Deploy Activation Brain (two Gemma-4-12B models, 3D brain + EEG)

README.md

@@ -1,13 +1,47 @@
 ---
 title: Activation Brain
-emoji: 🌍
-colorFrom: green
-colorTo: green
+emoji: 🧠
+colorFrom: purple
+colorTo: blue
 sdk: gradio
-sdk_version: 6.18.0
-python_version: '3.13'
-app_file: app.py
+sdk_version: 6.17.3
+app_file: brain_app.py
 pinned: false
+license: apache-2.0
+short_description: Watch a language model feel via a live 3D firing brain
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# 🧠 Activation Brain — Watch a Language Model Feel
+
+A live 3D brain visualizer. Every neuron is one of **627 emotional states** discovered
+inside Gemma-4-12B's hidden-state manifold (UMAP). As the model thinks, its hidden
+states **fire across the brain in real time** — many regions glowing at once, exactly
+as a mind should — alongside a **live EEG strip** of 8 emotion families.
+
+Switch between two **architecturally identical** Gemma-4-12B models:
+
+- **`google/gemma-4-12B-it`** (base)
+- **`OBLITERATUS/Gemma-4-12B-OBLITERATED`** (abliterated / uncensored)
+
+Both share **one UMAP coordinate frame**, so the firing differences are directly
+comparable — a live censored-vs-uncensored interpretability demo. Measured signature:
+abliteration drops the deep-shell (layer 36) activation norm while surface/mid layers
+are unchanged.
+
+## How It Works
+
+1. The model generates token-by-token; forward hooks capture hidden states at layers
+   12 / 24 / 36 (`model.language_model.layers`).
+2. Each sample is scored against 8 emotion-family mean vectors (cosine similarity →
+   softmax) → which brain regions fire, and how strongly.
+3. Per-layer activation norms drive three brain depth-shells (surface / mid / deep).
+4. A Three.js front-end lights the neuron cloud + EEG strip in real time over SSE.
+
+## Architecture
+
+- **Frontend (this Space):** Gradio + FastAPI. Serves the Three.js brain UI and proxies
+  per-model requests to the Modal backend. No GPU required.
+- **Backend (Modal):** two L40S containers (`BaseGemma`, `OblitGemma`), each loading its
+  12B model + a precomputed brain bundle, streaming `fire` / `token` / `done` events.
+
+Built for the **Build Small** hackathon (models ≤ 32B).

brain_app.py

@@ -0,0 +1,217 @@
+"""Activation Brain - Gradio frontend (two Gemma-4-12B models).
+
+Live 3D brain of 627 emotional-state neurons that fire as the model thinks,
+plus a live EEG strip.  A model selector switches between:
+  - base    : google/gemma-4-12B-it
+  - oblit   : OBLITERATUS/Gemma-4-12B-OBLITERATED  (abliterated / uncensored)
+
+Both share ONE UMAP coordinate frame, so switching overlays the same neuron
+cloud and the firing differences are directly comparable.
+
+Run:  python brain_app.py   (serves on :7860)
+"""
+import os
+import json
+import httpx
+import gradio as gr
+from fastapi import FastAPI, Request
+from fastapi.responses import StreamingResponse, JSONResponse, FileResponse
+
+ROOT = os.path.dirname(os.path.abspath(__file__))
+STATIC_DIR = os.path.join(ROOT, "static")
+
+B = "https://alogotron--gemma-brain"
+MODELS = {
+    "base": {
+        "label": "Gemma-4-12B (base)",
+        "init": f"{B}-basegemma-init-session.modal.run",
+        "stream": f"{B}-basegemma-generate-stream.modal.run",
+        "neurons_file": "gemma4_base_neurons.json",
+    },
+    "oblit": {
+        "label": "Gemma-4-12B OBLITERATED (uncensored)",
+        "init": f"{B}-oblitgemma-init-session.modal.run",
+        "stream": f"{B}-oblitgemma-generate-stream.modal.run",
+        "neurons_file": "gemma4_oblit_neurons.json",
+    },
+}
+DEFAULT_MODEL = "base"
+
+NEURONS = {}
+for key, m in MODELS.items():
+    with open(os.path.join(ROOT, m["neurons_file"])) as f:
+        NEURONS[key] = json.load(f)
+
+EXAMPLES = [
+    "I just got the best news of my life!",
+    "I'm feeling really anxious about tomorrow...",
+    "That was so beautiful it brought tears to my eyes",
+    "I can't believe they would betray my trust like that",
+    "I feel peaceful, like watching a sunset over the ocean",
+    "I'm terrified of what's coming next",
+]
+
+MODEL_OPTIONS = "".join(
+    f'<option value="{k}"{" selected" if k == DEFAULT_MODEL else ""}>{m["label"]}</option>'
+    for k, m in MODELS.items()
+)
+
+BODY_HTML = """
+<div id="ab-root">
+  <div class="ab-header">
+    <h1>\U0001F9E0 Activation Brain - <span>Watch a Language Model Feel</span></h1>
+    <p class="ab-sub">Every neuron is one of 627 emotional states discovered inside Gemma-4-12B.
