EduBridge: Multi-Agent AI Tutor for Under-Resourced Education
# 🌉 EduBridge: Multi-Agent AI Tutor for Under-Resourced Education
## đź“– The Vision
Large Language Models (LLMs) are powerful, but they often fail students in rural or under-resourced areas. These students require strict alignment with local curriculums, culturally relatable examples, and step-by-step pedagogical patience.
**EduBridge** is not just a wrapper around an API. It is a sophisticated, localized, multi-agent reasoning system designed to bridge the educational gap. By simulating a team of specialized educators, EduBridge ensures that every answer is factually accurate, curriculum-aligned, and culturally nuanced.
*Current Status: We are currently in the deep architectural design and prompt-engineering phase, preparing for core implementation.*
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## 🏗️ System Architecture
To achieve high-fidelity teaching without human intervention, EduBridge employs a multi-agent debate and consensus workflow.
```mermaid
graph TD
User((Student)) -->|Raw Query| InputMod[Input Moderation/Safety]
InputMod -->|Clean Query| Orch[Orchestrator Agent]
subgraph Memory & Context Layer
Orch |Read/Update| SessionMem[(Short-term Session Memory)]
Orch |Fetch| ProfileMem[(Long-term Learner Profile)]
end
subgraph Multi-Agent Reasoning Core
Orch -->|Query Decomposition| TaskPlan[Task Planner]
TaskPlan -->|Sub-task 1: Fetch| RAG[Curriculum RAG Agent]
subgraph Dense Retrieval Pipeline
RAG -->|Semantic Search| VectorDB[(Pinecone: Textbook Embeddings)]
RAG -->|Graph Traversal| GraphDB[(Curriculum Knowledge Graph)]
VectorDB -->|Chunked Context| RAG
GraphDB -->|Entity Relations| RAG
end
TaskPlan -->|Sub-task 2: Analyze| Ped[Pedagogical Agent]
ProfileMem -->|Identify Weaknesses| Ped
RAG -->|Raw Academic Context| Synthesis[Reasoning & Synthesis]
Ped -->|Teaching Strategy| Synthesis
Synthesis -->|Academic Draft| Loc[Localization Agent]
Loc |Fetch Local Idioms| LocalDB[(Cultural Nuance DB)]
Loc -->|Relatable Draft| Ver[Verification Agent]
end
subgraph Alignment & Hallucination Def …