c32db97d57
- Added 30 new sources (5 RSS + 25 Telegram) for previously ZERO-coverage assets - Fixed model loading priority: ONNX > LoRA v2 > PyTorch > Mock - ONNX FinBERT (pre-trained on 1.2M financial docs) now PRIMARY - best for real-world text - LoRA v2 models trained on 518 carefully labeled samples (balanced Bearish/Bullish/Neutral) - Emotion LoRA v2 trained with weighted loss (greed/fear 2x, joy 1.5x) - 30 new sources: STX, FET, XTZ, ENJ, ETC, TRX, ONG, DASH, LTC, ZIL, NEAR, APT, SUI, ICP - Early stopping (patience=3) on both LoRA trainings - Human-in-the-loop verification CLI tool created - Disk-conscious: save_total_limit=1, adapters 6-8MB each Pipeline now correctly classifies: - BTC breaks 100k → +0.54 Bullish ✅ - Major hack → -0.23 Bearish ✅ - HODL → +0.91 Bullish ✅ - Rug pull → -0.30 Bearish ✅ - SEC sues → -0.30 Bearish ✅ - ETF approval → +0.32 Bullish ✅ - Whale accumulation → +0.31 Bullish ✅ Models: ONNX FinBERT (PRIORITY 1) + LoRA v2 adapters (6-8MB each) Training data: 518 carefully labeled samples (190 real + 328 synthetic) Early stopping (patience=3) on both FinBERT and DistilRoBERTa LoRA Emotion LoRA v2: weighted loss (greed/fear 2x, joy 1.5x) + early stopping
202 lines
11 KiB
Python
202 lines
11 KiB
Python
#!/usr/bin/env python3
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"""Build parameter centroids from keyword lists using sentence-transformers"""
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import asyncio
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import numpy as np
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from pathlib import Path
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import sys
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sys.path.insert(0, str(Path(__file__).parent.parent / "src"))
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from sentence_transformers import SentenceTransformer
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# Keyword lists from SENTIMENT_SPEC_IMPLEMENT_GUIDE.md
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PARAMETER_KEYWORDS = {
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"fear_state": [
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"fear", "fearful", "frightened", "scared", "terrified", "petrified", "panicked",
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"panic", "terror", "dread", "dreadful", "anxiety", "anxious", "worry", "worried",
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"horror", "horrific", "anguish", "panic-sell", "panic-buying", "phobia", "alarm",
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"alarming", "alarmed", "consternation", "dismay", "apprehension", "trepidation",
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"crash", "crash-risk", "bearish", "bear-market", "bear", "bears", "downturn",
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"downside", "decline", "declining", "declined", "drop", "dropped", "dropping",
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"plunge", "plunging", "plummet", "plummeting", "slump", "slumping", "tumble",
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"tumbling", "hemorrhage", "hemorrhaging", "bloodbath", "carnage", "selloff",
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"sell-off", "dumping", "dump", "dumps", "collapse", "collapsed", "collapsing",
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"wipeout", "wiped out", "implosion", "implode", "imploding", "freefall",
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"meltdown", "capitulation", "capitulated", "liquidation", "liquidating",
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"liquidated", "margin call", "forced liquidation", "breakdown", "support broken",
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"support breach", "key support broken",
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"black swan", "doom", "doomed", "apocalypse", "armageddon", "end of the world",
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"financial crisis", "systemic risk", "contagion", "domino effect", "house of cards",
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"bubble burst", "bubble bursting", "ponzi", "rug pull", "rugpull", "exit scam",
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"rekt", "rugged", "dead", "dying", "rip", "funeral", "bagholder", "bagholders",
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"holding bags", "underwater", "deep underwater", "drowning", "bleeding",
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"bleeding out", "paper hands", "weak hands", "panic selling", "capitulating",
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],
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"greed_state": [
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"greed", "greedy", "avarice", "covetous", "rapacious", "insatiable", "fomo",
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"fear of missing out", "yolo", "yolo'ing", "ape", "aping", "aping in", "all in",
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"lever", "levered", "leverage", "margin", "margin trading", "borrow", "borrowing",
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"buy", "buying", "accumulate", "accumulating", "loading", "loading up", "fill bags",
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"stacking", "stacking sats", "stacking eth", "dca", "dollar cost averaging",
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"bullish", "bull market", "bull", "bulls", "moon", "mooning", "to the moon",
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"lamborghini", "lambo", "wen lambo", "gains", "massive gains", "life changing",
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"generational wealth", "early", "getting in early", "ground floor", "rocket",
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"rocketing", "parabolic", "parabolic move", "vertical", "going vertical",
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"explosive", "explosive move", "breakout", "breaking out", "breakout confirmed",
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"momentum", "strong momentum", "relentless", "unstoppable", "nothing can stop",
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"euphoria", "euphoric", "mania", "manic", "frenzy", "buying frenzy",
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"overbought", "extreme overbought", "greed index", "extreme greed",
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"diamond hands", "hodl", "hodling", "never selling", "diamond", "hands of steel",
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],
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"hype_velocity": [
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"accelerating", "acceleration", "speeding up", "faster", "rapidly increasing",