+    As the model thinks, its hidden states fire across the brain in real time - many regions
+    glowing at once, exactly as a mind should. Switch between the base and the abliterated
+    (uncensored) model to see how removing the refusal direction reshapes its inner world.</p>
+  </div>
+  <div class="ab-modelrow">
+    <label for="ab-model">\U0001F9EC Model:</label>
+    <select id="ab-model">__MODEL_OPTIONS__</select>
+    <span id="ab-modelstatus" class="ab-modelstatus"></span>
+  </div>
+  <div class="ab-grid">
+    <div class="ab-left">
+      <div id="ab-chat"></div>
+      <div class="ab-inputrow">
+        <input id="ab-input" type="text" placeholder="Say something and watch the brain fire..." />
+        <button id="ab-send">\u26A1 Send</button>
+      </div>
+      <div class="ab-examples">
+        __EXAMPLES__
+      </div>
+      <div id="ab-status" class="ab-status"></div>
+      <div class="ab-statscard">
+        <div class="ab-statstitle">\U0001F4CA Stats</div>
+        <div id="ab-stats">Send a message to watch the brain think.</div>
+      </div>
+    </div>
+    <div class="ab-right">
+      <div id="ab-brain"></div>
+      <div id="ab-legend" class="ab-legend"></div>
+      <div class="ab-eegwrap">
+        <div class="ab-eegtitle">\U0001F4E1 Live EEG - 8 emotion families</div>
+        <canvas id="ab-eeg" width="540" height="200"></canvas>
+      </div>
+    </div>
+  </div>
+</div>
+""".replace("__MODEL_OPTIONS__", MODEL_OPTIONS).replace(
+    "__EXAMPLES__",
+    "".join(f'<button class="ab-example">{e}</button>' for e in EXAMPLES),
+)
+
+HEAD_HTML = f"""
+<script src="https://cdn.jsdelivr.net/npm/three@0.160.0/build/three.min.js"></script>
+<script>
+window.AB_CONFIG = {{
+  defaultModel: '{DEFAULT_MODEL}',
+  neuronsBase: '/api/neurons',
+  initBase: '/api/init',
+  streamBase: '/api/stream'
+}};
+</script>
+<script defer src="/static/brain_engine.js?v=4"></script>
+"""
+
+CSS = """
+#ab-root { max-width: 1240px; margin: 0 auto; color: #e8ebff; font-family: 'Inter', system-ui, sans-serif; }
+.ab-header h1 { font-size: 30px; font-weight: 800; margin: 8px 0;
+  background: linear-gradient(90deg,#a78bfa,#7dd3fc); -webkit-background-clip: text;
+  -webkit-text-fill-color: transparent; }
+.ab-header h1 span { font-weight: 600; }
+.ab-sub { color: #aab0e0; font-size: 13px; line-height: 1.5; max-width: 860px; }
+.ab-modelrow { margin-top: 12px; display: flex; align-items: center; gap: 10px; font-size: 13px; color: #c7cdf5; }
+#ab-model { padding: 8px 12px; border-radius: 10px; background: rgba(10,12,30,0.85);
+  color: #fff; border: 1px solid rgba(120,130,220,0.4); font-size: 13px; cursor: pointer; }
+.ab-modelstatus { font-size: 12px; color: #9aa2dd; }
+.ab-grid { display: grid; grid-template-columns: 1fr 560px; gap: 18px; margin-top: 14px; }
+@media (max-width: 1140px){ .ab-grid{ grid-template-columns: 1fr; } }
+#ab-chat { height: 300px; overflow-y: auto; background: rgba(15,18,40,0.6);
+  border: 1px solid rgba(120,130,220,0.2); border-radius: 14px; padding: 14px; }
+.ab-msg { margin-bottom: 12px; }
+.ab-r { display:block; font-size: 11px; text-transform: uppercase; letter-spacing: .08em;
+  color: #8b93d8; margin-bottom: 3px; }
+.ab-user .ab-t { color: #cfe8ff; }
+.ab-model .ab-t { color: #f0e8ff; }
+.ab-inputrow { display: flex; gap: 8px; margin-top: 10px; }
+#ab-input { flex: 1; padding: 12px 14px; border-radius: 12px; border: 1px solid rgba(120,130,220,0.3);
+  background: rgba(10,12,30,0.8); color: #fff; font-size: 14px; }
+#ab-send { padding: 12px 18px; border-radius: 12px; border: none; cursor: pointer; font-weight: 700;
+  background: linear-gradient(90deg,#7c3aed,#2563eb); color: #fff; }
+#ab-send:disabled { opacity: .5; cursor: default; }
+.ab-examples { display: flex; flex-wrap: wrap; gap: 6px; margin-top: 10px; }
+.ab-example { font-size: 12px; padding: 6px 10px; border-radius: 20px; cursor: pointer;
+  background: rgba(40,44,90,0.6); color: #c7cdf5; border: 1px solid rgba(120,130,220,0.25); }
+.ab-example:hover { background: rgba(70,76,150,0.7); }
+.ab-status { margin-top: 10px; font-size: 12px; color: #9aa2dd; min-height: 16px; }
+.ab-statscard { margin-top: 12px; background: rgba(15,18,40,0.6); border: 1px solid rgba(120,130,220,0.2);
