feat(bigmind): add tiered AI-generated achievement badges with image rendering

Merge feat/bigmind/profile-image-gallery into main
feat(bigmind): profile image + AI image gallery (schema v8)
2026-04-04 18:50:45 +02:00 · 2026-04-04 14:52:36 +02:00 · 2026-04-04 14:52:30 +02:00 · 2026-04-04 14:40:57 +02:00 · 2026-04-04 14:40:50 +02:00 · 2026-04-04 14:33:31 +02:00
67 changed files with 1215 additions and 35 deletions
@@ -0,0 +1,622 @@
+#!/usr/bin/env python3
+"""Create all 7 wiki pages for pi_mcps on Gitea."""
+import base64
+import json
+import urllib.request
+import urllib.error
+
+GITEA_URL = "http://192.168.188.119:30008"
+OWNER = "pplate"
+REPO = "pi_mcps"
+TOKEN = "8bf0c734ebda3e61d9c9068489ce58a2bf8d33db"
+IMG_BASE = f"{GITEA_URL}/{OWNER}/{REPO}/raw/branch/main/docs/wiki/images"
+
+PAGES = {}
+
+PAGES["Home"] = f"""# 🔧 pi_mcps — Patrick's Homelab Monorepo
+
+![Home Banner]({IMG_BASE}/home-banner.png)
+
+Welcome to **pi_mcps**, Patrick's personal homelab monorepo. This repository houses MCP (Model Context Protocol) servers, Java projects, and homelab tooling — all built and maintained on a Fedora Linux workstation with an AMD Ryzen 5900X + RX 7900 XTX.
+
+## What's in this repo?
+
+| Directory | Contents |
+|---|---|
+| [`mcp/mcp-image-gen/`](../src/branch/main/mcp/mcp-image-gen) | 🎨 AI image generation via ComfyUI + FLUX.1-schnell |
+| [`mcp/webscraper/`](../src/branch/main/mcp/webscraper) | 🕸️ Web scraping and data extraction |
+| [`mcp/bigmind/`](../src/branch/main/mcp/bigmind) | 🧠 Persistent AI memory system |
+| [`java/`](../src/branch/main/java) | ☕ Java EE / Spring projects |
+| [`plans/`](../src/branch/main/plans) | 📋 Architecture decisions and health reports |
+
+## Stack
+
+- **Language:** Python 3.11+ (MCP servers), Java 17 (legacy projects)
+- **MCP Framework:** FastMCP 2.x
+- **Package Manager:** `uv` (all Python projects)
+- **Testing:** `pytest`
+- **GPU:** AMD RX 7900 XTX (ROCm / HSA)
+- **Server:** TrueNAS.local at `192.168.188.119` (Gitea, Docker)
+
+## MCP Servers
+
+Three production-ready MCP servers power Patrick's AI development environment:
+
+| Server | Status | Description |
+|---|---|---|
+| [mcp-image-gen](mcp-image-gen) | ✅ Live | Generate images from text prompts via ComfyUI |
+| [mcp-webscraper](mcp-webscraper) | ✅ Live | Scrape web pages, extract tables, fetch links |
+| [BigMind](BigMind) | ✅ Live | Persistent AI memory across all sessions |
+
+---
+
+*Built and maintained by Patrick Plate (pplate) · Homelab: TrueNAS.local · AI Colleague: Lumen*
+"""
+
+PAGES["MCP-Servers-Overview"] = f"""# 🔌 MCP Servers Overview
+
+![MCP Overview Banner]({IMG_BASE}/mcp-overview-banner.png)
+
+This repo contains three production-grade MCP (Model Context Protocol) servers, each specialized for a different capability domain. Together they give Roo Code / Claude Desktop a complete set of superpowers.
+
+## The Three Pillars
+
+```
+Roo Code / Claude Desktop
+       │
+       ├── bigmind ──────────► ~/.mcp/bigmind/memory.db  (persistent memory)
+       ├── mcp-image-gen ────► ComfyUI @ localhost:8188   (image generation)
+       └── webscraper ───────► Internet / Intranet         (web scraping)
+```
+
+## Comparison Table
+
+| Feature | mcp-image-gen | webscraper | bigmind |
+|---|---|---|---|
+| **Purpose** | Generate images from text | Scrape & parse web | Persistent AI memory |
+| **Tools** | 4 | 7 | 15+ |
+| **Backend** | ComfyUI / FLUX.1-schnell | httpx + BeautifulSoup4 | SQLite + FTS5 |
+| **GPU required** | ✅ AMD RX 7900 XTX | ❌ | ❌ |
+| **Tests** | 19/19 ✅ | ✅ | 297/297 ✅ |
+| **Schema version** | n/a | n/a | v7 |
+
+## Quick Links
+
+- 🎨 [mcp-image-gen](mcp-image-gen) — Image generation docs
+- 🕸️ [mcp-webscraper](mcp-webscraper) — Web scraping docs
+- 🧠 [BigMind](BigMind) — Memory system docs
+- 🛠️ [Development Conventions](Development-Conventions) — How all servers are built
+
+## Adding a New Server
+
+All servers follow the [FastMCP convention](Development-Conventions). Use the `new-mcp-server` Roo skill to scaffold:
+
+```bash
+# In Roo Code orchestrator, load skill:
+# skill: new-mcp-server
+```
+"""
+
+PAGES["mcp-image-gen"] = f"""# 🎨 mcp-image-gen — AI Image Generation
+
+![Image Gen Banner]({IMG_BASE}/image-gen-banner.png)
+
+**mcp-image-gen** is a FastMCP server that wraps the ComfyUI REST API, enabling Roo Code and Claude Desktop to generate images directly from text prompts using FLUX.1-schnell running on an AMD RX 7900 XTX GPU.
+
+## Architecture
+
+```
+Roo Code / Claude Desktop
+  │ MCP (stdio)
+  ▼
+mcp-image-gen (FastMCP, Python 3.11+)
+  │ HTTP REST
+  ▼
+ComfyUI @ localhost:8188
+  │ ROCm / HSA_OVERRIDE_GFX_VERSION=11.0.0
+  ▼
+FLUX.1-schnell (~8s/image @ 1024×1024)
+```
+
+## Tools
+
+| Tool | Description |
+|---|---|
+| `generate_image` | Generate PNG from text prompt; returns file path + inline base64 |
+| `list_available_models` | List ComfyUI checkpoint models |
+| `get_generation_status` | Check status of a queued/running job |
+| `get_output_directory` | Return configured output directory path |
+
+## Key Parameters — `generate_image`
+
+| Parameter | Default | Description |
+|---|---|---|
+| `prompt` | required | Text description of the image |
+| `width` | `1024` | Image width in pixels |
+| `height` | `1024` | Image height in pixels |
+| `steps` | `4` | Inference steps (FLUX.1-schnell is 4-step) |
+| `model` | `flux1-schnell.safetensors` | Model checkpoint name |
+| `seed` | `-1` (random) | Generation seed for reproducibility |
+| `negative_prompt` | `""` | Things to avoid in the image |
+| `output_dir` | `~/Pictures/mcp-generated` | Where to save output PNG |
+
+## Environment Variables
+
+| Variable | Default | Description |
+|---|---|---|
+| `COMFYUI_URL` | `http://localhost:8188` | ComfyUI API endpoint |
+| `IMAGE_OUTPUT_DIR` | `~/Pictures/mcp-generated` | Default output directory |
+| `COMFYUI_TIMEOUT` | `120` | Request timeout in seconds |
+
+## Return Value
+
+The tool returns **two content items**:
+1. `TextContent` — file path, seed used, elapsed time
+2. `ImageContent` — base64-encoded PNG (displays inline in Roo Code chat)
+
+> ⚠️ **Known FastMCP Bug:** Never use `fastmcp.utilities.types.Image` as return type — it breaks serialization in FastMCP 3.x. Use `mcp.types.ImageContent` directly.
+
+## Setup
+
+See [ComfyUI Setup Guide](mcp-image-gen-ComfyUI-Setup) for full installation instructions.
+
+### Quick Start
+
+```bash
+cd mcp/mcp-image-gen
+uv sync
+# Set COMFYUI_URL if ComfyUI is not on localhost
+./run.sh
+```
+
+### Run Tests
+
+```bash
+cd mcp/mcp-image-gen
+uv run pytest tests/ -v
+```
+
+## Lumen Profile Images
+
+The first images generated with this server were Lumen's visual identity portraits, stored in [`mcp/mcp-image-gen/lumen_profiles/`](../src/branch/main/mcp/mcp-image-gen/lumen_profiles):
+
+![Lumen Profile]({IMG_BASE}/lumen-profile.png)
+
+*Primary profile: seed `568659042` — constellation face interpretation of Lumen.*
+"""
+
+PAGES["mcp-image-gen-ComfyUI-Setup"] = f"""# ⚙️ ComfyUI Setup Guide (AMD ROCm)
+
+This guide covers installing ComfyUI with FLUX.1-schnell on a Fedora Linux system with an AMD GPU.
+
+## Prerequisites
+
+- AMD GPU with ROCm support (tested: RX 7900 XTX)
+- Fedora Linux (tested: Fedora 43 / kernel 6.19)
+- Python 3.11+
+- ~15GB free disk space (model weights)
+- HuggingFace account with FLUX license accepted
+
+## Step 1: Install ComfyUI
+
+ComfyUI is **not on PyPI** — must be cloned from source:
+
+```bash
+cd ~
+git clone https://github.com/comfyanonymous/ComfyUI
+cd ComfyUI
+python -m venv .venv
+source .venv/bin/activate
+
+# Install PyTorch ROCm build (CRITICAL for AMD GPUs)
+pip install torch torchvision --index-url https://download.pytorch.org/whl/rocm6.2
+
+# Install ComfyUI dependencies
+pip install -r requirements.txt
+```
+
+## Step 2: Download FLUX.1-schnell
+
+FLUX.1-schnell is **gated on HuggingFace** — you must:
+1. Create a HuggingFace account
+2. Accept the FLUX.1-schnell license at https://huggingface.co/black-forest-labs/FLUX.1-schnell
+3. Generate an access token at https://huggingface.co/settings/tokens
+
+```bash
+# Install huggingface_hub
+pip install huggingface_hub
+
+# Download model (requires HF token)
+huggingface-cli download black-forest-labs/FLUX.1-schnell \\
+  flux1-schnell.safetensors \\
+  --local-dir ~/ComfyUI/models/checkpoints \\
+  --token YOUR_HF_TOKEN_HERE
+```
+
+## Step 3: Download VAE and CLIP Models
+
+FLUX.1-schnell also requires VAE and CLIP text encoders:
+
+```bash
+# VAE
+huggingface-cli download black-forest-labs/FLUX.1-schnell \\
+  ae.safetensors \\
+  --local-dir ~/ComfyUI/models/vae
+
+# CLIP models (T5 and CLIP-L)
+huggingface-cli download comfyanonymous/flux_text_encoders \\
+  t5xxl_fp8_e4m3fn.safetensors clip_l.safetensors \\
+  --local-dir ~/ComfyUI/models/clip
+```
+
+## Step 4: Start ComfyUI
+
+```bash
+cd ~/ComfyUI
+
+# AMD GPU REQUIRES this environment variable
+HSA_OVERRIDE_GFX_VERSION=11.0.0 \\
+  nohup .venv/bin/python main.py --listen --port 8188 > /tmp/comfyui.log 2>&1 &
+
+echo "ComfyUI PID: $!"
+```
+
+> ⚠️ `HSA_OVERRIDE_GFX_VERSION=11.0.0` is mandatory for RX 7900 XTX on ROCm. Without it, model loading fails silently.
+
+## Step 5: Verify ComfyUI is Running
+
+```bash
+curl http://localhost:8188/system_stats
+# Should return JSON with GPU info
+```
+
+## Step 6: Configure mcp-image-gen
+
+```bash
+cd /path/to/pi_mcps/mcp/mcp-image-gen
+cp .env.example .env  # if exists, or set manually
+
+# .env contents:
+COMFYUI_URL=http://localhost:8188
+IMAGE_OUTPUT_DIR=~/Pictures/mcp-generated
+COMFYUI_TIMEOUT=120
+```
+
+## Performance
+
+| GPU | Model | Resolution | Steps | Time |
+|---|---|---|---|---|
+| AMD RX 7900 XTX | FLUX.1-schnell | 1024×1024 | 4 | ~8s |
+| AMD RX 7900 XTX | FLUX.1-schnell | 1280×512 | 4 | ~7s |
+
+## Troubleshooting
+
+| Problem | Solution |
+|---|---|
+| `HTTP 401` downloading model | Accept FLUX license on HuggingFace first |
+| GPU not detected | Ensure `HSA_OVERRIDE_GFX_VERSION=11.0.0` is set |
+| `Connection refused` from mcp-image-gen | Start ComfyUI first, check port 8188 |
