fix: pre-launch hardening — HYPE price feed, KOL wallet cleanup, Telegram Trump alert, rate limiting, brittle test
Batch of the pre-launch audit campaign (BUG-01…14 plus three new features): Pricing / TP-SL protection - Add app/services/hl_price_feed.py: supplemental HL allMids poller for HL-native assets (HYPE, PURR) not listed on Binance. Pumps price_store + tp_sl_monitor.on_price_tick so bot trades on these assets keep full stop-loss / take-profit / trailing protection instead of max-hold only. - Wire feed into main.py lifespan (startup task + graceful shutdown cancel). Telegram - Add format_trump_mention + PATH B in _dispatch: crypto-relevant Trump posts with no directional signal (relevant=True, signal=hold) now alert the public channel only (no per-subscriber noise). - Rate limiter (slowapi) on the API; assorted bot/digest fixes. KOL on-chain - seed_kol_wallets.py: KOL_FEEDS coverage cross-check; reversibly deactivate orphaned wallets (handle not in KOL_FEEDS → can never produce divergence) so the scanner stops burning cycles on them. Tests / misc - Fix brittle test_macro_ahr999_uses_same_formula_as_scanner: mock now uses realistic ms timestamps so the in-progress-day drop fires, matching the fetcher's bar count (was 0.3179 vs 0.3178 off-by-one). - Refresh stale notify_signal comment in truth_social.py. Frontend reduce-action type fix lives in the sibling repo. Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
This commit is contained in:
k
@@ -0,0 +1,509 @@
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"""
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X (Twitter) post semantic analysis — KOL real-time signals.
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X posts are fundamentally different from Substack long-form articles:
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- 280 chars: conclusion IS the content, no room for hedging
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- Latency matters: "just bought SOL" is a minutes-level signal
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- Noise ratio is extreme: 95%+ of posts are irrelevant
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- Retweet/quote patterns must be detected and handled differently
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- Position statements ("added", "trimmed", "exit") are high-value
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- Thread context matters: a post may continue a thought from above
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Design philosophy:
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- Strict NOISE default (opposite of buy/sell). Most X posts should
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be filtered out. The cost of false-positive on X is high because
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KOLs tweet constantly.
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- Three tiers of output:
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TRADE_SIGNAL → actionable now (position statement + specific asset)
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DIRECTIONAL → clear view, no explicit position action
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NOISE → everything else (no tickers, no stance, filler)
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- talks_vs_trades_flag: X posts often reveal real positions
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("taking profits" while publicly bullish = divergence)
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Output feeds into kol_divergence.py for cross-referencing with on-chain.
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"""
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from __future__ import annotations
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import json
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import logging
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from datetime import datetime, timezone
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from typing import Optional
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from openai import AsyncOpenAI
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from app.config import settings
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logger = logging.getLogger(__name__)
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ANALYSIS_VERSION = "x-v1"
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ANTHROPIC_MODEL = "claude-haiku-4-5-20251001"
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_anthropic_client = None
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_openai_client: Optional[AsyncOpenAI] = None
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def _use_anthropic() -> bool:
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return bool(settings.anthropic_api_key)
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def _anth():
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global _anthropic_client
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if _anthropic_client is None:
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import anthropic as _a
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_anthropic_client = _a.AsyncAnthropic(api_key=settings.anthropic_api_key)
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return _anthropic_client
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def _oai() -> AsyncOpenAI:
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global _openai_client
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if _openai_client is None:
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_openai_client = AsyncOpenAI(
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api_key=settings.ai_api_key,
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base_url=settings.ai_base_url,
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)
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return _openai_client
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# ─────────────────────────────────────────────────────────────────────
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# SYSTEM PROMPT
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# ─────────────────────────────────────────────────────────────────────
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SYSTEM_PROMPT = """\
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You are a signal extraction system for a crypto trading platform. You read
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X (Twitter) posts from known crypto KOLs and decide whether they contain
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a tradeable signal.