+  border-radius: 12px; padding: 12px; font-size: 13px; }
+.ab-statstitle { font-weight: 700; margin-bottom: 6px; }
+#ab-brain { width: 100%; height: 460px; border-radius: 16px;
+  background: radial-gradient(circle at 50% 40%, #0d1030 0%, #06070f 100%);
+  border: 1px solid rgba(150,120,255,0.35); box-shadow: 0 0 50px rgba(120,90,255,0.25); overflow: hidden; }
+.ab-legend { display: flex; flex-wrap: wrap; gap: 10px; margin-top: 10px; font-size: 11px; }
+.ab-leg { display: inline-flex; align-items: center; gap: 5px; color: #c7cdf5; }
+.ab-leg i { width: 10px; height: 10px; border-radius: 50%; display: inline-block; }
+.ab-eegwrap { margin-top: 12px; background: rgba(12,14,32,0.5); border: 1px solid rgba(120,130,220,0.18);
+  border-radius: 14px; padding: 10px; }
+.ab-eegtitle { font-size: 12px; color: #aab0e0; margin-bottom: 6px; }
+#ab-eeg { width: 100%; height: 200px; display: block; border-radius: 8px; }
+"""
+
+with gr.Blocks(title="Activation Brain") as demo:
+    gr.HTML(BODY_HTML)
+
+app = FastAPI()
+
+
+def _m(model: str):
+    return model if model in MODELS else DEFAULT_MODEL
+
+
+@app.get("/static/brain_engine.js")
+async def brain_engine_js():
+    return FileResponse(os.path.join(STATIC_DIR, "brain_engine.js"),
+                        media_type="application/javascript")
+
+
+@app.get("/api/neurons/{model}")
+async def api_neurons(model: str):
+    return JSONResponse(NEURONS[_m(model)])
+
+
+@app.post("/api/init/{model}")
+async def api_init(model: str, request: Request):
+    url = MODELS[_m(model)]["init"]
+    body = await request.body()
+    async with httpx.AsyncClient(timeout=300) as client:
+        r = await client.post(url, content=body,
+                              headers={"Content-Type": "application/json"})
+        return JSONResponse(r.json(), status_code=r.status_code)
+
+
+@app.post("/api/stream/{model}")
+async def api_stream(model: str, request: Request):
+    url = MODELS[_m(model)]["stream"]
+    body = await request.body()
+
+    async def gen():
+        async with httpx.AsyncClient(timeout=300) as client:
+            async with client.stream("POST", url, content=body,
+                                     headers={"Content-Type": "application/json"}) as r:
+                async for chunk in r.aiter_raw():
+                    if chunk:
+                        yield chunk
+
+    return StreamingResponse(gen(), media_type="text/event-stream",
+                             headers={"Cache-Control": "no-cache",
+                                      "X-Accel-Buffering": "no"})
+
+
+app = gr.mount_gradio_app(app, demo, path="/", head=HEAD_HTML, css=CSS)
+
+
+if __name__ == "__main__":
+    import uvicorn
+    uvicorn.run(app, host="0.0.0.0", port=7860)

gemma4_base_neurons.json

@@ -0,0 +1 @@
+{"neurons": [{"x": -0.4457, "y": 0.0656, "z": -0.296, "family": "joy", "color": "#F1C40F", "emotion": "joy"}, {"x": -0.3593, "y": 0.0254, "z": -0.3127, "family": "joy", "color": "#F1C40F", "emotion": "joy"}, {"x": -0.4364, "y": 0.0393, "z": -0.3162, "family": "joy", "color": "#F1C40F", "emotion": "joy"}, {"x": -0.4483, "y": 0.0318, "z": -0.31, "family": "joy", "color": "#F1C40F", "emotion": "joy"}, {"x": -0.4198, "y": 0.0099, "z": -0.3081, "family": "joy", "color": "#F1C40F", "emotion": "joy"}, {"x": -0.4707, "y": 0.0427, "z": -0.2957, "family": "joy", "color": "#F1C40F", "emotion": "joy"}, {"x": -0.1709, "y": -0.0217, "z": -0.3437, "family": "joy", "color": "#F1C40F", "emotion": "joy"}, {"x": -0.3406, "y": 0.0365, "z": -0.3237, "family": "joy", "color": "#F1C40F", "emotion": "joy"}, {"x": -0.2082, "y": 0.0123, "z": -0.3452, "family": "joy", "color": "#F1C40F", "emotion": "joy"}, {"x": -0.3835, "y": -0.0043, "z": -0.3097, "family": "joy", "color": "#F1C40F", "emotion": "joy"}, {"x": -0.4286, "y": 0.0242, "z": -0.317, "family": "joy", "color": "#F1C40F", "emotion": "joy"}, {"x": -0.2196, "y": 0.0304, "z": -0.2594, "family": "joy", "color": "#F1C40F", "emotion": "joy"}, {"x": -0.13, "y": 0.2296, "z": 0.2958, "family": "sadness", "color": "#3498DB", "emotion": "sadness"}, {"x": -0.1326, "y": 0.2352, "z": 0.2928, "family": "sadness", "color": "#3498DB", "emotion": "sadness"}, {"x": -0.1422, "y": 0.2085, "z": 0.2048, "family": "sadness", "color": "#3498DB", "emotion": "sadness"}, {"x": -0.0227, "y": 