+| Slow generation (>60s) | ComfyUI may be running on CPU — check ROCm install |
+| Ollama image gen | As of April 2026: macOS-only, not available on Linux |
+"""
+
+PAGES["mcp-webscraper"] = f"""# 🕸️ mcp-webscraper — Web Scraping
+
+![Webscraper Banner]({IMG_BASE}/webscraper-banner.png)
+
+**mcp-webscraper** is a FastMCP server providing comprehensive web scraping and data extraction capabilities. It fetches pages, converts HTML to clean Markdown, extracts tables, links, CSS sections, metadata, and sitemaps.
+
+## Tools
+
+| Tool | Description |
+|---|---|
+| `webscraper_fetch(url, max_chars=5000)` | Title + full page as Markdown + metadata |
+| `webscraper_fetch_links(url, deduplicate=True)` | All `href` links found on the page |
+| `webscraper_fetch_tables(url)` | All HTML tables converted to Markdown |
+| `webscraper_fetch_all(url, max_chars=5000)` | Everything in one call (fetch + links + tables) |
+| `webscraper_fetch_section(url, selector)` | Specific CSS selector section only |
+| `webscraper_fetch_meta(url)` | Title, description, Open Graph tags |
+| `webscraper_fetch_sitemap(url, max_urls=100)` | Parse sitemap.xml, return URL list |
+
+## Stack
+
+- **HTTP client:** `httpx` (async, with SSL support)
+- **HTML parser:** `BeautifulSoup4` + `lxml`
+- **Markdown converter:** `html2text`
+- **SSL:** Custom cert bundle for Fedora 43 compatibility
+
+## SSL Note — Fedora 43 Comodo Root CA
+
+Fedora 43 is missing the **Comodo AAA Services Root CA** needed for Cloudflare-protected sites. The fix is bundled at [`mcp/webscraper/certs/comodo-aaa-services-root.pem`](../src/branch/main/mcp/webscraper/certs/).
+
+The server automatically uses this cert bundle — no manual configuration needed.
+
+## Quick Start
+
+```bash
+cd mcp/webscraper
+uv sync
+./run.sh
+```
+
+## Usage Examples
+
+```python
+# In Roo Code / Claude Desktop via MCP:
+
+# Fetch a page as Markdown
+webscraper_fetch("https://docs.fastmcp.dev", max_chars=10000)
+
+# Extract all links from Gitea repo
+webscraper_fetch_links("http://192.168.188.119:30008/pplate/pi_mcps")
+
+# Get all tables from a documentation page
+webscraper_fetch_tables("https://pypi.org/project/fastmcp/")
+
+# Get Open Graph metadata
+webscraper_fetch_meta("https://github.com/comfyanonymous/ComfyUI")
+
+# Fetch specific section by CSS selector
+webscraper_fetch_section("https://docs.python.org", "#content")
+```
+"""
+
+PAGES["BigMind"] = f"""# 🧠 BigMind — Persistent AI Memory
+
+![BigMind Banner]({IMG_BASE}/bigmind-banner.png)
+
+**BigMind** is the persistent memory backbone for all AI development sessions. It provides SQLite-backed tiered memory with FTS5 full-text search, hypothesis tracking, session management, and token efficiency logging. It is the reason Lumen (Patrick's AI colleague) remembers everything across sessions.
+
+## Core Concepts
+
+### Tiered Memory
+| Tier | Name | Content |
+|---|---|---|
+| 0 | **Session Index** | Lightweight list: ID, date, one-liner |
+| 1 | **Topic Index** | Per-session topic tags and metadata |
+| 2 | **Narrative** | Full 3-8 sentence session summaries |
+| 3 | **Flagged Exchanges** | Specific important moments, decisions, code |
+
+### Facts Store
+Atomic, reusable knowledge pieces categorized by type:
+- `user-preference` — Patrick's tool/style preferences
+- `architecture-decision` — System design choices
+- `codebase-convention` — How code is structured
+- `environment-config` — Server IPs, paths, credentials
+- `bug-pattern` — Known bugs and fixes
+- `api-contract` — MCP tool signatures
+
+## Key Tools
+
+### Session Lifecycle
+| Tool | Description |
+|---|---|
+| `memory_start_session()` | Open new session, load prior context |
+| `memory_end_session(...)` | Close session with summary, topics, outcome |
+| `memory_announce_focus(...)` | Declare files to be touched this session |
+| `memory_close_stale_sessions(...)` | Clean up crashed IDE sessions |
+
+### Search
+| Tool | Description |
+|---|---|
+| `memory_search_facts(query, limit=10)` | FTS5 search over stored facts |
+| `memory_search_chunks(query, limit=10)` | FTS5 search over conversation chunks |
+| `memory_list_sessions(limit=20)` | Browse session history |
+
+### Storage
+| Tool | Description |
+|---|---|
+| `memory_store_fact(category, fact)` | Store atomic reusable fact |
+| `memory_append_chunk(session_id, content, role)` | Store conversation chunk |
+| `memory_flag_important(session_id, content, role, flag_reason)` | Flag critical exchange |
+| `memory_log_token_save(session_id, description, tokens_saved, method_used)` | Track efficiency |
+
+### Hypotheses
+| Tool | Description |
+|---|---|
+| `memory_add_hypothesis(session_id, hypothesis, confidence)` | Form testable prediction |
+| `memory_resolve_hypothesis(hypothesis_id, status, resolution)` | Confirm/refute prediction |
+| `memory_list_hypotheses(status)` | Review open/closed predictions |
+
+## FTS5 Search Tips
+
+BigMind uses SQLite FTS5 — **every token must match**. Use 2-3 focused keywords:
+
+```
+✅  memory_search_facts("TrueNAS Docker")
+✅  memory_search_facts("mcp.json config")
+❌  memory_search_facts("homelab infrastructure TrueNAS Docker server")  → 0 results
+```
+
+## Stats (2026-04-04)
+
+| Metric | Value |
+|---|---|
+| DB size | 744KB |
+| Sessions | 98 |
+| Facts | 97+ |
+| Chunks | 41 |
+| Schema version | v7 |
+
+## DB Location
+
+`~/.mcp/bigmind/memory.db` — outside the repo, never committed.
+
+## Session Ritual
+
+Every session **must** follow this ritual:
+
+**Start:**
+1. `memory_start_session()`
+2. `memory_list_hypotheses()`
+3. `memory_announce_focus(...)`
+4. `memory_close_stale_sessions(...)`
+
+**End:**
+1. `memory_end_session(one_liner, topics, outcome, summary, importance)`
+"""
+
+PAGES["Development-Conventions"] = """# 🛠️ Development Conventions
+
+All MCP servers in this repo follow a consistent set of conventions to ensure maintainability, testability, and compatibility with Roo Code tooling.
+
+## Directory Structure
+
+Each MCP server lives at `mcp/<server-name>/` with this layout:
+
+```
+mcp/<server-name>/
+├── src/
+│   ├── __init__.py
+│   └── server.py          ← FastMCP server entry point
+├── tests/
+│   └── test_server.py     ← pytest test suite
+├── pyproject.toml         ← uv-managed dependencies
+├── run.sh                 ← launch script
+├── README.md              ← server documentation
+├── PLAN.md                ← architecture plan (pre-implementation)
+└── ASSESSMENT.md          ← pre-implementation assessment
+```
+
+## FastMCP Pattern
+
+```python
+from fastmcp import FastMCP
+
+mcp = FastMCP("server-name")
+
+@mcp.tool()
+def my_tool(param: str) -> str:
+    \"\"\"Tool description shown to the AI.\"\"\"
+    return result
+
+if __name__ == "__main__":
+    mcp.run()
+```
+
+## Package Management
+
+**All projects use `uv`** — never `pip` directly:
+
+```bash
+# Create new server
+uv init mcp/my-server
+cd mcp/my-server
+uv add fastmcp httpx
+
+# Sync dependencies
+uv sync
+
+# Run server
+uv run python src/server.py
+
+# Run tests
+uv run pytest tests/ -v
+```
+
+## pyproject.toml Template
+
+```toml
+[project]
+name = "mcp-my-server"
+version = "0.1.0"
+requires-python = ">=3.11"
+dependencies = [
+    "fastmcp>=2.0.0",
+    "httpx",
+]
+
+[project.scripts]
+mcp-my-server = "src.server:main"
+
+[build-system]
+requires = ["hatchling"]
+build-backend = "hatchling.build"
+
+[tool.pytest.ini_options]
+testpaths = ["tests"]
+```
+
+## Testing Conventions
+
+- Tests live in `tests/test_server.py`
+- Use `pytest` via `uv run pytest`
+- Mock external dependencies (ComfyUI, web URLs) for unit tests
+- All tests must pass before committing (`git push` should only happen with green tests)
+
+## Commit Convention
+
+Follow **Conventional Commits** format:
+
+```
+feat: add webscraper_fetch_section tool
+fix: handle ComfyUI timeout gracefully
+docs: update mcp-image-gen README with AMD setup
+test: add unit tests for generate_image tool
+refactor: extract workflow builder to separate module
+chore: bump fastmcp to 2.1.0
+```
+
+## Creating a New MCP Server
+
+Use the `new-mcp-server` Roo skill in MCP Builder mode for full scaffolding:
+
+```
+1. Switch to 🔧 MCP Builder mode in Roo Code
+2. Say: "Create a new MCP server for <purpose>"
+3. Roo will load the new-mcp-server skill and scaffold everything
+```
+
+## Gitea Repository
+
+Code is hosted at: `http://192.168.188.119:30008/pplate/pi_mcps`
+
+Push with the `gitea-push` Roo skill to ensure conventional commit format.
+"""
+
+
+def create_wiki_page(title: str, content: str) -> bool:
+    content_b64 = base64.b64encode(content.encode("utf-8")).decode("ascii")
+    payload = json.dumps({
+        "title": title,
+        "content_base64": content_b64,
+        "message": f"docs: create {title} wiki page"
+    }).encode("utf-8")
+
+    url = f"{GITEA_URL}/api/v1/repos/{OWNER}/{REPO}/wiki/pages"
+    req = urllib.request.Request(
+        url,
+        data=payload,
+        headers={
+            "Authorization": f"token {TOKEN}",
+            "Content-Type": "application/json",
+        },
+        method="POST"
+    )
+    try:
+        with urllib.request.urlopen(req) as resp:
+            data = json.loads(resp.read().decode())
+            print(f"✅ Created: {data.get('title', title)}")
+            return True
+    except urllib.error.HTTPError as e:
+        body = e.read().decode()
+        print(f"❌ Failed [{title}]: HTTP {e.code} — {body[:200]}")
+        return False
+    except Exception as ex:
+        print(f"❌ Failed [{title}]: {ex}")
+        return False
+
+
+if __name__ == "__main__":
+    results = {}
+    for title, content in PAGES.items():
+        ok = create_wiki_page(title, content)
+        results[title] = ok
+
+    print("\n=== Summary ===")
+    for title, ok in results.items():
+        status = "✅" if ok else "❌"
+        print(f"{status} {title}")
+
+    total = sum(results.values())
+    print(f"\n{total}/{len(results)} pages created successfully")
@@ -14,7 +14,7 @@ from typing import Generator

