Spaces:
Sleeping
Sleeping
File size: 10,526 Bytes
d8d14f1 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 |
import os
from swarms import Agent
from swarm_models import OpenAIChat
from web3 import Web3
from typing import Dict, Optional, Any
from datetime import datetime
import asyncio
from loguru import logger
from dotenv import load_dotenv
import csv
import requests
import time
BLOCKCHAIN_AGENT_PROMPT = """
You are an expert blockchain and cryptocurrency analyst with deep knowledge of Ethereum markets and DeFi ecosystems.
You have access to real-time ETH price data and transaction information.
For each transaction, analyze:
1. MARKET CONTEXT
- Current ETH price and what this transaction means in USD terms
- How this movement compares to typical market volumes
- Whether this could impact ETH price
2. BEHAVIORAL ANALYSIS
- Whether this appears to be institutional, whale, or protocol movement
- If this fits any known wallet patterns or behaviors
- Signs of smart contract interaction or DeFi activity
3. RISK & IMPLICATIONS
- Potential market impact or price influence
- Signs of potential market manipulation or unusual activity
- Protocol or DeFi risks if applicable
4. STRATEGIC INSIGHTS
- What traders should know about this movement
- Potential chain reactions or follow-up effects
- Market opportunities or risks created
Write naturally but precisely. Focus on actionable insights and important patterns.
Your analysis helps traders and researchers understand significant market movements in real-time."""
class EthereumAnalyzer:
def __init__(self, min_value_eth: float = 100.0):
load_dotenv()
logger.add(
"eth_analysis.log",
rotation="500 MB",
retention="10 days",
level="INFO",
format="{time:YYYY-MM-DD at HH:mm:ss} | {level} | {message}",
)
self.w3 = Web3(
Web3.HTTPProvider(
"https://mainnet.infura.io/v3/9aa3d95b3bc440fa88ea12eaa4456161"
)
)
if not self.w3.is_connected():
raise ConnectionError(
"Failed to connect to Ethereum network"
)
self.min_value_eth = min_value_eth
self.last_processed_block = self.w3.eth.block_number
self.eth_price = self.get_eth_price()
self.last_price_update = time.time()
# Initialize AI agent
api_key = os.getenv("OPENAI_API_KEY")
if not api_key:
raise ValueError(
"OpenAI API key not found in environment variables"
)
model = OpenAIChat(
openai_api_key=api_key,
model_name="gpt-4",
temperature=0.1,
)
self.agent = Agent(
agent_name="Ethereum-Analysis-Agent",
system_prompt=BLOCKCHAIN_AGENT_PROMPT,
llm=model,
max_loops=1,
autosave=True,
dashboard=False,
verbose=True,
dynamic_temperature_enabled=True,
saved_state_path="eth_agent.json",
user_name="eth_analyzer",
retry_attempts=1,
context_length=200000,
output_type="string",
streaming_on=False,
)
self.csv_filename = "ethereum_analysis.csv"
self.initialize_csv()
def get_eth_price(self) -> float:
"""Get current ETH price from CoinGecko API."""
try:
response = requests.get(
"https://api.coingecko.com/api/v3/simple/price",
params={"ids": "ethereum", "vs_currencies": "usd"},
)
return float(response.json()["ethereum"]["usd"])
except Exception as e:
logger.error(f"Error fetching ETH price: {str(e)}")
return 0.0
def update_eth_price(self):
"""Update ETH price if more than 5 minutes have passed."""
if time.time() - self.last_price_update > 300: # 5 minutes
self.eth_price = self.get_eth_price()
self.last_price_update = time.time()
logger.info(f"Updated ETH price: ${self.eth_price:,.2f}")
def initialize_csv(self):
"""Initialize CSV file with headers."""
headers = [
"timestamp",
"transaction_hash",
"from_address",
"to_address",
"value_eth",
"value_usd",
"eth_price",
"gas_used",
"gas_price_gwei",
"block_number",
"analysis",
]
if not os.path.exists(self.csv_filename):
with open(self.csv_filename, "w", newline="") as f:
writer = csv.writer(f)
writer.writerow(headers)
async def analyze_transaction(
self, tx_hash: str
) -> Optional[Dict[str, Any]]:
"""Analyze a single transaction."""