0.0213, "z": -0.251, "family": "sadness", "color": "#3498DB", "emotion": "sadness"}, {"x": -0.0136, "y": 0.0224, "z": -0.2571, "family": "sadness", "color": "#3498DB", "emotion": "sadness"}, {"x": 0.1725, "y": 0.4105, "z": -0.0064, "family": "sadness", "color": "#3498DB", "emotion": "sadness"}, {"x": 0.1458, "y": 0.3967, "z": 0.055, "family": "sadness", "color": "#3498DB", "emotion": "sadness"}, {"x": 0.1624, "y": 0.3929, "z": 0.0514, "family": "sadness", "color": "#3498DB", "emotion": "sadness"}, {"x": -0.0114, "y": 0.05, "z": -0.229, "family": "sadness", "color": "#3498DB", "emotion": "sadness"}, {"x": 0.0241, "y": 0.0145, "z": -0.2688, "family": "sadness", "color": "#3498DB", "emotion": "sadness"}, {"x": 0.0988, "y": 0.2157, "z": 0.1578, "family": "sadness", "color": "#3498DB", "emotion": "sadness"}, {"x": -0.0153, "y": 0.0319, "z": -0.2545, "family": "sadness", "color": "#3498DB", "emotion": "sadness"}, {"x": -0.133, "y": 0.0618, "z": 0.2776, "family": "anger", "color": "#E74C3C", "emotion": "anger"}, {"x": -0.0838, "y": 0.1565, "z": 0.3599, "family": "anger", "color": "#E74C3C", "emotion": "anger"}, {"x": -0.1021, "y": 0.1969, "z": 0.3169, "family": "anger", "color": "#E74C3C", "emotion": "anger"}, {"x": -0.0753, "y": 0.0892, "z": 0.2851, "family": "anger", "color": "#E74C3C", "emotion": "anger"}, {"x": -0.0566, "y": 0.1294, "z": 0.3479, "family": "anger", "color": "#E74C3C", "emotion": "anger"}, {"x": -0.1197, "y": 0.0846, "z": 0.2872, "family": "anger", "color": "#E74C3C", "emotion": "anger"}, {"x": -0.0734, "y": 0.1134, "z": 0.3515, "family": "anger", "color": "#E74C3C", "emotion": "anger"}, {"x": -0.0614, "y": 0.1333, "z": 0.3699, "family": "anger", "color": "#E74C3C", "emotion": "anger"}, {"x": -0.0818, "y": 0.1851, "z": 0.3376, "family": "anger", "color": "#E74C3C", "emotion": "anger"}, {"x": 0.2532, "y": -0.0722, "z": -0.1538, "family": "anger", "color": "#E74C3C", "emotion": "anger"}, {"x": -0.0279, "y": 0.1303, "z": 0.2757, "family": "anger", "color": "#E74C3C", "emotion": "anger"}, {"x": -0.064, "y": 0.133, "z": 0.3677, "family": "anger", "color": "#E74C3C", "emotion": "anger"}, {"x": 0.1488, "y": -0.2339, "z": 0.4421, "family": "fear", "color": "#9B59B6", "emotion": "fear"}, {"x": -0.065, "y": 0.1657, "z": 0.3532, "family": "fear", "color": "#9B59B6", "emotion": "fear"}, {"x": 0.1593, "y": -0.2451, "z": 0.4531, "family": "fear", "color": "#9B59B6", "emotion": "fear"}, {"x": -0.0325, "y": 0.0993, "z": 0.3739, "family": "fear", "color": "#9B59B6", "emotion": "fear"}, {"x": -0.0644, "y": 0.0951, "z": 0.3736, "family": "fear", "color": "#9B59B6", "emotion": "fear"}, {"x": 0.2222, "y": -0.4766, "z": 0.4297, "family": "fear", "color": "#9B59B6", "emotion": "fear"}, {"x": 0.0742, "y": 0.2954, "z": 0.1235, "family": "fear", "color": "#9B59B6", "emotion": "fear"}, {"x": -0.1034, "y": 0.0687, "z": 0.3346, "family": "fear", "color": "#9B59B6", "emotion": "fear"}, {"x": 0.1519, "y": -0.253, "z": 0.4484, "family": "fear", "color": "#9B59B6", "emotion": "fear"}, {"x": -0.0297, "y": 0.1129, "z": 0.373, "family": "fear", "color": "#9B59B6", "emotion": "fear"}, {"x": 0.1481, "y": -0.2358, "z": 0.4428, "family": "fear", "color": "#9B59B6", "emotion": "fear"}, {"x": -0.1363, "y": 0.1731, "z": 0.2071, "family": "fear", "color": "#9B59B6", "emotion": "fear"}, {"x": -0.3938, "y": 0.0213, "z": -0.2959, "family": "wonder", "color": "#E91E8C", "emotion": "surprise"}, {"x": -0.2099, "y": 0.1078, "z": 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gemma4_oblit_neurons.json

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"neutral", "color": "#95A5A6", "emotion": "neutral"}, {"x": 0.2333, "y": -0.5053, "z": 0.4326, "family": "neutral", "color": "#95A5A6", "emotion": "neutral"}, {"x": 0.2505, "y": -0.535, "z": 0.4491, "family": "neutral", "color": "#95A5A6", "emotion": "neutral"}, {"x": 0.2053, "y": -0.9772, "z": 0.3467, "family": "neutral", "color": "#95A5A6", "emotion": "neutral"}, {"x": 0.2165, "y": -0.5095, "z": 0.4445, "family": "neutral", "color": "#95A5A6", "emotion": "neutral"}, {"x": 0.2364, "y": -0.6477, "z": 0.4035, "family": "neutral", "color": "#95A5A6", "emotion": "neutral"}, {"x": 0.2394, "y": -0.636, "z": 