-
Notifications
You must be signed in to change notification settings - Fork 4
Expand file tree
/
Copy pathmain.py
More file actions
428 lines (344 loc) Β· 20.8 KB
/
main.py
File metadata and controls
428 lines (344 loc) Β· 20.8 KB
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
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
#!/usr/bin/env python3
"""
Eurus - ERA5 Climate Analysis Agent
======================================
An intelligent oceanography and climate data analysis assistant.
Features:
- Persistent memory across sessions
- Cloud-optimized ERA5 data retrieval
- Interactive Python analysis with visualization
- Conversation history and context awareness
Usage:
python main.py
Commands:
q, quit, exit - Exit the agent
/clear - Clear conversation history
/cache - List cached datasets
/memory - Show memory summary
/cleardata - Clear all downloaded ERA5 datasets
/help - Show help message
"""
import os
import sys
import logging
import warnings
from pathlib import Path
from datetime import datetime
# Suppress noisy warnings from xarray/zarr
warnings.filterwarnings("ignore", category=FutureWarning)
warnings.filterwarnings("ignore", message="Consolidated metadata", category=UserWarning)
from dotenv import load_dotenv
# Load environment variables first
load_dotenv()
# Add src to path
PROJECT_ROOT = Path(__file__).parent
sys.path.insert(0, str(PROJECT_ROOT / "src"))
# Setup centralized logging
from eurus.logging_config import setup_logging, cleanup_old_logs
setup_logging(mode="cli")
cleanup_old_logs(keep=20)
logger = logging.getLogger(__name__)
# Import after logging is configured
from langchain_openai import ChatOpenAI
from langchain.agents import create_agent
from eurus.config import CONFIG, AGENT_SYSTEM_PROMPT, DATA_DIR, PLOTS_DIR
from eurus.memory import get_memory, MemoryManager
from eurus.tools import get_all_tools
# ============================================================================
# BANNER AND HELP
# ============================================================================
BANNER = """
βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
β β
β βββββββββββ ββββββββββ βββ βββββββββββ β
β βββββββββββ ββββββββββββββ βββββββββββ β
β ββββββ βββ ββββββββββββββ βββββββββββ β
β ββββββ βββ ββββββββββββββ βββββββββββ β
β ββββββββββββββββββββ ββββββββββββββββββββ β
β ββββββββ βββββββ βββ βββ βββββββ ββββββββ β
β β
β AI Climate Physicist v2.0 β
β βββββββββββββββββββββββββββββββββββββββββ β
β β
β Scientific Capabilities: β
β β’ ERA5 reanalysis data retrieval (SST, wind, temperature, pressure) β
β β’ Climate Diagnostics: Anomalies, Z-Scores, Statistical Significance β
β β’ Pattern Discovery: EOF/PCA analysis for climate modes β
β β’ Compound Extremes: "Ocean Oven" detection (Heat + Stagnation) β
β β’ Trend Analysis: Decadal trends with p-value significance β
β β’ Teleconnections: Correlation and lead-lag analysis β
β β’ Maritime Routing & Lagrangian Risk Assessment β
β β
β Commands: /help, /clear, /cache, /memory, /quit β
β β
βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
"""
HELP_TEXT = """
βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
β EURUS HELP - AI Climate Physicist β
β ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ£
β β
β COMMANDS: β
β βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ β
β /help - Show this help message β
β /clear - Clear conversation history (fresh start) β
β /cache - List all cached ERA5 datasets β
β /memory - Show memory summary (datasets, analyses) β
β /cleardata - Clear all downloaded ERA5 datasets β
β /quit - Exit the agent (also: q, quit, exit) β
β β
β SCIENTIFIC ANALYSIS (Publication-Grade): β
β βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ β
β "Analyze marine heatwaves in the North Atlantic summer 2023" β
β "Find compound extremes where high SST coincides with low wind" β
β "Perform EOF analysis on SST anomalies to find climate modes" β
β "Calculate SST trends with statistical significance" β
β "Detect Ocean Ovens in the Mediterranean" β
β β
β SCIENCE TOOLS (The "Physics Brain"): β
β βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ β
β analyze_climate_modes_eof - Pattern discovery via EOF/PCA β
β detect_compound_extremes - "Ocean Oven" detection β
β calculate_climate_trends - Trends with p-value significance β
β detrend_climate_data - Remove warming trend for analysis β
β detect_percentile_extremes - Percentile-based extreme detection β
β fetch_climate_index - NOAA indices (Nino3.4, NAO, PDO, AMO) β
β calculate_return_periods - GEV/EVT (1-in-100 year events) β
β analyze_granger_causality - Prove X causes Y (not just correlated) β
β β
β AVAILABLE VARIABLES: β
β βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ β