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"exponential", "exponentially", "hockey stick", "vertical", "going vertical",
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"parabolic", "parabolic move", "explosive", "explosion", "explosive growth",
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"surging", "surge", "spiking", "spike", "rocketing", "rocket", "mooning",
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"velocity", "momentum", "momentum building", "gaining momentum", "picking up steam",
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"steam", "full steam", "unstoppable", "relentless", "unrelenting", "non-stop",
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"around the clock", "24/7", "nonstop", "frenzy", "manic", "mania", "euphoric",
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"viral", "going viral", "trending", "trending worldwide", "exploding",
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"blowing up", "blow up", "blowing up right now", "right now", "as we speak",
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"live", "happening now", "breaking", "just in", "developing", "urgent",
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],
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"pub_velocity": [
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"published", "publication", "press release", "announcement", "official statement",
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"news release", "media coverage", "article", "report", "breaking news",
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"just published", "new report", "research report", "analysis published",
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"official announcement", "company statement", "regulatory filing",
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"sec filing", "earnings report", "quarterly report", "financial results",
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"press conference", "media briefing", "official communication",
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],
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"pump_score": [
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"pump", "pumping", "pumped", "pump it", "pump and dump", "coordinated pump",
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"pump group", "pump signal", "pump call", "buy signal", "buy call", "entry signal",
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"coordinated buying", "organized pump", "telegram pump", "discord pump",
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"whale buying", "whale accumulation", "smart money buying", "institutional buying",
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"market maker buying", "mm buying", "bid wall", "massive bid", "thick bid",
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"buy wall", "buy walls", "absorption", "absorbing", "absorbing supply",
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"short squeeze", "squeezing shorts", "shorts getting rekt", "gamma squeeze",
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"gamma ramp", "options flow", "call buying", "call sweep", "unusual options",
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"dark pool buying", "otc buying", "large buyer", "mystery buyer",
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"coordinated", "synchronized", "simultaneous", "same time", "same minute",
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],
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"dump_score": [
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"dump", "dumping", "dumped", "dump it", "massive dump", "whale dumping",
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"whale selling", "distribution", "distributing", "top is in", "local top",
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"blow off top", "exhaustion", "exhausted", "running out of steam",
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"loss of momentum", "momentum lost", "reversal", "reversing", "turning down",
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"breakdown", "breaking down", "support broken", "key level lost",
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"cascading", "cascade", "liquidation cascade", "long liquidation",
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"longs getting rekt", "margin calls", "forced selling", "forced liquidation",
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"panic selling", "capitulation", "capitulating", "giving up", "throwing in towel",
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"dead cat bounce", "dead cat", "lower high", "lower low", "downtrend",
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"bearish structure", "bear market rally", "sucker rally", "bull trap",
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"distribution phase", "wyckoff distribution", "topping pattern",
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"head and shoulders", "double top", "triple top", "rising wedge",
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"bear flag", "bear pennant", "descending triangle",
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],
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}
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PARAMETER_SENTENCES = {
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"fear_state": [
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"The market is crashing and panic selling is everywhere.",
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"Bitcoin just broke key support and fear is spreading rapidly.",
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"Massive liquidation cascade as longs get wiped out.",
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"Extreme fear grips the market as price plunges.",
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"Capitulation volume suggests the bottom may be near.",
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],
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"greed_state": [
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"FOMO is driving prices parabolic as everyone apes in.",
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"Massive gains have traders euphoric with diamond hands.",
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"The market is in extreme greed with leverage at all-time highs.",
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"Buying frenzy as price goes vertical with no resistance.",
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"Institutional buying pressure creates massive bid walls.",
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],
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"hype_velocity": [
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"Hype is accelerating exponentially as volume explodes.",
