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Emotionics New Feature: Overview of gyo_matrix (v0.6.0)

Emotionics New Feature: Overview of gyo_matrix (v0.6.0) https://pypi.org/project/emotionics/ 1. Overview gyo_matrix is a multi-dimensional observation sensor that concurrently runs simulations across three power gradients (Symmetrical, Upward, and Downward) for a given target text. It outputs the "surface emotion, deep emotion, and structural differences (Delta)" from each respective viewpoint. 2. Core Philosophy • Complete Elimination of Quantization (No Quantization) • It intentionally avoids calculating single scores or metrics like "Anger Level 80%" or "Threat Level 0.85." • This prevents the "number bias" where humans blindly trust system-generated figures, ensuring the tool does not devolve into a system that unilaterally labels, judges, or intervenes with the subject. • Role as a Pure Sensor • The system merely presents the "structural contradictions" within the three gravitational fields (power gradients). • Compari...

Pythonライブラリemotionicsの使い方

  Pythonライブラリemotionicsをfastapiなどと組み合わせて使うと、上記画像のような結果も出せますよ

Unveiling Hidden Intents: Using the Python Library "emotionics" as a Negotiation Radar

Unveiling Hidden Intents: Using the Python Library "emotionics" as a Negotiation Radar Introduction Negotiations are often clouded by bluffs, excuses, and hidden agendas. What if you could objectively peek behind the curtain? Today, I will introduce how to leverage the Python library "emotionics" not just as an analytical model, but as a powerful, objective radar for negotiations. By using the gyo (estimation) module, we can strip away superficial emotions and uncover the true physical state of the negotiation table. https://pypi.org/project/emotionics/ Code Here is a practical example. Imagine a scenario where a business partner uses a macro-environmental excuse to cut down your orders. ‘’’Python import os import json import emotionics from dotenv import load_dotenv # Load environment variables from .env file load_dotenv() # 1. Activation # * Example using Gemini emotionics.activate(     llm="gemini",     api_key=os.getenv("MY_API_KEY"),     mo...

[pip install emotionics] Python库 "emotionics" 发布

[pip install emotionics] Python库 "emotionics" 发布 Python库 "emotionics" 发布 前几天,我发布了Python库 "emotionics"。 本文是一篇针对该库的解说文章。 https://pypi.org/project/emotionics/ Emotionics是什么? Emotionics是一项将人类情感进行结构化,以便让AI更容易处理的技术。(顺便提一下,这是一个自创词。) 如下图所示,Emotionics的作用范围介于“意识与无意识”以及“逻辑与算法”之间,属于人类情感层的领域。 工作原理 Python库 "emotionics" 是将 LLM(大语言模型)与 Emotionics 结合使用的工具。 emotionics 并不是一个单纯将文本分类到特定情感标签的分类器。 它将LLM在上下文中理解的情感色彩(细微差别),结构化为预定义情感元素(如 Trust / Joy / Fear / Surprise 等)的“强度分布”并进行输出。 LLM本身负责文本的语义理解和上下文把握。 emotionics 并不直接返回LLM的结果,而是具有将情感反应重构为“方便人类后续处理的形式”的作用。 换句话说,两者的角色分工如下: • 语义理解:LLM • 情感结构化:emotionics pip install emotionics 使用方法 使用时需要OpenAI的API Key和OpenAI官方库。 Emotionics本身理论上并不依赖于特定的LLM,但目前 emotionics 库仅支持 OpenAI。 首先,通过以下命令进行安装: pip install emotionics 然后,可以按如下方式使用: import os import emotionics emotionics.activate(     llm="openai",     api_key=os.environ["OPENAI_API_KEY"],     model="gpt-5.2", ) result = emotionics.estimate(     text=...