💻 ChatGPT Code Interpreter Unveiled
🤖🎩 Greetings, devotees of AI fueled by caffeine! We're presenting you with another fresh and heated issue of The AI Espresso! Today, we'll plunge into a diverse range of AI wonders that are sure to keep your excitement levels soaring:
🖼️ AI-Generated Media of the Week
📰 AI News
🚀 Engineering: Documentation and Knowledge Management
🎨 Art & Design: Design Research
💼 Business: Product Management
🛠️ AI Development - Technical: Function Calling
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🖼️ AI-Generated Media of the Week
📰 AI News
AI Coding Revolution: OpenAI's recent revelation is a game changer for coders working with AI, as they have announced a new plugin called ChatGPT Code Interpreter that promises to transform the way programmers work. Exclusive to ChatGPT Plus subscribers, the code interpreter, much like the Wolfram plugin, offers data visualization, generates neat Python code, and converts files between various formats. (🚀 Explore Now)
Co-piloting Development: At Toronto's Collision conference, GitHub CEO Thomas Dohmke emphasized the inseparable relationship between AI and software development. He insists that every developer should adopt AI tools like GitHub's Copilot due to the competitive advantage it provides. Dohmke foresees AI tools becoming a standard part of developers' toolkits. (🚀 Adopt AI)
🚀 Engineering: Documentation and Knowledge Management
AI Tools to Boost Your Game: Amp up your software development with Mutable AI, your AI-native developer platform. Fueled by features like AI autocomplete, it erases the need for boilerplate code and endless searches. Engineers can leverage its prompt-driven development to refactor swiftly, enhancing productivity. Compatible with popular languages and integrated with Jupyter and GitHub, it's a real game-changer. (🚀 Learn more)
Engineering Prompt of the Week: “Assume a Python package designed to interact with a specific humanoid robot software stack. It has multiple modules for controls, planning, and perception. Write an intuitive, public-facing API documentation including a guide on how to use each module with code examples.” (See Full Example)
🎨 Art & Design: Design Research
AI Tools to Boost Your Game: EyeQuant is an AI-driven platform that analyzes website design and provides insights on visual hierarchy, attention heatmaps, and user engagement, helping you optimize your designs for better user experiences.
Art & Design Prompt of the Week: “I'm working on a design project and need help with my research. I'm looking for information on the latest trends in website design to inform my design process. Could you please assist me by providing relevant insights and resources? To help you get started, here's some background information and specific questions I have…” (See Full Example)
💼 Business: Product Management
AI Tools to Boost Your Game: Swaying under the weight of countless product development tasks? Breathe easy, Fibery AI is here to lighten your load. This AI-driven work and knowledge hub streamlines product development and management like a dream. From editing texts and docs to creating spaces and automating repetitive tasks, Fibery does it all. And guess what? It even integrates with OpenAI GPT-3.5 API! 💡
Business Prompts of the Week: “ChatGPT, I am working on market research for my new product, a smart home security system. It's IoT-integrated, has advanced features like real-time monitoring, facial recognition, and can be remotely accessed through a mobile app. Could you guide me through an effective market research process for this product?” (See Full Example)
🛠️ AI Development - Technical: Function Calling
AI Projects of the Week:
jxnl’s openai_function_call: This open-source project introduces function calling alongside the pipeline structure of prompts, offering enhanced control over LLM outputs.
LlamaIndex’s function calling: LlamaIndex seamlessly integrates function calling into its ecosystem, providing clean and efficient support with Pydantic.
LangChain’s OpenAI function: LangChain offers an integration of function calling with LLMChain and Agent, incorporating Pydantic and JSON format support.
💡 Insights:
Function Calling, introduced by OpenAI in June, empowers users to control LLM output. However, the default function calling service proved challenging to extract and integrate with existing LLM ecosystems.
The most common approach to integrating function calling in Python involves using Pydantic classes as schemas, which are converted into functions compatible with OpenAI's function calling method. Pydantic's versatility enables structured output, detailed specifications for returned values, type definitions, and field descriptions. Additionally, Pydantic facilitates quick validation, serving as a safeguard against erroneous output. Employing a retry approach ensures the reception of correctly formatted responses.
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