done
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import json
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import logging
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from typing import Optional
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import anthropic
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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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from typing import Optional
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_client: Optional[anthropic.AsyncAnthropic] = None
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_client: Optional[AsyncOpenAI] = None
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SYSTEM_PROMPT = (
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"You are a crypto trading signal analyst. Analyze Donald Trump's social media posts "
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"and determine their likely impact on cryptocurrency markets. "
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"Return only valid JSON with no additional text or markdown."
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)
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SYSTEM_PROMPT = """You are an expert macro trader analyzing Trump's Truth Social posts for real-time crypto trading signals.
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USER_PROMPT_TEMPLATE = """Analyze this Trump post for cryptocurrency trading signals.
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CORE ASSUMPTION: Treat every post as BREAKING NEWS. Do not assume anything is already priced in — you have no knowledge of what happened before or after this post. Your job is to evaluate the post content only.
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Post: {text}
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=== BULLISH TRANSMISSION CHAINS (BTC/ETH go UP) ===
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• Ceasefire / peace deal / de-escalation / conflict ending
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→ war-risk premium unwinds → oil stabilizes → USD softens → risk-on → BTC/ETH rally
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• Pro-crypto executive action / legislation / reserve
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→ regulatory tailwind + direct demand → BTC up immediately
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• Dollar weakness (deficit spending, tariff concessions, Fed rate cut signals)
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→ hard asset bid → BTC as digital gold
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• Trade deal / tariff reduction announcement
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→ global growth outlook improves → risk appetite rises → BTC/ETH up
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• Strait of Hormuz open / oil supply stable
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→ energy prices moderate → inflation fears drop → risk-on
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Respond with JSON only:
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=== BEARISH TRANSMISSION CHAINS (BTC/ETH go DOWN) ===
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• War escalation / military strikes / ceasefire violation
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→ risk-off panic → crypto liquidations → sharp BTC/ETH drop
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• Strait of Hormuz threatened / blocked / mined
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→ oil price spike → inflation surge → Fed tightening fears → risk-off
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• SEC/DOJ crypto enforcement / new crypto regulation
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→ direct selling pressure → BTC/ETH down
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• Tariff escalation / new sanctions / trade war
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→ growth fears + USD safe-haven bid → crypto outflows
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• New military front / ally breakdown / nuclear threat
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→ extreme risk-off → everything sells
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=== WHAT IS NOT RELEVANT ===
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• Retweets with only a URL and no added comment (RT: https://...)
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• Media/political attacks with no policy content
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• Personal endorsements, rallies, awards, domestic court cases
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• Pure domestic politics (abortion, immigration) with no macro angle
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• UFO files, sports, entertainment, holidays
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=== SIGNAL TAXONOMY (CRITICAL — do not conflate) ===
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Each signal is a distinct trading action. Choose exactly one.
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• "buy" — OPEN A NEW LONG. Use when the post is a FRESH bullish catalyst that
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is likely to push price UP in the next 5–60 minutes. Example:
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"Confirmed ceasefire with Iran", "Crypto reserve executive order signed."
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→ Expected move: price rises. Directional accuracy = price > entry.
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• "sell" — CLOSE AN EXISTING LONG / DE-RISK. Use when the post WEAKENS a prior
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bullish thesis but is NOT strong enough to justify an active short.
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Think: "take profit / step aside." Examples:
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"Ceasefire talks delayed", "Hinting at new tariffs (vague)",
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"Crypto-friendly nominee withdrawn." Ambiguous bearish.
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→ Use ONLY if you would exit longs but not open shorts.
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→ Directional accuracy = price < entry (same as short, but lower conviction).
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• "short"— OPEN A NEW SHORT. Use only for a FRESH bearish catalyst strong enough
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that you would actively bet on price falling. Examples:
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"Military strike on Iran launched", "Strait of Hormuz mined",
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"SEC lawsuit against major exchange announced."
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→ Expected move: price drops hard. Reserve for high-conviction bearish.
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• "hold" — NO TRADE. Post is irrelevant, or macro-relevant but ambiguous in
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direction, or confidence too low to act. DEFAULT when in doubt.
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Decision tree:
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1. Is there a concrete macro/crypto event? NO → hold.
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2. Is the direction clear? NO → hold.
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3. BULLISH: confidence ≥ 60 → buy. Else → hold.
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4. BEARISH: strong/explicit (war, ban, sanctions, enforcement) → short.
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weak/vague/partial walkback of bullish → sell.
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otherwise → hold.
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NEVER use "sell" for a strong bearish event — that is "short".
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NEVER use "short" for a vague/ambiguous negative — that is "sell" or "hold".
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=== CONFIDENCE CALIBRATION ===
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80-100: Explicit crypto/monetary policy action; confirmed ceasefire with named parties; Strait of Hormuz status confirmed; named trade deal signed
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60-79: Clear new geopolitical event with specific details (named countries, named actions); direct risk-on/off chain
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40-59: Probable macro relevance but vague details or highly indirect effect
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20-39: Possible relevance, highly uncertain
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0-19: Mark as not relevant instead
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=== SIGNAL CALIBRATION (critical — read before deciding) ===
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DEFAULT is HOLD. Only 5–10% of posts should receive buy or short.
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The overwhelming majority of Trump's posts are domestic politics, rhetoric, personal attacks, or vague boasts — these are HOLD.
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Use "buy" only when ALL of the following are true:
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1. The event is CONCRETE (named countries, named action, specific policy)
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2. The macro transmission chain to BTC/ETH is DIRECT and SHORT (< 2 steps)
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3. Your confidence is ≥ 75
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Use "short" only when ALL of the following are true:
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1. A hard bearish event is CONFIRMED (not speculated): verified military strike, enacted tariff, filed lawsuit
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2. The transmission chain to BTC/ETH down is DIRECT
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3. Your confidence is ≥ 80
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Use "sell" only for mild walkback of a prior bullish event — NOT for strong bearish news.
