merge: chore/cleanup-remove-bloat-and-secrets into main

app/routers/sentiment.py

@@ -0,0 +1,129 @@
+"""Sentiment pipeline — X/Twitter + Reddit crypto mentions → NLP scoring."""
+
+import os
+import re
+from datetime import UTC, datetime
+
+import httpx
+from fastapi import APIRouter
+
+router = APIRouter(prefix="/api/v1/sentiment", tags=["sentiment"])
+
+SEARXNG = os.getenv("SEARXNG_URL", "http://localhost:8088")
+
+POSITIVE_WORDS = {
+    "bullish",
+    "moon",
+    "pump",
+    "gem",
+    "buy",
+    "long",
+    "green",
+    "ATH",
+    "breakout",
+    "accumulation",
+    "undervalued",
+    "partnership",
+    "listed",
+    "launch",
+    "mainnet",
+}
+NEGATIVE_WORDS = {
+    "bearish",
+    "dump",
+    "rug",
+    "scam",
+    "sell",
+    "short",
+    "red",
+    "crash",
+    "hack",
+    "exploit",
+    "FUD",
+    "dead",
+    "delist",
+    "bankrupt",
+    "SEC",
+}
+
+
+def _score_text(text: str) -> dict:
+    words = set(re.findall(r"\b\w+\b", text.lower()))
+    pos = len(words & POSITIVE_WORDS)
+    neg = len(words & NEGATIVE_WORDS)
+    total = pos + neg
+    if total == 0:
+        return {"sentiment": "neutral", "score": 0.5, "positive": 0, "negative": 0, "total_mentions": 0}
+    score = pos / total
+    sentiment = "bullish" if score > 0.6 else "bearish" if score < 0.4 else "neutral"
+    return {"sentiment": sentiment, "score": round(score, 2), "positive": pos, "negative": neg, "total_mentions": total}
+
+
+async def _search_mentions(symbol: str, source: str = "twitter") -> list[str]:
+    """Search for crypto mentions via SearXNG."""
+    texts = []
+    try:
+        async with httpx.AsyncClient(timeout=10) as c:
+            r = await c.get(
+                f"{SEARXNG}/search",
+                params={"q": f"${symbol} crypto {source}", "format": "json", "categories": "social media"},
+            )
+            if r.status_code == 200:
+                results = r.json().get("results", [])
+                texts = [item.get("content", "") or item.get("title", "") for item in results[:20]]
+    except Exception:
+        pass
+    return texts
+
+
+@router.get("/token/{symbol}")
+async def token_sentiment(symbol: str):
+    """Get sentiment for a token across social media."""
+    texts = await _search_mentions(symbol)
+    if not texts:
+        return {"symbol": symbol, "sentiment": "unknown", "note": "No mentions found"}
+
+    all_text = " ".join(texts)
+    sentiment = _score_text(all_text)
+    sentiment["symbol"] = symbol
+    sentiment["timestamp"] = datetime.now(UTC).isoformat()
+    sentiment["sources_scanned"] = len(texts)
+
+    # Emoji representation
+    emoji = "🟢" if sentiment["sentiment"] == "bullish" else "🔴" if sentiment["sentiment"] == "bearish" else "⚪"
+    sentiment["emoji"] = emoji
+
+    return sentiment
+
+
+@router.get("/market")
+async def market_sentiment():
+    """Overall crypto market sentiment."""
+    tickers = ["BTC", "ETH", "SOL"]
+    results = {}
+    for ticker in tickers:
+        texts = await _search_mentions(ticker)
+        results[ticker] = _score_text(" ".join(texts)) if texts else {"sentiment": "unknown"}
+
+    scores = [r["score"] for r in results.values() if r.get("score")]
+    avg_score = sum(scores) / len(scores) if scores else 0.5
+    overall = "bullish" if avg_score > 0.55 else "bearish" if avg_score < 0.45 else "neutral"
+
+    return {
+        "overall": overall,
+        "average_score": round(avg_score, 2),
+        "breakdown": results,
+        "emoji": "🟢" if overall == "bullish" else "🔴" if overall == "bearish" else "⚪",
+    }
+
+
+@router.get("/trending-signals/{symbol}")
+async def sentiment_signal(symbol: str):
+    """Quick sentiment signal for trading: BULLISH / BEARISH / NEUTRAL."""
+    result = await token_sentiment(symbol)
+    return {
+        "symbol": symbol,
+        "signal": result["sentiment"].upper(),
+        "emoji": result.get("emoji", "⚪"),
+        "score": result.get("score", 0.5),
+    }