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AI Skill
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Product Showcase
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ITI Knowledge System
- Chapter 1: Introduction
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- Chapter 11: Dify — Knowledge Bases & RAG
- Chapter 12: The ITI Workflow Adapter
- Chapter 13: The ITI Shared Library
- Chapter 14: WordPress Plugin Development
- Chapter 15: Desktop Apps with Tauri 2
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- Chapter 2: Workspace Overview
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- Chapter 21: Knowledge Bases
- Chapter 22: Safety & Guardrails
- Chapter 23: Build Session Protocol
- Chapter 24: Required Product Artifacts
- Chapter 25: Testing
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- Chapter 28: Cursor Skills
- Chapter 29: Cursor Rules
- Chapter 3: The Docker Stack
- Chapter 30: MCP Integrations
- Chapter 31: Builder and Agent Roles
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- Chapter 33: Claims Integrity & Content Governance
- Chapter 4: Daily Operations
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AI Agent
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User Guide
- ADMIN-SHORTCODES.html Update Summary
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- Farmers Bounty Plugin v6.6.0 - Release Notes
- Farmers Bounty v2.0 - Complete User Guide
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- SEO Assistant with LLM
- 🌱 Farmers Bounty Homepage Shortcode - Quick Start
- 🌱 Farmers Bounty Shortcodes
- 🌹 Grateful Dead Chatbot - Quickstart Guide ⚡
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Requirements
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ScubaGPT
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Grateful Dead Chatbot
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Farmers Bounty
- 01 current state analysis
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- 03 data sources
- 05 cost analysis
- 06 database schema
- 08 ui ux changes
- 09 ai context optimization
- 10 testing validation
- 11 risk mitigation
- 12 implementation checklist
- ADMIN-SHORTCODES.html Update Summary
- Atlanta Gardening
- Beneficial Insects Guide for Georgia Gardens
- Botanical Garden Taxonomist
- Children's Garden Educator
- Farmers Bounty - Quick Start Guide
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- Farmers Bounty Chatbot - Complete Documentation
- Farmers Bounty Desktop User Guide
- Farmers Bounty Plugin - Gardener's Review Guide
- Farmers Bounty Plugin v6.6.0 - Release Notes
- Farmers Bounty v2.0 - Complete User Guide
- Farmers Bounty v5.3.0 - Complete User Guide
- Glossary
- Integrated Pest Management (IPM) Specialist
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Technical Document
- Accessibility Design
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- AI Inference Boundary Review
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- Antigravity Parallel Debug
- Antigravity Test Orchestration
- AppSec Engineer — IAM Security Specialist
- Chapter 22: Safety & Guardrails
- Chapter 26: Security Standards
- Civic Tech Privacy Architecture
- ClaimReview Schema Integration
- Claims Evidence Registry
- Code Review
- IT Influentials Express Agents Product Showcase
- Java Development
- MCP Client for Tauri
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- Nginx Reverse Proxy
- Pinecone Embedding Management
- PostgreSQL Administration
- Product Roadmap Update Prompt
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- RabbitMQ Messaging
- Redis Operations
- Release Management
- Retirement Calculator Engine
- Roadmap Build Planning
- Schema Markup Generation
- ScubaGPT — Architecture
- ScubaGPT Safety Guardrails - Quick Reference
- Session Context Protocol
- Stable Diffusion Image Generation
- Tauri Desktop Development
- Tavily & Pinecone Integrations
- Tavily API Quick Reference - Factchecker Plugin
- Tech Debt Analysis
- Test Plan Writing
- Travel Planner — n8n + Dify Integration Guide
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Answer Engine Optimizer
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SEO Optimizer
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Travel Planner
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Fact Checker
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Estate Manager
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ITI Marketing
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Patriot University
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Personal Assistant
FLUX Operations
name: flux-operations
description: Deploy, configure, and manage FLUX image generation backends (local Klein 4B and BFL cloud API) within the ITI multi-backend image generation service. Covers backend switching, API credential management, model downloads, health monitoring, Docker and native deployment, and troubleshooting. Use when configuring FLUX backends, managing BFL API credentials, switching between local and cloud FLUX, or troubleshooting FLUX-specific issues.
FLUX Operations
Instructions
Manage FLUX backends within the ITI image generation service at ITI/infrastructure/stable-diffusion/. The service supports three backends: sd (legacy Stable Diffusion), flux-local (FLUX.2 Klein 4B), and flux-api (BFL cloud API).
Setting the default backend:
# In .env (native mode) or docker-compose.yml
SD_DEFAULT_BACKEND=flux-api # BFL cloud (recommended default)
SD_DEFAULT_BACKEND=flux-local # Local Klein 4B
SD_DEFAULT_BACKEND=sd # Legacy Stable Diffusion
Per-request override: include "backend": "flux-api" or "flux-local" in the JSON body.
