Learning Generative AI - Explained Intuitively

Part 2 - Book Recommendations, Interesting Advice, Key Lessons and Career Tips from Steven Bartlett’s Diary of a CEO Podcast using Anthropic’s Claude API

claude3
genai
Discover the most recommended books and intriguing ideas from guests on Steven Bartlett’s Diary of a CEO podcast. This project analyzes 140 podcast transcripts from 2021-2022 using Anthropic’s Claude API, extracts guest bios and key insights, visualizes metrics, and estimates the total cost based on token usage.
Apr 6, 2024
Arun Prakash

Part 1 - Book Recommendations, Interesting Advices, Key Lessons and Career Tips from Steven Bartlett’s Diary of a CEO Podcast using Anthropic’s Claude 3 API

claude3
genai
Discover the most recommended books and intriguing ideas from guests on Steven Bartlett’s Diary of a CEO podcast. This project analyzes 126 podcast transcripts from 2023-2024 using Anthropic’s Claude 3 API, extracts guest bios and key insights, visualizes metrics, and estimates the total cost based on token usage.
Apr 6, 2024
Arun Prakash

Book Recommendations, Interesting Advices, Career Tips from Dwarkesh Patel’s Podcasts using Anthropic’s Claude 3 API

ai
nlp
data-analysis
visualization
Discover the most recommended books and intriguing ideas from Dwarkesh Patel’s podcast guests. This project analyzes 63 podcast transcripts using Anthropic’s Claude 3 API, visualizes key metrics, and estimates the total cost based on token usage.
Apr 1, 2024
Arun Prakash

Claude3 + Python: Automate Real Industry Workflows Like a Pro

ai
real-estate
property-appraisal
newsletter-generation
streamlit
Explore how AI can revolutionize the real estate industry through automated property appraisals and personalized event newsletters. Learn to leverage Anthropic’s Claude model to generate comprehensive appraisals and engaging newsletters, and build an interactive Streamlit app to showcase these AI-powered functionalities.
Mar 28, 2024
Arun Prakash

Anthropic Claude3: Messages API with Images

llm
claude3
messages-api
image-analysis
Anthropic’s Claude 3 models can understand and analyze images, allowing for conversations that include both text and visuals. Supported image formats include JPEG, PNG, GIF, and WebP. Multiple images can be included in a single request for analysis. Image analysis counts towards token usage. Claude has some limitations in image understanding but provides valuable interpretations.
Mar 22, 2024
Arun Prakash

Anthropic Claude3: Function Calling Tools in Python

llm
claude3
function-calling
python
Function calling tools in Python allow extending Claude’s capabilities by integrating external functions or APIs. Define functions, create tool descriptions, construct system prompts, and process user messages to generate responses with function calls. This powerful technique enables Claude to perform tasks beyond its built-in knowledge.
Mar 22, 2024
Arun Prakash

Anthropic Claude3: Messages API with JSON Mode

llm
claude3
messages-api
Anthropic’s Claude AI model can generate structured JSON data by following specific techniques. By providing clear instructions and examples, developers can extract JSON from Claude’s responses using string parsing, partial responses, stop sequences, or XML-like tags. The JSON can then be easily parsed and integrated into applications or workflows.
Mar 22, 2024
Arun Prakash

Anthropic Claude3: Messages API with Streaming

llm
claude3
messages-api
Anthropic’s Messages API supports streaming mode for real-time conversational AI responses. Using server-sent events (SSE), the API incrementally streams message content, allowing for dynamic user experiences. SDKs simplify implementation, while raw HTTP streaming is available for custom integrations. Developers can handle various event types and gracefully process unknown events.
Mar 22, 2024
Arun Prakash