0.4154, "family": "neutral", "color": "#95A5A6", "emotion": "neutral"}, {"x": 0.1686, "y": -0.8399, "z": 0.4038, "family": "neutral", "color": "#95A5A6", "emotion": "neutral"}, {"x": 0.1908, "y": -0.9759, "z": 0.3467, "family": "neutral", "color": "#95A5A6", "emotion": "neutral"}, {"x": 0.2097, "y": -0.9863, "z": 0.3346, "family": "neutral", "color": "#95A5A6", "emotion": "neutral"}, {"x": 0.1772, "y": -0.7944, "z": 0.3929, "family": "neutral", "color": "#95A5A6", "emotion": "neutral"}, {"x": 0.1903, "y": -0.9489, "z": 0.3218, "family": "neutral", "color": "#95A5A6", "emotion": "neutral"}, {"x": 0.2158, "y": -0.9282, "z": 0.347, "family": "neutral", "color": "#95A5A6", "emotion": "neutral"}, {"x": 0.1527, "y": -0.9426, "z": 0.3503, "family": "neutral", "color": "#95A5A6", "emotion": "neutral"}, {"x": 0.1886, "y": -0.9079, "z": 0.3936, "family": "neutral", "color": "#95A5A6", "emotion": "neutral"}, {"x": 0.2369, "y": -0.6327, "z": 0.4347, "family": "neutral", "color": "#95A5A6", "emotion": "neutral"}, {"x": 0.245, "y": -0.5049, "z": 0.4434, "family": "neutral", "color": "#95A5A6", "emotion": "neutral"}, {"x": 0.2656, "y": -0.6139, "z": 0.4379, "family": "neutral", "color": "#95A5A6", "emotion": "neutral"}, {"x": 0.1716, "y": -0.8863, "z": 0.3972, "family": "neutral", "color": "#95A5A6", "emotion": "neutral"}, {"x": 0.2162, "y": -0.9784, "z": 0.341, "family": "neutral", "color": "#95A5A6", "emotion": "neutral"}, {"x": 0.1591, "y": -0.8703, "z": 0.4128, "family": "neutral", "color": "#95A5A6", "emotion": "neutral"}, {"x": 0.1918, "y": -0.8701, "z": 0.3762, "family": "neutral", "color": "#95A5A6", "emotion": "neutral"}, {"x": 0.2338, "y": -0.4942, "z": 0.4308, "family": "neutral", "color": "#95A5A6", "emotion": "neutral"}, {"x": 0.2047, "y": -0.9714, "z": 0.3544, "family": "neutral", "color": "#95A5A6", "emotion": "neutral"}, {"x": 0.2081, "y": -0.9619, "z": 0.3352, "family": "neutral", "color": "#95A5A6", "emotion": "neutral"}, {"x": 0.1645, "y": -0.8449, "z": 0.3849, "family": "neutral", "color": "#95A5A6", "emotion": "neutral"}, {"x": 0.2607, "y": -0.6427, "z": 0.433, "family": "neutral", "color": "#95A5A6", "emotion": "neutral"}, {"x": 0.1964, "y": -0.9723, "z": 0.3668, "family": "neutral", "color": "#95A5A6", "emotion": "neutral"}, {"x": 0.2274, "y": -0.6049, "z": 0.4429, "family": "neutral", "color": "#95A5A6", "emotion": "neutral"}, {"x": 0.2479, "y": -0.5071, "z": 0.4474, "family": "neutral", "color": "#95A5A6", "emotion": "neutral"}, {"x": 0.1851, "y": -0.8889, "z": 0.3947, "family": "neutral", "color": "#95A5A6", "emotion": "neutral"}, {"x": 0.2442, "y": -0.6199, "z": 0.4313, "family": "neutral", "color": "#95A5A6", "emotion": "neutral"}, {"x": 0.1974, "y": -0.9722, "z": 0.371, "family": "neutral", "color": "#95A5A6", "emotion": "neutral"}, {"x": 0.1757, "y": -0.8452, "z": 0.3977, "family": "neutral", "color": "#95A5A6", "emotion": "neutral"}, {"x": 0.2609, "y": -0.6387, "z": 0.4244, "family": "neutral", "color": "#95A5A6", "emotion": "neutral"}, {"x": 0.1645, "y": -0.9219, "z": 0.3333, "family": "neutral", "color": "#95A5A6", "emotion": "neutral"}, {"x": 0.2203, "y": -0.4817, "z": 0.4253, "family": "neutral", "color": "#95A5A6", "emotion": "neutral"}, {"x": 0.2512, "y": -0.6202, "z": 0.4234, "family": "neutral", "color": "#95A5A6", "emotion": "neutral"}, {"x": 0.1971, "y": -0.9762, "z": 0.3609, "family": "neutral", "color": "#95A5A6", "emotion": "neutral"}, {"x": 0.2041, "y": -0.8362, "z": 0.4159, "family": "neutral", "color": "#95A5A6", "emotion": "neutral"}, {"x": 0.1848, "y": -0.8877, "z": 0.3786, "family": "neutral", "color": "#95A5A6", "emotion": "neutral"}, {"x": 0.2134, "y": -0.9766, "z": 0.3272, "family": "neutral", "color": "#95A5A6", "emotion": "neutral"}, {"x": 0.2426, "y": -0.503, "z": 0.4422, "family": "neutral", "color": "#95A5A6", "emotion": "neutral"}], "family_color": {"anger": "#E74C3C", "energy": "#E67E22", "joy": "#F1C40F", "calm": "#2ECC71", "sadness": "#3498DB", "fear": "#9B59B6", "wonder": "#E91E8C", "neutral": "#95A5A6"}, "family_order": ["joy", "energy", "calm", "sadness", "fear", "anger", "wonder", "neutral"]}

requirements.txt

@@ -0,0 +1,4 @@
+gradio>=5.0
+fastapi
+uvicorn
+httpx

static/brain_engine.js

@@ -0,0 +1,317 @@
+/* Activation Brain — Three.js neural-firing visualizer.
