feat: improve error clarity for LLM provider failures (#506)

Replace generic "An unexpected error occurred" messages with descriptive,
user-friendly error messages when LLM operations fail. Errors like invalid
API keys, wrong model names, and rate limits now surface clearly in the UI.

Adds error classification utility, global FastAPI exception handlers, and
frontend getApiErrorMessage() helper. Bumps version to 1.7.2.

open_notebook/graphs/source_chat.py

@@ -13,8 +13,10 @@ from typing_extensions import TypedDict
 from open_notebook.ai.provision import provision_langchain_model
 from open_notebook.config import LANGGRAPH_CHECKPOINT_FILE
 from open_notebook.domain.notebook import Source, SourceInsight
+from open_notebook.exceptions import OpenNotebookError
 from open_notebook.utils import clean_thinking_content
 from open_notebook.utils.context_builder import ContextBuilder
+from open_notebook.utils.error_classifier import classify_error
 
 
 class SourceChatState(TypedDict):
@@ -39,6 +41,18 @@ def call_model_with_source_context(
     3. Handles model provisioning with override support
     4. Tracks context indicators for referenced insights/content
     """
+    try:
+        return _call_model_with_source_context_inner(state, config)
+    except OpenNotebookError:
+        raise
+    except Exception as e:
+        error_class, user_message = classify_error(e)
+        raise error_class(user_message) from e
+
+
+def _call_model_with_source_context_inner(
+    state: SourceChatState, config: RunnableConfig
+) -> dict:
     source_id = state.get("source_id")
     if not source_id:
         raise ValueError("source_id is required in state")