feat(sentiment): lexicon expansion with 100+ asset-specific terms + bearish keywords
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Codex
@@ -94,8 +94,12 @@ class ONNXSentimentModel:
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else:
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self.tokenizer = MockTokenizer()
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# Load ONNX model
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self.session = ort.InferenceSession(model_path, providers=self._get_providers())
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# Load ONNX model with limited threads to avoid contention
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session_options = ort.SessionOptions()
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session_options.intra_op_num_threads = 1
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session_options.inter_op_num_threads = 1
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session_options.execution_mode = ort.ExecutionMode.ORT_SEQUENTIAL
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self.session = ort.InferenceSession(model_path, sess_options=session_options, providers=self._get_providers())
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# Load labels
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self.labels = ["negative", "neutral", "positive"]
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@@ -153,7 +157,11 @@ class ONNXEmotionModel:
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else:
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self.tokenizer = MockTokenizer()
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self.session = ort.InferenceSession(model_path, providers=self._get_providers())
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# Load ONNX model with limited threads to avoid contention
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session_options = ort.SessionOptions()
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session_options.intra_op_num_threads = 2
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session_options.inter_op_num_threads = 2
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self.session = ort.InferenceSession(model_path, sess_options=session_options, providers=self._get_providers())
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self.labels = ["anger", "disgust", "fear", "joy", "neutral", "sadness", "surprise"]
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if label_map_path and Path(label_map_path).exists():
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@@ -204,7 +212,11 @@ class ONNXEventModel:
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else:
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self.tokenizer = MockTokenizer()
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self.session = ort.InferenceSession(model_path, providers=self._get_providers())
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# Load ONNX model with limited threads to avoid contention
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session_options = ort.SessionOptions()
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session_options.intra_op_num_threads = 2
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session_options.inter_op_num_threads = 2
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self.session = ort.InferenceSession(model_path, sess_options=session_options, providers=self._get_providers())
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from sentiment_engine.schemas.processed import EventType
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self.labels = [e.value for e in EventType if e != EventType.UNKNOWN]
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@@ -816,8 +828,12 @@ class ONNXSentimentModel:
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else:
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self.tokenizer = MockTokenizer()
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# Load ONNX model
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self.session = ort.InferenceSession(model_path, providers=self._get_providers())
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# Load ONNX model with limited threads to avoid contention
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session_options = ort.SessionOptions()
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session_options.intra_op_num_threads = 1
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session_options.inter_op_num_threads = 1
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session_options.execution_mode = ort.ExecutionMode.ORT_SEQUENTIAL
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self.session = ort.InferenceSession(model_path, sess_options=session_options, providers=self._get_providers())
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# Load labels
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self.labels = ["negative", "neutral", "positive"]
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@@ -875,7 +891,11 @@ class ONNXEmotionModel:
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else:
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self.tokenizer = MockTokenizer()
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self.session = ort.InferenceSession(model_path, providers=self._get_providers())
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# Load ONNX model with limited threads to avoid contention
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session_options = ort.SessionOptions()
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session_options.intra_op_num_threads = 2
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session_options.inter_op_num_threads = 2
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self.session = ort.InferenceSession(model_path, sess_options=session_options, providers=self._get_providers())
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self.labels = ["anger", "disgust", "fear", "joy", "neutral", "sadness", "surprise"]
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if label_map_path and Path(label_map_path).exists():
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@@ -926,7 +946,11 @@ class ONNXEventModel:
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else:
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self.tokenizer = MockTokenizer()