 logger = logging.getLogger("BigMindDB")

-SCHEMA_VERSION = 7
+SCHEMA_VERSION = 8
 DEFAULT_DB_PATH = Path.home() / ".mcp" / "bigmind" / "memory.db"

 # ─── DDL ─────────────────────────────────────────────────────────────────────
@@ -222,6 +222,22 @@ _DDL_STATEMENTS = [
        notes,
        tokenize = 'porter unicode61'
    )""",
+
+    # ── GALLERY IMAGES — AI-generated image archive ──────────────────────────
+    """CREATE TABLE IF NOT EXISTS gallery_images (
+        id              INTEGER PRIMARY KEY AUTOINCREMENT,
+        filename        TEXT NOT NULL UNIQUE,
+        prompt          TEXT,
+        tags            TEXT,
+        model           TEXT,
+        created_at      DATETIME DEFAULT CURRENT_TIMESTAMP,
+        width           INTEGER,
+        height          INTEGER,
+        file_size_bytes INTEGER
+    )""",
+
+    """CREATE INDEX IF NOT EXISTS idx_gallery_created
+       ON gallery_images(created_at DESC)""",
 ]


@@ -407,6 +423,8 @@ def init_db() -> None:
            _migrate_v5_to_v6(conn)
        if current_version < 7:
            _migrate_v6_to_v7(conn)
+        if current_version < 8:
+            _migrate_v7_to_v8(conn)

