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src/eurus/config.py

@@ -499,7 +499,7 @@ class AgentConfig:
     """Configuration for the ERA5 Agent."""
 
     # LLM Settings
-    model_name: str = "gpt-5.2"
+    model_name: str = "gpt-5.4"
     temperature: float = 0
     max_tokens: int = 4096
 

src/eurus/tools/era5.py

@@ -13,7 +13,7 @@ QUERY_TYPE IS AUTO-DETECTED based on time/area rules:
 import logging
 from typing import Optional
 from datetime import datetime
-from functools import partial
+
 
 from pydantic import BaseModel, Field, field_validator
 from langchain_core.tools import StructuredTool
@@ -190,26 +190,53 @@ def retrieve_era5_data(
 # LANGCHAIN TOOL CREATION
 # ============================================================================
 
+_ERA5_TOOL_DESCRIPTION = (
+    "Retrieves ERA5 climate reanalysis data from Earthmover's cloud archive.\n\n"
+    "⚠️ query_type is AUTO-DETECTED - you don't need to specify it!\n\n"
+    "Just provide:\n"
+    "- variable_id: one of 22 ERA5 variables (sst, t2, d2, skt, u10, v10, u100, v100, "
+    "sp, mslp, blh, cape, tcc, cp, lsp, tp, ssr, ssrd, tcw, tcwv, sd, stl1, swvl1)\n"
+    "- start_date, end_date: YYYY-MM-DD format\n"
+    "- lat/lon bounds: Use values from maritime route bounding box!\n\n"
+    "DATA: 1975-2024.\n"
+    "Returns file path. Load with: xr.open_zarr('PATH')"
+)
+
+
 def create_era5_tool(api_key: Optional[str] = None) -> StructuredTool:
-    """Create an ERA5 tool, optionally binding a session-specific API key."""
-    func = partial(retrieve_era5_data, _api_key=api_key) if api_key else retrieve_era5_data
-    # partial objects lose __name__, so set it explicitly
-    if hasattr(func, 'func'):
-        func.__name__ = 'retrieve_era5_data'
+    """Create an ERA5 tool, optionally binding a session-specific API key.
+
+    Uses a closure instead of functools.partial because LangGraph's ToolNode
+    calls typing.get_type_hints() which crashes on partial objects.
+    """
+    def _bound_retrieve(
+        variable_id: str,
+        start_date: str,
+        end_date: str,
+        min_latitude: float,
+        max_latitude: float,
+        min_longitude: float,
+        max_longitude: float,
+        region: Optional[str] = None,
+    ) -> str:
+        return retrieve_era5_data(
+            variable_id=variable_id,
+            start_date=start_date,
+            end_date=end_date,
+            min_latitude=min_latitude,
+            max_latitude=max_latitude,
+            min_longitude=min_longitude,
+            max_longitude=max_longitude,
+            region=region,
+            _api_key=api_key,
+        )
+
+    func = _bound_retrieve if api_key else retrieve_era5_data
+
     return StructuredTool.from_function(
         func=func,
         name="retrieve_era5_data",
-        description=(
-            "Retrieves ERA5 climate reanalysis data from Earthmover's cloud archive.\n\n"
-            "⚠️ query_type is AUTO-DETECTED - you don't need to specify it!\n\n"
-            "Just provide:\n"
-            "- variable_id: one of 22 ERA5 variables (sst, t2, d2, skt, u10, v10, u100, v100, "
-            "sp, mslp, blh, cape, tcc, cp, lsp, tp, ssr, ssrd, tcw, tcwv, sd, stl1, swvl1)\n"
-            "- start_date, end_date: YYYY-MM-DD format\n"
-            "- lat/lon bounds: Use values from maritime route bounding box!\n\n"
-            "DATA: 1975-2024.\n"
-            "Returns file path. Load with: xr.open_zarr('PATH')"
-        ),
+        description=_ERA5_TOOL_DESCRIPTION,
         args_schema=ERA5RetrievalArgs,
     )
 

web/agent_wrapper.py

@@ -41,7 +41,7 @@ class AgentSession:
 
     # Available models for the selector
     AVAILABLE_MODELS = [
-        {"id": "gpt-5.2", "label": "GPT-5.2", "provider": "openai"},
+        {"id": "gpt-5.4", "label": "GPT-5.4", "provider": "openai"},
         {"id": "gpt-4.1", "label": "GPT-4.1", "provider": "openai"},
         {"id": "o3", "label": "o3", "provider": "openai"},
         {"id": "gemini-3.1-pro-preview", "label": "Gemini 3.1 Pro", "provider": "google"},