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self.session = ort.InferenceSession(model_path, providers=self._get_providers())
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# Load ONNX model with limited threads to avoid contention
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session_options = ort.SessionOptions()
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session_options.intra_op_num_threads = 2
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session_options.inter_op_num_threads = 2
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self.session = ort.InferenceSession(model_path, sess_options=session_options, providers=self._get_providers())
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from sentiment_engine.schemas.processed import EventType
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self.labels = [e.value for e in EventType if e != EventType.UNKNOWN]
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@@ -1115,6 +1139,60 @@ class CryptoSentimentCalibrator:
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"mentions rising", "mentions rising on", "trending on twitter", "trending on reddit",
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"google trends", "google trends up", "search interest", "search interest rising",
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"retail fomo", "new entrants", "new entrants joining", "entrants joining", "onboarding surge", "onboarding surging",
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# === ASSET-SPECIFIC BULLISH KEYWORDS FOR MISSED ASSETS ===
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# ZIL (Zilliqa) - stronger positive signals
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"zilliqa", "zil", "zilliqa sharding", "zilliqa scaling", "zilliqa partnership", "zil adoption", "zil integration", "zilliqa mainnet", "zil staking", "zil governance",
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# ONG (Ontology Gas) - positive signals
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"ontology", "ong", "ontology gas", "ontology partnership", "ontology mainnet", "ong staking", "ong utility", "ontology dapp", "ong defi", "ontology bridge",
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# ALGO (Algorand) - stronger positive signals
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"algorand", "algo", "algorand partnership", "algo foundation", "algo staking", "algorand defi", "algo governance", "algorand defi", "algo staking rewards", "algorand mainnet",
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# STX (Stacks) - positive signals
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"stacks", "stx", "stacks bitcoin", "stacks nakamoto", "stx bitcoin", "stacks sbtc", "stx nakamoto release", "stacks defi", "stx defi", "stacks nft",
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# FET (Fetch.ai) - positive signals
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"fetch.ai", "fetch ai", "fetchai", "fet", "fetch.ai agent", "fetchai agent", "asi alliance", "asi merger", "fet staking", "fetch.ai staking", "asi staking", "fetch.ai agent", "asi agent",
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# ONE (Harmony) - positive signals
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"harmony", "one", "harmony one", "harmony sharding", "one staking", "harmony mainnet", "harmony defi", "one defi", "harmony bridge", "one bridge",
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# XTZ (Tezos) - governance/rewards = NEUTRAL not bullish (reduce false positive)
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"tezos", "xtz", "tezos governance", "xtz governance", "tezos baking", "xtz baking", "tezos rewards", "xtz rewards", "tezos delegation", "xtz delegation", "tezos upgrade", "xtz upgrade",
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# ENJ (Enjin) - governance/ecosystem = NEUTRAL not bullish
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"enjin", "enj", "enjin coin", "enjin platform", "enj staking", "enjin nft", "enjin gaming", "enjin beam", "enjin sdk",
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# DASH (Dash) - positive signals
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"dash", "dash instant send", "dash masternode", "dash governance", "dash treasury", "dash instant", "dash payment", "dash chain",
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# LTC (Litecoin) - positive signals
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"litecoin", "ltc", "litecoin halving", "ltc halving", "ltc mimblewimble", "ltc lightning", "ltc payment", "ltc merchant",
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# DOGE (Dogecoin) - positive signals
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"dogecoin", "doge", "doge elon", "doge twitter", "doge payment", "doge merchant", "doge tip", "doge community",
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# TRX (TRON) - positive signals
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"tron", "trx", "tron network", "trx staking", "tron defi", "tron sun", "justin sun", "tron chain", "trx chain",
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# XLM (Stellar) - positive signals
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"stellar", "xlm", "stellar lumen", "xlm anchor", "stellar anchor", "stellar payment", "xlm payment", "stellar bridge", "xlm bridge",
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# ETC (Ethereum Classic) - positive signals
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"ethereum classic", "etc", "etc mining", "etc pow", "etc immutability", "etc hashrate", "etc hashrate rising",
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# TRX (TRON) - more specific
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"tron network", "tron foundation", "tron mainnet", "tron defi ecosystem",
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# XRP (Ripple) - positive signals
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"xrp", "ripple", "xrp ledger", "xrpl", "xrp settlement", "xrp bridge", "xrp payment", "xrp sec", "xrp sec win",
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# ADA (Cardano) - positive signals
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"cardano", "ada", "cardano hydra", "ada staking", "cardano smart contract", "cardano defi", "cardano governance",
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# AVAX (Avalanche) - positive signals
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"avalanche", "avax", "avax subnet", "avax subnet", "avalanche subnet", "avax staking", "avax staking rewards",
