# πŸ€— GreenLight AI & ML Extension **Extension to GreenLight for HuggingFace & AI Infrastructure** --- ## πŸ€– AI Model Lifecycle States Add these to the **Lifecycle States** category: | Emoji | State | Code | Trinary | Description | |-------|-------|------|---------|-------------| | πŸ€— | MODEL_LOADING | `model_loading` | 0 | Loading model into memory | | 🧠 | MODEL_READY | `model_ready` | +1 | Model loaded and ready | | ⚑ | INFERENCE_RUNNING | `inference_running` | +1 | Generating output | | πŸ”„ | TOKEN_STREAMING | `token_streaming` | +1 | Streaming tokens | | πŸ’Ύ | MODEL_CACHED | `model_cached` | +1 | Model in cache | | πŸ“₯ | MODEL_DOWNLOADING | `model_downloading` | 0 | Downloading weights | | πŸ‹οΈ | MODEL_TRAINING | `model_training` | +1 | Model training | | πŸ“Š | MODEL_EVAL | `model_eval` | 0 | Evaluating performance | | πŸ”§ | MODEL_FINE_TUNING | `model_fine_tuning` | +1 | Fine-tuning model | | ⏱️ | INFERENCE_TIMEOUT | `inference_timeout` | -1 | Request timed out | --- ## 🎯 AI Task Categories Add to **Domain Tags**: | Emoji | Category | Code | Description | |-------|----------|------|-------------| | πŸ’¬ | TEXT_GEN | `text_gen` | Text generation / completion | | πŸ—£οΈ | CHAT | `chat` | Chat completions | | 🎨 | IMAGE_GEN | `image_gen` | Image generation | | πŸ–ΌοΈ | IMAGE_EDIT | `image_edit` | Image editing / inpainting | | πŸ”€ | EMBEDDINGS | `embeddings` | Vector embeddings | | πŸ” | OCR | `ocr` | Optical character recognition | | πŸŽ™οΈ | TTS | `tts` | Text to speech | | πŸ‘‚ | STT | `stt` | Speech to text | | πŸŽ₯ | VIDEO_GEN | `video_gen` | Video generation | | πŸ”¬ | CLASSIFICATION | `classification` | Classification tasks | --- ## πŸ—οΈ AI Infrastructure Components | Emoji | Component | Code | Description | |-------|-----------|------|-------------| | πŸ€— | HUGGINGFACE | `huggingface` | HuggingFace platform | | ⚑ | VLLM | `vllm` | vLLM inference server | | πŸ¦™ | LLAMA_CPP | `llama_cpp` | llama.cpp engine | | πŸ”₯ | TRANSFORMERS | `transformers` | Transformers library | | 🌐 | INFERENCE_ENDPOINT | `inference_endpoint` | HF Inference Endpoint | | πŸ“¦ | MODEL_HUB | `model_hub` | Model repository | | πŸš€ | SPACE | `space` | HuggingFace Space | | πŸ’Ύ | MODEL_CACHE | `model_cache` | Model caching layer | | πŸ–₯️ | GPU_INSTANCE | `gpu_instance` | GPU compute instance | --- ## πŸŽ›οΈ GPU Instance Types | Emoji | Instance | Code | VRAM | Description | |-------|----------|------|------|-------------| | 🟒 | T4 | `t4` | 16GB | Small models / testing | | πŸ”΅ | L4 | `l4` | 24GB | 7B-13B models | | 🟑 | A10G | `a10g` | 24GB | Production inference | | 🟠 | A100 | `a100` | 80GB | Large models (70B+) | | πŸ”΄ | H100 | `h100` | 80GB | Maximum performance | | 🟣 | JETSON | `jetson` | 8GB | Edge inference | --- ## 🎨 Composite Patterns for AI ### Model Operations ``` πŸ€—πŸ“₯πŸ‘‰πŸ“Œ = Downloading model, micro scale πŸ§ βœ…πŸŽ’β­ = Model loaded, macro impact, high priority βš‘πŸ”„πŸ’¬πŸŒ€ = Streaming chat tokens, AI domain πŸŽ¨βœ…πŸ‘‰πŸ“Œ = Image generated, micro scale ``` ### Inference Flows ``` βš‘πŸ’¬πŸ§ βœ… = Chat inference running, model ready βš‘πŸŽ¨πŸ–ΌοΈβœ… = Image generation complete πŸ”€πŸ’ΎπŸŽ’βœ… = Embeddings cached, macro scale πŸ”πŸ“„πŸ‘‰βœ… = OCR completed, micro scale ``` ### Infrastructure ``` πŸš€πŸ€—πŸŒβœ… = HF Space deployed πŸŒβš‘πŸŸ‘πŸ“Œ = Inference endpoint on A10G πŸ’ΎπŸ§ πŸŽ’β­ = Model cached, high priority ⏱️❌🧠πŸ”₯ = Inference timeout, fire priority ``` ### Combined AI Flow ``` [⚑πŸ“₯] [πŸ€—πŸ§ ] [βš‘πŸ’¬] [πŸ”„πŸ“Š] [βœ…πŸŽ‰] = Request β†’ Load β†’ Inference β†’ Stream β†’ Complete [🎨⚑] [πŸ–ΌοΈβœ…] = Image generation β†’ success [πŸ”€πŸ’Ύ] [βœ…πŸŽ’] = Embeddings β†’ cached ``` --- ## πŸ“ NATS Subject Patterns (AI) ### Inference Events ``` greenlight.inference.started.micro.ai.