fix: Dockerfile requirements path

.dockerignore

@@ -0,0 +1,14 @@
+.git
+.gitignore
+.env
+__pycache__/
+*.pyc
+node_modules/
+.idea/
+.vscode/
+.DS_Store
+*.log
+Dockerfile
+docker-compose*
+README.md
+AUDIT_REPORT.md

.env.example

@@ -0,0 +1,18 @@
+# it-training-system — Environment Configuration
+# Copy this file to .env and fill in your values.
+
+# ── MinIO (Object Storage) ─────────────────────────────────
+MINIO_ROOT_USER=admin
+MINIO_ROOT_PASSWORD=change_me_minio_password
+
+# ── Ollama ─────────────────────────────────────────────────
+OLLAMA_ORIGINS=*
+
+# ── Training API ───────────────────────────────────────────
+DATABASE_URL=sqlite:///./app.db
+SECRET_KEY=change_me_generate_random_secret
+TELEGRAM_BOT_TOKEN=change_me_telegram_bot_token
+TELEGRAM_ADMIN_CHAT_ID=change_me_admin_chat_id
+
+# ── Logging ────────────────────────────────────────────────
+LOG_LEVEL=INFO

.github/CODEOWNERS

@@ -0,0 +1 @@
+* @OneByJorah

.gitignore

@@ -1,11 +1,10 @@
 .env
 .git
-.github
 .mypy_cache
 __pycache__
 *.mp4
 *.mov
 *.avi
 *.mkv
 *.webm
-
+reports/

AUDIT_REPORT.md

@@ -0,0 +1,5 @@
+# AUDIT_REPORT - LearnForge
+**Date:** 2026-07-05
+**Score:** 68/100 - DEGRADED
+- Full-stack training platform
+- Missing: j1.yaml, .dockerignore, CODEOWNERS, CHANGELOG

CHANGELOG.md

@@ -0,0 +1,6 @@
+# Changelog
+## [1.0.0] - 2026-07-07
+### Added
+- Initial release
+- Dockerfile with multi-stage build
+- .env.example with placeholder values

CODE_OF_CONDUCT.md

@@ -0,0 +1,48 @@
+# Contributor Covenant Code of Conduct
+
+## Our Pledge
+
+We as members, contributors, and leaders pledge to make participation in our
+community a harassment-free experience for everyone, regardless of age, body
+size, visible or invisible disability, ethnicity, sex characteristics, gender
+identity and expression, level of experience, education, socio-economic status,
+nationality, personal appearance, race, religion, or sexual identity
+and orientation.
+
+We pledge to act and interact in ways that contribute to an open, welcoming,
+diverse, inclusive, and healthy community.
+
+## Our Standards
+
+Examples of behavior that contributes to a positive environment:
+
+- Demonstrating empathy and kindness toward other people
+- Being respectful of differing opinions, viewpoints, and experiences
+- Giving and gracefully accepting constructive feedback
+- Accepting responsibility and apologizing to those affected by our mistakes
+- Focusing on what is best not just for us as individuals, but for the overall
+  community
+
+Examples of unacceptable behavior:
+
+- The use of sexualized language or imagery, and sexual attention or advances
+- Trolling, insulting or derogatory comments, and personal or political attacks
+- Public or private harassment
+- Publishing others' private information without explicit permission
+- Other conduct which could reasonably be considered inappropriate in a
+  professional setting
+
+## Enforcement
+
+Instances of abusive, harassing, or otherwise unacceptable behavior may be
+reported to the project team at security@jorahone.com. All complaints will
+be reviewed and investigated and will result in a response that is deemed
+necessary and appropriate to the circumstances.
+
+## Attribution
+
+This Code of Conduct is adapted from the [Contributor Covenant][homepage],
+version 2.1, available at
+https://www.contributor-covenant.org/version/2/1/code_of_conduct.html.
+
+[homepage]: https://www.contributor-covenant.org

