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3 Commits
pr-58
...
70dfba2ffc
| Author | SHA1 | Date | |
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70dfba2ffc | ||
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2b7f54703e | ||
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99dded8d16 |
@@ -163,28 +163,6 @@ TOOLS = [
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},
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},
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},
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{
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"type": "function",
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"function": {
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"name": "get_trending",
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"description": "Get trending tokens on a blockchain. Use when user asks what's trending, top tokens, or popular tokens right now.",
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"parameters": {
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"type": "object",
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"properties": {
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"chain": {
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"type": "string",
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"description": "Blockchain chain (default: bsc)",
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"default": "bsc",
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},
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"limit": {
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"type": "integer",
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"description": "Number of trending tokens to return (default: 10, max: 50)",
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"default": 10,
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},
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},
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},
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},
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},
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{
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"type": "function",
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"function": {
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@@ -253,7 +231,6 @@ You have access to tools:
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- get_token(address, chain): Get detailed information about a specific token. Use when user asks for token details.
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- get_price(token_ids): Get current price(s) for tokens. Use when user asks for token price.
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- get_risk(address, chain): Get risk analysis for a token. Use when user asks about token safety or honeypot analysis.
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- get_trending(chain, limit): Get trending tokens on a blockchain. Use when user asks what's trending, top tokens, or popular tokens.
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- run_backtest(token_address, timeframe, start_date, end_date): Run a backtest on historical data. Returns performance metrics. Use when user asks to backtest or check historical performance.
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- manage_simulation(action, token_address, kline_interval): Manage trading simulations. Actions: 'start' (begin new), 'stop' (stop running), 'status' (check if running), 'results' (get current/latest results).
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@@ -318,11 +295,11 @@ class ConversationalAgent:
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},
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)
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result = resp.json() or {}
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result = resp.json()
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# Extract thinking from reasoning_content
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thinking = None
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if result.get("choices") and len(result.get("choices", [])) > 0:
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if "choices" in result and len(result["choices"]) > 0:
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choice = result["choices"][0]
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if "message" in choice:
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message = choice["message"]
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@@ -354,12 +331,7 @@ class ConversationalAgent:
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if code == 0:
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try:
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data = json.loads(output)
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# Handle both dict with 'tokens' key and direct list
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data_field = data.get("data", [])
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if isinstance(data_field, list):
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tokens = data_field
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else:
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tokens = data_field.get("tokens", [])
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tokens = data.get("data", {}).get("tokens", [])
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if tokens:
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token_list = ""
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for t in tokens[:limit]:
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@@ -370,11 +342,7 @@ class ConversationalAgent:
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"token_price_change_24h", "N/A"
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)
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mc = t.get("market_cap", "N/A")
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try:
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mc_str = f"${float(mc):,.0f}"
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except (ValueError, TypeError):
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mc_str = str(mc)
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token_list += f"- **{symbol}** ({name}): `{addr}` - MC: {mc_str} - 24h: {price_change}%\n"
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token_list += f"- **{symbol}** ({name}): `{addr}` - MC: ${mc:,.0f} - 24h: {price_change}%\n"
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response_text = f"Here are the search results for '{keyword}' on BSC:\n\n{token_list}\nWould you like me to set up a strategy for any of these?"
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else:
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response_text = f"No tokens found for '{keyword}'. Try a different keyword."