{model_name} greenlight.inference.completed.micro.ai.{model_name} greenlight.inference.failed.micro.ai.{model_name} greenlight.inference.timeout.micro.ai.{model_name} ``` ### Model Events ``` greenlight.model.loaded.macro.ai.{model_name} greenlight.model.cached.micro.ai.{model_name} greenlight.model.downloading.micro.ai.{model_name} greenlight.model.uploaded.macro.ai.{model_name} ``` ### Endpoint Events ``` greenlight.endpoint.created.macro.ai.{endpoint_name} greenlight.endpoint.paused.micro.ai.{endpoint_name} greenlight.endpoint.resumed.micro.ai.{endpoint_name} greenlight.endpoint.scaled.macro.ai.{endpoint_name} ``` ### Task-Specific Events ``` greenlight.chat.completed.micro.ai.{model} greenlight.image.generated.micro.ai.{model} greenlight.embeddings.cached.micro.ai.{model} greenlight.ocr.completed.micro.ai.{file} ``` --- ## πŸ”¨ AI Memory Templates ### Model Operations ```bash # Model loading gl_model_loading() { local model_name="$1" local size="${2:-unknown}" gl_log "πŸ€—πŸ“₯πŸ‘‰πŸ“Œ" "model_loading" "$model_name" \ "Loading model: $size" } # Model ready gl_model_ready() { local model_name="$1" local vram="${2:-unknown}" gl_log "πŸ§ βœ…πŸŽ’β­" "model_ready" "$model_name" \ "Model loaded, VRAM: $vram" } # Model cached gl_model_cached() { local model_name="$1" local cache_key="$2" gl_log "πŸ’ΎπŸ§ πŸ‘‰πŸ“Œ" "model_cached" "$model_name" \ "Model cached: $cache_key" } # Model downloading gl_model_downloading() { local model_name="$1" local size="${2:-unknown}" gl_log "πŸ“₯πŸ€—πŸ‘‰πŸ“Œ" "model_downloading" "$model_name" \ "Downloading: $size" } # Model uploaded gl_model_uploaded() { local model_name="$1" local repo_id="$2" gl_log "πŸ“€πŸ€—πŸŽ’βœ…" "model_uploaded" "$model_name" \ "Uploaded to: $repo_id" } ``` ### Inference Operations ```bash # Inference started gl_inference_start() { local task_type="$1" # chat, text_gen, image_gen, etc. local model="$2" local request_id="${3:-$(uuidgen)}" local task_emoji="" case "$task_type" in chat) task_emoji="πŸ’¬" ;; text_gen) task_emoji="πŸ’¬" ;; image_gen) task_emoji="🎨" ;; embeddings) task_emoji="πŸ”€" ;; ocr) task_emoji="πŸ”" ;; tts) task_emoji="πŸŽ™οΈ" ;; video_gen) task_emoji="πŸŽ₯" ;; *) task_emoji="πŸ€–" ;; esac gl_log "⚑${task_emoji}πŸ‘‰πŸ“Œ" "inference_start" "$model" \ "$task_type inference started: $request_id" } # Inference complete gl_inference_complete() { local task_type="$1" local model="$2" local duration="${3:-unknown}" local task_emoji="" case "$task_type" in chat) task_emoji="πŸ’¬" ;; text_gen) task_emoji="πŸ’¬" ;; image_gen) task_emoji="🎨" ;; embeddings) task_emoji="πŸ”€" ;; ocr) task_emoji="πŸ”" ;; *) task_emoji="πŸ€–" ;; esac gl_log "βœ…${task_emoji}πŸŽ’πŸŽ‰" "inference_complete" "$model" \ "$task_type complete in $duration" } # Inference failed gl_inference_failed() { local task_type="$1" local model="$2" local error="${3:-unknown error}" gl_log "βŒβš‘πŸ€–πŸ”₯" "inference_failed" "$model" \ "$task_type failed: $error" } # Token streaming gl_token_streaming() { local model="$1" local tokens_generated="$2" gl_log "πŸ”„πŸ’¬βš‘πŸ‘‰" "token_streaming" "$model" \ "Streaming: $tokens_generated tokens" } # Inference timeout gl_inference_timeout() { local model="$1" local timeout_seconds="$2" gl_log "β±οΈβŒπŸ€–πŸ”₯" "inference_timeout" "$model" \ "Timed out after ${timeout_seconds}s" } ``` ### Endpoint Management ```bash # Endpoint created gl_endpoint_created() { local endpoint_name="$1" local model="$2" local instance_type="${3:-unknown}" local instance_emoji="" case "$instance_type" in *t4*) instance_emoji="🟒" ;; *l4*) instance_emoji="πŸ”΅" ;; *a10g*) instance_emoji="🟑" ;; *a100*) instance_emoji="🟠" ;; *h100*) instance_emoji="πŸ”΄" ;; *) instance_emoji="πŸ–₯️" ;; esac gl_log "πŸš€πŸŒ${instance_emoji}βœ…" "endpoint_created" "$endpoint_name" \ "Endpoint created: $model on $instance_type" } # Endpoint paused gl_endpoint_paused() { local endpoint_name="$1" gl_log "βΈοΈπŸŒπŸ‘‰πŸ“Œ" "endpoint_paused" "$endpoint_name" \ "Endpoint paused (cost savings)" } # Endpoint resumed gl_endpoint_resumed() { local endpoint_name="$1" gl_log "β–ΆοΈπŸŒπŸ‘‰πŸ“Œ" "endpoint_resumed" "$endpoint_name" \ "Endpoint resumed" } # Endpoint scaled gl_endpoint_scaled() { local endpoint_name="$1" local replicas="$2" gl_log "πŸ“ˆπŸŒπŸŽ’β­" "endpoint_scaled" "$endpoint_name" \ "Scaled to $replicas replicas" } # Endpoint deleted gl_endpoint_deleted() { local endpoint_name="$1" gl_log "πŸ—‘οΈπŸŒπŸ‘‰πŸ“Œ" "endpoint_deleted" "$endpoint_name" \ "Endpoint deleted" } ``` ### Space Operations ```bash # Space deployed gl_space_deployed() { local space_name="$1" local url="$2" gl_log "πŸš€πŸ€—πŸŒβœ…" "space_deployed" "$space_name" \ "Space deployed: $url" } # Space invoked gl_space_invoked() { local space_id="$1" local task_type="$2" gl_log "βš‘πŸ€—πŸ‘‰πŸ“Œ" "space_invoked" "$space_id" \ "Space invoked for: $task_type" } ``` --- ## 🎯 Example Integration: Complete Inference Flow ### Scenario: Chat inference with DeepSeek ```bash # 1. Load model gl_model_loading "deepseek-ai/DeepSeek-V3.2" "7B" # [πŸ€—πŸ“₯πŸ‘‰πŸ“Œ] model_loading: deepseek-ai/DeepSeek-V3.2 β€” Loading model: 7B # 2. Model ready gl_model_ready "deepseek-ai/DeepSeek-V3.2" "16GB" # [πŸ§ βœ…πŸŽ’β­] model_ready: deepseek-ai/DeepSeek-V3.2 β€” Model loaded, VRAM: 16GB # 3. Start inference gl_inference_start "chat" "deepseek-ai/DeepSeek-V3.2" "req_abc123" # [βš‘πŸ’¬πŸ‘‰πŸ“Œ] inference_start: deepseek-ai/DeepSeek-V3.2 β€” chat inference started: req_abc123 # 4. Token streaming gl_token_streaming "deepseek-ai/DeepSeek-V3.2" "247" # [πŸ”„πŸ’¬βš‘πŸ‘‰] token_streaming: deepseek-ai/DeepSeek-V3.2 β€” Streaming: 247 tokens # 5. Complete gl_inference_complete "chat" "deepseek-ai/DeepSeek-V3.2" "3.2s" # [βœ…πŸ’¬πŸŽ’πŸŽ‰] inference_complete: deepseek-ai/DeepSeek-V3.2 β€” chat complete in 3.2s ``` ### Scenario: Image generation with FLUX ```bash # 1. Space invoked gl_space_invoked "black-forest-labs/FLUX.1-dev" "image_gen" # [βš‘πŸ€—πŸ‘‰πŸ“Œ] space_invoked: black-forest-labs/FLUX.1-dev β€” Space invoked for: image_gen # 2. Start inference gl_inference_start "image_gen" "FLUX.1-dev" "img_xyz789" # [βš‘πŸŽ¨πŸ‘‰πŸ“Œ] inference_start: FLUX.1-dev β€” image_gen inference started: img_xyz789 # 3. Complete gl_inference_complete "image_gen" "FLUX.1-dev" "12.4s" # [βœ…πŸŽ¨πŸŽ’πŸŽ‰] inference_complete: FLUX.1-dev β€” image_gen complete in 12.4s ``` ### Scenario: Endpoint lifecycle (Lucidia) ```bash # 1. Create endpoint gl_endpoint_created "lucidia-inference" "blackroadio/Lucidia" "nvidia-a10g" # [πŸš€πŸŒπŸŸ‘βœ…] endpoint_created: lucidia-inference β€” Endpoint created: blackroadio/Lucidia on nvidia-a10g # 2. Run inference gl_inference_start "chat" "lucidia-inference" "req_lucidia_001" # [βš‘πŸ’¬πŸ‘‰πŸ“Œ] inference_start: lucidia-inference β€” chat inference started: req_lucidia_001 # 3. Complete gl_inference_complete "chat" "lucidia-inference" "2.1s" # [βœ…πŸ’¬πŸŽ’πŸŽ‰] inference_complete: lucidia-inference β€” chat complete in 2.1s # 4. Pause for cost savings gl_endpoint_paused "lucidia-inference" # [βΈοΈπŸŒπŸ‘‰πŸ“Œ] endpoint_paused: lucidia-inference β€” Endpoint paused (cost savings) # 5. Resume when needed gl_endpoint_resumed "lucidia-inference" # [β–ΆοΈπŸŒπŸ‘‰πŸ“Œ] endpoint_resumed: lucidia-inference β€” Endpoint resumed ``` ### Scenario: Inference failure and timeout ```bash # 1. Start inference gl_inference_start "chat" "large-model" "req_fail" # [βš‘πŸ’¬πŸ‘‰πŸ“Œ] inference_start: large-model β€” chat inference started: req_fail # 2. Timeout gl_inference_timeout "large-model" "30" # [β±οΈβŒπŸ€–πŸ”₯] inference_timeout: large-model β€” Timed out after 30s # 3. Failed gl_inference_failed "chat" "large-model" "OOM error" # [βŒβš‘πŸ€–πŸ”₯] inference_failed: large-model β€” chat failed: OOM error ``` --- ## πŸ“Š AI Analytics Integration ### Performance Tracking ```bash # Inference latency gl_log "πŸ“Šβš‘πŸŽ’πŸ“Œ" "latency_metric" "ai-metrics" "p95 latency: 3.2s (chat)" # Token throughput gl_log "πŸ“ŠπŸ’¬πŸ‘‰πŸ“Œ" "throughput_metric" "ai-metrics" "Throughput: 45 tokens/sec" # Cache hit rate gl_log "πŸ“ŠπŸ’ΎπŸŽ’β­" "cache_metric" "ai-metrics" "Cache hit rate: 78%" ``` ### Cost Tracking ```bash # GPU costs gl_log "πŸ’°πŸ–₯οΈπŸŽ’πŸ“Œ" "gpu_cost" "ai-billing" "A10G usage: $2.47/hour" # Inference costs gl_log "πŸ’°βš‘πŸ‘‰πŸ“Œ" "inference_cost" "ai-billing" "1,247 requests: $12.34" ``` --- ## πŸ“š Integration Checklist - [x] Extended lifecycle states for AI operations - [x] Added AI task category tags - [x] Created infrastructure component tags - [x] Mapped GPU instance types - [x] Created composite patterns for inference flows - [x] Extended NATS subjects for AI events - [x] Built 15+ AI-specific templates - [x] Integrated with 27-step GreenLight workflow - [x] Added analytics tracking patterns - [x] Added cost tracking patterns --- ## 🎯 HuggingFace Account Details **Username:** blackroadio **Profile:** https://huggingface.co/blackroadio **Models:** 2 (Lucidia, qwen3-235b-a22b) **API Tokens:** https://huggingface.co/settings/tokens **Endpoints:** https://endpoints.huggingface.co ### Recommended Models **Text Generation:** - openai/gpt-oss-20b (7.2M downloads) - deepseek-ai/DeepSeek-V3.2 (90.9K downloads) - nvidia/Nemotron-3-Nano-30B-A3B (247.7K downloads) **Image Generation:** - black-forest-labs/FLUX.1-dev (809.7K downloads) - stabilityai/stable-diffusion-xl-base-1.0 (2.1M downloads) **Embeddings:** - sentence-transformers/all-MiniLM-L6-v2 (149.3M downloads) - BAAI/bge-m3 (8.2M downloads) **OCR:** - deepseek-ai/DeepSeek-OCR (4.7M downloads) ### Available Spaces (15+) - evalstate/flux1_schnell - Fast image generation - mcp-tools/FLUX.1-Krea-dev - High quality images - not-lain/background-removal - Remove backgrounds - ResembleAI/Chatterbox - Text to speech - mcp-tools/DeepSeek-OCR-experimental - OCR --- **Created:** December 23, 2025 **For:** HuggingFace AI Infrastructure **Version:** 2.0.0-ai **Status:** πŸ”¨ IMPLEMENTATION