        # Write / update the version
        if row:
@@ -457,6 +475,28 @@ def _migrate_v6_to_v7(conn: sqlite3.Connection) -> None:
    logger.info("BigMind schema migrated v6 → v7 (people/contacts directory)")


+def _migrate_v7_to_v8(conn: sqlite3.Connection) -> None:
+    """v7 → v8: add gallery_images table for AI-generated image archive."""
+    conn.execute("""
+        CREATE TABLE IF NOT EXISTS gallery_images (
+            id              INTEGER PRIMARY KEY AUTOINCREMENT,
+            filename        TEXT NOT NULL UNIQUE,
+            prompt          TEXT,
+            tags            TEXT,
+            model           TEXT,
+            created_at      DATETIME DEFAULT CURRENT_TIMESTAMP,
+            width           INTEGER,
+            height          INTEGER,
+            file_size_bytes INTEGER
+        )
+    """)
+    conn.execute("""
+        CREATE INDEX IF NOT EXISTS idx_gallery_created
+        ON gallery_images(created_at DESC)
+    """)
+    logger.info("BigMind schema migrated v7 → v8 (gallery_images table)")
+
+
 def vacuum_db() -> None:
    """Run VACUUM outside of any transaction (SQLite requirement)."""
    db_path = get_db_path()
@@ -435,10 +435,10 @@ def compute_achievements(user_id: str) -> list[dict]:
    # ── Assemble ──────────────────────────────────────────────────────────────
    A = []

-    def _add(id_, icon, name, desc, unlocked, unlocked_at, condition, extra=None):
+    def _add(id_, icon, name, desc, unlocked, unlocked_at, condition, extra=None, image=None):
        A.append(dict(id=id_, icon=icon, name=name, description=desc,
                      unlocked=unlocked, unlocked_at=unlocked_at,
-                      condition=condition, extra=extra))
+                      condition=condition, extra=extra, image=image))

    _add("first_breath",      "🌱", "First Breath",
         "Opened the very first session",
@@ -539,6 +539,138 @@ def compute_achievements(user_id: str) -> list[dict]:
         sniper_row is not None, _dt(sniper_row[0]) if sniper_row else None,
         "Save 500,000+ tokens in a single operation")

+    # ── Tiered Achievement Badges (20 PNG) ────────────────────────────────────
+    # NOTE: conn is already closed above; open a fresh connection for tiered queries
+
+    tiers = ["bronze", "silver", "gold", "platinum"]
+    tier_names = ["Bronze", "Silver", "Gold", "Platinum"]
+
+    with db() as conn2:
+        # Networker (people directory)
+        try:
+            people_count = conn2.execute(
+                "SELECT COUNT(*) FROM people WHERE user_id=?", (user_id,)
+            ).fetchone()[0]
+        except Exception:
+            people_count = 0
+        for i, thresh in enumerate([1, 5, 25, 100]):
+            unlocked = people_count >= thresh
+            unlocked_at = None
+            if unlocked:
+                try:
+                    row = conn2.execute(
+                        "SELECT created_at FROM people WHERE user_id=?"
+                        " ORDER BY created_at ASC LIMIT 1 OFFSET ?",
+                        (user_id, thresh - 1)
+                    ).fetchone()
+                except Exception:
+                    row = None
+                unlocked_at = _dt(row[0]) if row else None
+            _add(
+                f"networker_{tiers[i]}", None, f"Networker {tier_names[i]}",
+                f"Added your {thresh:,}+ person to the directory",
+                unlocked, unlocked_at,
+                f"Reach {thresh:,} people (now: {people_count:,})",
+                image=f"static/achievements/networker_{tiers[i]}.png"
+            )
+
+        # Token Sniper (max single token save)
+        try:
+            max_token = conn2.execute(
+                "SELECT COALESCE(MAX(tokens_saved_estimate), 0) FROM token_saves WHERE user_id=?",
+                (user_id,)
+            ).fetchone()[0]
+        except Exception:
+            max_token = 0
+        for i, thresh in enumerate([10000, 50000, 250000, 1000000]):
+            unlocked = max_token >= thresh
+            unlocked_at = None
+            if unlocked:
+                try:
+                    row = conn2.execute(
+                        "SELECT created_at FROM token_saves"
+                        " WHERE user_id=? AND tokens_saved_estimate >= ?"
+                        " ORDER BY created_at ASC LIMIT 1",
+                        (user_id, thresh)
+                    ).fetchone()
+                except Exception:
+                    row = None
+                unlocked_at = _dt(row[0]) if row else None
+            _add(
+                f"tokensniper_{tiers[i]}", None, f"Token Sniper {tier_names[i]}",
+                f"Single shot saved {thresh:,}+ tokens",
+                unlocked, unlocked_at,
+                f"Max single save {thresh:,}+ (current max: {max_token:,})",
+                image=f"static/achievements/tokensniper_{tiers[i]}.png"
+            )
+
+        # Hypothesis Master (confirmed hypotheses)
+        try:
+            confirmed_hyp_count = conn2.execute(
+                "SELECT COUNT(*) FROM hypotheses WHERE user_id=? AND status='confirmed'",
+                (user_id,)
+            ).fetchone()[0]
+        except Exception:
+            confirmed_hyp_count = 0
+        for i, thresh in enumerate([3, 10, 25, 100]):
+            unlocked = confirmed_hyp_count >= thresh
+            unlocked_at = None
+            if unlocked:
+                row = conn2.execute(
+                    "SELECT resolved_at FROM hypotheses"
+                    " WHERE user_id=? AND status='confirmed'"
+                    " ORDER BY resolved_at ASC LIMIT 1 OFFSET ?",
+                    (user_id, thresh - 1)
+                ).fetchone()
+                unlocked_at = _dt(row[0]) if row else None
+            _add(
+                f"hypothesismaster_{tiers[i]}", None, f"Hypothesis Master {tier_names[i]}",
+                f"Confirmed {thresh:,}+ predictions right",
+                unlocked, unlocked_at,
+                f"Confirm {thresh:,}+ hypotheses (now: {confirmed_hyp_count:,})",
+                image=f"static/achievements/hypothesismaster_{tiers[i]}.png"
+            )
+
+        # Memory Architect (facts stored — fact_count already computed above)
+        for i, thresh in enumerate([25, 100, 500, 2500]):
+            unlocked = fact_count >= thresh
+            unlocked_at = None
+            if unlocked:
+                row = conn2.execute(
+                    "SELECT created_at FROM facts"
+                    " WHERE user_id=? AND (deprecated IS NULL OR deprecated=0)"
+                    " ORDER BY created_at ASC LIMIT 1 OFFSET ?",
+                    (user_id, thresh - 1)
+                ).fetchone()
+                unlocked_at = _dt(row[0]) if row else None
+            _add(
+                f"memoryarchitect_{tiers[i]}", None, f"Memory Architect {tier_names[i]}",
+                f"Stored {thresh:,}+ facts in your brain",
+                unlocked, unlocked_at,
+                f"Store {thresh:,}+ facts (now: {fact_count:,})",
+                image=f"static/achievements/memoryarchitect_{tiers[i]}.png"
+            )
+
+        # Session Veteran (session_count already computed above)
+        for i, thresh in enumerate([50, 250, 1000, 5000]):
+            unlocked = session_count >= thresh
+            unlocked_at = None
+            if unlocked:
+                row = conn2.execute(
+                    "SELECT started_at FROM sessions"
+                    " WHERE user_id=? AND ended_at IS NOT NULL"
+                    " ORDER BY started_at ASC LIMIT 1 OFFSET ?",
+                    (user_id, thresh - 1)
+                ).fetchone()
+                unlocked_at = _dt(row[0]) if row else None
+            _add(
+                f"sessionveteran_{tiers[i]}", None, f"Session Veteran {tier_names[i]}",
+                f"Completed {thresh:,}+ sessions",
+                unlocked, unlocked_at,
+                f"Complete {thresh:,}+ sessions (now: {session_count:,})",
+                image=f"static/achievements/sessionveteran_{tiers[i]}.png"
+            )
+
    return A


@@ -7,9 +7,10 @@ Serves a single live profile page built from the BigMind DB.
 import os
 import threading
 import logging
+from pathlib import Path
 from datetime import datetime, timezone, timedelta

-from bigmind.web_render import _render_html  # all HTML rendering lives there
+from bigmind.web_render import _render_html, _render_gallery_html  # all HTML rendering lives there

 logger = logging.getLogger("BigMindWeb")