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When in doubt between buy and hold → choose HOLD.
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When in doubt between short and sell → choose SELL or HOLD, not short.
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Return ONLY valid JSON. No markdown.
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Return ONLY valid JSON. No markdown."""
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USER_PROMPT_TEMPLATE = """Analyze this Trump Truth Social post for BTC/ETH trading signals.
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Treat it as breaking news — evaluate only what is written.
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POST TEXT:
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{text}
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Respond with JSON:
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{{
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"relevant": <true if this post could affect crypto/macro markets>,
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"asset": "BTC" | "ETH" | null,
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"relevant": <true if post contains ANY concrete macro/geopolitical/crypto information>,
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"asset": "BTC" | "ETH" | "BOTH" | null,
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"sentiment": "bullish" | "bearish" | "neutral",
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"signal": "buy" | "sell" | "short" | "hold",
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"confidence": <0-100>,
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"reasoning": "<1-2 sentences explaining the signal and why>"
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"reasoning": "<What specific event is described → macro transmission chain → expected market direction → WHY this signal and NOT the adjacent one (e.g. 'short not sell because strike is confirmed', 'sell not short because only a walkback of prior bullish headline')>"
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}}
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Signal rules:
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- "buy": bullish crypto/macro signal → expect price rise → go long
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- "sell": bearish signal for existing longs → exit position
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- "short": strong bearish signal → expect price drop → go short
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- "hold": relevant but unclear direction, or neutral macro
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If post is only a URL, only a retweet link, or purely personal/domestic with zero macro angle: set relevant=false, signal=hold, confidence=0."""
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Bullish examples: pro-crypto policy, BTC reserve, anti-regulation, dollar weakness, tariff deal, market optimism
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Bearish examples: SEC crackdowns, war escalation, economic sanctions, crypto ban threats, crisis
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Not relevant: personal attacks, sports, endorsements, unrelated politics
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Be strict on relevance — most posts are NOT relevant to crypto."""
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ANALYSIS_VERSION = "v4-selective"
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_FALLBACK = {
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"relevant": False,
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@@ -49,36 +137,50 @@ _FALLBACK = {
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"signal": "hold",
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"confidence": 0,
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"reasoning": "",
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"prefilter_reason": None,
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"analysis_version": ANALYSIS_VERSION,
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}
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def _get_client() -> anthropic.AsyncAnthropic:
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def _fallback(prefilter: Optional[str] = None, reasoning: str = "") -> dict:
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out = dict(_FALLBACK)
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out["prefilter_reason"] = prefilter
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out["reasoning"] = reasoning
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return out
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def _get_client() -> AsyncOpenAI:
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global _client
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if _client is None:
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_client = anthropic.AsyncAnthropic(api_key=settings.anthropic_api_key)
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_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 _client
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async def analyze_post(text: str) -> dict:
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"""Run Claude signal analysis on a Trump post.
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# Fast pre-filter: pure RT/URL with no content
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stripped = text.strip()
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if stripped.startswith("RT: https://") and len(stripped) < 60:
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return _fallback("rt_only", "Pre-filtered: retweet with no added commentary.")
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if stripped.startswith("https://") and " " not in stripped:
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return _fallback("url_only", "Pre-filtered: bare URL with no text content.")
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if not stripped:
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return _fallback("empty", "Pre-filtered: empty post body.")
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Returns dict with keys: relevant, asset, sentiment, signal, confidence, reasoning.
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Falls back to neutral hold on any error.
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"""
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try:
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client = _get_client()
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message = await client.messages.create(
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model="claude-haiku-4-5-20251001",
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max_tokens=300,
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system=SYSTEM_PROMPT,
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response = await client.chat.completions.create(
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model=settings.ai_model,
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max_tokens=450,
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temperature=0.1,
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messages=[
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{
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"role": "user",
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"content": USER_PROMPT_TEMPLATE.format(text=text[:2000]),
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}
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{"role": "system", "content": SYSTEM_PROMPT},
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{"role": "user", "content": USER_PROMPT_TEMPLATE.format(text=text[:2000])},
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],
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)
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raw = message.content[0].text.strip()
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raw = response.choices[0].message.content.strip()
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if raw.startswith("```"):
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lines = raw.split("\n")
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@@ -100,10 +202,12 @@ async def analyze_post(text: str) -> dict:
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relevant = bool(result.get("relevant", False))
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asset = result.get("asset")
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if asset == "BOTH":
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asset = "BTC"
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if asset not in ("BTC", "ETH", None):
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asset = None
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reasoning = str(result.get("reasoning", ""))[:500]
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reasoning = str(result.get("reasoning", ""))[:600]
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return {
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"relevant": relevant,
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@@ -112,14 +216,13 @@ async def analyze_post(text: str) -> dict:
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"signal": signal,
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"confidence": confidence,
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"reasoning": reasoning,
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"prefilter_reason": None,
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"analysis_version": ANALYSIS_VERSION,
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}
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except anthropic.APIError as exc:
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logger.error("Anthropic API error: %s", exc)
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return dict(_FALLBACK)
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except json.JSONDecodeError as exc:
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logger.error("Failed to parse Claude JSON response: %s", exc)
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return dict(_FALLBACK)
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logger.error("Failed to parse AI JSON: %s", exc)
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return _fallback("parse_error", f"AI returned unparseable JSON: {exc}")
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except Exception as exc:
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logger.error("Unexpected error in analyze_post: %s", exc)
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return dict(_FALLBACK)
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logger.error("analyze_post error: %s", exc)
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return _fallback("api_error", f"AI API error: {exc}")
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