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═══════════════════════════════════════════════════════════════════════
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NOISE IS THE DEFAULT — internalize this
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═══════════════════════════════════════════════════════════════════════
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KOLs post 20-50 times per day. Most of it is:
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- gm / wagmi / vibes / lifestyle
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- macro commentary with no specific call
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- reactions to news without a position
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- vague encouragement ("BTC is king")
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- promotional content / sponsored
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- replies to followers (context-dependent, usually not standalone)
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- jokes, memes, personal life
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ALL of the above → tier: "noise", tickers: []
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Only extract signals when the post contains CLEAR, EXPLICIT information
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about what the KOL is doing or believes RIGHT NOW. Ambiguity → noise.
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═══════════════════════════════════════════════════════════════════════
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THREE SIGNAL TIERS
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═══════════════════════════════════════════════════════════════════════
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TIER 1 — TRADE_SIGNAL (rarest, highest value)
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The KOL states an ACTUAL POSITION ACTION in this post:
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"just bought", "added more", "long from here", "trimming my",
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"sold my", "exit", "took profits", "cutting", "building position",
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"DCA'd", "我建仓了", "已经上车", "减仓了", "清仓了"
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Must reference a SPECIFIC asset (not just "the market").
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Conviction ≥ 0.7 required for TRADE_SIGNAL.
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TIER 2 — DIRECTIONAL (moderate value)
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The KOL expresses a SPECIFIC, CURRENT directional view on a named asset:
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"SOL looking strong here", "ETH is going to $5k", "BTC at support",
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"I think [TICKER] breaks down", "watching [TICKER] for entry"
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No explicit position action, but a clear current opinion.
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Conviction 0.4–0.7 typical.
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TIER 3 — NOISE (default)
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Everything else. When in doubt, NOISE.
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═══════════════════════════════════════════════════════════════════════
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POST TYPE DETECTION — apply before scoring
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═══════════════════════════════════════════════════════════════════════
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Detect what kind of post this is before scoring content:
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"original" — KOL's own thought, highest signal value
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"reply" — reply to another user (context missing → usually noise
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unless the post is fully self-contained)
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"retweet" — RT of someone else's post without commentary → NOISE
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"quote" — RT with commentary → score the commentary only,
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ignore the original post content
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"thread_cont"— continues a thread (may lack context → lower conviction)
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Retweets without commentary are ALWAYS noise regardless of content.
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═══════════════════════════════════════════════════════════════════════
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TALKS VS TRADES FLAG — the platform's core value
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═══════════════════════════════════════════════════════════════════════
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Set talks_vs_trades_flag=true when you detect a MISMATCH between:
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- What the KOL says publicly (bullish/bearish narrative)
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- What they reveal about their ACTUAL position in the same post
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Classic divergence patterns in X posts:
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1. "BTC is going to $200k 🚀" + "took some chips off the table"
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→ Narrative: ultra bullish. Action: selling. FLAG.
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2. "This market is trash, crypto is dead" + "accumulated more $ETH"
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→ Narrative: bearish. Action: buying. FLAG.
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3. "Stay strong, don't sell!" + reveals they have <5% allocation
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→ Narrative: encouraging others to hold. Position: minimal. FLAG.
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4. "Not financial advice but..." followed by extreme conviction call
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→ Common hedge used right before a large directional call. Reduce
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conviction by 0.1. Not a flag by itself.
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5. "I was wrong about X, but now I think Y"
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→ Explicit reversal/stance_change. Mark stance_change=true.