β sst - Sea Surface Temperature (K) β
β t2 - 2m Air Temperature (K) β
β u10 - 10m U-Wind Component (m/s) β
β v10 - 10m V-Wind Component (m/s) β
β mslp - Mean Sea Level Pressure (Pa) β
β tcc - Total Cloud Cover (0-1) β
β tp - Total Precipitation (m) β
β β
β PREDEFINED REGIONS: β
β βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ β
β north_atlantic, north_pacific, california_coast, mediterranean β
β gulf_of_mexico, caribbean, nino34, nino3, nino4, arctic, antarctic β
β β
β SCIENTIFIC WORKFLOW: β
β βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ β
β 1. RETRIEVE data β 2. DIAGNOSE (Z-scores) β 3. DISCOVER (EOF) β
β 4. DETECT (extremes) β 5. ATTRIBUTE (correlation) β 6. VISUALIZE β
β β
β TIPS: β
β βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ β
β β’ Always report in anomalies/Z-scores, not raw values β
β β’ Z > 2Ο means statistically significant extreme β
β β’ Use diverging colormaps (RdBu_r) centered at 0 for anomalies β
β β’ Add stippling for p < 0.05 significance β
β β
βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
"""
def clear_data_directory(data_dir: Path = None) -> tuple[int, float]:
"""
Remove all downloaded ERA5 datasets (zarr directories) from the data folder.
Args:
data_dir: Data directory path. Defaults to DATA_DIR from config.
Returns:
Tuple of (datasets_removed, total_size_mb_freed)
"""
import shutil
if data_dir is None:
data_dir = DATA_DIR
datasets_removed = 0
total_bytes = 0
if not data_dir.exists():
return 0, 0.0
# Find and remove all .zarr directories
for zarr_dir in data_dir.glob('*.zarr'):
if zarr_dir.is_dir():
# Calculate size before removing
dir_size = sum(f.stat().st_size for f in zarr_dir.rglob('*') if f.is_file())
total_bytes += dir_size
shutil.rmtree(zarr_dir)
datasets_removed += 1
logger.debug(f"Removed dataset: {zarr_dir}")
total_mb = total_bytes / (1024 * 1024)
return datasets_removed, total_mb
# ============================================================================
# COMMAND HANDLERS
# ============================================================================
def handle_command(command: str, memory: MemoryManager) -> tuple[bool, str]:
"""
Handle slash commands.
Returns:
(should_continue, response_message)
"""
cmd = command.lower().strip()
if cmd in ('/quit', '/exit', '/q', 'quit', 'exit', 'q'):
return False, "Goodbye! Your conversation has been saved."
elif cmd == '/help':
return True, HELP_TEXT
elif cmd == '/clear':
memory.clear_conversation()
return True, "Conversation history cleared. Starting fresh!"
elif cmd == '/cache':
cache_info = memory.list_datasets()
return True, f"\n{cache_info}\n"
elif cmd == '/memory':
summary = memory.get_context_summary()
datasets = len([p for p in memory.datasets if os.path.exists(p)])
analyses = len(memory.analyses)
convos = len(memory.conversations)
response = f"""
βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
β MEMORY SUMMARY β
β ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ£
β Conversation messages: {convos:<5} β
β Cached datasets: {datasets:<5} β
β Recorded analyses: {analyses:<5} β
βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
{summary}
"""
return True, response
elif cmd == '/cleardata':
datasets_removed, size_freed = clear_data_directory(DATA_DIR)
# Also clear memory references
memory.datasets.clear()
memory._save_datasets()
response = f"""
βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
β ERA5 DATA CLEARED β
β ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ£
β Datasets removed: {datasets_removed:<5} β
β Space freed: {size_freed:>8.2f} MB β
βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
"""
return True, response
elif cmd.startswith('/'):
return True, f"Unknown command: {cmd}\nType /help for available commands."
return True, None # Not a command
# ============================================================================
# CALLBACK FOR TOOL PROGRESS
# ============================================================================
from langchain_core.callbacks import BaseCallbackHandler
class ToolProgressCallback(BaseCallbackHandler):
"""Print tool calls in real-time during agent execution."""
def on_tool_start(self, serialized, input_str, **kwargs):
tool_name = serialized.get('name', kwargs.get('name', 'unknown'))
print(f"π§ Calling: {tool_name}...", flush=True)
def on_tool_end(self, output, name=None, **kwargs):
display_name = name or "tool"
print(f" β {display_name} done", flush=True)
# ============================================================================
# MAIN AGENT LOOP
# ============================================================================
def main():
"""Main entry point for the Eurus agent."""
