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from langchain.tools import BaseTool
from pydantic import BaseModel, Field
from typing import Dict, Any, List, Optional
import json
import asyncio
from src.utils.logger import get_logger
logger = get_logger(__name__)
class ChartDataInput(BaseModel):
"""Input schema for chart data requests"""
chart_type: str = Field(description="Chart type: price_chart, market_overview, defi_tvl, portfolio_pie, gas_tracker")
symbol: Optional[str] = Field(default=None, description="Asset symbol (e.g., bitcoin, ethereum)")
timeframe: Optional[str] = Field(default="30d", description="Time range: 1d, 7d, 30d, 90d, 365d")
protocols: Optional[List[str]] = Field(default=None, description="DeFi protocol names")
network: Optional[str] = Field(default="ethereum", description="Blockchain network")
class ChartDataTool(BaseTool):
"""
Chart Data Provider Tool
This tool provides structured data that can be used to create charts.
Instead of returning HTML, it returns clean JSON data for visualization.
"""
name: str = "chart_data_provider"
description: str = """Provides structured data for creating cryptocurrency charts.
Returns JSON data in this format:
{{
"chart_type": "price_chart|market_overview|defi_tvl|portfolio_pie|gas_tracker",
"data": {{...}},
"config": {{...}}
}}
Chart types:
- price_chart: Bitcoin/crypto price and volume data
- market_overview: Top cryptocurrencies market data
- defi_tvl: DeFi protocol TVL comparison
- portfolio_pie: Portfolio allocation breakdown
- gas_tracker: Gas fees across networks
"""
args_schema: type[ChartDataInput] = ChartDataInput
def _run(self, chart_type: str, symbol: str = None, timeframe: str = "30d",
protocols: List[str] = None, network: str = "ethereum") -> str:
"""Synchronous execution"""
return asyncio.run(self._arun(chart_type, symbol, timeframe, protocols, network))
async def _arun(self, chart_type: str, symbol: str = None, timeframe: str = "30d",
protocols: List[str] = None, network: str = "ethereum") -> str:
"""Provide chart data based on request"""
try:
logger.info(f"Providing {chart_type} data for {symbol or 'general'}")
# Convert timeframe to days
days = self._parse_timeframe(timeframe)
if chart_type == "price_chart":
return await self._get_price_chart_data(symbol or "bitcoin", days)
elif chart_type == "market_overview":
return await self._get_market_overview_data()
elif chart_type == "defi_tvl":
return await self._get_defi_tvl_data(protocols or ["uniswap", "aave", "compound"])
elif chart_type == "portfolio_pie":
return await self._get_portfolio_data()
elif chart_type == "gas_tracker":
return await self._get_gas_data(network)
else:
return json.dumps({
"chart_type": "error",
"error": f"Unknown chart type: {chart_type}",
"available_types": ["price_chart", "market_overview", "defi_tvl", "portfolio_pie", "gas_tracker"]
})
except Exception as e:
logger.error(f"Chart data error: {e}")
return json.dumps({
"chart_type": "error",
"error": str(e),
"message": "Failed to generate chart data"
})
async def _get_price_chart_data(self, symbol: str, days: int) -> str:
"""Get price chart data"""
# Generate realistic mock price data
import time
import random
base_price = 35000 if symbol.lower() == "bitcoin" else 1800 if symbol.lower() == "ethereum" else 100
base_timestamp = int(time.time() * 1000) - (days * 24 * 60 * 60 * 1000)
price_data = []
volume_data = []
for i in range(days):
timestamp = base_timestamp + (i * 24 * 60 * 60 * 1000)
# Generate realistic price movement
price_change = random.uniform(-0.05, 0.05) # ±5% daily change
price = base_price * (1 + price_change * i / days)
price += random.uniform(-price*0.02, price*0.02) # Daily volatility
volume = random.uniform(1000000000, 5000000000) # Random volume
price_data.append([timestamp, round(price, 2)])
volume_data.append([timestamp, int(volume)])
return json.dumps({
"chart_type": "price_chart",
"data": {
"prices": price_data,
"total_volumes": volume_data,
"symbol": symbol.upper(),
"name": symbol.title()
},
"config": {
"title": f"{symbol.title()} Price Analysis ({days} days)",
"timeframe": f"{days}d",
"currency": "USD"
}
})
async def _get_market_overview_data(self) -> str:
"""Get market overview data"""
return json.dumps({
"chart_type": "market_overview",
"data": {
"coins": [
{"name": "Bitcoin", "symbol": "BTC", "current_price": 35000, "market_cap_rank": 1, "price_change_percentage_24h": 2.5},
{"name": "Ethereum", "symbol": "ETH", "current_price": 1800, "market_cap_rank": 2, "price_change_percentage_24h": -1.2},
{"name": "Cardano", "symbol": "ADA", "current_price": 0.25, "market_cap_rank": 3, "price_change_percentage_24h": 3.1},
{"name": "Solana", "symbol": "SOL", "current_price": 22.5, "market_cap_rank": 4, "price_change_percentage_24h": -2.8},
{"name": "Polygon", "symbol": "MATIC", "current_price": 0.52, "market_cap_rank": 5, "price_change_percentage_24h": 1.9}
]
},
"config": {
"title": "Top Cryptocurrencies Market Overview",
"currency": "USD"
}
})
async def _get_defi_tvl_data(self, protocols: List[str]) -> str:
"""Get DeFi TVL data"""
tvl_data = []
for protocol in protocols[:5]: # Limit to 5 protocols
import random
tvl = random.uniform(500000000, 5000000000) # $500M to $5B TVL
tvl_data.append({
"name": protocol.title(),
"tvl": int(tvl),
"change_24h": random.uniform(-10, 15)
})
return json.dumps({
"chart_type": "defi_tvl",
"data": {
"protocols": tvl_data
},
"config": {
"title": "DeFi Protocols TVL Comparison",
"currency": "USD"
}
})
async def _get_portfolio_data(self) -> str:
"""Get portfolio allocation data"""
return json.dumps({
"chart_type": "portfolio_pie",
"data": {
"allocations": [
{"name": "Bitcoin", "symbol": "BTC", "value": 40, "color": "#f7931a"},
{"name": "Ethereum", "symbol": "ETH", "value": 30, "color": "#627eea"},
{"name": "Cardano", "symbol": "ADA", "value": 15, "color": "#0033ad"},
{"name": "Solana", "symbol": "SOL", "value": 10, "color": "#9945ff"},
{"name": "Other", "symbol": "OTHER", "value": 5, "color": "#666666"}
]
},
"config": {
"title": "Sample Portfolio Allocation",
"currency": "Percentage"
}
})
async def _get_gas_data(self, network: str) -> str:
"""Get gas fee data"""
import random
import time
# Generate 24 hours of gas data
gas_data = []
base_timestamp = int(time.time() * 1000) - (24 * 60 * 60 * 1000)
for i in range(24):
timestamp = base_timestamp + (i * 60 * 60 * 1000)
gas_price = random.uniform(20, 100) if network == "ethereum" else random.uniform(1, 10)
gas_data.append([timestamp, round(gas_price, 2)])
return json.dumps({
"chart_type": "gas_tracker",
"data": {
"gas_prices": gas_data,
"network": network.title()
},
"config": {
"title": f"{network.title()} Gas Fee Tracker (24h)",
"unit": "Gwei"
}
})
def _parse_timeframe(self, timeframe: str) -> int:
"""Convert timeframe string to days"""
timeframe_map = {
"1d": 1, "7d": 7, "30d": 30, "90d": 90, "365d": 365, "1y": 365
}
return timeframe_map.get(timeframe, 30)
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