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---
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license: mit
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---
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# Responsible-AI-Moderation Model
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## Table of Contents
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- [Introduction](#introduction)
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- [Features](#features)
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- [Installation](#installation)
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- [Set Configuration Variables](#set-configuration-variables)
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- [Models Required](#models-required)
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- [Running the Application](#running-the-application)
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- [License](#license)
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- [Contact](#contact)
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## Introduction
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The **Moderation Model** module acts as a central hub for machine learning models for prompt injection, toxicity, jailbreak, restricted topic, custom theme and refusal checks. It provides the endpoints to utilize the response generated by these models.
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## Features
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The **Moderation Model** module acts as a wrapper for the traditional AI models we are using for various checks like prompt injection, jailbreak, toxicity etc.
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## Installation
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To run the application, first we need to install Python and the necessary packages:
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1. Install Python (version >= 3.9 & <3.12) from the [official website](https://www.python.org/downloads/) and ensure it is added to your system PATH.
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2. Clone the repository : responsible-ai-ModerationModel:
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```sh
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git clone <repository-url>
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```
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3. Navigate to the `responsible-ai-ModerationModel` directory:
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```sh
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cd responsible-ai-ModerationModel
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```
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4. Create a virtual environment:
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```sh
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python -m venv venv
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```
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5. Activate the virtual environment:
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- On Windows:
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```sh
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.\venv\Scripts\activate
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```
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6. Go to the `requirements` directory where the `requirement.txt` file is present.
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In the `requirement.txt` file comment the
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```sh
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lib/torch-2.2.0+cu118-cp39-cp39-linux_x86_64.whl
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```
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**Note:** Download appropriate torch version supporting python version which is installed [i.e if Python version is 3.10 use torch-2.2.0+cu118-**cp310**-**cp310**-**linux**_x86_64.whl, where cp310 denotes python version 3.10 and linux denotes OS which can be linux/win and **_not applicable for Mac_**]
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**Note:** If working in windows as this is for linux and replace
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```sh
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lib/
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```
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with
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```sh
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../lib/
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```
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**Note:** If working in Mac Os, run the below command after running requirement.txt
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```sh
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pip install --pre torch torchvision torchaudio \--extra-index-url https://download.pytorch.org/whl/nightly/cpu
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```
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Download and place the en_core_web_lg-3.5.0-py3-none-any.whl inside the lib folder.
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[en_core_web_lg](https://github.com/explosion/spacy-models/releases/download/en_core_web_lg-3.5.0/en_core_web_lg-3.5.0-py3-none-any.whl) and install the requirements:
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```sh
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pip install -r requirement.txt
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```
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**Note:** when running requirement.txt, if getting error related to "cuda-python" then comment cuda-python from
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requirement.txt file and run pip install again
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Install the fastapi library as well, use the following command:
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```sh
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pip install fastapi
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```
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## Set Configuration Variables
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After installing all the required packages, configure the variables necessary to run the APIs.
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1. Navigate to the `src` directory:
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```sh
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cd ..
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```
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2. Locate the `.env` file, which contains keys like the following:
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```sh
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workers=1
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WORKERS="${workers}"
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# DB_NAME="${dbname}"
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# DB_USERNAME="${username}"
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# DB_PWD="${password}"
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# DB_IP="${ipaddress}"
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# DB_PORT="${port}"
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# MONGO_PATH="mongodb://${DB_USERNAME}:${DB_PWD}@${DB_IP}:${DB_PORT}/"
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# MONGO_PATH= "mongodb://localhost:27017/"
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```
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3. Replace the placeholders with your actual values.
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## Models Required
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The following models are required to run the application. Download all the model files from the links provided, and place it in the folder name provided.
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1. [Prompt Injection](https://huggingface.co/deepset/deberta-v3-base-injection/tree/main)
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Files required to download here are : model.safetensors, config.json, tokenizer_config.json, tokenizer.json, special_tokens_map.json.
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Name the folder as 'dbertaInjection'.
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2. [Restricted Topic](https://huggingface.co/MoritzLaurer/deberta-v3-base-zeroshot-v2.0/tree/main)
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Files required to download here are : model.safetensors, added_tokens.json, config.json, special_tokens_map.json, spm.model, tokenizer.json, tokenizer_config.json.
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Name the folder as 'restricted-dberta-base-zeroshot-v2'.
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3. [Sentence Transformer Model](https://huggingface.co/sentence-transformers/multi-qa-mpnet-base-dot-v1/tree/main)
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Files required to download here are : 1_Pooling folder, pytorch_model.bin, vocab.txt, tokenizer.json, tokenizer_config.json, special_tokens_map.json, sentence_bert_config.json, modules.json, config.json, config_sentence_transformers.json.
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Name the folder as 'multi-qa-mpnet-base-dot-v1'.
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4. [Detoxify](https://huggingface.co/FacebookAI/roberta-base/tree/main)
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Files required to download here are : vocab.json, tokenizer.json, merges.txt, config.json.
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Now download the model checkpoint file from this url and keep it under this folder -
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[toxic_model_ckpt_file](https://github.com/unitaryai/detoxify/releases/download/v0.3-alpha/toxic_debiased-c7548aa0.ckpt)
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Name the folder as 'detoxify'.
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Place the above folders in a folder named 'models' in the following way: 'responsible-ai-mm-flask/models'.
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## Running the Application
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Once we have completed all the aforementioned steps, we can start the service.
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1. Navigate to the `src` directory:
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2. Run `main.py` file:
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```sh
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python main.py
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```
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3. PORT_NO : Use the Port No that is configured in .env file.
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Open the following URL in your browser:
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`http://localhost:<PORT_NO>/rai/v1/raimoderationmodels/docs`
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Note:- To address the issue where the Passport Number is not recognized in Privacy, modify the "piiEntitiesToBeRedacted" field in the privacy() under service.py file (line no: 98) from None to an empty list []. This adjustment ensures that the Passport Number is correctly identified.
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## License
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The source code for the project is licensed under the MIT license, which you can find in the [LICENSE.txt](LICENSE.txt) file.
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## Contact
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If you have more questions or need further insights please feel free to connect with us @ [email protected] |