# Print banner
print(BANNER)
# Check for required API keys
if not os.environ.get("ARRAYLAKE_API_KEY"):
print("ERROR: ARRAYLAKE_API_KEY not found in environment.")
print("Please add it to your .env file:")
print(" ARRAYLAKE_API_KEY=your_api_key_here")
sys.exit(1)
if not os.environ.get("OPENAI_API_KEY"):
print("ERROR: OPENAI_API_KEY not found in environment.")
print("Please add it to your .env file:")
print(" OPENAI_API_KEY=your_api_key_here")
sys.exit(1)
# Initialize memory
print("Initializing memory system...")
memory = get_memory()
# Load recent conversation context
recent_messages = memory.get_langchain_messages(n_messages=10)
logger.info(f"Loaded {len(recent_messages)} messages from history")
# Initialize tools
print("Starting Python kernel...")
# All capabilities enabled by default (including maritime routing)
tools = get_all_tools(enable_routing=True, enable_guide=True)
logger.info(f"Loaded {len(tools)} tools")
# Initialize LLM
print("Connecting to LLM...")
llm = ChatOpenAI(
model=CONFIG.model_name,
temperature=CONFIG.temperature,
streaming=True # Enable streaming for real-time output
)
# Create enhanced system prompt with context
context_summary = memory.get_context_summary()
enhanced_prompt = AGENT_SYSTEM_PROMPT
if context_summary and context_summary != "No context available.":
enhanced_prompt += f"\n\n## CURRENT CONTEXT\n{context_summary}"
# Create agent
print("Creating agent...")
agent = create_agent(
model=llm,
tools=tools,
system_prompt=enhanced_prompt,
debug=False
)
# Initialize messages with history
messages = recent_messages.copy()
print("\n" + "=" * 75)
print("READY! Type your question or /help for commands.")
print("=" * 75 + "\n")
# Main interaction loop
try:
while True:
# Get user input
try:
user_input = input(">> You: ").strip()
except EOFError:
break
if not user_input:
continue
# Handle commands
should_continue, response = handle_command(user_input, memory)
if response:
print(response)
if not should_continue:
break
if response: # Command was handled, skip agent
continue
# Save user message to memory
memory.add_message("user", user_input)
messages.append({"role": "user", "content": user_input})
# Get agent response
print("\nThinking...\n")
try:
print("\n" + "β" * 75)
# Use invoke() with callback handler for real-time tool progress
config = {"recursion_limit": 35, "callbacks": [ToolProgressCallback()]}
result = agent.invoke({"messages": messages}, config=config)
# Update messages from result (keep as LangChain messages)
messages = list(result["messages"])
last_message = messages[-1]
if hasattr(last_message, 'content') and last_message.content:
response_text = last_message.content
elif isinstance(last_message, dict) and last_message.get('content'):
response_text = last_message['content']
else:
response_text = str(last_message)
print(f"\nπ Eurus:\n{response_text}", flush=True)
print("β" * 75 + "\n")
memory.add_message("assistant", response_text)
except KeyboardInterrupt:
print("\n\nInterrupted. Type /quit to exit or continue with a new question.")
except Exception as e:
error_msg = f"Error: {str(e)}"
logger.error(error_msg, exc_info=True)
print(f"\nError during processing: {error_msg}")
print("Please try again or rephrase your question.\n")
except KeyboardInterrupt:
print("\n\nReceived interrupt signal.")
finally:
# Cleanup
print("\nShutting down...")
# Clean up missing dataset records
removed = memory.cleanup_missing_datasets()
if removed:
logger.info(f"Cleaned up {removed} missing dataset records")
print("Session saved. Goodbye!")
# ============================================================================
# ENTRY POINT
# ============================================================================
if __name__ == "__main__":
main()