Fixed dashboard
added brainmap
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parent
e72678b242
commit
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2
.gitignore
vendored
2
.gitignore
vendored
@ -174,3 +174,5 @@ cython_debug/
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/data/memory/context.json
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/data/memory/dreams.json
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/data/memory/vocab.json
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data/memory/vocab.json
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data/memory/brainmap.json
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@ -1,9 +1,11 @@
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from flask import Flask, render_template
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from model.brainmap import get_brainmap
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from model.journal import read_journal_entries
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from model.memory import load_dreams
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from model.tokenizer import Tokenizer
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from model.abstraction import cluster_vocab
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from context.context import load_context
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import json
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import os
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import time
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@ -43,6 +45,25 @@ def index():
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next_cycle=remaining)
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@app.route("/brainmap")
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def brainmap():
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map_data = get_brainmap()
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nodes = []
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links = []
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for word, connections in map_data.items():
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nodes.append({"id": word})
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for linked_word, weight in connections.items():
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links.append({
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"source": word,
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"target": linked_word,
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"value": weight
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})
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return render_template("brainmap.html", nodes=json.dumps(nodes), links=json.dumps(links))
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@app.route("/journal")
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def journal():
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entries = read_journal_entries()
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61
dashboard/templates/brainmap.html
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61
dashboard/templates/brainmap.html
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@ -0,0 +1,61 @@
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<!DOCTYPE html>
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<html lang="en">
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<head>
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<meta charset="UTF-8">
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<title>Ruby's Brain Map</title>
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<script src="https://cdn.jsdelivr.net/npm/force-graph"></script>
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<style>
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body {
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background-color: #121212;
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color: #e0e0e0;
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margin: 0;
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padding: 0;
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overflow: hidden;
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}
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#graph {
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width: 100vw;
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height: 100vh;
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}
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.nav {
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position: absolute;
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top: 10px;
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left: 10px;
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background-color: #1e1e1e;
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padding: 10px;
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z-index: 1000;
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}
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.nav a {
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color: #e0e0e0;
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margin-right: 20px;
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text-decoration: none;
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}
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</style>
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</head>
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<body>
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<div class="nav">
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<a href="/">🏠 Home</a>
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<a href="/journal">📓 Journal</a>
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<a href="/concepts">🧠 Concepts</a>
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<a href="/brainmap">🕸️ Brain Map</a>
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</div>
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<div id="graph"></div>
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<script>
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const graphData = {
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nodes: {{ nodes | safe }},
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links: {{ links | safe }}
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};
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const Graph = ForceGraph()(document.getElementById('graph'))
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.graphData(graphData)
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.nodeAutoColorBy('id')
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.nodeLabel('id')
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.linkWidth(link => Math.log(link.value + 1))
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.linkColor(() => 'rgba(255,255,255,0.2)')
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.backgroundColor('#121212');
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</script>
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</body>
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</html>
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@ -23,9 +23,31 @@
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list-style-type: square;
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padding-left: 20px;
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}
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.entry {
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margin-bottom: 15px;
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padding-bottom: 10px;
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border-bottom: 1px solid #333;
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}
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.nav {
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background-color: #1e1e1e;
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padding: 10px;
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margin-bottom: 20px;
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}
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.nav a {
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color: #e0e0e0;
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margin-right: 20px;
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text-decoration: none;
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}
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</style>
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</head>
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<body>
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<div class="nav">
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<a href="/">🏠 Home</a>
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<a href="/journal">📓 Journal</a>
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<a href="/concepts">🧠 Concepts</a>
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<a href="/brainmap">🕸️ Brain Map</a>
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</div>
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<h1>🧠 Ruby's Concept Clusters</h1>
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{% for cluster_id, words in clusters.items() %}