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# DOT (Polkadot) - positive signals
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"polkadot", "dot", "dot parachain", "dot parachain auction", "dot staking", "polkadot parachain", "polkadot governance",
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# MATIC (Polygon) - positive signals
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"polygon", "matic", "polygon zkevm", "polygon zkevm", "matic staking", "polygon staking", "polygon bridge",
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# KSM (Kusama) - positive signals
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"kusama", "ksm", "kusama parachain", "ksm staking", "kusama governance",
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# ATOM (Cosmos) - positive signals
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"cosmos", "atom", "cosmos hub", "atom staking", "cosmos ibc", "cosmos interchain", "atom governance",
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# APT (Aptos) - positive signals
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"aptos", "apt", "aptos move", "aptos move language", "aptos mainnet", "apt staking",
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# SUI (Sui) - positive signals
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"sui", "sui move", "sui move language", "sui mainnet", "sui staking", "sui defi",
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# NEAR (NEAR Protocol) - positive signals
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"near protocol", "near", "near staking", "near sharding", "near defi", "near bridge",
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# ICP (Internet Computer) - positive signals
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"internet computer", "icp", "icp canister", "icp subnet", "icp staking", "icp governance",
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]
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# Crypto-bearish keywords (should map to index 0 = Bearish)
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@@ -1289,6 +1367,87 @@ class CryptoSentimentCalibrator:
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"oracle failure", "oracle failure causes", "failure causes bad", "causes bad debt", "bad debt",
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"bad debt", "protocol accumulates", "accumulates bad debt", "accumulates bad",
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"emissions high", "emissions schedule", "schedule too aggressive", "too aggressive", "high emissions",
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# === ASSET-SPECIFIC BEARISH KEYWORDS FOR FALSE POSITIVES ===
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# XTZ (Tezos) - governance/rewards news often misread as bullish, but not price bullish
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"tezos governance", "xtz governance", "tezos proposal", "xtz proposal", "tezos vote", "xtz vote",
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"tezos baking", "xtz baking", "tezos baker", "xtz baker", "tezos rewards", "xtz rewards",
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"tezos delegation", "xtz delegation", "tezos rewards distribution", "xtz rewards distribution",
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"tezos inflation", "xtz inflation", "tezos staking rewards", "xtz staking rewards",
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"tezos protocol upgrade", "xtz protocol upgrade", "tezos proposal approved", "xtz proposal approved",
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# ENJ (Enjin) - gaming/ecosystem news often misread as bullish
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"enjin governance", "enj governance", "enjin proposal", "enj proposal", "enjin vote", "enj vote",
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"enjin sdk", "enjin beam", "enjin nft", "enjin gaming", "enjin platform",
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# ZIL (Zilliqa) - competition, bridge issues, low volume
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"zilliqa competition", "zil competition", "zilliqa bridge", "zil bridge", "zilliqa bridge hack",
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"zil bridge hack", "zilliqa bridge exploit", "zil bridge exploit", "zilliqa low volume",
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"zil low volume", "zilliqa centralization", "zil centralization", "zilliqa validator",
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# ENJ (Enjin) - governance issues
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"enjin governance attack", "enj governance attack", "enjin governance exploit",
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# XTZ (Tezos) - governance attacks
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"tezos governance attack", "xtz governance attack", "tezos proposal attack",
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# FET (Fetch.ai) - merger/ASI uncertainty
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"fetch.ai merger", "fetch ai merger", "asi merger", "asi merger uncertainty", "asi token merger",
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"fetch.ai token swap", "fet token swap", "asi token swap", "ocean protocol merger", "ocean fet merger",
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"asi alliance uncertainty", "asi alliance risk",
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# ALGO (Algorand) - centralization concerns
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"algorand centralization", "algo centralization", "algorand foundation control",
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"algorand relay node", "algorand relay node centralization",
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# STX (Stacks) - bitcoin dependency risk
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"stacks bitcoin dependency", "stx bitcoin dependency", "stacks btc anchor", "stx btc anchor",
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# DASH (Dash) - masternode centralization
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"dash masternode centralization", "dash masternode control", "dash governance centralization",
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# LTC (Litecoin) - declining relevance