Starting the service (native — M3 Max with MPS):
cd ITI/infrastructure/stable-diffusion
source .venv/bin/activate
SD_DEVICE=auto SD_OUTPUT_DIR=./outputs SD_MODEL_DIR=./models \
SD_DEFAULT_BACKEND=flux-api \
SD_BFL_API_KEY=<your-key> \
SD_BFL_DEFAULT_MODEL=flux-2-pro-preview \
uvicorn app.main:app --host 0.0.0.0 --port 7860
Starting the service (Docker):
cd ITI/infrastructure/n8n-dify
docker compose --profile sd up -d stable-diffusion
Ensure the docker-compose.yml stable-diffusion service has these environment variables:
environment:
SD_DEFAULT_BACKEND: ${SD_DEFAULT_BACKEND:-flux-api}
SD_BFL_API_KEY: ${SD_BFL_API_KEY}
SD_BFL_DEFAULT_MODEL: ${SD_BFL_DEFAULT_MODEL:-flux-2-pro-preview}
SD_FLUX_MODEL_ID: ${SD_FLUX_MODEL_ID:-black-forest-labs/FLUX.2-klein-4B}
BFL API credential management:
- Obtain an API key at https://api.bfl.ai/
- Store in
.envasSD_BFL_API_KEY=bfl_...— NEVER commit this value - The
.gitignoreatITI/infrastructure/stable-diffusion/.gitignoreexcludes.envfiles - For Docker, set
SD_BFL_API_KEYinITI/infrastructure/n8n-dify/.env
Health check and backend status:
# Full health (reports all backends)
curl -s http://localhost:7860/health | python3 -m json.tool
# Quick backend availability
curl -s http://localhost:7860/api/backends | python3 -m json.tool
# Available models
curl -s http://localhost:7860/api/models | python3 -m json.tool
FLUX Klein local model management:
The Klein 4B model downloads from Hugging Face on first use (~8 GB). Cache location:
| Mode | Cache Path |
|---|---|
| Native | ./models/ |
| Docker | sd_models volume |
Pre-download to avoid first-request delay:
python3 -c "
from diffusers import Flux2KleinPipeline
Flux2KleinPipeline.from_pretrained(
'black-forest-labs/FLUX.2-klein-4B',
cache_dir='./models'
)
print('FLUX Klein 4B downloaded successfully')
"
Requirements: diffusers>=0.37.0, transformers>=4.45.0, sentencepiece.
BFL API model configuration:
| Environment Variable | Default | Purpose |
|---|---|---|
SD_BFL_API_KEY |
(required) | BFL authentication |
SD_BFL_API_BASE |
https://api.bfl.ai/v1 |
API endpoint |
SD_BFL_DEFAULT_MODEL |
flux-2-pro-preview |
Default FLUX model |
SD_BFL_POLL_INTERVAL |
1.0 |
Seconds between status polls |
SD_BFL_POLL_TIMEOUT |
120.0 |
Max seconds to wait for result |
Available BFL models:
| Model ID | Quality | Speed | Price/MP |
|---|---|---|---|
flux-2-pro-preview |
Highest (latest) | ~5s | $0.03 |
flux-2-pro |
High (fixed snapshot) | ~5s | $0.03 |
flux-2-max |
Ultra (grounding search) | ~8s | $0.07 |
flux-2-flex |
High (typography) | ~6s | $0.06 |
flux-2-klein-4b |
Good (fast) | <1s | $0.014 |
flux-2-klein-9b-preview |
Better (balanced) | ~1s | $0.015 |
FLUX Klein local parameter configuration:
| Environment Variable | Default | Purpose |
|---|---|---|
SD_FLUX_MODEL_ID |
black-forest-labs/FLUX.2-klein-4B |
Hugging Face model ID |
SD_FLUX_DEFAULT_STEPS |
4 |
Inference steps (distilled) |
SD_FLUX_DEFAULT_GUIDANCE_SCALE |
4.0 |
Guidance scale |
SD_FLUX_MAX_IMAGE_SIZE |
2048 |
Max dimension in pixels |
Troubleshooting:
| Symptom | Diagnosis | Fix | |
|---|---|---|---|
| 402 Payment Required from BFL | Insufficient API credits | Add credits at https://api.bfl.ai/ | |
| 401 Unauthorized from BFL | Invalid API key | Verify SD_BFL_API_KEY value |
|
| Timeout on BFL generation | Network or model load time | Increase SD_BFL_POLL_TIMEOUT; check BFL status |
|
| OOM with FLUX Klein local | Model requires ~13 GB | Use MPS (Apple Silicon) or enable CPU offload | |
| FLUX Klein slow on CPU | GPU required for reasonable speed | Set SD_DEVICE=auto for MPS; use flux-api otherwise |
|
| Model download fails | Hugging Face access or network | Set SD_HUGGINGFACE_TOKEN; check connectivity |
|
| Port 7860 in use | Previous instance not terminated | `lsof -ti:7860 | xargs kill -9` then restart |
Flux2KleinPipeline not found |
diffusers too old |
Upgrade: pip install 'diffusers>=0.37.0' |
Disk management:
# Check FLUX model cache
du -sh ./models/models--black-forest-labs--FLUX.2-klein-4B/ 2>/dev/null
# Check outputs
du -sh ./outputs/
# Prune old outputs (keep last 7 days)
find ./outputs -name "*.png" -mtime +7 -delete
n8n integration from Docker network:
| Service Mode | n8n URL |
|---|---|
| Docker (same network) | http://stable-diffusion:7860/api/txt2img |
| Native (outside Docker) | http://host.docker.internal:7860/api/txt2img |
Cost monitoring for BFL API:
Track spend by counting API calls in outputs directory or server logs. Budget estimation:
| Volume | Estimated Monthly (Pro) | Estimated Monthly (Klein API) |
|---|---|---|
| 100 images/month | $3.00 | $1.40 |
| 1,000 images/month | $30.00 | $14.00 |
| 10,000 images/month | $300.00 | $140.00 |
Key file paths:
| Path | Contents |
|---|---|
ITI/infrastructure/stable-diffusion/app/config.py |
Backend enum, all settings |
ITI/infrastructure/stable-diffusion/app/pipeline.py |
Multi-backend dispatch logic |
ITI/infrastructure/stable-diffusion/app/main.py |
FastAPI endpoints |
ITI/infrastructure/stable-diffusion/.env.example |
Configuration template |
ITI/infrastructure/stable-diffusion/.env |
Local credentials (gitignored) |
ITI/infrastructure/n8n-dify/docker-compose.yml |
Docker service definition |