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@ -30,6 +30,12 @@
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</style>
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</head>
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<body>
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<div style="background-color: #1e1e1e; padding: 10px; margin-bottom: 20px;">
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<a href="/" style="color: #e0e0e0; margin-right: 20px;">🏠 Home</a>
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<a href="/journal" style="color: #e0e0e0; margin-right: 20px;">📓 Journal</a>
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<a href="/concepts" style="color: #e0e0e0; margin-right: 20px;">🧠 Concepts</a>
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<a href="/brainmap" style="color: #e0e0e0;">🕸️ Brain Map</a>
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</div>
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<h1>Ruby is Running 🧠</h1>
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<div class="section">
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@ -9,6 +9,7 @@
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color: #e0e0e0;
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font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif;
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padding: 20px;
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margin: 0;
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}
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h1 {
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color: #ffffff;
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@ -18,13 +19,32 @@
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padding-bottom: 10px;
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border-bottom: 1px solid #333;
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}
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.nav {
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background-color: #1e1e1e;
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padding: 10px;
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margin-bottom: 20px;
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}
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.nav a {
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color: #e0e0e0;
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margin-right: 20px;
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text-decoration: none;
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}
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</style>
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</head>
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<body>
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<div class="nav">
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<a href="/">🏠 Home</a>
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<a href="/journal">📓 Journal</a>
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<a href="/concepts">🧠 Concepts</a>
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<a href="/brainmap">🕸️ Brain Map</a>
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</div>
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<h1>📓 Ruby's Journal</h1>
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{% for entry in entries %}
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<div class="entry">{{ entry }}</div>
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{% endfor %}
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</body>
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</html>
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@ -4,5 +4,11 @@
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"how": 3,
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"are": 4,
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"you": 5,
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"today": 6
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"today": 6,
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"the": 7,
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"cat": 8,
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"ran": 9,
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"across": 10,
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"sunny": 11,
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"street": 12
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}
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@ -9,11 +9,10 @@ def cluster_vocab(n_clusters=10):
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vocab_items = list(tokenizer.vocab.items())
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words, ids = zip(*vocab_items)
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embeds = torch.nn.Embedding(len(ids), 256) # Same as model size
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with torch.no_grad():
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vectors = embeds(torch.tensor(list(ids)))
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# Instead of embeddings, let's make random small vectors manually
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vectors = torch.randn(len(ids), 64) # 64d random vectors for clustering
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kmeans = KMeans(n_clusters=n_clusters)
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kmeans = KMeans(n_clusters=min(n_clusters, len(ids)))
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labels = kmeans.fit_predict(vectors.cpu().numpy())
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clusters = {}
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39
model/brainmap.py
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39
model/brainmap.py
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@ -0,0 +1,39 @@
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import os
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import json
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from collections import defaultdict
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BRAINMAP_FILE = "data/memory/brainmap.json"
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def load_brainmap():
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if os.path.exists(BRAINMAP_FILE):
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with open(BRAINMAP_FILE, "r", encoding="utf-8") as f:
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return json.load(f)
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return {}
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def save_brainmap(map_data):
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with open(BRAINMAP_FILE, "w", encoding="utf-8") as f:
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json.dump(map_data, f, indent=2)
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brain_map = load_brainmap()
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def update_brainmap(words):
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for i, word in enumerate(words):
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for j in range(i+1, len(words)):
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w1 = word
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w2 = words[j]
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if w1 == w2:
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continue
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if w1 not in brain_map:
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brain_map[w1] = {}
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if w2 not in brain_map[w1]:
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brain_map[w1][w2] = 0
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brain_map[w1][w2] += 1
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save_brainmap(brain_map)
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def get_brainmap():
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return brain_map
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@ -3,6 +3,7 @@ import time
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from model.brain_state import model, tokenizer, DEVICE, optimizer, loss_fn
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from context.context import add_to_context, get_recent_context
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from model.dynamic_expand import expand_model_if_needed
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from model.brainmap import update_brainmap
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LOSS_FILE = "data/logs/loss.log"
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@ -22,6 +23,8 @@ def train_on_message(text: str):
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if len(tokens) < 2:
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return
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words = tokenizer.detokenize(tokens).split()
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update_brainmap(words)
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input_tensor = torch.tensor(tokens[:-1], dtype=torch.long, device=DEVICE).unsqueeze(0)
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target_tensor = torch.tensor(tokens[1:], dtype=torch.long, device=DEVICE).unsqueeze(0)
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