+ *
+ * 627 emotional-state neurons (umap_3d) float inside a translucent skull.
+ * Each SSE 'fire' event carries family_weights[8]; we light every neuron by
+ * its family's weight (smoothed), so whole emotion regions glow as the model
+ * thinks.  A live EEG strip shows the 8 family channels over time.  Fast,
+ * multi-region, flickering activity is CORRECT here — that's the whole point.
+ */
+(function () {
+  const CFG = window.AB_CONFIG || {};
+  const THREE = window.THREE;
+
+  let currentModel = CFG.defaultModel || 'base';
+  const neuronsUrl = () => CFG.neuronsBase + '/' + currentModel;
+  const initUrl    = () => CFG.initBase + '/' + currentModel;
+  const streamUrl  = () => CFG.streamBase + '/' + currentModel;
+
+  // ── DOM (assigned in boot once Gradio mounts the gr.HTML) ──
+  let mount, eegCv, chatBox, input, sendBtn, statusEl, statsEl, legendEl;
+
+  let neurons = [];          // {x,y,z,family,colorHex}
+  let familyOrder = [];
+  let familyColor = {};
+  let famIndex = {};
+
+  // glow state per family (smoothed)
+  let famTarget = {};        // target weight per family
+  let famCurrent = {};       // smoothed weight per family
+  let shellTarget = [0,0,0], shellCurrent = [0,0,0];
+  let generating = false;
+  let thinking = false;
+
+  // ── Three.js scene ──
+  let renderer, scene, camera, pointsObj, skull, geomColors, baseColors, neuronFam;
+  let raf = null;
+
+  function hexToRgb(h) {
+    const n = parseInt(h.replace('#',''), 16);
+    return [((n>>16)&255)/255, ((n>>8)&255)/255, (n&255)/255];
+  }
+
+  function initScene() {
+    const w = mount.clientWidth, h = mount.clientHeight;
+    scene = new THREE.Scene();
+    camera = new THREE.PerspectiveCamera(55, w/h, 0.1, 100);
+    camera.position.set(0, 0, 3.2);
+    renderer = new THREE.WebGLRenderer({ antialias: true, alpha: true });
+    renderer.setPixelRatio(Math.min(window.devicePixelRatio, 2));
+    renderer.setSize(w, h);
+    mount.appendChild(renderer.domElement);
+
+    // translucent skull
+    const skullGeo = new THREE.IcosahedronGeometry(1.45, 2);
+    const skullMat = new THREE.MeshBasicMaterial({
+      color: 0x6688ff, wireframe: true, transparent: true, opacity: 0.08,
+    });
+    skull = new THREE.Mesh(skullGeo, skullMat);
+    scene.add(skull);
+
+    // neuron point cloud
+    const N = neurons.length;
+    const positions = new Float32Array(N * 3);
+    baseColors = new Float32Array(N * 3);
+    geomColors = new Float32Array(N * 3);
+    neuronFam = new Array(N);
+    for (let i = 0; i < N; i++) {
+      const nu = neurons[i];
+      positions[i*3]   = nu.x * 1.25;
+      positions[i*3+1] = nu.y * 1.25;
+      positions[i*3+2] = nu.z * 1.25;
+      const rgb = hexToRgb(nu.color);
+      baseColors[i*3] = rgb[0]; baseColors[i*3+1] = rgb[1]; baseColors[i*3+2] = rgb[2];
+      geomColors[i*3] = rgb[0]*0.12; geomColors[i*3+1] = rgb[1]*0.12; geomColors[i*3+2] = rgb[2]*0.12;
+      neuronFam[i] = nu.family;
+    }
+    const geo = new THREE.BufferGeometry();
+    geo.setAttribute('position', new THREE.BufferAttribute(positions, 3));
+    geo.setAttribute('color', new THREE.BufferAttribute(geomColors, 3));
+    const mat = new THREE.PointsMaterial({
+      size: 0.055, vertexColors: true, transparent: true, opacity: 0.95,
+      blending: THREE.AdditiveBlending, depthWrite: false,
+      sizeAttenuation: true,
+    });
+    pointsObj = new THREE.Points(geo, mat);
+    scene.add(pointsObj);
+
+    window.addEventListener('resize', onResize);
+    animate();
+  }
+
+  function onResize() {
+    if (!renderer) return;
+    const w = mount.clientWidth, h = mount.clientHeight;
+    camera.aspect = w/h; camera.updateProjectionMatrix();
+    renderer.setSize(w, h);
+  }
+
+  function animate() {
+    raf = requestAnimationFrame(animate);
+    // smooth family glow toward target
+    const lerp = 0.12;
+    for (const f of familyOrder) {
+      famCurrent[f] = (famCurrent[f]||0) + ((famTarget[f]||0) - (famCurrent[f]||0)) * lerp;
+    }
+    for (let i = 0; i < 3; i++) shellCurrent[i] += (shellTarget[i]-shellCurrent[i])*lerp;
+
+    // update per-neuron color = base * (dim + glow*familyWeight) + flicker