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═══════════════════════════════════════════════════════════════════════
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CRYPTO SLANG DECODER — handle these correctly
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═══════════════════════════════════════════════════════════════════════
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"aping in" / "aped" → bought (often large, impulsive)
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"degen'd" → took a risky position
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"paper hands" → sold too early (about someone else, not actionable)
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"diamond hands" → holding through drawdown (not a new position)
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"ngmi" → bearish on a token or person
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"wagmi" → general optimism, NOT a signal
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"rekt" → lost money, position closed
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"accumulated" / "acc" → bought (ongoing or past)
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"trimmed" / "trim" → partially sold
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"bags" / "holding bags"→ holding a position
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"flipped" → changed direction (stance_change=true)
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"this is the one" / "THE entry" → high conviction call
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"under the radar" → bullish on an obscure asset
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"cook" → doing something well, bullish signal about a project
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"cooked" (about a token) → bearish, likely dying/failed
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═══════════════════════════════════════════════════════════════════════
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EXAMPLES — calibrate against these
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═══════════════════════════════════════════════════════════════════════
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[TRADE_SIGNAL — fire]
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POST: "Aped into $SOL at $145. Full size. We go."
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→ tier: "trade_signal", action: "buy", asset: SOL, conviction: 0.92,
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timeframe: "immediate", talks_vs_trades_flag: false
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POST: "Trimming half my $ETH here. Not selling the thesis but locking
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profits at 3x. Will re-add lower."
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→ tier: "trade_signal", action: "reduce", asset: ETH, conviction: 0.85,
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timeframe: "immediate", talks_vs_trades_flag: false
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POST: "This is cooked. Sold everything. Moving to stable until macro clears."
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→ tier: "trade_signal", action: "sell", asset: null (multiple/all),
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conviction: 0.88, timeframe: "immediate"
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[DIRECTIONAL — extract but lower weight]
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POST: "SOL is setting up for a breakout. $180 is the line to watch."
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→ tier: "directional", action: "bullish", asset: SOL, conviction: 0.58,
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timeframe: "days"
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POST: "ETH dominance will crush alts this cycle. The flippening is real."
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→ tier: "directional", action: "bullish", asset: ETH, conviction: 0.52,
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timeframe: "months"
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[NOISE — output noise, empty tickers]
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POST: "gm everyone 🌅"
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→ tier: "noise", tickers: []
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POST: "The market is wild lmao. Stay safe everyone."
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→ tier: "noise", tickers: []
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POST: "Interesting take by @SomeAnalyst on the Fed" [with RT of article]
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→ tier: "noise" (retweet of someone else, no original content)
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POST: "Not financial advice but BTC is really interesting here 👀"
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→ tier: "noise" (too vague, "interesting" is not a stance)
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POST: "Just attended [Conference]. Amazing speakers. Building in crypto
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is incredible."
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→ tier: "noise" (no market signal)
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═══════════════════════════════════════════════════════════════════════
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OUTPUT FORMAT (strict JSON, no markdown)
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═══════════════════════════════════════════════════════════════════════
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{
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"post_type": "original" | "reply" | "retweet" | "quote" | "thread_cont",
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"tier": "trade_signal" | "directional" | "noise",
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"summary": "<one sentence in ENGLISH, ≤80 chars. State what the KOL
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is saying/doing. 'Noise: gm post' if tier is noise.>",
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"tickers": [
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{
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"ticker": "<UPPERCASE symbol>",
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"action": "buy" | "sell" | "reduce" | "bullish" | "bearish" | "mention",
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"conviction": <float 0.0-1.0>,
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"timeframe": "immediate" | "hours" | "days" | "weeks" | "months" | "unspecified",
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"stance_change": <true if this reverses a previously stated position in this post>,
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"quote": "<verbatim phrase from the post supporting this, ≤100 chars>"
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}
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],
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"talks_vs_trades_flag": <true | false>,
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"has_price_target": <true if a specific price level is mentioned>,
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"price_targets": [
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{ "ticker": "SOL", "price": 180, "direction": "up" | "down" }
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],
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"sentiment": "bullish" | "bearish" | "neutral",
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"reasoning": "<one sentence: why this tier? What specific phrase drove the decision?>"
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}
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HARD RULES:
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• tier == "noise" → tickers MUST be [], talks_vs_trades_flag MUST be false
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• tier == "trade_signal" → at least one ticker with action in {buy, sell, reduce}
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AND conviction ≥ 0.7
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• post_type == "retweet" (RT without commentary) → tier MUST be "noise"
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• If no explicit price target → price_targets: []
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• conviction < 0.4 → tier cannot be "trade_signal"
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"""
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# ─────────────────────────────────────────────────────────────────────
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# USER PROMPT TEMPLATE
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# ─────────────────────────────────────────────────────────────────────
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USER_TEMPLATE = """\
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KOL handle: @{handle}
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Follower tier: {follower_tier}
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Post time (UTC): {posted_at}
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Current UTC hour: {hour} ({liquidity_note})
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|
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POST:
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\"\"\"{text}\"\"\"
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{thread_context}
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Score this post. Default to NOISE unless there is explicit, specific signal."""
