fix: improve xwang compatibility and vendor fallback

tradingagents/dataflows/interface.py

@@ -132,10 +132,17 @@ def get_vendor(category: str, method: str = None) -> str:
     return config.get("data_vendors", {}).get(category, "default")
 
 def route_to_vendor(method: str, *args, **kwargs):
-    """Route method calls to appropriate vendor implementation with fallback support."""
+    """Route method calls to appropriate vendor implementation with fallback support.
+
+    Fallback policy:
+    - Try configured vendor order first, then other available vendors.
+    - On any vendor error, continue trying next vendor.
+    - Return first successful result.
+    - If all vendors fail, raise a summarized runtime error.
+    """
     category = get_category_for_method(method)
     vendor_config = get_vendor(category, method)
-    primary_vendors = [v.strip() for v in vendor_config.split(',')]
+    primary_vendors = [v.strip() for v in vendor_config.split(',') if v.strip()]
 
     if method not in VENDOR_METHODS:
         raise ValueError(f"Method '{method}' not supported")
@@ -147,6 +154,7 @@ def route_to_vendor(method: str, *args, **kwargs):
         if vendor not in fallback_vendors:
             fallback_vendors.append(vendor)
 
+    errors = []
     for vendor in fallback_vendors:
         if vendor not in VENDOR_METHODS[method]:
             continue
@@ -156,7 +164,9 @@ def route_to_vendor(method: str, *args, **kwargs):
 
         try:
             return impl_func(*args, **kwargs)
-        except AlphaVantageRateLimitError:
-            continue  # Only rate limits trigger fallback
+        except Exception as e:
+            errors.append(f"{vendor}: {type(e).__name__}: {e}")
+            continue
 
-    raise RuntimeError(f"No available vendor for '{method}'")
+    details = " | ".join(errors) if errors else "no vendor candidates"
+    raise RuntimeError(f"No available vendor for '{method}'. Tried: {details}")

tradingagents/default_config.py

@@ -12,6 +12,7 @@ DEFAULT_CONFIG = {
     "deep_think_llm": "gpt-5.2",
     "quick_think_llm": "gpt-5-mini",
     "backend_url": "https://api.openai.com/v1",
+    "default_headers": {"User-Agent": "curl/8.0"},
     "factor_rules_path": os.getenv("TRADINGAGENTS_FACTOR_RULES_PATH", ""),
     # Provider-specific thinking configuration
     "google_thinking_level": None,      # "high", "minimal", etc.

tradingagents/graph/trading_graph.py

@@ -145,6 +145,10 @@ class TradingAgentsGraph:
             if reasoning_effort:
                 kwargs["reasoning_effort"] = reasoning_effort
 
+        default_headers = self.config.get("default_headers")
+        if default_headers:
+            kwargs["default_headers"] = default_headers
+
         return kwargs
 
     def _create_tool_nodes(self) -> Dict[str, ToolNode]:

tradingagents/llm_clients/openai_client.py

@@ -61,7 +61,7 @@ class OpenAIClient(BaseLLMClient):
         elif self.base_url:
             llm_kwargs["base_url"] = self.base_url
 
-        for key in ("timeout", "max_retries", "reasoning_effort", "api_key", "callbacks"):
+        for key in ("timeout", "max_retries", "reasoning_effort", "api_key", "callbacks", "default_headers"):
             if key in self.kwargs:
                 llm_kwargs[key] = self.kwargs[key]