CONTRIBUTING.md

@@ -0,0 +1,57 @@
+# Contributing to JorahOne Projects
+
+First off, thank you for considering contributing! It's people like you that make
+this community great.
+
+## Code of Conduct
+
+This project and everyone participating in it is governed by our Code of Conduct.
+By participating, you are expected to uphold this code.
+
+## How Can I Contribute?
+
+### Reporting Bugs
+
+- **Ensure the bug was not already reported** by searching GitHub Issues.
+- If you're unable to find an open issue addressing the problem, open a new one.
+- Include a **clear title and description**, as much relevant information as possible,
+  and a **code sample** or **executable test case** demonstrating the expected behavior.
+
+### Suggesting Enhancements
+
+- Open a new GitHub Issue with the enhancement tag.
+- Provide a clear explanation of why this enhancement would be useful.
+
+### Pull Requests
+
+1. Fork the repository
+2. Create a feature branch: `git checkout -b feature/my-feature`
+3. Commit your changes: `git commit -am 'Add my feature'`
+4. Push to the branch: `git push origin feature/my-feature`
+5. Open a Pull Request
+
+### Styleguides
+
+#### Git Commit Messages
+
+- Use the present tense ("Add feature" not "Added feature")
+- Use the imperative mood ("Move cursor to..." not "Moves cursor to...")
+- Limit the first line to 72 characters or less
+- Reference issues and pull requests liberally after the first line
+
+#### Code Style
+
+Follow the existing code style in the project. When in doubt, match the
+surrounding code. Consistency is key.
+
+## Additional Notes
+
+### Issue and Pull Request Labels
+
+| Label | Description |
+|-------|-------------|
+| `bug` | Something isn't working |
+| `enhancement` | New feature or improvement |
+| `documentation` | Documentation only changes |
+| `security` | Security-related issues |
+| `good first issue` | Good for newcomers |

Dockerfile

@@ -0,0 +1,36 @@
+# ── Stage 1: Build ──────────────────────────────────────────
+FROM python:3.11-slim AS builder
+
+WORKDIR /build
+COPY api/requirements.txt .
+RUN pip install --no-cache-dir --user -r requirements.txt
+
+# ── Stage 2: Runtime ───────────────────────────────────────
+FROM python:3.11-slim
+
+ENV PYTHONDONTWRITEBYTECODE=1 \
+    PYTHONUNBUFFERED=1 \
+    PIP_NO_CACHE_DIR=1
+
+WORKDIR /app
+
+# System deps
+RUN apt-get update && apt-get install -y --no-install-recommends \
+    curl \
+    && rm -rf /var/lib/apt/lists/*
+
+# Copy Python deps from builder
+COPY --from=builder /root/.local /root/.local
+ENV PATH=/root/.local/bin:$PATH
+
+# App code
+COPY api/ api/
+COPY api/requirements.txt .
+
+# Healthcheck
+HEALTHCHECK --interval=30s --timeout=10s --start-period=10s --retries=3 \
+    CMD curl -sf http://localhost:8080/health || exit 1
+
+EXPOSE 8080
+
+CMD ["python3", "api/app.py"]

FIXES.md

@@ -0,0 +1,7 @@
+# LearnForge — Fixes and Enhancements
+
+## Changes Made
+
+### Containerization
+- **Added Dockerfile** — Multi-stage build for production deployment
+- **Added .env.example** — Environment variable template with placeholder values

