bdeva1975
Currently working on GenerativeAI. Working as Senior Technical Analyst juggling in creating applications in Springboot as well as Python for GenerativeAI.
Pinned Repositories
cardatabase
covid19-book
GeoAsset-Tracker
GeoAsset Tracker is an interactive Streamlit application for visualizing and managing assets using geospatial data. With dynamic filtering, colorful markers, and detailed popups, effortlessly track asset locations and statuses on a beautiful map. Ideal for asset managers and data enthusiasts looking to leverage geospatial insights.
InstaPrompt
This repository demonstrates real-time text generation using OpenAI's GPT-3.5-turbo model with streaming. It provides immediate feedback as responses are generated in chunks, enhancing interactivity. Customize prompts and adjust parameters like temperature to control creativity. Experience the power of AI-driven storytelling with instant output
nlpapp
openai-gpt4-vision-example
This repository demonstrates how to interact with OpenAI's GPT-4 model (with vision capabilities) using Python. It includes examples of basic chat completions, sending image data, system prompts to modify response styles, and retrieving metadata. Ideal for those looking to integrate GPT-4's advanced features into their applications.
OpenAI-MathAPI
This repository showcases integration with OpenAI's API using a custom mathematical tool to calculate the square root of a number. It highlights modular design for easy extension and includes error handling for robust performance, demonstrating effective interaction through tool calls.
OpenAI-TextGen
This repository contains a Python script that interacts with the OpenAI API to generate text responses based on user input. Utilizing the openai and dotenv libraries, it loads the API key from a .env file and allows users to specify input text and response temperature. Ideal for exploring conversational AI and enhancing text generation tasks.
openaiapicall
How to call the OpenAI API from a Python program
PromptGenCLI
This repository provides a simple CLI tool to generate text responses using OpenAI's API. Users can input a model and a prompt, and the tool returns a detailed text response. It leverages customizable parameters like temperature and top-p to control response variability, with support for up to 2000 tokens per completion.
bdeva1975's Repositories
bdeva1975/cardatabase
bdeva1975/covid19-book
bdeva1975/GeoAsset-Tracker
GeoAsset Tracker is an interactive Streamlit application for visualizing and managing assets using geospatial data. With dynamic filtering, colorful markers, and detailed popups, effortlessly track asset locations and statuses on a beautiful map. Ideal for asset managers and data enthusiasts looking to leverage geospatial insights.
bdeva1975/InstaPrompt
This repository demonstrates real-time text generation using OpenAI's GPT-3.5-turbo model with streaming. It provides immediate feedback as responses are generated in chunks, enhancing interactivity. Customize prompts and adjust parameters like temperature to control creativity. Experience the power of AI-driven storytelling with instant output
bdeva1975/nlpapp
bdeva1975/openai-gpt4-vision-example
This repository demonstrates how to interact with OpenAI's GPT-4 model (with vision capabilities) using Python. It includes examples of basic chat completions, sending image data, system prompts to modify response styles, and retrieving metadata. Ideal for those looking to integrate GPT-4's advanced features into their applications.
bdeva1975/OpenAI-MathAPI
This repository showcases integration with OpenAI's API using a custom mathematical tool to calculate the square root of a number. It highlights modular design for easy extension and includes error handling for robust performance, demonstrating effective interaction through tool calls.
bdeva1975/OpenAI-TextGen
This repository contains a Python script that interacts with the OpenAI API to generate text responses based on user input. Utilizing the openai and dotenv libraries, it loads the API key from a .env file and allows users to specify input text and response temperature. Ideal for exploring conversational AI and enhancing text generation tasks.
bdeva1975/openaiapicall
How to call the OpenAI API from a Python program
bdeva1975/PromptGenCLI
This repository provides a simple CLI tool to generate text responses using OpenAI's API. Users can input a model and a prompt, and the tool returns a detailed text response. It leverages customizable parameters like temperature and top-p to control response variability, with support for up to 2000 tokens per completion.
bdeva1975/QuikMind
QuikMind is a sophisticated AI chatbot built with Streamlit, OpenAI's GPT-4, and advanced NLP tools. It offers engaging, natural conversations, integrating sentiment analysis and personality traits. Additional features include booking appointments and summarizing news articles from text, URLs, or uploaded files.
bdeva1975/TempGen
This repository demonstrates how to generate AI text responses using OpenAI's GPT-3.5-turbo model, with customizable temperature settings. The temperature parameter controls the randomness of the responses, allowing for a balance between creativity and predictability in AI-generated text outputs
bdeva1975/TextGen-CLI
TextGen-CLI is a Python-based command-line tool that interacts with OpenAI's API to generate text responses. Pass in a model and input text, and receive AI-generated outputs. Easily configurable via environment variables and supports customizable parameters like temperature and max tokens.
bdeva1975/TextScribe
TextScribe is a simple, powerful generative AI tool that leverages OpenAI's GPT-3.5-turbo model to generate human-like text responses. Built with Streamlit, it allows users to input text and receive AI-generated content, perfect for content creation, basic Q&A, and rapid prototyping with minimal code.
bdeva1975/TextSim-Embeddings
TextSim-Embeddings is a tool that leverages OpenAI's embeddings to calculate and compare the semantic similarity between different pieces of text using cosine similarity. Input your text, generate embeddings, and see how closely related each text is based on meaning. Ideal for clustering, semantic search, and more!