Overview
Semantica is an open-source Python AI context-graph and decision-intelligence framework for AI Agents, GraphRAG, and enterprise LLM app developers. It addresses how ordinary vector search or chat memory struggle to express entity relations, temporal change, causal chains, and decision rationale—adding structured context, explainable reasoning, and full audit trails to AI apps. It supports Python 3.8+, is MIT-licensed, and free to use. Install via pip, build a context graph with entities, relations, sources, and decision records, then connect LangGraph, CrewAI, LlamaIndex, Claude Code, and similar tools. Versus frameworks that only orchestrate flows or retrieve docs, Semantica emphasizes that AI memory, reasoning, and final decisions can be tracked, queried, and reviewed. Capabilities — Context graph and structured memory: store entities, relations, attributes, and time validity as a queryable graph so Agents understand links between knowledge, not only similar text. Decision tracking and causal reasoning: record inputs, rationale, outcomes, and confidence, and trace causal chains, precedents, and downstream effects to explain “why this decision.”
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Semantica 是一个开源的 Python AI 上下文图与决策智能框架，主要面向 AI Agent、GraphRAG 和企业级 LLM 应用开发者。它解决普通向量检索或对话记忆难以表达实体关系、时间变化、因果链和决策依据的问题，为 AI 应用增加结构化上下文、可解释推理和完整审计记录。项目支持 Python 3.8+，采用 MIT 许可证，可免费使用。开发者可以通过 pip 安装 Semantica，创建上下文图并加入实体、关系、来源和决策记录，再将其接入 LangGraph、CrewAI、LlamaIndex、Claude Code 等 AI 工具。相比只负责流程编排或文档检索的框架，Semantica 更强调让 AI 的记忆、推理过程和最终决策能够被追踪、查询与复核。能力说明核心功能上下文图与结构化记忆：将实体、关系、属性和时间有效期保存为可查询的图结构，帮助 Agent 理解知识之间的关联，而不只是匹配相似文本。决策追踪与因果推理：记录 AI 决策的输入、理由、结果和置信度，并追踪因果链、历史先例及后续影响，方便解释“为什么这样决定”。