Create a folder with name "pdf" and also create a file ".env" for api key and then install the requirements file and you can run the code in Postman
I will be focusing on expanding my capabilities in reading various file formats such as docx, among others, and refining the chunking process to incorporate semantic understanding on a sentence-by-sentence basis. This entails creating chunks that encapsulate the meaning of each sentence effectively. By doing so, I aim to develop a comprehensive understanding of different chunking methodologies, allowing for an assessment of their suitability for our documents.
About my current application:-
RAG Framework: Offers real-time Anomaly Detection and Prevention capabilities.
Flask Implementation: Utilizes Flask for web server functionality, facilitating easy deployment and integration into frontend applications.
Conversational AI: Maintains a conversation chain, enabling seamless interaction with the chatbot for users.
Modular Structure: Organized into modular functions, enhancing code readability and facilitating maintenance.
Error Handling: Includes robust error handling at each step, ensuring smooth operation and reliability.
External Libraries Integration: Integrates with external libraries like PyPDF2 and OpenAI's GPT-3.5 model for enhanced functionality.
Global State Management: Manages conversation history globally, allowing for efficient tracking of user interactions and responses.
Security and Scalability: Implements secure practices like environment variable configuration and is scalable to handle increasing user traffic.
Create a folder with name "pdf" and also create a file ".env" for api key and then install the requirements file and you can run the code in Postman
I will be focusing on expanding my capabilities in reading various file formats such as docx, among others, and refining the chunking process to incorporate semantic understanding on a sentence-by-sentence basis. This entails creating chunks that encapsulate the meaning of each sentence effectively. By doing so, I aim to develop a comprehensive understanding of different chunking methodologies, allowing for an assessment of their suitability for our documents.
About my current application:-
RAG Framework: Offers real-time Anomaly Detection and Prevention capabilities.
Flask Implementation: Utilizes Flask for web server functionality, facilitating easy deployment and integration into frontend applications.
Conversational AI: Maintains a conversation chain, enabling seamless interaction with the chatbot for users.
Modular Structure: Organized into modular functions, enhancing code readability and facilitating maintenance.
Error Handling: Includes robust error handling at each step, ensuring smooth operation and reliability.
External Libraries Integration: Integrates with external libraries like PyPDF2 and OpenAI's GPT-3.5 model for enhanced functionality.
Global State Management: Manages conversation history globally, allowing for efficient tracking of user interactions and responses.
Security and Scalability: Implements secure practices like environment variable configuration and is scalable to handle increasing user traffic.