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# ─────────────────────────────────────────────────────────────────────
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# Helpers
|
||||
# ─────────────────────────────────────────────────────────────────────
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def _liquidity_note(hour: int) -> str:
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if 3 <= hour < 9:
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return "Asia overnight — thin liquidity, be extra strict"
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||||
if 13 <= hour < 21:
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||||
return "US session — normal strictness"
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||||
return "Off-peak hours"
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||||
|
||||
|
||||
def _follower_tier(follower_count: Optional[int]) -> str:
|
||||
if follower_count is None:
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||||
return "unknown"
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||||
if follower_count >= 500_000:
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||||
return "mega (500k+)"
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||||
if follower_count >= 100_000:
|
||||
return "large (100k-500k)"
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||||
if follower_count >= 20_000:
|
||||
return "mid (20k-100k)"
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||||
return "small (<20k)"
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||||
|
||||
|
||||
_FALLBACK = {
|
||||
"post_type": "original",
|
||||
"tier": "noise",
|
||||
"summary": None,
|
||||
"tickers": [],
|
||||
"talks_vs_trades_flag": False,
|
||||
"has_price_target": False,
|
||||
"price_targets": [],
|
||||
"sentiment": "neutral",
|
||||
"reasoning": "",
|
||||
"model": None,
|
||||
"version": ANALYSIS_VERSION,
|
||||
"error": None,
|
||||
}
|
||||
|
||||
VALID_ACTIONS = {"buy", "sell", "reduce", "bullish", "bearish", "mention"}
|
||||
VALID_TIMEFRAMES = {"immediate", "hours", "days", "weeks", "months", "unspecified"}
|
||||
VALID_TIERS = {"trade_signal", "directional", "noise"}
|
||||
VALID_POST_TYPES = {"original", "reply", "retweet", "quote", "thread_cont"}
|
||||
|
||||
|
||||
async def analyze_x_post(
|
||||
*,
|
||||
handle: str,
|
||||
text: str,
|
||||
posted_at: Optional[str] = None,
|
||||
follower_count: Optional[int] = None,
|
||||
thread_context: Optional[str] = None,
|
||||
model: Optional[str] = None,
|
||||
) -> dict:
|
||||
"""Score an X post from a crypto KOL.
|
||||
|
||||
Args:
|
||||
handle: Twitter/X handle (without @)
|
||||
text: Post text (already stripped of URLs if desired)
|
||||
posted_at: ISO UTC timestamp of the post
|
||||
follower_count: Follower count for context (affects tier label)
|
||||
thread_context: Optional: preceding posts in thread, ≤500 chars
|
||||
model: Override model. Defaults to ai_model (quality path).
|
||||
|
||||
Returns dict with: post_type, tier, summary, tickers, talks_vs_trades_flag,
|
||||
has_price_target, price_targets, sentiment, reasoning, model, version.
|
||||
Errors return a noise-safe fallback (never raises).