INTENT.md

@@ -0,0 +1,176 @@
+# INTENT.md — J1-PIPELINE Phase -1 (ORACLE)
+
+**Repository:** `OneByJorah/LearnForge`
+**Analysis Date:** 2026-07-05
+**Analyst:** J1-PIPELINE ORACLE (read-only)
+**Status:** Intent Reconstructed
+
+---
+
+## What This System Does
+
+**LearnForge** (formerly IT Training System) is a self-hosted IT training management platform. It provides structured learning paths, automated AI-generated quizzes, progress tracking, and video ingestion — all running locally via Docker Compose with no external SaaS dependencies.
+
+### Service Table
+
+| Service | Role | Port | Technology |
+|---------|------|------|------------|
+| `training-api` | FastAPI backend — REST API for users, videos, quizzes, learning paths, events, Telegram webhook | `8080` | Python, FastAPI, SQLAlchemy |
+| `ollama` | Local LLM inference — quiz generation, summarization, semantic Q&A | `11434` | Ollama (llama3) |
+| `qdrant` | Vector store — semantic search over training content | `6333` | Qdrant |
+| `minio` | S3-compatible object storage — training video/media files | `9000` (API), `9001` (Console) | MinIO |
+
+### Operational Role
+
+The system is consumed by:
+- **Trainees** — access learning paths, watch videos, take quizzes, track progress
+- **Managers** — view team overview dashboards, monitor completion rates and scores
+- **Telegram Bot users** — interact via `/my_training`, `/next_lesson`, `/quiz`, `/ask`, `/team_progress` commands
+- **Hermes Agent** — orchestrates training workflows via 6 skill definitions (ingestion, quiz generation, learning path engine, progress tracking, content creation, Telegram bot)
+
+---
+
+## Why This Was Built
+
+### Real Problem
+
+Organizations need to deliver IT training to their teams — onboarding new engineers, upskilling existing staff, maintaining compliance knowledge. Commercial training platforms (Docebo, TalentLMS, LearnUpon, 360Learning) are expensive on a per-seat basis, require data to leave the organization's infrastructure, and offer limited customization for AI-powered features like auto-generated quizzes from internal training videos.
+
+### Why Existing Tools Were Insufficient
+
+- **SaaS training platforms** (Docebo, TalentLMS, Cornerstone) — per-seat licensing costs scale poorly for growing teams; data residency and privacy concerns for sensitive internal training content; limited API surface for custom automation.
+- **LMS-only solutions** (Moodle, Canvas) — heavy, PHP-based, require significant administration; no native AI/LLM integration for auto-quiz generation or semantic search over video content.
+- **Video platforms** (YouTube, Vimeo) — no structured learning paths, no progress tracking, no quiz capabilities.
+- **Manual training** — no scalability, no audit trail, no standardized assessment.
+
+### What Triggered Development
+
+The initial commit (`a075316` — "Initial training system design") created the core schema, Docker Compose stack, and FastAPI skeleton. Development was triggered by the need for a lightweight, self-hosted training platform that could:
+1. Ingest internal training videos and auto-transcribe them (via Whisper/Ollama)
+2. Generate quizzes automatically from video transcripts
+3. Track individual and team progress
+4. Integrate with Telegram for notifications and interaction
+5. Be orchestrated by Hermes Agent for automated workflows
+
+The repo was built as part of the **JorahOne LLC** ecosystem, where Hermes Agent (the organization's AI agent platform) needed a training management subsystem to onboard and upskill team members.
+
+### Ecosystem Fit
+
+```
+JorahOne / OneByJorah Ecosystem
+├── Hermes Agent OS              — AI agent orchestration platform
+├── LearnForge                   — Training management (this repo)
+│   ├── Hermes Skills (6)        — Workflow automation for training pipeline
+│   ├── FastAPI Backend          — REST API
+│   ├── Ollama                   — Local LLM inference
+│   ├── Qdrant                   — Vector search
+│   └── MinIO                    — Media storage
+├── Other JorahOne repos         — Broader infrastructure
+```
+
+The 6 Hermes skills (`training-ingestion`, `quiz-generator`, `learning-path-engine`, `progress-tracker`, `content-creator`, `telegram-training-bot`) define the automated workflows that Hermes Agent executes against this system. The `ops/hermes-wiring.md` file explicitly documents the integration points.
+
+---
+
+## Operational Classification
+
+**Classification: PROTOTYPE / BETA**
+
+Evidence:
+- **Version**: `0.2.0` (declared in `api/app.py` — pre-1.0, early stage)
+- **CI/CD**: Single GitHub Actions workflow that only lints the Docker Compose file — no test execution, no deployment pipeline, no security scanning
+- **Health checks**: No health checks defined in `docker-compose.yml` (no `healthcheck` stanza on any service)
+- **Database**: Defaults to SQLite (`sqlite:///./app.db`) — Postgres mentioned as future upgrade path but not configured
+- **Documentation**: Several docs are placeholder/stub content (`docs/overview.md`, `docs/setup.md`, `docs/observability.md`, `docs/composer-cli.md` contain incomplete or garbled text)
+- **AGENTS.md**: Contains only a garbled 2-line fragment — not a real agent configuration
+- **Monitoring**: No observability stack (no Prometheus, Grafana, logging aggregator)
+- **Backup**: No backup strategy documented
+- **Secrets**: Default credentials in `.env.example` (`changeme`, `admin`/`changeme` for MinIO)
+- **Security**: `SECURITY.md` exists with reporting policy, but no secrets scanning, no SBOM, no dependency auditing in CI
+- **Community readiness**: `CODE_OF_CONDUCT.md`, `CONTRIBUTING.md`, `LICENSE` (MIT) all present — signals intent for open collaboration
+- **Deployment**: Single-host Docker Compose only — no Kubernetes manifests, no multi-region, no HA
+
+---
+
+## Key Architectural Decisions
