Gate Telegram market context for Leo research (#18)

telegram/bot.py

@@ -60,6 +60,7 @@ from http_chat_proxy import (
     extract_paid_work_order_id,
     extract_smart_research_goal,
     post_chat_proxy,
+    should_attach_structured_market_context,
     smart_research_command_names,
 )
 
@@ -1208,9 +1209,12 @@ async def handle_tagged(update: Update, context: ContextTypes.DEFAULT_TYPE):
     if AGENT_HTTP_RESEARCH_PROXY_URL and smart_research_goal:
         payment_gate = _smart_research_payment_gate(msg.chat_id)
         proxy_research_goal = smart_research_goal
-        market_context, market_data_audit, market_duration, market_tokens = await _market_context_for_message(
-            smart_research_goal
-        )
+        if should_attach_structured_market_context(smart_research_goal):
+            market_context, market_data_audit, market_duration, market_tokens = await _market_context_for_message(
+                smart_research_goal
+            )
+        else:
+            market_context, market_data_audit, market_duration, market_tokens = "", {}, 0, []
         if market_context:
             logger.info(
                 "%s smart research added structured market context for %s in %dms",

telegram/http_chat_proxy.py

@@ -50,6 +50,22 @@ _PAID_WORK_ORDER_ID_RE = re.compile(
     r"\b((?:sponsored_work_orders|payment_receipts):[a-f0-9]{16,64})\b",
     re.IGNORECASE,
 )
+_MARKET_CONTEXT_RE = re.compile(
+    r"\b("
+    r"volume|fdv|fully\s+diluted|market\s+cap|mcap|liquidity|price|chart|"
+    r"token|coin|pair|pool|dex|dexscreener|birdeye|jupiter|"
+    r"buy|sell|should\s+i|yes\s+or\s+no"
+    r")\b",
+    re.IGNORECASE,
+)
+_SOCIAL_DISCUSSION_RE = re.compile(
+    r"\b(twitter|x\.com|x\/twitter|tweet|tweets|social)\b.*"
+    r"\b(current|latest|recent|discussion|discussions|trend|trends|narrative|sentiment|fault|blame|position|stance)\b"
+    r"|"
+    r"\b(current|latest|recent|discussion|discussions|trend|trends|narrative|sentiment|fault|blame|position|stance)\b.*"
+    r"\b(twitter|x\.com|x\/twitter|tweet|tweets|social)\b",
+    re.IGNORECASE,
+)
 
 
 def smart_research_command_names(
@@ -158,6 +174,16 @@ def extract_paid_work_order_id(message: str) -> str | None:
     return match.group(1)
 
 
+def should_attach_structured_market_context(message: str) -> bool:
+    """Return true only for explicit market-data questions, not social narrative research."""
+    text = message.strip()
+    if not text:
+        return False
+    if _SOCIAL_DISCUSSION_RE.search(text):
+        return False
+    return bool(_MARKET_CONTEXT_RE.search(text))
+
+
 def build_smart_research_proxy_payload(
     *,
     research_goal: str,

tests/test_telegram_leo_x402_bridge.py

@@ -18,6 +18,7 @@ from http_chat_proxy import (  # noqa: E402
     extract_paid_work_order_id,
     extract_chat_proxy_reply,
     extract_smart_research_goal,
+    should_attach_structured_market_context,
     smart_research_command_names,
 )
 from market_data import extract_market_data_tokens, format_price_context  # noqa: E402
@@ -238,6 +239,20 @@ def test_market_data_token_extraction_maps_natural_market_question():
     assert extract_market_data_tokens(message) == ["OMFG", "AVICI", "UMBRA"]
 
 
+@pytest.mark.parametrize(
+    ("message", "expected"),
+    [
+        ("what is the volume and fdv of omnipair avici umbra? should i buy them yes or no", True),
+        ("show me price and liquidity for AVICI", True),
+        ("what are the current discussions about MetaDAO Ranger Finance on Twitter?", False),
+        ("who was at fault for Ranger according to Twitter?", False),
+        ("how much revenue does MetaDAO make today?", False),
+    ],
+)
+def test_should_attach_structured_market_context_only_for_market_data_intent(message, expected):
+    assert should_attach_structured_market_context(message) is expected
+
+
 def test_market_data_context_formats_dexscreener_fdv_volume_liquidity():
     context = format_price_context(
         {