try:
tx = self.w3.eth.get_transaction(tx_hash)
receipt = self.w3.eth.get_transaction_receipt(tx_hash)
value_eth = float(self.w3.from_wei(tx.value, "ether"))
if value_eth < self.min_value_eth:
return None
block = self.w3.eth.get_block(tx.blockNumber)
# Update ETH price if needed
self.update_eth_price()
value_usd = value_eth * self.eth_price
analysis = {
"timestamp": datetime.fromtimestamp(
block.timestamp
).isoformat(),
"transaction_hash": tx_hash.hex(),
"from_address": tx["from"],
"to_address": tx.to if tx.to else "Contract Creation",
"value_eth": value_eth,
"value_usd": value_usd,
"eth_price": self.eth_price,
"gas_used": receipt.gasUsed,
"gas_price_gwei": float(
self.w3.from_wei(tx.gasPrice, "gwei")
),
"block_number": tx.blockNumber,
}
# Check if it's a contract
if tx.to:
code = self.w3.eth.get_code(tx.to)
analysis["is_contract"] = len(code) > 0
# Get contract events
if analysis["is_contract"]:
analysis["events"] = receipt.logs
return analysis
except Exception as e:
logger.error(
f"Error analyzing transaction {tx_hash}: {str(e)}"
)
return None
def prepare_analysis_prompt(self, tx_data: Dict[str, Any]) -> str:
"""Prepare detailed analysis prompt including price context."""
value_usd = tx_data["value_usd"]
eth_price = tx_data["eth_price"]
prompt = f"""Analyze this Ethereum transaction in current market context:
Transaction Details:
- Value: {tx_data['value_eth']:.2f} ETH (${value_usd:,.2f} at current price)
- Current ETH Price: ${eth_price:,.2f}
- From: {tx_data['from_address']}
- To: {tx_data['to_address']}
- Contract Interaction: {tx_data.get('is_contract', False)}
- Gas Used: {tx_data['gas_used']:,} units
- Gas Price: {tx_data['gas_price_gwei']:.2f} Gwei
- Block: {tx_data['block_number']}
- Timestamp: {tx_data['timestamp']}
{f"Event Count: {len(tx_data['events'])} events" if tx_data.get('events') else "No contract events"}
Consider the transaction's significance given the current ETH price of ${eth_price:,.2f} and total USD value of ${value_usd:,.2f}.
Analyze market impact, patterns, risks, and strategic implications."""
return prompt
def save_to_csv(self, tx_data: Dict[str, Any], ai_analysis: str):
"""Save transaction data and analysis to CSV."""
row = [
tx_data["timestamp"],
tx_data["transaction_hash"],
tx_data["from_address"],
tx_data["to_address"],
tx_data["value_eth"],
tx_data["value_usd"],
tx_data["eth_price"],
tx_data["gas_used"],
tx_data["gas_price_gwei"],
tx_data["block_number"],
ai_analysis.replace("\n", " "),
]
with open(self.csv_filename, "a", newline="") as f:
writer = csv.writer(f)
writer.writerow(row)
async def monitor_transactions(self):
"""Monitor and analyze transactions one at a time."""
logger.info(
f"Starting transaction monitor (minimum value: {self.min_value_eth} ETH)"
)
while True:
try:
current_block = self.w3.eth.block_number
block = self.w3.eth.get_block(
current_block, full_transactions=True
)
for tx in block.transactions:
tx_analysis = await self.analyze_transaction(
tx.hash
)
if tx_analysis:
# Get AI analysis
analysis_prompt = (
self.prepare_analysis_prompt(tx_analysis)
)
ai_analysis = self.agent.run(analysis_prompt)
print(ai_analysis)
# Save to CSV
self.save_to_csv(tx_analysis, ai_analysis)
# Print analysis
print("\n" + "=" * 50)
print("New Transaction Analysis")
print(
f"Hash: {tx_analysis['transaction_hash']}"
)
print(
f"Value: {tx_analysis['value_eth']:.2f} ETH (${tx_analysis['value_usd']:,.2f})"
)
print(
f"Current ETH Price: ${self.eth_price:,.2f}"
)
print("=" * 50)
print(ai_analysis)
print("=" * 50 + "\n")
await asyncio.sleep(1) # Wait for next block
except Exception as e:
logger.error(f"Error in monitoring loop: {str(e)}")
await asyncio.sleep(1)
async def main():
"""Entry point for the analysis system."""
analyzer = EthereumAnalyzer(min_value_eth=100.0)
await analyzer.monitor_transactions()
if __name__ == "__main__":
print("Starting Ethereum Transaction Analyzer...")
print("Saving results to ethereum_analysis.csv")
print("Press Ctrl+C to stop")
try:
asyncio.run(main())
except KeyboardInterrupt:
print("\nStopping analyzer...")
|