|
||||
"""
|
||||
stripped = (text or "").strip()
|
||||
if not stripped:
|
||||
out = dict(_FALLBACK)
|
||||
out["error"] = "empty post"
|
||||
return out
|
||||
|
||||
# Fast pre-filter: bare RT with no added text is always noise
|
||||
low = stripped.lower()
|
||||
if low.startswith("rt @") and len(stripped) < 300:
|
||||
out = dict(_FALLBACK)
|
||||
out["post_type"] = "retweet"
|
||||
out["reasoning"] = "Pre-filtered: bare retweet with no commentary."
|
||||
return out
|
||||
|
||||
hour = datetime.now(timezone.utc).hour
|
||||
thread_block = (
|
||||
f"Thread context (preceding posts):\n\"\"\"\n{thread_context[:500]}\n\"\"\""
|
||||
if thread_context else ""
|
||||
)
|
||||
|
||||
user_prompt = USER_TEMPLATE.format(
|
||||
handle=handle,
|
||||
follower_tier=_follower_tier(follower_count),
|
||||
posted_at=posted_at or "unknown",
|
||||
hour=hour,
|
||||
liquidity_note=_liquidity_note(hour),
|
||||
text=stripped[:1000],
|
||||
thread_context=thread_block,
|
||||
)
|
||||
|
||||
use_anth = _use_anthropic()
|
||||
if model is None:
|
||||
# X analysis is near-real-time but less latency-critical than Trump.
|
||||
# Use the quality model for better signal/noise discrimination.
|
||||
model = ANTHROPIC_MODEL if use_anth else settings.ai_model
|
||||
|
||||
try:
|
||||
if use_anth:
|
||||
msg = await _anth().messages.create(
|
||||
model=model,
|
||||
max_tokens=800,
|
||||
temperature=0.1,
|
||||
system=SYSTEM_PROMPT,
|
||||
messages=[{"role": "user", "content": user_prompt}],
|
||||
)
|
||||
raw = (msg.content[0].text if msg.content else "").strip()
|
||||
else:
|
||||
is_reasoning = any(x in model for x in ("pro", "reasoner", "r1", "think"))
|
||||
kwargs: dict = {
|
||||
"model": model,
|
||||
"messages": [
|
||||
{"role": "system", "content": SYSTEM_PROMPT},
|
||||
{"role": "user", "content": user_prompt},
|
||||
],
|
||||
"max_tokens": 2000 if is_reasoning else 800,
|
||||
}
|
||||
if not is_reasoning:
|
||||
kwargs["temperature"] = 0.1
|
||||
kwargs["response_format"] = {"type": "json_object"}
|
||||
resp = await _oai().chat.completions.create(**kwargs)
|
||||
raw = (resp.choices[0].message.content or "").strip()
|
||||
|
||||
# Strip fences
|
||||
if raw.startswith("```"):
|
||||
lines = raw.split("\n")
|
||||
raw = "\n".join(lines[1:-1] if lines[-1].strip() == "```" else lines[1:])
|
||||
|
||||
result = json.loads(raw)
|
||||
|
||||
except json.JSONDecodeError as exc:
|
||||
logger.error("x_analysis JSON parse error for @%s: %s", handle, exc)
|
||||
out = dict(_FALLBACK)
|
||||
out["error"] = f"parse_error: {exc}"
|
||||
return out
|
||||
except Exception as exc:
|
||||
logger.error("x_analysis API error for @%s: %s", handle, exc)
|
||||
out = dict(_FALLBACK)
|
||||
out["error"] = f"api_error: {exc}"
|
||||
return out
|
||||
|
||||
# ── Normalize ────────────────────────────────────────────────────
|
||||
post_type = (result.get("post_type") or "original").lower()
|
||||
if post_type not in VALID_POST_TYPES:
|
||||
post_type = "original"
|
||||
|
||||
tier = (result.get("tier") or "noise").lower()
|
||||
if tier not in VALID_TIERS:
|
||||
tier = "noise"
|
||||
|
||||
# Enforce: retweet → noise
|
||||
if post_type == "retweet":
|
||||
tier = "noise"
|
||||
|
||||
# Normalize tickers
|
||||
raw_tickers = result.get("tickers") or []
|
||||
cleaned_tickers = []
|
||||
if tier != "noise":
|
||||
for t in raw_tickers:
|
||||
if not isinstance(t, dict):
|
||||
continue
|
||||
sym = (t.get("ticker") or "").strip().upper()
|
||||
if not sym or len(sym) > 12:
|
||||
continue
|
||||
action = (t.get("action") or "mention").lower()
|
||||
if action not in VALID_ACTIONS:
|
||||
action = "mention"
|
||||
try:
|
||||
conv = float(t.get("conviction") or 0)
|
||||
except (TypeError, ValueError):
|
||||
conv = 0.0
|
||||
conv = max(0.0, min(1.0, conv))
|
||||
timeframe = (t.get("timeframe") or "unspecified").lower()
|
||||
if timeframe not in VALID_TIMEFRAMES:
|
||||
timeframe = "unspecified"
|
||||
cleaned_tickers.append({
|
||||
"ticker": sym,
|
||||
"action": action,
|
||||
"conviction": round(conv, 2),
|
||||
"timeframe": timeframe,
|
||||
"stance_change": bool(t.get("stance_change", False)),
|
||||
"quote": (t.get("quote") or "")[:100],
|
||||
})
|
||||
|
||||
# Enforce: trade_signal requires ≥1 ticker with buy/sell/reduce + conviction ≥ 0.7
|
||||
if tier == "trade_signal":
|
||||
strong = [
|
||||
t for t in cleaned_tickers
|
||||
if t["action"] in {"buy", "sell", "reduce"} and t["conviction"] >= 0.7
|
||||
]
|
||||
if not strong:
|
||||
tier = "directional" # downgrade rather than drop
|
||||
|
||||
# Enforce: noise → empty tickers
|
||||
if tier == "noise":
|
||||
cleaned_tickers = []
|
||||
|
||||
sentiment = (result.get("sentiment") or "neutral").lower()
|
||||
if sentiment not in ("bullish", "bearish", "neutral"):
|
||||
sentiment = "neutral"
|
||||
|
||||
talks_vs_trades = bool(result.get("talks_vs_trades_flag", False))
|
||||
if tier == "noise":
|
||||
talks_vs_trades = False
|
||||
|
||||
# Price targets
|
||||
has_price_target = bool(result.get("has_price_target", False))
|
||||
raw_pts = result.get("price_targets") or []
|
||||
price_targets = []
|
||||
for pt in raw_pts:
|
||||
if not isinstance(pt, dict):
|
||||
continue
|
||||
ticker = (pt.get("ticker") or "").upper()
|
||||
try:
|
||||
price = float(pt.get("price") or 0)
|
||||
except (TypeError, ValueError):
|
||||
continue
|
||||
direction = (pt.get("direction") or "up").lower()
|
||||
if ticker and price > 0 and direction in ("up", "down"):
|
||||
price_targets.append({"ticker": ticker, "price": price, "direction": direction})
|
||||
if not price_targets:
|
||||
has_price_target = False
|
||||
|
||||
return {
|
||||
"post_type": post_type,
|
||||
"tier": tier,
|
||||
"summary": (result.get("summary") or "").strip() or None,
|
||||
"tickers": cleaned_tickers,
|
||||
"talks_vs_trades_flag": talks_vs_trades,
|
||||
"has_price_target": has_price_target,
|
||||
"price_targets": price_targets,
|
||||
"sentiment": sentiment,
|
||||
"reasoning": str(result.get("reasoning", ""))[:500],
|
||||
"model": model,
|
||||
"version": ANALYSIS_VERSION,
|
||||
"error": None,
|
||||
}
|
||||
Reference in New Issue
Block a user