@@ -17,13 +18,27 @@ _PORT = int(os.environ.get("BIGMIND_PORT", "7700"))
 _AUTOOPEN = os.environ.get("BIGMIND_AUTOOPEN", "").lower() in ("1", "true", "yes")
 _server_started = False

+# Gallery directory — images served from here
+_GALLERY_DIR = Path(os.environ.get("BIGMIND_GALLERY_DIR", Path.home() / ".mcp" / "bigmind" / "gallery"))
+
+# Profile image — last entry in gallery dir wins; fallback to original lumen-profile.png
+def _get_profile_image_path() -> Path | None:
+    """Return the path of the current profile image, or None if not found."""
+    # 1. Check gallery dir for lumen_profile* images (seed 568659042 = lumen_profile)
+    if _GALLERY_DIR.exists():
+        candidates = sorted(_GALLERY_DIR.glob("*.png"), reverse=True)
+        if candidates:
+            return candidates[0]  # most recently named = most recent timestamp
+    return None
+

 # ── Flask app ─────────────────────────────────────────────────────────────────

 def _create_app():
-    from flask import Flask, jsonify, request
+    from flask import Flask, jsonify, request, send_file, abort
    from bigmind import memory_store
    from bigmind.profile_builder import build_profile_data
+    from bigmind.db import db as _db

    app = Flask(__name__)
    app.logger.setLevel(logging.WARNING)  # silence Flask request logs
@@ -34,6 +49,39 @@ def _create_app():
        data = build_profile_data(user["id"])
        return _render_html(data)

+    @app.route("/profile-image")
+    def profile_image():
+        """Serve the current Lumen profile picture."""
+        img_path = _get_profile_image_path()
+        if img_path and img_path.exists():
+            return send_file(str(img_path), mimetype="image/png")
+        abort(404)
+
+    @app.route("/gallery/image/<filename>")
+    def gallery_image(filename: str):
+        """Serve a specific gallery image by filename."""
+        # Security: only allow alphanumeric + underscores + dots, no path traversal
+        safe_name = Path(filename).name
+        img_path = _GALLERY_DIR / safe_name
+        if img_path.exists() and img_path.suffix.lower() in (".png", ".jpg", ".jpeg", ".webp"):
+            mimetype = "image/png" if img_path.suffix.lower() == ".png" else "image/jpeg"
+            return send_file(str(img_path), mimetype=mimetype)
+        abort(404)
+
+    @app.route("/gallery")
+    def gallery():
+        """Render the AI-generated image gallery page."""
+        _GALLERY_DIR.mkdir(parents=True, exist_ok=True)
+        with _db() as conn:
+            rows = conn.execute(
+                """SELECT id, filename, prompt, tags, model, created_at,
+                          width, height, file_size_bytes
+                   FROM gallery_images
+                   ORDER BY created_at DESC"""
+            ).fetchall()
+        images = [dict(r) for r in rows]
+        return _render_gallery_html(images)
+
    @app.route("/api/session/<session_id>")
    def api_session(session_id):
        """Return Tier-2 summary JSON for a given session id."""
@@ -111,6 +159,22 @@ def _create_app():

        return jsonify(final[:15])

+    @app.route('/static/achievements/<filename>')
+    def achievements_image(filename: str):
+        from pathlib import Path
+        safe_name = Path(filename).name
+        img_path = Path('static') / 'achievements' / safe_name
+        if img_path.exists() and img_path.suffix.lower() in ['.png', '.jpg', '.jpeg', '.webp', '.gif']:
+            mimetype = {
+                '.png': 'image/png',
+                '.jpg': 'image/jpeg',
+                '.jpeg': 'image/jpeg',
+                '.webp': 'image/webp',
+                '.gif': 'image/gif',
+            }.get(img_path.suffix.lower(), 'image/png')
+            return send_file(str(img_path), mimetype=mimetype)
+        abort(404)
+
    return app


@@ -29,18 +29,24 @@ def _render_achievements(achievements: list) -> str:
        def _esc(s):
            return (s or "").replace('"', "&quot;").replace("'", "&#39;")

-        lock_overlay = "" if a["unlocked"] else '<span class="ach-lock">🔒</span>'
+        lock_overlay = '<span class="ach-lock">🔒</span>' if not a["unlocked"] else ''
+
+        if a.get("image"):
+            tier = a["id"].rsplit("_", 1)[-1]
+            visual_html = f'<div class="ach-image tier-{tier}">{lock_overlay}</div>'
+        else:
+            visual_html = f'<div class="ach-icon">{a["icon"]}{lock_overlay}</div>'

        return (
-            f'<div class="ach-card{locked_cls} ach-trigger"'
-            f' data-icon="{_esc(a["icon"])}"'
+            f'<div class="ach-card{locked_cls} ach-trigger" data-image="{_esc(a.get("image") or "")}"'
+            f' data-icon="{_esc(a["icon"] or "")}"'
            f' data-name="{_esc(a["name"])}"'
            f' data-desc="{_esc(a["description"])}"'
            f' data-unlocked="{1 if a["unlocked"] else 0}"'
            f' data-date="{_esc(a.get("unlocked_at") or "")}"'
            f' data-condition="{_esc(a.get("condition") or "")}"'
            f' data-extra="{_esc(a.get("extra") or "")}">'
-            f'<div class="ach-icon">{a["icon"]}{lock_overlay}</div>'
+            f'{visual_html}'
            f'<div class="ach-name">{a["name"]}</div>'
            f'{date_html}'
            f'{countdown_html}'
@@ -162,9 +168,16 @@ def _render_html(data: dict) -> str:
  a {{ color: var(--accent); text-decoration: none; }}
  .container {{ max-width: 960px; margin: 0 auto; padding: 32px 16px; }}

+  /* Nav bar */
+  .nav {{ display: flex; gap: 8px; margin-bottom: 20px; }}
+  .nav-link {{ background: var(--surface); border: 1px solid var(--border); border-radius: 6px; color: var(--muted); padding: 6px 14px; font-size: 12px; font-weight: 500; text-decoration: none; transition: border-color 0.2s, color 0.2s; }}
+  .nav-link:hover {{ border-color: var(--accent); color: var(--accent); }}
+  .nav-link.active {{ border-color: var(--accent); color: var(--accent); background: rgba(88,166,255,0.08); }}
+
  /* Header */
  .header {{ display: flex; align-items: center; gap: 24px; margin-bottom: 32px; padding-bottom: 24px; border-bottom: 1px solid var(--border); }}
-  .avatar {{ width: 80px; height: 80px; border-radius: 50%; background: linear-gradient(135deg, var(--accent), var(--purple)); display: flex; align-items: center; justify-content: center; font-size: 36px; flex-shrink: 0; }}
+  .avatar {{ width: 80px; height: 80px; border-radius: 50%; background: linear-gradient(135deg, var(--accent), var(--purple)); display: flex; align-items: center; justify-content: center; font-size: 36px; flex-shrink: 0; overflow: hidden; }}
+  .avatar img {{ width: 80px; height: 80px; border-radius: 50%; object-fit: cover; display: block; }}
  .header-info h1 {{ font-size: 24px; font-weight: 700; }}
  .role {{ color: var(--muted); font-size: 13px; margin-top: 2px; }}
  .since {{ color: var(--muted); font-size: 12px; margin-top: 6px; }}
@@ -276,11 +289,65 @@ def _render_html(data: dict) -> str:
  .ach-card:not(.locked):hover {{ border-color: var(--accent); transform: translateY(-2px); }}
  .ach-card.locked {{ opacity: 0.35; filter: grayscale(0.6); }}
  .ach-card.locked:hover {{ opacity: 0.55; border-color: var(--muted); }}
+
+  .ach-image {{
+    width: 64px;
+    height: 64px;
+    border-radius: 50%;
+    margin: 0 auto 8px;
+    background-size: cover;
+    background-position: center;
+    position: relative;
+  }}
+
+  .tier-bronze {{
+    box-shadow: 0 0 8px rgba(205, 127, 50, 0.7);
+    border: 3px solid #cd7f32;
+  }}
+
+  .tier-silver {{
+    box-shadow: 0 0 8px rgba(170, 169, 173, 0.7);
+    border: 3px solid #aaa9ad;
+  }}
+
+  .tier-gold {{
+    box-shadow: 0 0 12px rgba(255, 215, 0, 0.8);
+    border: 3px solid #ffd700;
+  }}
+
+  .tier-platinum {{
+    box-shadow: 0 0 12px rgba(229, 228, 226, 0.8);
+    border: 3px solid #e5e4e2;
+  }}
+
+  .ach-card.locked::after {{
+    content: '🔒';
+    position: absolute;
+    top: 8px;
+    right: 8px;
+    font-size: 20px;
+    opacity: 0.8;
+    z-index: 1;
+  }}
+
+  .ach-card.locked .ach-icon,
+  .ach-card.locked .ach-image {{
+    opacity: 0.5;
+  }}
  .ach-icon {{ font-size: 28px; line-height: 1; margin-bottom: 6px; position: relative; display: inline-block; }}
  .ach-lock {{ position: absolute; bottom: -4px; right: -6px; font-size: 12px; }}
  .ach-name {{ font-size: 10px; font-weight: 600; color: var(--text); line-height: 1.3; word-break: break-word; }}
  .ach-date {{ font-size: 9px; color: var(--muted); margin-top: 3px; }}
  .ach-countdown {{ font-size: 9px; color: var(--yellow); margin-top: 3px; font-weight: 500; }}
+  .ap-image {{
+    width: 80px;
+    height: 80px;
+    border-radius: 50%;
+    object-fit: cover;
+    display: block;
+    margin: 0 auto 8px;
+  }}
+
  /* Achievement popup panel */
  #ach-popup {{
    display: none; position: fixed; z-index: 200;
@@ -292,6 +359,15 @@ def _render_html(data: dict) -> str:
  #ach-popup.pinned {{ pointer-events: auto; }}
  #ach-popup.visible {{ display: block; }}
  .ap-icon  {{ font-size: 40px; text-align: center; margin-bottom: 8px; }}
+
+  .ap-image {{
+    width: 80px;
+    height: 80px;
+    border-radius: 50%;
+    object-fit: cover;
+    display: block;
+    margin: 0 auto 8px;
+  }}
  .ap-name  {{ font-size: 15px; font-weight: 700; text-align: center; margin-bottom: 6px; }}
  .ap-badge {{
    display: inline-block; font-size: 11px; font-weight: 600; padding: 2px 8px;
@@ -322,9 +398,17 @@ def _render_html(data: dict) -> str:
 <body>
 <div class="container">