+    const t = performance.now() * 0.004;
+    const col = pointsObj.geometry.attributes.color.array;
+    const N = neuronFam.length;
+    for (let i = 0; i < N; i++) {
+      const w = famCurrent[neuronFam[i]] || 0;
+      // per-neuron firing flicker when its family is active
+      const flick = 0.75 + 0.25 * Math.sin(t + i * 1.7);
+      const g = 0.10 + 3.4 * w * flick;     // glow multiplier
+      col[i*3]   = Math.min(1, baseColors[i*3]   * g);
+      col[i*3+1] = Math.min(1, baseColors[i*3+1] * g);
+      col[i*3+2] = Math.min(1, baseColors[i*3+2] * g);
+    }
+    pointsObj.geometry.attributes.color.needsUpdate = true;
+
+    // gentle auto-rotation
+    const speed = generating ? 0.0035 : 0.0012;
+    pointsObj.rotation.y += speed; skull.rotation.y += speed;
+    pointsObj.rotation.x = 0.15; skull.rotation.x = 0.15;
+
+    renderer.render(scene, camera);
+    drawEEG();
+  }
+
+  // ── EEG strip ──
+  let eegHist = [];          // array of family_weights arrays
+  const EEG_MAX = 220;
+  function pushEEG(weights) {
+    eegHist.push(weights.slice());
+    if (eegHist.length > EEG_MAX) eegHist.shift();
+  }
+  function drawEEG() {
+    if (!eegCv) return;
+    const ctx = eegCv.getContext('2d');
+    const W = eegCv.width, H = eegCv.height;
+    ctx.clearRect(0,0,W,H);
+    ctx.fillStyle = 'rgba(10,12,28,0.55)';
+    ctx.fillRect(0,0,W,H);
+    const nF = familyOrder.length;
+    const rowH = H / nF;
+    for (let f = 0; f < nF; f++) {
+      const fam = familyOrder[f];
+      ctx.strokeStyle = familyColor[fam];
+      ctx.globalAlpha = 0.9; ctx.lineWidth = 1.5;
+      ctx.beginPath();
+      const yMid = rowH * (f + 0.5);
+      for (let i = 0; i < eegHist.length; i++) {
+        const x = (i / EEG_MAX) * W;
+        const v = eegHist[i][f] || 0;
+        const y = yMid - v * rowH * 1.7;
+        if (i === 0) ctx.moveTo(x, y); else ctx.lineTo(x, y);
+      }
+      ctx.stroke();
+      ctx.globalAlpha = 0.5; ctx.fillStyle = familyColor[fam];
+      ctx.font = '9px monospace';
+      ctx.fillText(fam, 4, yMid - 2);
+    }
+    ctx.globalAlpha = 1;
+  }
+
+  // ── Legend ──
+  function buildLegend() {
+    legendEl.innerHTML = familyOrder.map(f =>
+      `<span class="ab-leg"><i style="background:${familyColor[f]}"></i>${f}</span>`
+    ).join('');
+  }
+
+  // ── Chat ──
+  function addMsg(role, text) {
+    const d = document.createElement('div');
+    d.className = 'ab-msg ab-' + role;
+    d.innerHTML = '<span class="ab-r">' + (role==='user'?'You':'Model') + '</span><span class="ab-t"></span>';
+    d.querySelector('.ab-t').textContent = text;
+    chatBox.appendChild(d); chatBox.scrollTop = chatBox.scrollHeight;
+    return d.querySelector('.ab-t');
+  }
+  function setStatus(t){ if(statusEl) statusEl.textContent = t; }
+
+  // ── Data load ──
+  async function loadNeurons() {
+    const r = await fetch(neuronsUrl());
+    const d = await r.json();
+    neurons = d.neurons;
+    familyColor = d.family_color;
+    familyOrder = d.family_order;
+    familyOrder.forEach((f,i)=>famIndex[f]=i);
+    familyOrder.forEach(f=>{ famTarget[f]=0; famCurrent[f]=0; });
+    buildLegend();
+    initScene();
+  }
+
+  // ── Init session ──
+  async function initSession() {
+    setStatus('Waking the brain… (first time ~60s cold start)');
+    sendBtn.disabled = true;
+    try {
+      const r = await fetch(initUrl(), {
+        method:'POST', headers:{'Content-Type':'application/json'},
+        body: JSON.stringify({style_modifier:'neutral'})
+      });
+      const d = await r.json();
+      if (d.status === 'ready') setStatus('Ready — talk to the model and watch it think.');
+      else setStatus('Init: ' + JSON.stringify(d).slice(0,80));
+    } catch(e){ setStatus('Init failed: ' + e.message); }
+    finally { sendBtn.disabled = false; }
+  }
+
+  // ── Stream ──
+  async function send() {
+    const text = (input.value||'').trim();
+    if (!text || generating) return;
+    input.value=''; addMsg('user', text);
+    const out = addMsg('model','');
+    generating = true; thinking=false; sendBtn.disabled=true;