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@@ -403,51 +371,24 @@ class ConversationalAgent:
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if code == 0:
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try:
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data = json.loads(output)
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data_field = data.get("data")
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# Handle both dict and list responses
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token_data = data_field if isinstance(data_field, dict) else {}
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# Token details may be nested in 'token' key
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token_info = token_data.get("token", token_data)
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# Check if token has valid symbol/name (not None, not 'N/A')
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symbol = token_info.get("symbol") or token_data.get("symbol")
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name = token_info.get("name") or token_data.get("name")
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if not symbol or symbol == "N/A" or not name or name == "N/A":
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response_text = f"Token not found for {address}. Raw response: {output[:500]}"
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else:
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# Try different price field names
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price = (token_info.get("current_price_usd")
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or token_info.get("price_usd")
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or token_info.get("price")
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or token_data.get("price")
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or "N/A")
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mc = (token_info.get("market_cap")
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or token_info.get("fdv")
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or token_data.get("market_cap")
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or "N/A")
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vol = (token_info.get("tx_volume_u_24h")
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or token_info.get("volume_24h")
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or token_data.get("volume_24h")
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or "N/A")
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pairs = token_info.get("top_pairs") or token_data.get("top_pairs") or []
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token_data = data.get("data", {})
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if token_data:
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symbol = token_data.get("symbol", "N/A")
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name = token_data.get("name", "N/A")
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price = token_data.get("price", "N/A")
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mc = token_data.get("market_cap", "N/A")
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vol = token_data.get("volume_24h", "N/A")
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pairs = token_data.get("top_pairs", [])
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pairs_text = ""
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if pairs:
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pairs_text = "\n**Top Pairs:**\n"
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for p in pairs[:3]:
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liq = p.get('liquidity', 'N/A')
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try:
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liq_str = f"${float(liq):,.0f}"
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except (ValueError, TypeError):
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liq_str = str(liq)
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pairs_text += f"- {p.get('pair', 'N/A')}: {liq_str} liquidity\n"
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try:
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mc_str = f"${float(mc):,.0f}" if mc != "N/A" else "N/A"
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except (ValueError, TypeError):
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mc_str = str(mc)
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try:
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vol_str = f"${float(vol):,.0f}" if vol != "N/A" else "N/A"
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except (ValueError, TypeError):
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vol_str = str(vol)
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response_text = f"**{symbol}** ({name})\n\nPrice: ${price}\nMarket Cap: {mc_str}\n24h Volume: {vol_str}{pairs_text}"
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pairs_text += f"- {p.get('pair', 'N/A')}: ${p.get('liquidity', 'N/A'):,.0f} liquidity\n"
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response_text = f"**{symbol}** ({name})\n\nPrice: ${price}\nMarket Cap: ${mc:,.0f}\n24h Volume: ${vol:,.0f}{pairs_text}"
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else:
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response_text = (
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f"Token not found: {address}"
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)
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except json.JSONDecodeError:
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response_text = "Failed to parse token data."
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else:
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@@ -477,9 +418,6 @@ class ConversationalAgent:
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try:
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data = json.loads(output)
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prices = data.get("data", {})
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# Ensure prices is a dict
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if not isinstance(prices, dict):
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prices = {}
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if prices:
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price_text = "**Token Prices:**\n"
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for (
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@@ -525,53 +463,27 @@ class ConversationalAgent:
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if code == 0:
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try:
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data = json.loads(output)
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data_field = data.get("data")
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# Handle both dict and list responses
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risk_data = data_field if isinstance(data_field, dict) else {}
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risk_data = data.get("data", {})
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if risk_data:
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is_honeypot = risk_data.get(
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"is_honeypot", "unknown"
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)
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buy_tax = risk_data.get("buy_tax", 0)
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sell_tax = risk_data.get("sell_tax", 0)
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buy_tax = risk_data.get("buy_tax", "N/A")
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sell_tax = risk_data.get("sell_tax", "N/A")
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status = risk_data.get("status", "unknown")
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# Convert is_honeypot to string for comparison
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if isinstance(is_honeypot, bool):
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is_honeypot_str = str(is_honeypot).lower()
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elif isinstance(is_honeypot, int):
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if is_honeypot == 1:
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is_honeypot_str = "true"
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elif is_honeypot == 0:
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is_honeypot_str = "false"
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else:
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is_honeypot_str = "unknown" # -1 or other means couldn't determine
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else:
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is_honeypot_str = str(is_honeypot).lower() if is_honeypot else "unknown"
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# Format honeypot display value
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if is_honeypot_str == "unknown":
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honeypot_display = "Unknown (could not determine)"
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else:
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honeypot_display = is_honeypot_str
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# Convert tax values to float for comparison
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try:
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buy_tax_val = float(buy_tax) if buy_tax not in (None, "N/A") else 0
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except (ValueError, TypeError):
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buy_tax_val = 0
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try:
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sell_tax_val = float(sell_tax) if sell_tax not in (None, "N/A") else 0
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except (ValueError, TypeError):
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sell_tax_val = 0
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risk_text = (
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f"**Risk Analysis for {address}**\n\n"
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)
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risk_text += f"- Status: {status}\n"
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risk_text += f"- Honeypot: {honeypot_display}\n"
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risk_text += f"- Honeypot: {is_honeypot}\n"
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risk_text += f"- Buy Tax: {buy_tax}%\n"
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risk_text += f"- Sell Tax: {sell_tax}%\n"
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if is_honeypot_str == "true":
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if is_honeypot.lower() == "true":
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risk_text += "\n⚠️ **Warning: This token appears to be a honeypot. Do not buy!**"
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elif buy_tax_val > 10 or sell_tax_val > 10:
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elif (
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float(buy_tax or 0) > 10
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or float(sell_tax or 0) > 10
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):
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risk_text += "\n⚠️ **Warning: High tax detected. Trade with caution!**"
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else:
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risk_text += "\n✅ This token appears safe to trade."