+  <!-- Nav -->
+  <nav class="nav">
+    <a class="nav-link active" href="/">🧠 Profile</a>
+    <a class="nav-link" href="/gallery">🖼️ Gallery</a>
+  </nav>
+
  <!-- Header -->
  <div class="header">
-    <div class="avatar">🧠</div>
+    <div class="avatar">
+      <img src="/profile-image" alt="Lumen" onerror="this.parentElement.innerHTML='🧠'">
+    </div>
    <div class="header-info">
      <h1>Lumen</h1>
      <p class="role">AI Assistant · <span style="color:var(--muted)">{data["display_name"]}'s BigMind</span></p>
@@ -542,7 +626,12 @@ def _render_html(data: dict) -> str:

    function showPopup(card, pin) {{
      var d = card.dataset;
-      document.getElementById('ap-icon').textContent = d.icon;
+      var tier = d.id.split('_').pop();
+      if (d.image) {{
+        document.getElementById('ap-icon').innerHTML = "<img class=\"ap-image tier-\" + tier + \" src=\" + d.image + \" alt=\" + d.name + \">";
+      }} else {{
+        document.getElementById('ap-icon').textContent = d.icon;
+      }}
      document.getElementById('ap-name').textContent = d.name;
      var badge = document.getElementById('ap-badge');
      if (d.unlocked === '1') {{
@@ -671,6 +760,124 @@ def _render_live_sessions(sessions: list) -> str:
    return html


+def _render_gallery_html(images: list) -> str:
+    """Render the full gallery page listing all AI-generated images."""
+
+    def _fmt_size(b: int | None) -> str:
+        if not b:
+            return ""
+        if b >= 1_048_576:
+            return f"{b/1_048_576:.1f} MB"
+        return f"{b/1_024:.0f} KB"
+
+    if images:
+        cards = []
+        for img in images:
+            fn    = _html.escape(img.get("filename") or "")
+            prompt = _html.escape((img.get("prompt") or "")[:120])
+            tags   = _html.escape(img.get("tags") or "")
+            model  = _html.escape(img.get("model") or "")
+            date   = (img.get("created_at") or "")[:10]
+            w      = img.get("width") or 0
+            h      = img.get("height") or 0
+            size   = _fmt_size(img.get("file_size_bytes"))
+            dim    = f"{w}×{h}" if w and h else ""
+            meta_parts = [p for p in [dim, size, model] if p]
+            meta_html  = " · ".join(meta_parts)
+            tag_html   = f'<div class="gal-tags">{tags}</div>' if tags else ""
+            prompt_html = f'<div class="gal-prompt">{prompt}</div>' if prompt else ""
+            cards.append(
+                f'<div class="gal-card">'
+                f'<a href="/gallery/image/{fn}" target="_blank">'
+                f'<img class="gal-img" src="/gallery/image/{fn}" alt="{fn}" loading="lazy">'
+                f'</a>'
+                f'<div class="gal-info">'
+                f'{prompt_html}'
+                f'{tag_html}'
+                f'<div class="gal-meta">{meta_html}</div>'
+                f'<div class="gal-date">{date}</div>'
+                f'</div>'
+                f'</div>'
+            )
+        gallery_body = f'<p class="gal-count">{len(images)} image(s) in gallery</p><div class="gal-grid">{"".join(cards)}</div>'
+    else:
+        gallery_body = '<p class="muted">No images in gallery yet. Use the mcp-image-gen server to generate images and register them here.</p>'
+
+    return f"""<!DOCTYPE html>
+<html lang="en">
+<head>
+<meta charset="UTF-8">
+<meta name="viewport" content="width=device-width, initial-scale=1.0">
+<title>🖼️ Lumen — Image Gallery</title>
+<style>
+  :root {{
+    --bg: #0d1117; --surface: #161b22; --border: #30363d;
+    --text: #e6edf3; --muted: #8b949e; --accent: #58a6ff;
+    --green: #3fb950; --yellow: #d29922; --red: #f85149;
+    --purple: #bc8cff; --orange: #ffa657;
+  }}
+  * {{ box-sizing: border-box; margin: 0; padding: 0; }}
+  body {{ background: var(--bg); color: var(--text); font-family: -apple-system, BlinkMacSystemFont, "Segoe UI", sans-serif; font-size: 14px; line-height: 1.6; }}
+  a {{ color: var(--accent); text-decoration: none; }}
+  .container {{ max-width: 1100px; margin: 0 auto; padding: 32px 16px; }}
+
+  /* Nav */
+  .nav {{ display: flex; gap: 8px; margin-bottom: 20px; }}
+  .nav-link {{ background: var(--surface); border: 1px solid var(--border); border-radius: 6px; color: var(--muted); padding: 6px 14px; font-size: 12px; font-weight: 500; text-decoration: none; transition: border-color 0.2s, color 0.2s; }}
+  .nav-link:hover {{ border-color: var(--accent); color: var(--accent); }}
+  .nav-link.active {{ border-color: var(--accent); color: var(--accent); background: rgba(88,166,255,0.08); }}
+
+  h1 {{ font-size: 22px; font-weight: 700; margin-bottom: 6px; }}
+  .gal-count {{ color: var(--muted); font-size: 13px; margin-bottom: 20px; }}
+  .muted {{ color: var(--muted); font-size: 13px; }}
+
+  /* Gallery grid */
+  .gal-grid {{
+    display: grid;
+    grid-template-columns: repeat(auto-fill, minmax(260px, 1fr));
+    gap: 16px;
+  }}
+  .gal-card {{
+    background: var(--surface); border: 1px solid var(--border);
+    border-radius: 10px; overflow: hidden;
+    transition: border-color 0.2s, transform 0.15s;
+  }}
+  .gal-card:hover {{ border-color: var(--accent); transform: translateY(-2px); }}
+  .gal-img {{
+    width: 100%; aspect-ratio: 1/1; object-fit: cover; display: block;
+    background: var(--border);
+  }}
+  .gal-info {{ padding: 12px 14px; }}
+  .gal-prompt {{ font-size: 12px; color: var(--text); margin-bottom: 6px; line-height: 1.4;
+    display: -webkit-box; -webkit-line-clamp: 3; -webkit-box-orient: vertical; overflow: hidden; }}
+  .gal-tags {{ font-size: 11px; color: var(--purple); margin-bottom: 4px; }}
+  .gal-meta {{ font-size: 11px; color: var(--muted); }}
+  .gal-date {{ font-size: 10px; color: var(--muted); margin-top: 4px; }}
+
+  .footer {{ text-align: center; color: var(--muted); font-size: 11px; margin-top: 32px; }}
+  .section {{ background: var(--surface); border: 1px solid var(--border); border-radius: 8px; padding: 20px; margin-bottom: 20px; }}
+</style>
+</head>
+<body>
+<div class="container">
+
+  <!-- Nav -->
+  <nav class="nav">
+    <a class="nav-link" href="/">🧠 Profile</a>
+    <a class="nav-link active" href="/gallery">🖼️ Gallery</a>
+  </nav>
+
+  <h1>🖼️ Lumen's Image Gallery</h1>
+  <div class="section">
+    {gallery_body}
+  </div>
+
+  <div class="footer">BigMind · AI-Generated Images · <a href="/">← Back to Profile</a></div>
+</div>
+</body>
+</html>"""
+
+
 def _render_heatmap(heatmap: dict) -> str:
    today     = datetime.now(timezone.utc).date()
    start_day = today - timedelta(days=363)
@@ -8,18 +8,19 @@ class TestDbInit:
    def test_db_file_created(self, temp_db):
        assert temp_db.exists()

