開発スタッフがアプリ関連の最新技術やニュースをご紹介します。

今回はOpenAI APIをWebアプリケーションに組み込んで活用する方法を説明します。
PythonのWebアプリケーションフレームワークといえばDjangoが有名ですが、
今回はテスト用途なので、軽量でシンプルなフレームワークである
Flaskを試してみたいと思います。

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Unitreeという中国のロボットメーカーがGPTを搭載した
犬型ロボットUnitree Go2の販売を開始しているようです。

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Today, I would like to share about top LLM Python libraries. Let’s take a look.

OpenAI

OpenAI is at the forefront of AI and LLMs globally. Their GPT-3 and GPT-4 models have brought about a revolutionary change with their remarkable language understanding capabilities.

OpenAI provides the OpenAI API, a Python library that facilitates seamless integration of models into applications. Through this API, developers can effortlessly generate text, respond to queries, extract structured data, and undertake a variety of other NLP tasks.

LangChain

LangChain is a framework for developing LLM-powered applications with a focus on composability. It aims to simplify the creation, management, and scaling of LLM-powered applications in Python, emphasizing a simple and modular design. With various tools and utilities, LangChain assists developers in streamlining their workflow and efficiently deploying LLM-based solutions.

Hugging Face

Hugging Face is renowned in the NLP community for its extensive collection of pretrained language models and user-friendly transformers library. Their transformers library provides a plethora of Python tools for effectively working with LLMs, encompassing pre-processing, training, fine-tuning, and deployment. With support for multiple model architectures, it stands as a flexible option for developers.

LlamaIndex

LlamaIndex, previously known as GPT Index, stands as a comprehensive and cutting-edge framework specially designed to empower LLMs with the capabilities of handling private and custom data augmentation. This innovative framework encompasses a wide range of essential components, including data connectors, LLM-compatible indices, and graphs, along with a sophisticated query interface meticulously crafted to interact seamlessly with the underlying data. By integrating LlamaIndex into their applications, developers gain unparalleled flexibility and enhanced capabilities for augmenting LLMs with private and custom datasets, facilitating more dynamic and sophisticated natural language processing tasks.

Cohere

Cohere stands as a prominent LLM provider, offering an array of pre-trained models and a Python SDK, allowing effortless integration into applications. Their platform is dedicated to generating natural, context-aware text, encompassing various domains, while placing a strong emphasis on ethical AI practices. With a focus on mitigating potential biases and guaranteeing human-like text outputs, Cohere equips developers with essential tools to maintain fairness and inclusivity. Designed with utmost user-friendliness in mind, their platform streamlines the process of creating, testing, and deploying AI-powered applications, ensuring minimal effort for developers.

This is all for now. Hope you enjoy that.

By Asahi

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Google makes ChatGPT rival Bard available to a wider audience today, releases generative AI chatbots in over 40 languages, and finally hits the European Union (EU) after initial delays due to privacy concerns introduced. .

Google first mocked Bard in February, apparently in a hasty response to ChatGPT’s success. Bard originally entered early access in English in the US and UK in March, but with a global release across nearly 180 countries and additional support for Japanese and Korean, the initial waiting list is his. Finished in May. But one notable omission so far has been in the EU, where privacy regulators voiced their concerns, prompting Google to postpone its EU launch.

“We have been actively working with privacy experts, policy makers and regulators on this expansion,” “We’ve proactively engaged with experts, policymakers and privacy regulators on this expansion,” Bard product lead Jack Krawczyk, and VP of engineering Amarnag Subramanya, wrote in a blog post.

Now users can change the tone and style of Bard’s responses with five different options: “simple,” “long,” “short,” “professional” or “casual.”

Bard can now vocalize its responses thanks to a new text-to-speech AI feature. Supporting over 40 languages, the chatbot’s audible responses can be accessed by clicking the new sound icon next to a prompt.

On the productivity side, Bard can now export code to more places — specifically Python code to Replit, the browser-based integrated development environment. Images can be used in prompts — users can upload images with prompts (only in English for now) and Bard will analyze the photo. New options allow users to pin, rename and pick up recent conversations with Bard. And Bard’s responses can now more easily be shared with the outside world through links.

Google struggled mightily with Bard early in the chatbot’s life cycle, failing to match the quality of responses from rival bots such as ChatGPT. But Google claims that Bard is improving in measurable ways, particularly in areas like math and programming. It’s also gained extensions, including from Google’s own apps and services as well as third-party partners like Adobe, and the ability to explain code, structure data in a table, and surface images in its responses.

Yuuma

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今回も引き続きOpenAI APIのプロンプトデザインについて紹介します。
OpenAI APIのレスポンスは必ずしも正確な情報ではなく、
誤った情報をあたかも正確であるかのようにレスポンスされる場合もあります。
今回はそのような場合のプロンプトデザインの例を紹介します。

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