use the get_knowledge_bases method.

  response = client.get_knowledge_bases()
print(response)
  

Getting details of a knowledge base link

To get details of a knowledge base, use the get_knowledge_base method with the knowledge base id.

  response = client.get_knowledge_base('knowledge_base_id')
print(response)
  

Creating a conversation link

To create a conversation, use the create_chat_session method with the knowledge base id and the question. This will return the AI response along with the chat session id.

  response = client.create_chat_session('knowledge_base_id', 'question')
print(response)
# {'answer': 'Hello! How can I help you today? \n', 'session_id': '66fa625fb58f5a4b9a30b983', 'userId': '66c4151c98bd0d3d47de682a'}
  

Adding a message to a conversation link

To add a message to a conversation, use the same method create_chat_session with the chat session id and the message.

  response = client.create_chat_session('knowledge_base_id', 'message', 'chat_session_id')
print(response)
  

Getting all conversations link

To get all conversations, use the get_chat_sessions method.

  response = client.get_chat_sessions()
print(response)
  

Getting details of a conversation link

To get details of a conversation (which contains chat history for this conversation), use the get_chat_session method with the chat session id.

  response = client.get_chat_session('chat_session_id')
print(response)
  

Get uploaded documents link

To get all uploaded documents, use the get_uploaded_documents method.

  response = client.get_uploaded_documents()
print(response)
  

Examples link

Here is a complete example demonstrating how to use the rivalz-client to create a simple RAG conversation based on a PDF document:

  # main.py

import os
from dotenv import load_dotenv
from rivalz_client.client import RivalzClient


def main():
    # Load environment variables from .env file
    load_dotenv()

    # Get the secret token from environment variables
    secret_token = os.getenv('SECRET_TOKEN')

    if not secret_token:
        raise ValueError("SECRET_TOKEN is not set in the environment variables.")

    # Initialize the RivalzClient with the secret token
    client = RivalzClient(secret_token)

    # create knowledge base
    knowledge_base = client.create_rag_knowledge_base('sample.pdf', 'knowledge_base_name')
    knowledge_base_id = knowledge_base['id']
    # create conversation
    conversation = client.create_chat_session(knowledge_base_id, 'what is the document about?')
    conversation_id = conversation['session_id']
    # add message to conversation
    conversation = client.create_chat_session(knowledge_base_id, 'what is the document about?', conversation_id)
    print(conversation['answer'])


if __name__ == '__main__':
    main()