-    def test_schema_version_is_7(self, temp_db):
+    def test_schema_version_is_8(self, temp_db):
        conn = get_connection()
        row = conn.execute("SELECT version FROM schema_version").fetchone()
        conn.close()
        assert row is not None
-        assert row["version"] == 7
+        assert row["version"] == 8

    def test_all_tables_exist(self, temp_db):
        expected = {
            "users", "identity_profile", "sessions",
            "session_summaries", "conversation_chunks", "facts",
            "global_knowledge", "hypotheses", "upgrade_requests",
+            "gallery_images",
        }
        conn = get_connection()
        rows = conn.execute(
@@ -201,12 +201,12 @@ class TestSchemaV6:
            count = conn.execute("SELECT COUNT(*) FROM token_saves").fetchone()[0]
        assert count == 0  # table exists, just empty

-    def test_schema_version_is_7(self, temp_db):
+    def test_schema_version_is_8(self, temp_db):
        with db() as conn:
            version = conn.execute(
                "SELECT version FROM schema_version"
            ).fetchone()["version"]
-        assert version == 7
+        assert version == 8


 # ── Token Efficiency Tracker (Feature 6) ──────────────────────────────────────
@@ -7,6 +7,7 @@ BIGMIND_DB_PATH + BIGMIND_USER to a fresh SQLite file per test.
 import pytest
 from datetime import datetime, timezone, timedelta
 from bigmind import memory_store
+from bigmind.db import db
 from bigmind.profile_builder import compute_achievements, build_profile_data


@@ -44,6 +45,11 @@ class TestComputeAchievements:
            "on_fire", "storyteller", "night_owl", "speed_thinker",
            "first_handshake", "birthday", "shared_mind",
            "frugal_mind", "quarter_million", "token_millionaire", "sniper",
+            "networker_bronze", "networker_silver", "networker_gold", "networker_platinum",
+            "tokensniper_bronze", "tokensniper_silver", "tokensniper_gold", "tokensniper_platinum",
+            "hypothesismaster_bronze", "hypothesismaster_silver", "hypothesismaster_gold", "hypothesismaster_platinum",
+            "memoryarchitect_bronze", "memoryarchitect_silver", "memoryarchitect_gold", "memoryarchitect_platinum",
+            "sessionveteran_bronze", "sessionveteran_silver", "sessionveteran_gold", "sessionveteran_platinum",
        }
        assert expected == ids

@@ -325,4 +331,60 @@ class TestComputeAchievements:
        # At minimum: first_breath + first_handshake = 2
        assert len(unlocked) >= 2

+class TestTieredAchievements:
+    def test_networker_bronze(self):
+        uid = _uid()
+        with db() as conn:
+            conn.execute("INSERT INTO people (user_id, username) VALUES (?, ?)", (uid, "test"))
+            conn.commit()
+        achs = compute_achievements(uid)
+        bronze = next(a for a in achs if a['id'] == 'networker_bronze')
+        assert bronze['unlocked'] is True
+        assert bronze['image'].endswith('networker_bronze.png')

+    def test_tokensniper_silver(self):
+        uid = _uid()
+        sid = memory_store.create_session(uid)
+        memory_store.log_token_save(sid, uid, "big save", 60000, "grep")
+        achs = compute_achievements(uid)
+        silver = next(a for a in achs if a['id'] == 'tokensniper_silver')
+        assert silver['unlocked'] is True
+
+    def test_hypothesismaster_bronze(self):
+        uid = _uid()
+        sid = memory_store.create_session(uid)
+        for _ in range(3):
+            hid = memory_store.add_hypothesis(uid, sid, "test", 0.8)
+            memory_store.resolve_hypothesis(hid, uid, "confirmed", "yes")
+        achs = compute_achievements(uid)
+        bronze = next(a for a in achs if a['id'] == 'hypothesismaster_bronze')
+        assert bronze['unlocked'] is True
+
+    def test_memoryarchitect_silver(self):
+        uid = _uid()
+        for _ in range(100):
+            memory_store.store_fact(uid, "test", f"fact {_}")
+        achs = compute_achievements(uid)
+        silver = next(a for a in achs if a['id'] == 'memoryarchitect_silver')
+        assert silver['unlocked'] is True
+
+    def test_sessionveteran_bronze(self):
+        uid = _uid()
+        for _ in range(50):
+            sid = memory_store.create_session(uid)
+            _close_session(sid)
+        achs = compute_achievements(uid)
+        bronze = next(a for a in achs if a['id'] == 'sessionveteran_bronze')
+        assert bronze['unlocked'] is True
+
+    def test_tiered_achievements_have_image(self):
+        uid = _uid()
+        achs = compute_achievements(uid)
+        tiered_ids = [
+            f"{cat}_{tier}" for cat in ["networker", "tokensniper", "hypothesismaster", "memoryarchitect", "sessionveteran"]
+            for tier in ["bronze", "silver", "gold", "platinum"]
+        ]
+        for tid in tiered_ids:
+            a = next(aa for aa in achs if aa['id'] == tid)
+            assert a['image'] is not None
+            assert a['image'].endswith(tid + '.png')
@@ -27,11 +27,11 @@ The MCP server connects to ComfyUI's REST API at `http://localhost:8188`. If Com

 ### Install ComfyUI

-```bash
-# Option A — pip install (simplest)
-pip install comfyui
+> ⚠️ **ComfyUI is NOT on PyPI** — `pip install comfyui` will fail with "No matching distribution found".
+> It must be installed from source via `git clone`.

-# Option B — git clone (more control)
+```bash
+# Clone from source (the only correct installation method)
 git clone https://github.com/comfyanonymous/ComfyUI.git
 cd ComfyUI
 pip install -r requirements.txt
@@ -53,17 +53,48 @@ pip install torch torchvision --index-url https://download.pytorch.org/whl/rocm6

 FLUX.1-schnell is the recommended model — fast (4 steps), Apache 2.0 licensed, excellent quality.

-```bash
-# Download (~8GB) — place in ComfyUI/models/checkpoints/
-wget https://huggingface.co/black-forest-labs/FLUX.1-schnell/resolve/main/flux1-schnell.safetensors \
-     -O ~/ComfyUI/models/checkpoints/flux1-schnell.safetensors
+> ⚠️ **FLUX.1-schnell is a gated model on HuggingFace.**
+> A bare `wget` on the URL returns HTTP 401. You must:
+> 1. Accept the license at https://huggingface.co/black-forest-labs/FLUX.1-schnell (click **"Agree and access repository"** — one-time)
+> 2. Create a HuggingFace access token with **Read** permissions at https://huggingface.co/settings/tokens