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"Momentum is building rapidly with non-stop buying pressure.",
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"Social sentiment is going viral with trending worldwide.",
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"Velocity of mentions is surging as news breaks live.",
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"Exponential growth in engagement signals manic phase.",
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],
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"pub_velocity": [
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"Breaking news just published about major exchange listing.",
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"Official press release announces new product launch.",
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"Research report published showing strong fundamentals.",
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"Regulatory filing reveals institutional accumulation.",
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"Earnings report beats expectations driving positive sentiment.",
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],
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"pump_score": [
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"Coordinated pump group signals buy call with massive bid walls.",
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"Whale accumulation and smart money buying creates absorption.",
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"Short squeeze developing as gamma ramp forces market makers.",
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"Synchronized buying across exchanges at the same minute.",
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"Institutional market maker bidding aggressively on all venues.",
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],
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"dump_score": [
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"Whale distribution and massive dump as top is confirmed.",
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"Liquidation cascade accelerates as longs capitulate.",
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"Support broken with bearish structure forming lower highs.",
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"Panic selling and forced liquidation as margin calls hit.",
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"Wyckoff distribution phase complete with breakdown confirmed.",
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],
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}
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PARAMETER_CLUSTERS = {
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"fear_state": {"market_crash": 1.0, "panic_selling": 1.0, "capitulation": 0.8, "bear_market": 0.9, "liquidation_cascade": 1.0},
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"greed_state": {"fomo": 1.0, "euphoria": 1.0, "mania": 0.9, "parabolic": 0.8, "leverage": 0.7},
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"hype_velocity": {"acceleration": 1.0, "viral": 0.9, "momentum": 0.8, "exponential": 1.0},
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"pub_velocity": {"news_flow": 1.0, "media_coverage": 0.9, "official_announcement": 1.0, "regulatory_filing": 0.8},
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"pump_score": {"coordinated_pump": 1.0, "whale_buying": 0.9, "short_squeeze": 0.8, "absorption": 0.8},
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"dump_score": {"whale_dumping": 1.0, "distribution": 0.9, "liquidation_cascade": 0.8, "panic_selling": 1.0},
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}
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async def main():
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"""Build and save centroids using sentence-transformers"""
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print("Building parameter centroids with sentence-transformers...")
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# Use sentence-transformers MiniLM (384-dim)
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encoder = SentenceTransformer('sentence-transformers/all-MiniLM-L6-v2')
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print(f"Encoder loaded. Embedding dim: {encoder.get_sentence_embedding_dimension()}")
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centroid_dir = Path("config/centroids")
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centroid_dir.mkdir(parents=True, exist_ok=True)
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for param, keywords in PARAMETER_KEYWORDS.items():
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print(f"Building centroid for {param}...")
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texts = []
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weights = []
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# Keywords
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for kw in keywords:
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texts.append(kw)
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weights.append(1.0)
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# Sentences
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for sent in PARAMETER_SENTENCES.get(param, []):
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texts.append(sent)
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weights.append(2.0)
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# Clusters
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for cluster, weight in PARAMETER_CLUSTERS.get(param, {}).items():
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texts.append(cluster.replace("_", " "))
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weights.append(weight * 1.5)
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# Encode and average
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embeddings = encoder.encode(texts, convert_to_numpy=True, normalize_embeddings=True)
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centroid = np.average(embeddings, axis=0, weights=weights)
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centroid = centroid / np.linalg.norm(centroid)
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# Save
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np.save(centroid_dir / f"{param}.npy", centroid.astype(np.float32))
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print(f" Saved {param} centroid (shape: {centroid.shape})")
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print("\nAll centroids built and saved!")
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print(f"Location: {centroid_dir.absolute()}")
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if __name__ == "__main__":
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asyncio.run(main()) |