What's included

• NestJS OpenID Connect Service Provider (Oauth 2.0)

  I have developed a NestJS-based service provider with the following functionalities: Technologies Used: Backend Framework: NestJS Programming Language: TypeScript Authentication Protocol: OAuth 2.0 Data Storage: Cookies Features Implemented: User Authentication: Users can authenticate through their Google accounts. Implemented OAuth 2.0 for secure authentication. User Logout: Provided a logout endpoint to disconnect the user's session securely. Identity Data Handling: After successful login, the service provider receives and views the user's identity data. The received identity data is saved and stored in cookies. User Recognition: The application can recognize returning users based on the saved identity data in cookies. Debugging Information (Bonus): Additional information to help debug the kinematics of the authentication process. Unit Testing: Comprehensive unit tests were written for each implemented functionality. Appropriate test frameworks for NestJS were used. Tests cover all essential parts of the code, focusing on boundary cases and possible errors. Deliverables: A link to a Git repository containing the source code. A README file describing the steps to run the application locally. Scripts to run unit tests. API Access Secret: The provided API access secret ensures secure access to the relevant APIs used in the project. Summary: This project showcases a robust implementation of an OpenID Connect service provider using NestJS. It includes authentication, logout, user data handling, and secure storage using cookies, with comprehensive unit testing to ensure functionality and reliability.

• AI agent on custom data using LLMs

  My role. Developer Project description. •It will read data from custom multiple pdf. •It will scrap data from custom multiple urls. •It will answer the questions related to pdf and urls •It will create conversational chain. Language : Python LLM : GOOGLE PALM UI : Streamlit , html template Framework : Langchain PyLib : PyPDF2 , Unstructured Vector Database : FAISS