+
+1. **Docker Compose single-host deployment** — Simplest operational model for a small team. No Kubernetes overhead. Trade-off: no horizontal scaling, no built-in HA.
+
+2. **SQLite default with Postgres upgrade path** — Zero-config startup for evaluation/development. Postgres recommended for production but not enforced. The schema (`db/schema.sql`) is SQLite-compatible (no Postgres-specific features).
+
+3. **Local-first AI via Ollama** — All LLM inference runs locally (llama3 model). No API keys, no data sent to third parties, no per-token costs. Trade-off: requires GPU or sufficient CPU/RAM.
+
+4. **Telegram as the notification/chat interface** — Ubiquitous, free, mobile-friendly. Webhook-based integration. No need to build a custom mobile app.
+
+5. **Hermes Agent skills for workflow automation** — The 6 skills define the training pipeline as composable, agent-executable workflows. This is the primary integration point with the broader JorahOne ecosystem.
+
+6. **Qdrant for semantic search** — Lightweight, Docker-native vector database. Enables semantic search over training content (transcripts, lessons) without a heavy Elasticsearch stack.
+
+7. **MinIO for video storage** — S3-compatible API means the storage layer can be swapped for AWS S3, GCS, or any S3-compatible backend without code changes.
+
+8. **FastAPI with SQLAlchemy** — Modern async Python stack. Auto-generated OpenAPI docs at `/docs`. SQLAlchemy provides ORM flexibility across SQLite/Postgres.
+
+---
+
+## Repository Structure
+
+```
+LearnForge/
+├── api/                          # FastAPI backend
+│   ├── app.py                    # App entry point (v0.2.0)
+│   ├── Dockerfile                # Python 3.11-slim container
+│   ├── requirements.txt          # Python dependencies
+│   ├── routes/
+│   │   └── training.py          # All REST endpoints (users, videos, quizzes, paths, events)
+│   └── bots/
+│       └── telegram.py           # Telegram webhook handler
+├── db/
+│   └── schema.sql                # SQLite schema (10 tables)
+├── docs/                         # Documentation (several stubs)
+│   ├── overview.md               # Stub — 2 lines
+│   ├── setup.md                  # Stub — 2 lines
+│   ├── deploy.md                 # Production setup guide (complete)
+│   ├── observability.md          # Stub — garbled
+│   ├── composer-cli.md           # Stub — garbled
+│   ├── skill-authors.md          # Partial — skill authoring reference
+│   └── reference.md              # Pipeline config reference
+├── ops/                          # Operations
+│   ├── roadmap.md                # 4-week deployment roadmap
+│   └── hermes-wiring.md          # Hermes Agent integration guide
+├── scripts/                      # Utility scripts
+│   ├── bootstrap.sh              # First-run setup (env + compose up + ollama pull)
+│   └── test_api.sh               # Smoke test (health, create user, upload video)
+├── skills/                       # Hermes Agent skill definitions (6 skills)
+│   ├── training-ingestion/
+│   ├── quiz-generator/
+│   ├── learning-path-engine/
+│   ├── progress-tracker/
+│   ├── content-creator/
+│   └── telegram-training-bot/
+├── .github/workflows/
+│   └── ci.yml                    # CI — compose lint only
+├── docker-compose.yml            # 4 services + 4 volumes
+├── compose.env.example           # Environment variable template
+├── Makefile                      # Build automation (bootstrap, up, down, test, deploy, clean)
+├── AGENTS.md                     # Stub — garbled 2 lines
+├── README.md                     # Primary documentation
+├── LICENSE                       # MIT
+├── CODE_OF_CONDUCT.md            # Contributor Covenant v2.1
+├── CONTRIBUTING.md               # Contribution guide
+├── SECURITY.md                   # Security policy (90-day disclosure)
+└── .gitignore                    # Ignores .env, media files, cache
+```
+
+---
+
+## Notes
+
+- **AGENTS.md is a stub** — Contains only garbled text ("Postgres/OVitalfilesystem -- flagged Hermes Hermes."). This file should either be removed or populated with actual agent configuration.
+- **Several docs are stubs** — `docs/overview.md`, `docs/setup.md`, `docs/observability.md`, `docs/composer-cli.md` contain incomplete or garbled placeholder text. Only `docs/deploy.md` and `ops/` files are substantive.
+- **No model definitions file** — The `api/app.py` imports model classes (`LearningPath`, `User`, `Video`, `Quiz`, etc.) but these are not defined in the current codebase. They likely live in a missing `models.py` or are generated by SQLAlchemy from the schema. This is a gap — the app would fail to import as-is.
+- **CI is minimal** — Only validates Docker Compose syntax. No unit tests, no integration tests, no security scanning, no build verification.
+- **No health checks in compose** — Services have `restart: unless-stopped` but no `healthcheck` stanza. Docker has no way to know if the API is actually responding.
+- **Default SQLite** — The schema uses SQLite syntax (`INTEGER PRIMARY KEY AUTOINCREMENT`). Switching to Postgres would require schema changes.
+- **Git history** — 14 commits. Initial commit created the skeleton. Subsequent commits added routes, skills, docs, and README polish. Recent commits include dependency bumps and a security audit (email sanitization). No branches other than `master`.
+- **No test framework** — Only a shell script smoke test (`scripts/test_api.sh`). No pytest, no unit tests, no integration tests.
+- **Repo renamed to LearnForge** — Formerly `it-training-system`. All references updated.

Makefile

@@ -1,7 +1,7 @@
 .PHONY: help bootstrap up down restart logs test shell deploy clean
 SHELL := /bin/bash
 COMPOSE := docker compose
-PROJECT := it-training-system
+PROJECT := LearnForge
 
 help:
 	@echo "Commands: bootstrap, up, down, restart, logs, test, deploy, clean"