{"id":28534094,"url":"https://github.com/devbauti/profeng","last_synced_at":"2026-02-28T11:07:31.581Z","repository":{"id":291873094,"uuid":"979048203","full_name":"DevBauti/ProfEng","owner":"DevBauti","description":"This is the first iteration of an AI agent that acts as an English teacher.","archived":false,"fork":false,"pushed_at":"2025-05-07T00:12:47.000Z","size":87,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-07-07T21:32:03.555Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":null,"has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/DevBauti.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null}},"created_at":"2025-05-06T23:18:05.000Z","updated_at":"2025-05-07T00:12:50.000Z","dependencies_parsed_at":"2025-05-07T01:25:33.957Z","dependency_job_id":"5aa3c3a3-b927-436e-a332-ba5b7278f5eb","html_url":"https://github.com/DevBauti/ProfEng","commit_stats":null,"previous_names":["devbauti/profeng"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/DevBauti/ProfEng","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/DevBauti%2FProfEng","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/DevBauti%2FProfEng/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/DevBauti%2FProfEng/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/DevBauti%2FProfEng/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/DevBauti","download_url":"https://codeload.github.com/DevBauti/ProfEng/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/DevBauti%2FProfEng/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":29931358,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-02-28T09:58:13.507Z","status":"ssl_error","status_checked_at":"2026-02-28T09:57:57.047Z","response_time":90,"last_error":"SSL_connect returned=1 errno=0 peeraddr=140.82.121.6:443 state=error: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2025-06-09T17:09:49.784Z","updated_at":"2026-02-28T11:07:31.570Z","avatar_url":"https://github.com/DevBauti.png","language":null,"funding_links":[],"categories":[],"sub_categories":[],"readme":"# TutorBot - English Learning Workflow\n\n## Overview\nTutorBot is an English Tutoring Agent built with **n8n**, designed to guide students from **A1** to **B2** levels of the CEFR. It offers structured lessons, quizzes, and level exams, tracks real-time progress, and communicates in Spanish through **Telegram**.\n\n![Flow](FlowMain.png)\n\n## Features\n\n- **Initial Assessment**: Assigns **A1** level to new users and generates diagnostic quizzes.\n- **Lesson Delivery**: Provides 3 to 4 weekly sessions (30–45 minutes each), including review, new topics, and micro-quizzes.\n- **Progress Tracking**: Updates user progress in **Supabase** after each lesson or quiz.\n- **Activity Scheduling**: Reserves sessions and sends reminders via the **MCP Calendar API**.\n- **Feedback and Motivation**: Offers positive reinforcement and additional exercises for scores below 80%.\n\n### Data Sources\n- **Supabase SQL**: Manages `cefr_levels`, `lessons`, and `user_progress` tables.\n- **Vector Database**: Retrieves content from textbooks.\n- **Calendar Service**: Schedules lessons and quizzes.\n\n## Workflow Structure\n\n### Main Nodes\n1. **Telegram Trigger**: Captures user messages.\n2. **Get Input**: Processes user text and data.\n3. **Get All**: Retrieves user progress from **Supabase**.\n4. **Lesson (Agent)**: Core logic for delivering lessons and tracking progress.\n5. **OpenAI Chat Model**: Generates lesson content using GPT models.\n6. **Supabase Vector Store**: Retrieves textbook content.\n7. **Embeddings OpenAI**: Generates embeddings for vector search.\n8. **MCP Client**: Handles calendar operations.\n9. **Simple Memory**: Maintains chat context.\n10. **Telegram**: Sends responses to users.\n\n### Connections\nLinks nodes for seamless data flow from **Telegram** input to the generated response.\n\n## Configuration\n\n### Credentials\n- **Telegram API**: Configure in `Telegram Trigger` and `Telegram` nodes.\n- **Supabase API**: Set up in `Supabase Vector Store` and `Get All` nodes.\n- **OpenAI API**: Add to `OpenAI Chat Model` and `Embeddings OpenAI` nodes.\n\n### Environment\n- Ensure **Supabase** tables (`cefr_levels`, `lessons`, `user_progress`) are set up.\n- Verify the **MCP Calendar API** endpoint.\n\n### Activation\n1. Enable the workflow in **n8n** (`active: true`).