Anthropic Claude3: Messages API with Multimodal Input

llm
claude3
messages-api
Anthropic’s Messages API enables creating sophisticated conversational AI experiences with text and image inputs. Customize model behavior using system prompts, fine-tune randomness with temperature, and stream responses. The API supports single queries and multi-turn conversations, making it versatile for various applications.
Mar 22, 2024
Arun Prakash

crewAI: Simulating a Classroom with CrewAI Agents

llm
openai
agents
We use crewAI library to develop many agents and make them work together. We build a project where we simulate a classroom with students and teachers. Teacher agent teach a topic, student agents ask questions, then teacher agents incorporate the questions into the topic and teach again.
Feb 2, 2024
Arun Prakash

OpenAI ChatCompletions vs OpenAI Assistants API: A Hands-on Comparison

llm
openai
openai_assistants_api
chat_completions
handson
Assistants API offers advanced features like conversation threading, code execution, and data retrieval, ideal for complex AI applications. In contrast, Chat Completion Models are lightweight and efficient, ideal for simple AI applications.
Jan 20, 2024
Arun Prakash

Morning with Jarvis: Craft Your Own News Universe from Social Media and News Digests

llm
openai
function_calling
openai_assistants_api
handson
Revolutionize your morning routine with an AI-powered tool that delivers personalized audio news briefings on your topic of interest directly to your telegram. This project uses openai assistants API, Selenium, telegram API, openai text to speech models, DuckDuckGo for search, and many more.
Jan 14, 2024
Arun Prakash

Transform Your Travel: How to Build a Personalised Planner with OpenAI Assistants API

llm
openai
function_calling
openai_assistants_api
handson
In this article, we will build a personalised travel planner using OpenAI Assistants API. We will explore multiple parallel function calling, creating multiple assistants each focuses on a specific task, and we create a thread that interacts with multiple assistants. We create a fun project that does interactive maps, a personalised travel guide with real time weather updates, and a personalised travel planner.
Jan 10, 2024
Arun Prakash

Master the Art of Function Calling in OpenAI Assistants API: A Comprehensive Guide for Beginners

llm
openai
function_calling
openai_assistants_api
Discover how to leverage function calling in the OpenAI Assistant API with our comprehensive guide. This tutorial, suitable for both seasoned developers and beginners, covers the basics of function calling, creating an assistant, initiating a thread, and more. Learn how to identify when a message requires a function call, determine which function to call and what arguments to pass, and retrieve the response from a function call. We illustrate these concepts with a simple demo of reversing a string using a function integrated with the assistant. Enhance your AI applications with a clear, practical understanding of function calling in the OpenAI Assistant API
Jan 5, 2024
Arun Prakash

MoodCast: Leveraging OpenAI Parallel Function Calling for Real-Time Weather-Based Music Playlists

llm
openai
function_calling
The blog post introduces MoodCast, a project that uses OpenAI’s parallel function calling feature to create real-time, weather-based music playlists. It integrates OpenWeather and Spotify APIs, demonstrating the power and flexibility of OpenAI’s function calling. This feature allows developers to describe a function, and the model generates a JSON output containing arguments. It doesn’t call any function itself, but generates the JSON that can be used to call a function from your code. This is a significant advancement as it allows developers to interact with AI in a more structured and systematic way, overcoming the challenges of dealing with unstructured data outputs. The blog post provides a detailed guide on how to use function calling for OpenAI’s chat completion endpoints, with MoodCast serving as a real-world example. It aims to provide valuable insights into the potential of OpenAI’s function calling feature for both seasoned developers and beginners in the field of AI
Jan 3, 2024
Arun Prakash

Understanding OpenAI ChatCompletion Model Parameters

llm
openai
Details: Dive into the intricacies of LLM token generation with our insightful notebook. We cover key parameters like temperature, top_p, frequency_penalty, and presence_penalty, examining their value ranges and OpenAI’s defaults.We highlight the generation probability using log_probs. Our comprehensive guide includes real examples to demonstrate how these settings impact the token generation process, providing a valuable resource for developers and AI enthusiasts alike
Dec 17, 2023
Arun Prakash
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