Privacera Securechat

Secure Chat is a conversational AI chatbot . Secure chat allows users to create conversations with an AI chatbot which can optionally be governed by Privacera AI Governance Services(PAIG). Secure chat library provides an easy to use, plugable platform which will allow developers/users to have open sourced chatbot python library.

Contents

• Installation
• Usage
• Configuration
• Configure Privacera Shield Config

Installation

Privacera Secure chat is a python library which can be installed using pip.

pip install privacera_securechat

Usage

Privacera Secure chat can be used in following ways: Before starting the securechat , please download your Privacera Shield Config file.Then run the following command to copy file to desired destination.

mkdir -p custom-configs
cp <path to privacera-shield-app-name-config.json> custom-configs/privacera-shield-config.json

1. Run as a service: You can simply run the secure chat as a service by running following command:

privacera_securechat run

To get the help for the command and see all available [OPTIONS], you can run the following command:

privacera_securechat --help

Example:

privacera_securechat run --port 2324 --host 0.0.0.0 --openai_api_key <API_KEY> 

2. Run as a library: You can run Privacera Secure chat in background by importing the library in your python code. Please run help command to see all available options you can pass while calling launch_app method.

from privacera_securechat import launcher
# Start the Privacera Secure Chatbot
session = launcher.launch_app()
# To start without PAIG Shield
# session = launcher.launch_app(disable_paig_shield_plugin=True)
# To get active sessions
active_session = launcher.get_active_session()
print(active_session)
# To view the chatbot in the browser/Iframe
print(active_session.url)
# To view the chatbot in the Iframe
active_session.view()
# To stop the chatbot
launcher.close_app()

Configuration

Privacera Secure chat provides overlay configuration. You can provide the custom configuration in the following ways:

1. Create a new directory in the present working directory of the project with the name custom-configs.
2. Create a new custom configuration file named standalone_config.yaml in the custom-configs folder which is provided to the application.
3. In custom configuration file , user should provide new configuration key-values or override the existing configuration.
4. User can configure response_if_no_docs_found to provide a custom response when vector DB return no docs, If user want response from AI Model then set response_if_no_docs_found to null
   Example: custom-configs/standalone_config.yaml

#MODELS CONFIG
AI_applications:
  file_path: "configs/AI_applications.json"
  default_implementation_class: "services.OpenAI_Application.OpenAIClient.OpenAIClient"
  response_if_no_docs_found: "I cannot answer this question as there was no context provided"
  sales_model:
    conversation_history_k: 5
    paig_shield_config_file: "custom-configs/privacera-shield-config.json"
    disable_conversation_chain: false
    vectordb:
      index_path: "securechat/sales/index"
      data_path: "securechat/sales/data"
      vector_type: "chroma"

Configure Privacera Shield Config

Privacera Secure chat provides an option to configure the Privacera Shield Config. You can refer to standalone_config.yaml to see location of the shield config file. All you need to do is to copy Privacera Shield Config file to the location mentioned in the standalone_config.yaml file.