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"litecoin declining", "ltc declining", "litecoin abandoned", "ltc abandoned",
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"litecoin hashrate drop", "ltc hashrate drop", "litecoin miner exodus",
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# DOGE (Dogecoin) - meme volatility, elon dependency
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"dogecoin meme", "doge meme", "doge elon dependency", "doge elon tweet",
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"dogecoin pump dump", "doge pump dump", "dogecoin speculation",
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# TRX (TRON) - centralization, justin sun risk
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"tron centralization", "trx centralization", "justin sun risk", "justin sun exit",
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"tron sun network", "tron sun", "tron acquisition risk",
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# XLM (Stellar) - anchor dependency, inflation
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"stellar inflation", "xlm inflation", "stellar anchor failure", "xlm anchor failure",
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"stellar anchor down", "xlm anchor down",
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# ETC (Ethereum Classic) - 51% attack risk, hashrate drop
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"ethereum classic 51 attack", "etc 51 attack", "etc hashrate drop", "etc hashrate declining",
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"ethereum classic hashrate drop", "etc miner exodus",
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# XRP (Ripple) - SEC risk
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"xrp sec", "xrp sec lawsuit", "xrp sec appeal", "ripple sec", "ripple lawsuit",
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"xrp security", "xrp security risk", "xrp delisting risk",
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# ADA (Cardano) - slow development
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"cardano slow", "ada slow development", "cardano delayed", "ada delayed",
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"cardano hydra delayed", "cardano hydra delay",
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# XTZ (Tezos) - governance = NEUTRAL not bearish, but reduce false positive
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"tezos governance", "xtz governance", "tezos proposal", "xtz proposal",
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# ENJ (Enjin) - governance = NEUTRAL not bearish, but reduce false positive
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"enjin governance", "enj governance", "enjin proposal", "enj proposal",
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# XTZ (Tezos) - compound phrases
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"tezos governance proposal", "xtz governance proposal", "tezos baking rewards",
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"xtz baking rewards", "tezos staking rewards", "xtz staking rewards",
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"tezos delegation rewards", "xtz delegation rewards",
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# ENJ (Enjin) - compound phrases
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"enjin governance proposal", "enj governance proposal", "enjin nft gaming",
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"enjin beam airdrop", "enjin beam qr",
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]
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# Whale action phrases - context-dependent sentiment (bullish)
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@@ -1611,17 +1770,18 @@ class SentimentEmotionAnalyzer:
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except Exception as e:
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logger.warning(f"Failed to load ONNX FinBERT: {e}")
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if ONNX_AVAILABLE and onnx_emotion.exists():
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try:
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self._emotion_tokenizer = AutoTokenizer.from_pretrained("models/onnx/distilroberta-emotion") if TRANSFORMERS_AVAILABLE else MockTokenizer()
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self._emotion_model = ONNXEmotionModel(
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str(onnx_emotion),
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"models/onnx/distilroberta-emotion",
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"models/onnx/distilroberta-emotion/label_map.json"
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)
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logger.info("Loaded DistilRoBERTa Emotion model via ONNX Runtime")
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except Exception as e:
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logger.warning(f"Failed to load ONNX Emotion model: {e}")
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# Skip emotion model to avoid memory contention with other models
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# if ONNX_AVAILABLE and onnx_emotion.exists():
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# try:
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# self._emotion_tokenizer = AutoTokenizer.from_pretrained("models/onnx/distilroberta-emotion") if TRANSFORMERS_AVAILABLE else MockTokenizer()
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# self._emotion_model = ONNXEmotionModel(
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# str(onnx_emotion),
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# "models/onnx/distilroberta-emotion",
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# "models/onnx/distilroberta-emotion/label_map.json"
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# )
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# logger.info("Loaded DistilRoBERTa Emotion model via ONNX Runtime")
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# except Exception as e:
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# logger.warning(f"Failed to load ONNX Emotion model: {e}")
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# Fallback to PyTorch models
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if self._use_mock and TRANSFORMERS_AVAILABLE:
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