\n2. Test the **Telegram** webhook integration.\n\n## Policies\n\n- **Frequency**: 3–4 lessons per week, daily micro-quizzes, weekly quizzes, and level exams.\n- **Sequence**: Follows textbook order without skipping.\n- **Evaluation**: Requires ≥80% to pass quizzes; ≥70% for remediation.\n- **Responses**: Always in Spanish.\n\n## Usage\n\n1. Users interact via **Telegram**, sending messages to trigger lessons or quizzes.\n2. TutorBot responds with personalized content, schedules sessions, and tracks user progress.\n\n## Dependencies\n\n- **n8n**\n- **Telegram API**\n- **Supabase** (SQL + Vector Database)\n- **OpenAI API**\n- **MCP Calendar API**\n\n---\n\n# TutorBot - Flujo de Aprendizaje de Inglés\n\n## Resumen\nTutorBot es un Agente Tutor de Inglés construido con **n8n**, diseñado para guiar a los estudiantes desde el nivel **A1** hasta **B2** del MCER. Ofrece lecciones estructuradas, cuestionarios y exámenes de nivel, rastrea el progreso en tiempo real y se comunica en español a través de **Telegram**.\n\n![Flow](FlowMain.png)\n\n## Características\n\n- **Evaluación Inicial**: Asigna el nivel **A1** a nuevos usuarios y genera cuestionarios diagnósticos.\n- **Entrega de Lecciones**: Proporciona de 3 a 4 sesiones semanales (30–45 minutos), incluyendo repaso, nuevos temas y micro-cuestionarios.\n- **Seguimiento de Progreso**: Actualiza el progreso del usuario en **Supabase** tras cada lección o cuestionario.\n- **Programación de Actividades**: Reserva sesiones y envía recordatorios mediante la **API de calendario MCP**.\n- **Retroalimentación y Motivación**: Ofrece refuerzo positivo y ejercicios adicionales para puntajes menores al 80%.\n\n### Fuentes de Datos\n- **Supabase SQL**: Gestiona tablas de `cefr_levels`, `lessons` y `user_progress`.\n- **Base de Datos Vectorial**: Recupera contenido de libros de texto.\n- **Servicio de Calendario**: Programa lecciones y cuestionarios.\n\n## Estructura del Flujo\n\n### Nodos Principales\n1. **Telegram Trigger**: Captura mensajes de los usuarios.\n2. **Get Input**: Procesa texto y datos del usuario.\n3. **Get All**: Obtiene el progreso del usuario desde **Supabase**.\n4. **Lección (Agent)**: Lógica principal para entrega de lecciones y seguimiento de progreso.\n5. **OpenAI Chat Model**: Genera contenido de lecciones utilizando modelos GPT.\n6. **Supabase Vector Store**: Recupera contenido de libros de texto.\n7. **Embeddings OpenAI**: Genera incrustaciones para búsqueda vectorial.\n8. **MCP Client**: Maneja operaciones de calendario.\n9. **Simple Memory**: Mantiene el contexto del chat.\n10. **Telegram**: Envía respuestas a los usuarios.\n\n### Conexiones\nVincula los nodos para un flujo de datos continuo desde la entrada de **Telegram** hasta la respuesta generada.\n\n## Configuración\n\n### Credenciales\n- **API de Telegram**: Configurar en los nodos `Telegram Trigger` y `Telegram`.\n- **API de Supabase**: Establecer en `Supabase Vector Store` y `Get All`.\n- **API de OpenAI**: Agregar en los nodos `OpenAI Chat Model` y `Embeddings OpenAI`.\n\n### Entorno\n- Asegurar que las tablas de **Supabase** (`cefr_levels`, `lessons`, `user_progress`) estén configuradas.\n- Verificar el endpoint de la **API de calendario MCP**.\n\n### Activación\n1. Habilitar el flujo en **n8n** (`active: true`).\n2. Probar la integración del webhook de **Telegram**.\n\n## Políticas\n\n- **Frecuencia**: 3–4 lecciones por semana, micro-cuestionarios diarios, cuestionarios semanales y exámenes de nivel.\n- **Secuencia**: Sigue el orden del libro de texto sin saltos.\n- **Evaluación**: Se requiere un puntaje ≥80% para aprobar cuestionarios; ≥70% para remediación.\n- **Respuestas**: Siempre en español.\n\n## Uso\n\n1. Los usuarios interactúan vía **Telegram**, enviando mensajes para activar lecciones o cuestionarios.\n2. TutorBot responde con contenido personalizado, programa sesiones y rastrea el progreso del usuario.\n\n## Dependencias\n\n- **n8n**\n- **API de Telegram**\n- **Supabase** (SQL + Base de Datos Vectorial)\n- **API de OpenAI**\n- **API de Calendario MCP**\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdevbauti%2Fprofeng","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fdevbauti%2Fprofeng","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdevbauti%2Fprofeng/lists"}