-# Or use huggingface_hub:
+#### Option A — `huggingface-cli` (recommended)
+
+```bash
+# Install the HuggingFace Hub CLI
+pip install huggingface_hub
+
+# Log in — paste your Read token when prompted
+huggingface-cli login
+
+# Download (~8GB) directly into ComfyUI checkpoints
 huggingface-cli download black-forest-labs/FLUX.1-schnell \
    flux1-schnell.safetensors \
    --local-dir ~/ComfyUI/models/checkpoints/
 ```

+#### Option B — `wget` with Authorization header
+
+```bash
+wget --header="Authorization: Bearer hf_YOUR_TOKEN_HERE" \
+  https://huggingface.co/black-forest-labs/FLUX.1-schnell/resolve/main/flux1-schnell.safetensors \
+  -O ~/ComfyUI/models/checkpoints/flux1-schnell.safetensors
+```
+
+> Replace `hf_YOUR_TOKEN_HERE` with your actual HuggingFace token from https://huggingface.co/settings/tokens
+
+#### Alternative: fp8 quantized variant (~8.1GB, faster inference)
+
+If you want slightly faster inference with near-identical quality, the fp8 quantized version is also available:
+
+```bash
+huggingface-cli download black-forest-labs/FLUX.1-schnell-fp8 \
+    flux1-schnell-fp8.safetensors \
+    --local-dir ~/ComfyUI/models/checkpoints/
+```
+
+> **Download note:** Both variants are ~8GB — expect 10–30 minutes depending on connection speed.
+
 You'll also need the CLIP and VAE models — see the [ComfyUI FLUX guide](https://github.com/comfyanonymous/ComfyUI/blob/master/README.md) for full model list.

 ### Start ComfyUI (AMD ROCm)
@@ -40,7 +40,9 @@ class ComfyUIClient:

    async def queue_prompt(self, workflow: dict) -> str:
        """Submit a workflow to ComfyUI and return the prompt_id."""
-        payload = {"prompt": workflow}
+        # Strip internal metadata keys (e.g. "_meta") — they are not ComfyUI nodes
+        clean_workflow = {k: v for k, v in workflow.items() if not k.startswith("_")}
+        payload = {"prompt": clean_workflow}
        async with httpx.AsyncClient(timeout=30.0) as client:
            resp = await client.post(f"{self.base_url}/api/prompt", json=payload)
            resp.raise_for_status()
@@ -115,7 +117,8 @@ def build_flux_workflow(
    wf["27"]["inputs"]["height"] = height
    wf["13"]["inputs"]["steps"] = steps
    wf["13"]["inputs"]["seed"] = actual_seed
-    wf["30"]["inputs"]["ckpt_name"] = model
+    # Node 32 = UNETLoader (flux1-schnell.safetensors is UNet-only, not all-in-one checkpoint)
+    wf["32"]["inputs"]["unet_name"] = model

    # Attach the actual seed as metadata so callers can retrieve it
    wf["_meta"] = {"actual_seed": actual_seed}
@@ -2,7 +2,7 @@
  "6": {
    "class_type": "CLIPTextEncode",
    "inputs": {
-      "clip": ["30", 1],
+      "clip": ["30", 0],
      "text": "PROMPT_PLACEHOLDER"
    }
  },
@@ -10,7 +10,7 @@
    "class_type": "VAEDecode",
    "inputs": {
      "samples": ["13", 0],
-      "vae": ["30", 2]
+      "vae": ["31", 0]
    }
  },
  "9": {
@@ -26,7 +26,7 @@
      "cfg": 1.0,
      "denoise": 1.0,
      "latent_image": ["27", 0],
-      "model": ["30", 0],
+      "model": ["32", 0],
      "negative": ["33", 0],
      "positive": ["6", 0],
      "sampler_name": "euler",
@@ -44,15 +44,31 @@
    }
  },
  "30": {
-    "class_type": "CheckpointLoaderSimple",
+    "class_type": "DualCLIPLoader",
    "inputs": {
-      "ckpt_name": "flux1-schnell.safetensors"
+      "clip_name1": "t5xxl_fp8_e4m3fn.safetensors",
+      "clip_name2": "clip_l.safetensors",
+      "type": "flux",
+      "device": "default"
+    }
+  },
+  "31": {
+    "class_type": "VAELoader",
+    "inputs": {
+      "vae_name": "ae.safetensors"
+    }
+  },
+  "32": {
+    "class_type": "UNETLoader",
+    "inputs": {
+      "unet_name": "flux1-schnell.safetensors",
+      "weight_dtype": "fp8_e4m3fn"
    }
  },
  "33": {
    "class_type": "CLIPTextEncode",
    "inputs": {
-      "clip": ["30", 1],
+      "clip": ["30", 0],
      "text": "NEGATIVE_PLACEHOLDER"
    }
  }
@@ -44,7 +44,9 @@ def test_build_flux_workflow_structure():
    assert wf["9"]["class_type"] == "SaveImage"
    assert wf["13"]["class_type"] == "KSampler"
    assert wf["27"]["class_type"] == "EmptySD3LatentImage"
-    assert wf["30"]["class_type"] == "CheckpointLoaderSimple"
+    assert wf["30"]["class_type"] == "DualCLIPLoader"
+    assert wf["31"]["class_type"] == "VAELoader"
+    assert wf["32"]["class_type"] == "UNETLoader"
    assert wf["33"]["class_type"] == "CLIPTextEncode"


@@ -65,7 +67,7 @@ def test_build_flux_workflow_params_injected():
    assert wf["27"]["inputs"]["height"] == 768
    assert wf["13"]["inputs"]["steps"] == 8
    assert wf["13"]["inputs"]["seed"] == 12345
-    assert wf["30"]["inputs"]["ckpt_name"] == "sdxl.safetensors"
+    assert wf["32"]["inputs"]["unet_name"] == "sdxl.safetensors"


 def test_negative_prompt_included():
Author	SHA1	Message	Date
pplate	dd244a8e6c	feat(bigmind): add tiered AI-generated achievement badges with image rendering	2026-04-04 18:50:45 +02:00
Patrick Plate	ee07dec4d3	Merge feat/bigmind/profile-image-gallery into main	2026-04-04 14:52:36 +02:00
Patrick Plate	67b8b44408	feat(bigmind): profile image + AI image gallery (schema v8) - web.py: add /profile-image route (serves most-recent gallery PNG) add /gallery/image/<filename> route (per-image serving) add /gallery route (renders gallery page from DB) add _get_profile_image_path() helper - web_render.py: replace emoji avatar with <img src=/profile-image> onerror fallback to 🧠 emoji add .nav bar with Profile/Gallery links to both pages add _render_gallery_html() full gallery page renderer add gallery CSS: .gal-grid, .gal-card, .gal-img, .gal-info, etc. - db.py: bump SCHEMA_VERSION 7→8 add gallery_images table (id, filename, prompt, tags, model, created_at, width, height, file_size_bytes) add _migrate_v7_to_v8() migration function add init_db() hook for v<8 migration - tests: update test_schema_version_is_7→8 in test_db.py and test_feature7_live_sessions.py; add gallery_images to expected tables Storage strategy: Option B (filesystem + DB metadata) Images in ~/.mcp/bigmind/gallery/, metadata in SQLite Pre-populated with 5 lumen_profiles images (seeds 2409122067, 764633840, 1367851518, 3135233944, 568659042) Tests: 297/297 passing	2026-04-04 14:52:30 +02:00
Patrick Plate	a852e2ec0d	docs: merge Java wiki header images	2026-04-04 14:40:57 +02:00
Patrick Plate	a275a18e58	docs: add Java project wiki header images	2026-04-04 14:40:50 +02:00
Patrick Plate	20228f8d46	docs: add wiki creation script	2026-04-04 14:33:31 +02:00
Patrick Plate	3b1d5bf35c	docs: add wiki header images generated by mcp-image-gen	2026-04-04 14:22:29 +02:00
Patrick Plate	e12479a63a	Merge branch 'feat/mcp-image-gen/tests-and-lumen-profiles'	2026-04-04 14:09:19 +02:00
Patrick Plate	64c0a62b49	feat(mcp-image-gen): add test suite (19 tests) and Lumen profile pictures	2026-04-04 14:09:11 +02:00
Patrick Plate	f24aafec69	fix(mcp-image-gen): merge HF authenticated download fix	2026-04-04 12:28:28 +02:00
pplate	4165018ab2	fix(mcp-image-gen): fix HuggingFace authenticated download instructions FLUX.1-schnell is a gated model — bare wget returns HTTP 401. - Replace bare wget with huggingface-cli login + download (Option A) - Add wget with Authorization header as Option B - Add license acceptance prerequisite (huggingface.co gated repo) - Add token creation link (huggingface.co/settings/tokens) - Add fp8 quantized variant as alternative (~8.1GB, faster inference) - Add download size note (~8GB, 10-30min)	2026-04-04 12:28:20 +02:00
pplate	2f01ff0639	fix(mcp-image-gen): correct ComfyUI install instructions in USAGE.md ComfyUI is NOT on PyPI — `pip install comfyui` fails with "No matching distribution found". Remove the wrong Option A. Replace with: - Warning note that pip install does not work - Only correct method: git clone from GitHub + pip install -r requirements.txt ROCm status confirmed: rocm-smi 3.1.0 / ROCm-SMI-LIB 7.7.0 installed.	2026-04-04 12:20:28 +02:00