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@@ -593,49 +505,6 @@ class ConversationalAgent:
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"success": True,
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}
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elif func_name == "get_trending":
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chain = args.get("chain", "bsc")
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limit = args.get("limit", 10)
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code, output = self._call_ave_script(
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"trending",
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["--chain", chain, "--page-size", str(min(limit, 50))],
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)
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if code == 0:
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try:
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data = json.loads(output)
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data_field = data.get("data")
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# Handle both dict and list responses
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tokens = data_field if isinstance(data_field, list) else data_field.get("tokens", [])
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if tokens:
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token_list = ""
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for t in tokens[:limit]:
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addr = t.get("token", "")
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symbol = t.get("symbol", "")
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name = t.get("name", "")
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price_change = t.get("token_price_change_24h", "N/A")
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mc = t.get("market_cap", "N/A")
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try:
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mc_str = f"${float(mc):,.0f}"
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except (ValueError, TypeError):
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mc_str = str(mc)
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token_list += f"- **{symbol}** ({name}): `{addr}` - MC: {mc_str} - 24h: {price_change}%\n"
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response_text = f"🔥 Trending tokens on {chain.upper()}:\n\n{token_list}\nWould you like me to set up a strategy for any of these?"
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else:
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response_text = f"No trending tokens found on {chain.upper()}."
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except json.JSONDecodeError:
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response_text = "Failed to parse trending data."
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else:
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response_text = f"Failed to get trending tokens: {output}"
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return {
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"response": response_text,
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"thinking": thinking,
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"strategy_updated": False,
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"strategy_needs_confirmation": False,
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"success": True,
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}
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elif func_name == "run_backtest":
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token_address = args.get("token_address")
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timeframe = args.get("timeframe", "1d")
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@@ -731,12 +600,7 @@ class ConversationalAgent:
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if code == 0:
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try:
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data = json.loads(output)
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# Handle both dict with 'tokens' key and direct list
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data_field = data.get("data", [])
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if isinstance(data_field, list):
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tokens = data_field
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else:
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tokens = data_field.get("tokens", [])
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tokens = data.get("data", {}).get("tokens", [])
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if tokens:
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token_list = ""
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for t in tokens[:limit]:
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@@ -747,11 +611,7 @@ class ConversationalAgent:
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"token_price_change_24h", "N/A"
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)
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mc = t.get("market_cap", "N/A")
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try:
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mc_str = f"${float(mc):,.0f}"
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except (ValueError, TypeError):
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mc_str = str(mc)
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token_list += f"- **{symbol}** ({name}): `{addr}` - MC: {mc_str} - 24h: {price_change}%\n"
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token_list += f"- **{symbol}** ({name}): `{addr}` - MC: ${mc:,.0f} - 24h: {price_change}%\n"
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response_text = f"Here are the search results for '{keyword}' on BSC:\n\n{token_list}\nWould you like me to set up a strategy for any of these?"
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else:
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response_text = f"No tokens found for '{keyword}'. Try a different keyword."
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@@ -775,7 +635,7 @@ class ConversationalAgent:
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if strategy_update:
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# Extract token name from conditions
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token_name = None
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for cond in (strategy_update.get("conditions") or []):
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for cond in strategy_update.get("conditions", []):
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if not cond.get("token_address") and cond.get("token"):
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token_name = cond.get("token")
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strategy_needs_confirmation = True
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@@ -790,12 +650,7 @@ class ConversationalAgent:
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)
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if code == 0:
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data = json.loads(output)
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# Handle both dict with 'tokens' key and direct list
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data_field = data.get("data", [])
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if isinstance(data_field, list):
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tokens = data_field
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else:
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tokens = data_field.get("tokens", [])
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tokens = data.get("data", {}).get("tokens", [])
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if tokens:
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token_search_results = [
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{
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@@ -1218,7 +1073,7 @@ Would you like me to adjust the strategy parameters based on these results?"""
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settings = get_settings()
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repo_root = os.path.dirname(
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os.path.dirname(os.path.dirname(os.path.dirname(os.path.dirname(os.path.dirname(__file__)))))
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os.path.dirname(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
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)
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ave_skill_path = os.path.join(
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repo_root, "ave-cloud-skill", "scripts", "ave_data_rest.py"
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@@ -1237,11 +1092,7 @@ Would you like me to adjust the strategy parameters based on these results?"""
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env=env,
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timeout=30,
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)
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# Include stderr in output for debugging
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output = result.stdout
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if result.returncode != 0 and result.stderr:
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output = f"{output}\n{result.stderr}".strip()
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return result.returncode, output
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return result.returncode, result.stdout
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except subprocess.TimeoutExpired:
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return 1, "Error: Command timed out"
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except Exception as e:
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Reference in New Issue
Block a user