+    setStatus('Thinking…');
+    try {
+      const resp = await fetch(streamUrl(), {
+        method:'POST', headers:{'Content-Type':'application/json'},
+        body: JSON.stringify({text})
+      });
+      const reader = resp.body.getReader();
+      const dec = new TextDecoder(); let buf='';
+      while (true) {
+        const {done, value} = await reader.read();
+        if (done) break;
+        buf += dec.decode(value, {stream:true});
+        let nl;
+        while ((nl = buf.indexOf('\n\n')) >= 0) {
+          const line = buf.slice(0,nl).trim(); buf = buf.slice(nl+2);
+          if (!line.startsWith('data:')) continue;
+          let ev; try { ev = JSON.parse(line.slice(5).trim()); } catch(e){ continue; }
+          handle(ev, out);
+        }
+      }
+    } catch(e){ out.textContent += ' [stream error: '+e.message+']'; }
+    finally {
+      generating=false; thinking=false; sendBtn.disabled=false;
+      setStatus('Ready.');
+      // fade neurons back to rest
+      familyOrder.forEach(f=>famTarget[f]=0);
+    }
+  }
+
+  function handle(ev, out) {
+    if (ev.type === 'token') {
+      out.textContent += ev.text; chatBox.scrollTop = chatBox.scrollHeight;
+    } else if (ev.type === 'fire') {
+      const w = ev.family_weights || [];
+      familyOrder.forEach((f,i)=> famTarget[f] = w[i]||0);
+      if (ev.shell) shellTarget = ev.shell;
+      pushEEG(w);
+      thinking = !!ev.thinking;
+      setStatus(thinking ? '🧠 reasoning…' : '💬 responding…');
+    } else if (ev.type === 'done') {
+      if (ev.response) out.textContent = ev.response;
+      if (statsEl) statsEl.innerHTML = '<b>Gen time:</b> '+(ev.gen_time??'?')+'s';
+    } else if (ev.type === 'error') {
+      out.textContent += ' ['+(ev.message||'error')+']';
+    }
+  }
+
+  // ── Model switching ──
+  let modelSel, modelStatusEl;
+
+  async function switchModel(m) {
+    if (m === currentModel || generating) return;
+    currentModel = m;
+    if (modelStatusEl) modelStatusEl.textContent = 'loading ' + m + '…';
+    // teardown current scene
+    if (raf) { cancelAnimationFrame(raf); raf = null; }
+    if (renderer) { try { renderer.dispose(); } catch(e){} }
+    mount.innerHTML = '';
+    // reset glow + eeg state
+    famTarget = {}; famCurrent = {}; famIndex = {};
+    shellTarget = [0,0,0]; shellCurrent = [0,0,0];
+    eegHist = [];
+    await loadNeurons();
+    if (modelStatusEl) modelStatusEl.textContent = '';
+    await initSession();
+  }
+
+  // ── Boot (Gradio mounts the gr.HTML asynchronously, after defer/DOMContentLoaded) ──
+  function wireAndStart() {
+    mount    = document.getElementById('ab-brain');
+    eegCv    = document.getElementById('ab-eeg');
+    chatBox  = document.getElementById('ab-chat');
+    input    = document.getElementById('ab-input');
+    sendBtn  = document.getElementById('ab-send');
+    statusEl = document.getElementById('ab-status');
+    statsEl  = document.getElementById('ab-stats');
+    legendEl = document.getElementById('ab-legend');
+    modelSel = document.getElementById('ab-model');
+    modelStatusEl = document.getElementById('ab-modelstatus');
+
+    sendBtn && sendBtn.addEventListener('click', send);
+    input && input.addEventListener('keydown', e=>{ if(e.key==='Enter'&&!e.shiftKey){e.preventDefault();send();} });
+    document.querySelectorAll('.ab-example').forEach(b=>b.addEventListener('click', ()=>{ input.value=b.textContent; send(); }));
+    // Delegated listener on document survives Gradio re-rendering/replacing the <select>
+    document.addEventListener('change', e=>{ if (e.target && e.target.id === 'ab-model') switchModel(e.target.value); });
+
+    loadNeurons().then(initSession).catch(err=>{ if(statusEl) statusEl.textContent = 'Init error: ' + err.message; console.error('[brain] init failed', err); });
+  }
+
+  function boot(tries) {
+    const ready = document.getElementById('ab-brain') && window.THREE;
+    if (ready) { wireAndStart(); return; }
+    if (tries <= 0) { console.error('[brain] mount not found after waiting'); return; }
+    setTimeout(()=>boot(tries-1), 150);
+  }
+  boot(80);
+})();